# Changelog
Source: https://docs.sprig.com/changelog
# New: Backward navigation for link Surveys
*by Laura Desmond-Black*
We’re happy to share that it is now possible to add a back button to Surveys. Once enabled, it lets respondents taking a Survey navigate back to previous questions and change their answers.
The back button is easy to use: previous answers are preserved as respondents move backward so that once they begin moving forward again they don’t have to re-enter everything. If changing an earlier answer impacts the logic of the survey or future questions, once the respondent begins moving forward, they’ll proceed through the new path smoothly. Dynamic questions or content, like AI Follow-ups and Response Piping, will pick up the new responses and re-generate appropriately.
Ready to add a back button to your Survey? Follow these steps:
* Create or locate an existing Survey
* Open it in edit mode and switch to the **Settings** tab
* Scroll to the **Survey Navigation** section and enable the **Allow backward navigation** toggle
Once the setting is one, the back button will appear in the preview, aligned to the left edge of the content. Respondents can go back through most question types, including Conjoint and MaxDiff.
Want to learn more? Check out [the documentation](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/backward-navigation).
For those of you wondering if this setting will be added to In-Product Surveys, we’re happy to confirm that the answer is yes; it will be coming in October!
# Updated: Link behavior for mobile In-Product Surveys
*by Laura Desmond-Black*
Tapping a link in a Text / URL Prompt question in an In-Product Survey used to send respondents to their phone's default browser, taking them out of your app. That made it easy to lose someone before they finished the study, or for them to get distracted and never come back.
Now, Text/URL Prompt questions in mobile In-Product Surveys can open the browser in the app, making it easy for respondents to get back to what they were doing before taking the survey. This new option lives on the **Settings** tab of the survey when at least one Text/URL Prompt question is present and the platform is set to mobile. In addition to keeping people in their flow, the in-app browser view follows your light and dark theme settings, ensuring the experience feels cohesive no matter your settings.
In-Product Surveys in a draft state at the time of this release or created after this release will be set to have links open in-app by default. In-Product Surveys that were In-Progress or Paused at the time of this release will have the setting for the old link-out behavior on, however they can be switched to the new option at any time. The iOS and Android SDKs with this improvement are already out, updated React Native and Flutter SDKs are coming soon.
Check out [the documentation](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/questions#link-behavior-on-mobile) to learn more!
# New: Images in Response Options
*by Paresh Vakhariya*
*Add images to multiple choice answers*
Attach an image to each answer choice in Single Select and Multi Select questions. Respondents pick between designs, layouts, or products by tapping image cards instead of reading descriptions of them.
* Still a multiple choice question underneath, so skip logic, randomization, and AI Follow-ups work unchanged
* Results show image thumbnails on the Responses page and Data tab, with one-click expand to full size
* Upload JPEG, PNG, or WebP, up to 10MB per option
* If an image ever fails to load, the option falls back to a text row and responses keep collecting
Available on all plans for Surveys. Requires SDK update.
Read the documentation for more details
# New: Carry Forward Logic
*by Laura Desmond-Black*
Ever ask respondents to select which brands or features they use, then want to dig deeper into just the options they selected in the following questions? Carry Forward makes this easy by letting you take a respondent's answers from one question and automatically pull them into a later one, so they're choosing from their own choices instead of starting over. This keeps surveys more relevant and simplifies the survey-taking experience ensuring you get the best, and most, data possible.
What’s available:
* **Source questions:** Multi-Select and Matrix questions
* **Destination questions:** Multiple Choice (single- and multi-select), Rank Order, and Matrix questions
To use Carry Forward options, click the arrow next to the “Add Choice” menu at the bottom of a supported question type, select “**Carry forward responses**” and then select a prior question to pull from. Carry Forward works with Skip Logic, Display Logic, and even Randomization (Sprig ensures the source question always comes before the destination).
Now available for customers on the Enterprise plan. [Learn more](https://docs.sprig.com/docs/sprig-studies/surveys/carry-forward-functionality#carry-forward-functionality) and give it a try in your next Survey, In-Product Survey, or Feedback study!
# Updated: Dark mode for web and mobile In-Product Surveys
*by Laura Desmond-Black*
We’re happy to share that while it’s been possible to add custom dark mode styling to In-Product Surveys for a while, there’s now a default dark theme for teams who want a faster solution.
Previously, if you wanted to display In-Product Surveys with a dark theme, you had to build the CSS yourself. With today’s release, in **Settings** > **Surveys** > **Look & Feel**, there is now a toggle in the **Study Style** section to **Enable Default Dark Mode CSS**. Once on (don’t forget to Save!), the new built-in dark theme will automatically show if a user has their device set to dark mode. Enabling this setting will also reveal a toggle in the Study Builder preview that allows you to switch between light and dark themes so you can easily see how a survey looks in either theme. Note: this setting will result in the preview reacting to your computer’s own setting which means it might be in dark mode before you even try the toggle!
Once enabled, the built-in dark theme will apply to all web and mobile In-Product Surveys, as well as Feedback studies.
Ready to customize Sprig’s default dark theme to match your app’s look? Take a look at [the updated documentation](https://docs.sprig.com/docs/developer-center/styling/dark-mode) to get started today!
# New: Send Sprig Data/Responses/Reports to AI Tools
*by Paresh Vakhariya*
*Send your Sprig data to ChatGPT, Claude, or Cursor in one click*
Send to AI Tools adds a button on study Data, Responses, and AI Study Reports that opens the content in the AI tool of your choice, pre-loaded as a prompt. No more screenshotting charts, exporting CSVs, or pasting responses block by block.
* Runs on the Sprig MCP connector: sign in with your Sprig account once per tool, then every send is one click. The connection is read-only
* You can pull Sprig data: compare studies, fetch more responses, trend a metric
* Admins control Sprig MCP connections for your Sprig account
Available on all Enterprise plans. Read the details in the docs.
# New: Validated Text Questions
*by Laura Desmond-Black*
Collect text responses that are ready to use the moment they arrive. With the new Validated Text question type, a respondent's answer is checked against a required format before they can proceed, so you spend less time cleaning up phone numbers with missing zip codes or numbers that accidentally gained a letter
Choose from built-in formats for email addresses, phone numbers, URLs, and numeric entries, or define your own format with a custom regular expression. If a response doesn't match, respondents see an error message explaining what to fix, and that message can be customized and translated like other study copy.
Validated Text questions work for both required and optional questions. When optional, respondents can leave the question blank, but any text they do enter must pass validation.
Available now for all customers and all study types that support questions. Check out [the documentation](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/questions#validated-text) to learn more and use it in your next survey!
# New: Exclude Responses from Analysis
*by Laura Desmond-Black*
Have a response that isn’t useful? Now you can easily exclude it from the in-app analysis.
To take advantage of this new option, navigate to the **Responses** tab of a survey, locate the response you want to exclude, and click the `…` menu in the upper right corner of the response. You’ll see a new “**Exclude from analysis**” option in the dropdown menu. Select it to hide the response from question summaries on the Data tab of the survey and the AI Study Report.
Once it’s hidden you’ll see an indicator on the response so it’s easy to tell what's happened with it. You can undo the exclusion if needed by heading back to the same menu. Enjoy cleaner data, with less effort.
# New: Email distribution from Sprig
*by Laura Desmond-Black*
Get your survey in front of the right people without spinning up a separate email tool. With Sprig's email distribution functionality, you can send your survey to a list of contacts using your own domain, customize the email's content, and review open rates.
Sprig's email distribution supports the needs of enterprises by allowing you to:
* Upload a Contact List once and reuse it across future Email Runs and Surveys.
* Personalize the email message with recipient data uploaded through the CSV, insert your survey link in one click, and take branding to the next level with a full HTML editor.
* Meet unsubscribe requirements with automatically included unsubscribe links that route recipients to a branded page.
* Schedule emails to go out on survey launch or at a later time. Add additional Email Runs to the same survey at any time, each tracked separately for sends, opens, and response rates.
Available now for use with link Surveys and customers on the Enterprise plan. [Learn more](https://docs.sprig.com/docs/sprig-studies/surveys/delivering-surveys-by-email) or reach out to your Customer Success Manager to get started!
# New: Conjoint questions for Surveys
*by Laura Desmond-Black*
Want to know what your users would actually choose, not just what they say they prefer? Now you can find out quickly with Sprig's new [Conjoint question](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/questions#conjoint). Show respondents realistic combinations of features and ask them to pick one, just like a real purchase decision, so you can understand the components of the package that matter most.
Use Conjoint questions for pricing and packaging research, understanding willingness to pay, and estimating relative feature importance.
With Sprig's Conjoint you can:
* Build your own experiment: define features and levels, choose how many options appear per task and how many tasks each respondent will complete.
* Optionally randomize the order of features across respondents to avoid bias.
* Exclude unrealistic combinations with Exclusion Groups, and optionally add a “None of these” choice for more realistic results.
Results are summarized for quick scanning, broken out by feature and level. Alternatively, export full response-level data as a CSV for deeper analysis or send it over to your favorite LLM using [Sprig's MCP](https://docs.sprig.com/docs/native-ai/sprig-mcp).
Available now for Surveys and customers on the Enterprise plan.
# New: Sprig Panels
*by Laura Desmond-Black*
Need feedback from outside your existing user base?
With [Sprig Panels](https://docs.sprig.com/docs/sprig-studies/surveys/delivering-surveys-using-sprig-panels), you can recruit verified participants and deliver your survey to them without leaving Sprig. Reach fresh audiences for concept testing, brand perception research, and more, without over-surveying your own users.
Target exactly who you need with 300+ recruitment criteria, from location and job title to industry and income, with live audience size and cost estimates as you build.
Sprig calculates and handles incentive payouts automatically, so there’s no manual tracking or spreadsheets.
Run multiple panels on a single survey to reach different audience segments at once.
Available now for Surveys and customers on the Enterprise plan. Reach out to your Customer Success team to get started.
# AI File Upload: now with more survey options
*by Paresh Vakhariya*
The AI File Upload Builder now imports more question types, more study types, and more of your survey/display logic, so the draft Sprig builds matches your document even more closely. Upload a PDF or Word doc and get a launch-ready survey with skip logic, display logic, randomization, and required questions already in place.
## New
* **Voice and video questions.** Include voice or video questions in your document and Sprig builds them into the draft, ready for respondents to answer by speaking or on camera.
* **AI Dynamic Questions and AI Follow-Ups.** Specify either in your document and Sprig configures them during import, so your survey adapts in real time from the first launch.
* **Consent and legal questions.** Capture respondent consent or legal acknowledgment as part of your imported survey.
* **Display logic.** Add "DISPLAY LOGIC:" notes next to questions to show them only when a condition is met. Sprig brings the logic in exactly as written.
* **MQSP and IPS support.** Upload documents for Multi-Question Single Page studies and In-Product Surveys, not just standard Surveys. When your document explicitly specifies IPS, Sprig defaults to building an In-Product Survey.
## Improved
* **Rate every draft.** Use the new up/down vote buttons on file upload output to tell us how the draft turned out. Your feedback directly improves the builder.
* **Refreshed interface.** The builder now matches Sprig's new design system.
* **Easier review.** The Design Agent pane and survey editor scroll independently, and the pane auto-scrolls to reveal the latest Design Agent messages.
* **More accurate imports.** Upgraded the underlying model and refined the question and study schemas for cleaner, more reliable drafts.
## Fixed
* File caching that could serve an older version of your uploaded document
* "END" skip logic terminology not being picked up, leaving fields blank
* Question numbering off by one
* Single select questions incorrectly converting to text prompts
# New: AI Translations
*by Paresh Vakhariya*
Great news! Now, you can translate your entire survey with AI, every question, description, choice, and button label, in seconds.
No more exporting CSVs, routing files to translators, and waiting days to launch global research.
To use AI Translations, select **Add language** in the Language card of your study's Questions tab, choose your language(s), and select **Translate with AI**. Review and edit any translation inline, then set your language targeting and launch.
If you update your survey, regenerate translations anytime. Note that regenerating replaces all existing translations, including manual edits.
# New: Response-based Quotas for Surveys
*by Laura Desmond-Black*
Get exactly the responses you need by setting response-based quotas for Surveys.
Create up to three screener questions that can be used to define user segments that you want to collect data for. Set targets for each segment. Use quotas to filter the responses collected.
Check out [the documentation](https://docs.sprig.com/docs/sprig-studies/surveys/quotas-for-surveys) so you can use them in your next Survey!
# New: Add an image to a question
*by Laura Desmond-Black*
Great news! You can now add an image or gif to a question and easily test a new logo, name, or UI element.
It's easy to get started: look for the **Add Media** button near the "Required" toggle in the question header; it's available for most question types. Follow the file type and size requirements and preview and test the survey as usual. If you prefer not to use this, Admins can always disable it in Settings > Surveys > Configure. [Learn more](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/add-an-image-to-question) to get started today!
Available for Surveys and In-Product Surveys on mobile and web.
Note: The Admin setting was initially off by default. This was changed to being on by default on July 10th.
# New: Hide custom branding on surveys
*by Laura Desmond-Black*
Now you can hide your logo and brand color when sharing a Survey. To turn off custom branding, navigate to the **Settings** tab within a Survey (make sure to be in Edit mode), scroll down to the **Survey Branding** section and select the **Hide Branding** option.
Available to customers on the Enterprise plan.
# New: Surveys have an updated look
*by Laura Desmond-Black*
Based on your feedback we’ve updated the respondent experience for Surveys to make it even easier to get rich, rapid responses with a beautiful, easy-to-read experience.
## What’s changed
* The forward button is now closer to questions and larger so it requires less mouse movement to access.
* Autofocus has been removed from pages with multiple questions so respondents can drive their own progress.
* Situations where there was both a forward button in the question and a page-level forward button have been eliminated.
* Text/URL questions in Surveys no longer have the “No button” option as it’s no longer necessary.
* The number of buttons that show on a page with multiple questions has been reduced; they’re still visible when AI Follow-up or AI Dynamic questions are present.
* The display of Matrix questions has been improved.
* They’ll now expand horizontally if there’s space - no more horizontal scrolling.
* If the viewport is too narrow, the question will automatically switch to an accordion layout.
# New: Create Surveys from your AI client with MCP
*by Paresh Vakhariya*
You can now create Sprig studies directly from Claude, ChatGPT, or any connected AI client using Sprig MCP. Describe your research goal in plain language and your AI client drafts the study, configures the questions, and them prompt it to save it to Sprig as a draft ready for your review.
Studies created via MCP are always saved as drafts first. Launching requires a manual action from you in the Sprig UI.
**Example prompts to get started:**
"Create a 5-question onboarding study to understand why users drop off before completing setup."
One a survey has been generated you can prompt it to create a study within Sprig.
See [Create a Sprig study from your AI client](https://sprig.mintlify.app/docs/native-ai/sprig-mcp-create-study) for setup instructions and prompt tips.
# New: AI Follow-ups for more Question Types
*by Paresh Vakhariya*
## What's new in this release
Add AI follow-up questions to
* Ratings (number, smiley, star)
* Multiple choice (single and multi-select)
* NPS
* Matrix, and
* Rank order questions so any of these can probe for the "why" behind a response, not just open text.
Also, you can now also run **skip logic** on a parent question while AI follow-up is enabled. Skip logic runs after the parent question: if a response matches a rule, the AI follow-up is skipped and the respondent routes to the designated question (or the survey ends). Previously you had to choose one or the other.
# Sprig MCP is now available
*by Paresh Vakhariya*
Connect your Sprig workspace to AI tools using the Model Context Protocol (MCP). Your studies, responses, segments, and Agent Context are now accessible as live context in Claude, Claude Code, ChatGPT, Cursor, Gemini CLI, GitHub Copilot, and more.
## What's new
**Sprig MCP server** Exposes your Sprig workspace data as callable tools via a standard MCP endpoint at `https://mcp.sprig.com/mcp`
Any MCP-compatible AI client can connect and query your data directly.
**3 tools available at launch**
| Tool | What it does |
| :- | :- |
| `Retrieve Surveys` | Returns all studies in your workspace |
| `Retrieve Responses` | Fetches responses for a given study |
| `Retrieve Themes` | retrieve themes, along with the responses that are associated with each theme |
**OAuth authorization** Connections use OAuth 2.0. No API keys to manage. Admins authorize once at the workspace level; members connect their individual accounts with a single click.
**Admin and member controls** Workspace admins connect Sprig for their org. Members authorize their own accounts independently. Access is scoped to each user's existing workspace permissions.
## Supported clients at launch
Anthropic: Claude, Claude Code, Claude Cowork
OpenAI: ChatGPT, Codex
Google: Gemini CLI
Microsoft: GitHub Copilot
Code editors: Cursor
## What you can do
Pull Sprig data directly into any connected AI client without exporting or copy/pasting:
* Summarize study results and surface top themes
* Compare responses across studies or time periods
* Analyze how responses differ across user segments
* Generate research summaries, readouts, and hypotheses
* Look up any study by name or ID
**MCP to MCP workflows** When Sprig and another tool are both connected to the same AI client, you can act on Sprig data in other systems automatically.
e.g. Create Linear or Jira tickets from feedback themes, write research summaries into Notion or Confluence, log NPS signals to HubSpot or Salesforce, and export responses to Google Sheets.
## How to connect
Go to **Settings → Agents → Sprig MCP** to get your MCP server URL and follow the setup steps for your AI client.
## New: AI Study Report
*by Laura Desmond-Black*
Use Sprig's Synthesize Agent to quickly go from raw responses to a structured report that can easily be edited, downloaded, or shared with team members. Spend less time on manual analysis and more time ensuring insights are able to influence critical decisions.
Influence the content of the AI Study Report by adding [Agent Context](/docs/native-ai/synthesize-agent/agent-context) to ensure the report accurately reflects your goals and the particular focus area for the study. Reports are generated based on the Agent Context, the study's raw responses, and AI Insights generated for the study.
Reports follow research best practices with an executive summary, and sections for key insights, strengths, and opportunities. Meaningful quotes from open text questions are included to add depth to findings.
Editors can generate reports for in-progress studies that have 10 or more responses, or completed studies.
AI Study Reports are available for customers on the Enterprise plan for Surveys, In-Product Surveys, and Feedback studies. [Learn more](/docs/native-ai/synthesize-agent/ai-study-reports) about generating a report for your next study!
**Note**: this feature is being released in stages so you may not see it yet. We expect rollout to be complete by early May.
## AI Dynamic Questions
*by Paresh Vakhariya*
**AI Dynamic Questions** Enterprise tier only
Surveys now adapt in real time. AI Dynamic Questions (utilizing the Field Agent) automatically generate relevant open text question based on what each respondents prior questions/responses
* Add an AI Dynamic Question anywhere in your study. You can also add a custom (optional) prompt to each question.
* AI reads all prior questions and responses, then generates a short, neutral follow-up using NLP signals like sentiment, intent, and keywords. If it can't generate safely or quickly, the question is skipped.
* Results appear in Reports alongside your standard responses.
* **Question styles:** Clarification · Depth · Context · Impact · Sentiment · Keyword
* **Safeguards:** Moderation filters block PII, bias, and unsafe content. Skip logic and quotas are always respected.
* **Available on:** In-product surveys, surveys, and feedback button: Enterprise plans only. No limit on the number of AI Dynamic Questions per study.
**What AI uses to generate questions**
* Team context (if available)
* Agent context pka Study Goals (if provided)
* All prior questions and responses
* Question prompt (if entered)
* NLP signals: intent, sentiment, topics, and entities
💡 Start with 1–2 AI Dynamic questions per survey to add depth without increasing respondent fatigue.
## Prototype Testing Enhancements
*by Laura Desmond-Black*
For those of you who use Sprig to test new ideas and concepts, we have two enhancements to share:
1. You can now include **published** Figma Make and Lovable prototypes in Surveys. Get feedback on these highly dynamic prototypes just like you can for more traditional prototypes by placing them within a broader survey that might include multiple ideas. [Learn more](/docs/sprig-studies/prototype-studies/index).
2. For those who share AI-generated prototypes directly with users, we've validated that you can install the Sprig SDK into the prototypes themselves so that Feedback studies or In-Product Surveys can be part of the experience. Results show in Sprig just like when you launch studies in your live apps. Now you no longer have to rely on manual, in-person, or ad-hoc processes to get feedback on these vibe-coded ideas. [Learn more](/docs/sprig-studies/prototype-studies/index#embed-sprig-in-product-surveys-within-ai-generated-prototypes).
Happy testing!
# AI Follow-up Question
*by Paresh Vakhariya*
AI Follow-Up automatically generates personalized, open-ended probes based on a respondent’s specific answer, capturing richer detail without manual programming.
## Key Features
* Supports Open Text questions; currently unavailable for Voice/Video. More question types to have AI Follow-up questions soon.
* Users must choose between AI Follow-Up or Skip Logic per question.
* Skips automatically if a relevant or safe question cannot be generated quickly.
## Why use AI follow-up questions?
* AI follow-up questions help turn vague feedback into specific, actionable insights by probing for clarity, examples, and root causes.
* They mimic a live interviewer at scale, improving response quality without adding researcher workload.
## How to Use
* Enable via the toggle in Study Setup for any Open Text question.
* Context used: Uses study goals, previous responses, and NLP signals (sentiment, intent) to tailor probes.
* Generates questions focused on clarification, impact, sentiment, or depth.
* Results: View both the AI-generated probe and the respondent’s answer in the Results tab.
## Best Practice
* Use 1–2 AI Follow-Up questions per survey to balance deeper insights with respondent experience.
# New: Display Logic
*by Laura Desmond-Black*
Display Logic is now available for Surveys, In-Product Surveys, and Feedback studies for customers on the Enterprise plan 🎉
Now you can easily configure questions to show when a respondent meets specific criteria based on their prior responses in the survey or user attributes you've stored in Sprig, like their plan or region. This allows you to ask customers a question with options that are relevant to them (Mets, Jets, or Nets for those in New York and Bears, Cubs, and Bulls for those in Chicago) which will lead to higher engagement and richer data.
Check out [the documentation](/docs/shared-study-foundations/main-tasks/survey-logic#display-logic) to learn more about setting up Display Logic.
# New: Attribute Piping
*by Laura Desmond-Black*
Generic questions are out; tailored experiences are in. Starting today, you can use the attribute data you already store in Sprig to customize your survey questions and descriptions in real-time.
**Why this is great:** more context for respondents means higher completion rates and higher quality responses. Instead of asking, "How much value do you feel like you're getting from your paid plan?" ask, "How much value do you feel like you're getting from your **Enterprise** plan, **Sarah**?"
**How it works:** Just like Response Piping, reference any attribute stored in Sprig directly within the question or description text.
**Availability:** Attribute Piping is available for customers on the Enterprise plan across In-Product Surveys, Surveys, and Feedback studies.
👉 [See how to set it up](/docs/shared-study-foundations/main-tasks/survey-logic#attribute-piping)
# Display Limits for Choice Randomization
*by Laura Desmond-Black*
With this release customers on the Enterprise plan gain an additional configuration option when randomizing the choices offered to respondents in Multiple Choice: Multi-Select and Matrix questions.
Now when setting choices to display in a randomized order in these questions there will be an option to limit the number of choices displayed. For example, if you have a list of 20 themes that you'd like respondents to select from but you don't want them to become overwhelmed with the full list, you can choose to limit the number of choices displayed to only 6 or 8.
See [our Help Center documentation](/docs/shared-study-foundations/main-tasks/survey-logic#randomize-the-order-of-response-options-in-questions) to learn more.
# Date filters for CSV Exports
*by Laura Desmond-Black*
Do you ever wish you could export survey response data for a specific timeframe?
Well, now you can! You can now choose a timeframe when requesting a CSV export so you can jump into analysis faster. Choose between preset or custom timeframes. If your survey has more responses than are supported for CSV exports (950,000) you can reduce the number of responses using the new filters and continue with your work. [Learn more.](/docs/shared-study-foundations/export-survey-data#/)
# New Question Type: MaxDiff
*by Laura Desmond-Black*
MaxDiff questions are here! 🎉 🥳
Gather detailed insights from respondents as you consider how to prioritize improvements or refine brand messaging with intuitive researcher and respondent experiences. Use the recommended setting to configure the question quickly or define your own experiment structure with the custom setting. Get a sense for how respondents feel about what you're asking them to rate using the built-in best-worst summary or download the CSV to run your own analysis. Check out [the documentation](/docs/shared-study-foundations/main-tasks/questions#maxdiff) to learn more.
# Conversational Surveys
*by Paresh Vakhariya*
We have introduced Conversational Surveys: a new, chat-style survey experience that makes responding feel more natural and engaging.
Instead of displaying multiple questions on a single page, Conversational Surveys present questions one at a time, creating a smooth, dialogue-like flow. Respondents interact as if they’re in a friendly conversation, leading to a more human, immersive, and enjoyable experience.
Check out [Conversational surveys](/docs/shared-study-foundations/main-tasks/conversational-surveys#/) to learn more about using this new functionality in your surveys!
# Validation for Multiple Choice Multi-Select questions
*by Laura Desmond-Black*
We've added new validation options for Multiple Choice Multi-Select questions so that you can capture exactly the data you need from respondents. There are now three settings for validating responses to these questions:
* Unlimited - Respondents can select as many choices from the list as they'd like.
* Maximum - Set an upper limit for how many choices respondents can select.
* Range - Set both lower and upper limits for how many choices respondents can select.
Check out [the documentation](/docs/shared-study-foundations/main-tasks/questions#response-validation-options) to learn more about using this new functionality in your surveys!
# Surveys are out of beta
*by Laura Desmond-Black*
We're pleased to announce that Surveys have reached general availability!
Over the course of the 3 month beta we added tons of new functionality including page-level Randomization, Rank Order questions, multiple questions per page, and Response Piping. We loved seeing how quickly you incorporated these new capabilities into your surveys and and appreciate all of the feedback you shared as you tested and launched surveys.
While the beta is over, we're just getting started--we have many releases planned for the next few months including:
* **Conversational Respondent UI**: A modern, chat-style survey experience that feels more human and drives better response rates. Choose when to deliver surveys in this format or the standard format with a per-study setting.
* **MaxDiff questions**: Quickly get detailed information about your users' preferences with an easily configurable question.
* **AI Study Builder:** Upload your research plan and generate a complete survey in moments.
Wondering what happens now that the beta is over? Starting November 1st, access to Surveys will be limited to 25 responses per month for customers who don't have Surveys in their contract. If you're interested in continuing to send Surveys, reach out to our [Sales team](https://sprig.com/sales-demos) or your Customer Success Manager!
# New: Response Piping
*by Laura Desmond-Black*
Response Piping is now available for In-Product Surveys, Surveys, and Feedback studies.
Now you can provide a highly-personalized experience for respondents and ensure they get the most relevant survey-taking experience possible, which will result in increased response rates and better response data for you.
Check out [the documentation](/docs/shared-study-foundations/main-tasks/survey-logic#response-piping) to learn more and include it in your next survey!
# Introducing: Rank Order Questions
*by Laura Desmond-Black*
Now available for In-Product and Surveys: Rank Order Questions 🎉
With this new question type, you can see exactly how your users rank multiple options. That clarity helps you make confident, data-driven decisions. No more guessing which features, messages, or experiences matter most.
Rank Order questions are available today in Surveys. To use them with In-Product surveys you'll need the latest version of the web SDK which was released yesterday. Native mobile SDKs will be available by the end of the week, and React Native and Segment.io SDKs will be available next week. Check the [Changelog](/docs/developer-center/sdk-changelog/index) for updates. Also available are [new CSS classes and styles](/docs/sprig-studies/in-product-surveys/microsurvey-look-and-feel) so Rank Order questions can match your brand.
Learn more about setting up Rank Order Questions in [Help Center](/docs/shared-study-foundations/main-tasks/questions#rank-order).
# Sprig Mobile Replays: Capture WKWebView views and SwiftUI text and images
*by Laura Desmond-Black*
Starting with iOS SDK version 4.24.7, you can opt-in to capturing WKWebView views as well as SwiftUI text and images so that more content from your app is visible in Replays. These options can be found in Settings > Replays > Configure > iOS.
These new settings give you the ability to capture more content from iOS apps while also respecting any selections you've made from the Basic, Moderate, and Strict privacy options.
# Randomization for pages and questions
*by Laura Desmond-Black*
We’ve added the ability to [randomize](/docs/shared-study-foundations/main-tasks/questions#randomization) pages and questions within Surveys. Now you can:
* Randomize all the pages and questions in a survey with one click (and undo it with one click too)
* Pin specific questions so they stay in place
* Easily see which questions are randomized or pinned with new indicators that show next to question and page titles
To try it, look for the new “Randomize” button in the Action Bar at the top of the Study Editor, it'll appear once the survey has at least one question.
We’ve also added this functionality to Feedback and In-Product Surveys–look for the same button in the Action Bar.
# Surveys: Beta now open
*by Laura Desmond-Black*
The beta for Long-From Surveys is now open to all customers on paid plans. From now until October 15, 2025 you can use Long-From Surveys, up to 2,500 responses/month, for free. Share longer surveys, with multiple questions per page with your user base wherever you can embed a link. Send personalized surveys in multiple languages, with logic that ensures respondents answer the right questions. Get insights quickly from Sprig AI, the same way you can for In-Product Surveys. Check out [the documentation](/docs/sprig-studies/long-form-surveys/index) to learn more.
# Easily Collaborate With Direct Response Sharing in Slack
*by Maha Chaudhry*
It’s now easier to share Sprig insights with your team. Slack notifications for new responses include direct links to specific feedback so you can quickly dive in. In the Sprig app, the Responses tab also features a new Share Response dropdown option, making it simple to send individual responses to your teammates. [Set up your Slack integration](https://app.sprig.com/integrations/collaboration/slack), or [try sharing a response today](https://app.sprig.com/studylist/all).
## Get More Actionable Themes With Improved Replays AI
*by Maha Chaudhry*
AI Analysis for Replays just got a powerful upgrade. Sprig AI now processes more clips more often and with greater accuracy. Your themes are now richer, more actionable, and always reflect the latest trends in your users' behavior. [Check out the improved AI themes in your Replays.](https://app.sprig.com/studylist/all)
## Detect Friction At Scale With Frustration Signals for Always-On Replays
*by Maha Chaudhry*
Frustration Signals are now in beta for Always-On Replays. Sprig automatically flags sessions with rage and dead clicks, making it easier to identify points of friction and take action to improve the user experience.
## Surface the Highest-Signal Sessions With Daily Clip Limits
*by Maha Chaudhry*
You can now set a daily cap on Always-On Replay clips by product and environment, giving you more control over volume and helping your team stay focused on the sessions that matter most. By reducing noise, you can more easily prioritize high-signal behavior and uncover actionable insights faster. [Head to the Configure tab within your Heatmaps & Replays settings to try it out.](https://app.sprig.com/settings/heatmaps-replays-configure)
## Reveal Friction Automatically with AI-Powered Always-On Replays
*by Maha Chaudhry*
Understand how users move through your product and spot friction faster with AI-Powered Always-On Replays. Sprig AI automatically recreates sessions, organizes behaviors into clear flows, and highlights key pain points. Plus, built-in advanced privacy controls make it easy to mask sensitive fields and customize exclusions. [Explore AI-Powered Always-On Replays by heading to the Behavior tab in your Sprig account.](https://app.sprig.com/behavior/pages) *(Requires Sprig SDK update)*
## Earn \$250 for Every Qualified Referral to Sprig
*by Maha Chaudhry*
[**Sprig’s Referral Program**](https://sprig.com/customer-referral-program?utm_source=new-in-sprig) makes it easy to share Sprig with your network—and get rewarded for it.
If you know someone who’d benefit from Sprig's product experience platform, [**refer them to our team**](https://sprig.com/customer-referral-program?utm_source=new-in-sprig). Whenever your referral leads to a qualified meeting, we’ll send you a \$250 gift card as a thank-you.
Here’s how it works:
1. **Submit a qualified referral**
* Your referral must meet all of the following:
* Role: UXR or Product Design, manager level+
* Company: 150+ employees, U.S.-based
* Budget: Can purchase Sprig Enterprise
* Sales status: Not in an active deal with Sprig
1. **Receive your bonus**
* Payout timing: After an annual contract is signed
* Bonus amount: \$250 via digital gift card
* Referral limit: Unlimited—get rewarded for each qualified referral
* Payout method: Sent via Sendoso
[**👉 Click here to refer a contact here**](https://sprig.com/customer-referral-program?utm_source=new-in-sprig)
## Uncover Friction Points with Frustration Signals in Sprig Replays
*by Maha Chaudhry*
Quickly spot friction points in your product with **frustration signals** in Sprig Replays. Now, Sprig can detect and highlight **dead clicks** (clicks that have no effect on a page) and **rage clicks** (multiple rapid clicks in one area) within a user's session. By surfacing these moments of user frustration, you can take immediate action to streamline workflows, reduce user pain points, and improve conversion rates. [Go to any Replay study and play back the session clips to see any frustration signals in your user's experience.](https://app.sprig.com/studylist/all)
## Unlock Continuous User Insights with Always-On Replays
*by Maha Chaudhry*
Get continuous, real-time insights into user behavior across your product with Always-On Replays. This feature (currently in beta) automatically reproduces user sessions across your product without any manual setup, enabling you to surface behavioral patterns and usability pain points passively. If you want to try Always-On Replays firsthand, [request access to our beta program today](https://a.sprig.com/U0pjVmZxLTdRUX5zaWQ6MzhiYjM0OGMtMWZjZC00Y2U4LWIwMzktYjFlNmQ0N2QzZDdl)! *(Sprig SDK update required)*
## Reproduce Users’ App Journey with Replays for Mobile
*by Maha Chaudhry*
Understand how users navigate your mobile app and uncover opportunities to improve the experience with Sprig Replays for iOS, Android, and React Native. Replays for Mobile lets you reproduce key moments from the user journey, helping you identify friction points, validate changes, and prioritize new features for your mobile experience. To try it out, [create a new Replay study and select Mobile App under Delivery Platform](https://app.sprig.com/create). *(Sprig SDK update required)*
# Account Passwords & Management
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/changing-account-passwords
## Password Requirements
Sprig passwords must meet the following requirements:
* Minimum length: 10 characters
* Must contain:
* At least one uppercase letter (A-Z)
* At least one lowercase letter (a-z)
* At least one number (0-9)
## Changing Passwords
To change the password to your Sprig account:
Click the account menu.
Click Log Out.
Click Forgot Password.
Type in your email.
Click Send password reset email.
Follow the instructions in the email you receive to reset your Sprig password.
Note: If you login to Sprig using the Sign in with Google option or the Sign in with SSO option, you will need to change your password with Google or the Identity Provider your company uses for Single Sign-On.
# Login & Provisioning
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/index
How to help your team sign up for Sprig
Sprig believes that product experience insights are the most powerful when an entire team is empowered to learn from them and take action. That's why we offer unlimited seats, so there are no additional costs to collaborate with your colleagues. Consider inviting team members to your Sprig account from Product, Design, User Research, and Engineering, as well as Marketing, Customer Success, Support, and Sales.
## Ways of adding users to Sprig:
You can add team members to Sprig:
* [manually](/docs/account-and-settings/account-and-login/manually-adding-users)
* through [domain-based team discovery](/docs/account-and-settings/account-and-login/team-discovery)
* or through [Single Sign-On](/docs/account-and-settings/account-and-login/sso-1/index)
## Ways of authenticating users in Sprig:
* Standard username and password (default)
* Authentication with your companies identity provider (IdP) through single-sign-on (SSO)
* [Auth0](/docs/account-and-settings/account-and-login/sso-1/auth0)
* [Google Workspace](/docs/account-and-settings/account-and-login/sso-1/google-workspace)
* [KeyCloak](/docs/account-and-settings/account-and-login/sso-1/keycloak)
* [Microsoft Entra ID](/docs/account-and-settings/account-and-login/sso-1/microsoft-entra-id)
* [Okta](/docs/account-and-settings/account-and-login/sso-1/okta)
* [OneLogin](/docs/account-and-settings/account-and-login/sso-1/onelogin)
# Manually Adding Users
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/manually-adding-users
To manually add a team member to Sprig:
1. Click [**Settings > Team**](http://app.sprig.com/settings/team), then click **+ Add Member**.
2. In the modal that opens, enter the team member's name, email address, and the [role](/docs/account-and-settings/team-management-roles/roles-permissions) you want them to have. Click Save.
Note: Users with the Admin role can add team members at any role level. Users with other roles can add team members at their role level or below.
## Activating your Account
The new member will receive a verification email from Sprig. In the verification email, they should click **Activate your account** to be redirected to Sprig, where they will set a password for their account.
If they do not receive an email, ask them to check their spam/junk folder. If they still can't locate the email, please contact [support@sprig.com](mailto:support@sprig.com).
In the verification email, new members should click **Activate your account** to be redirected to Sprig and set a password for their account.
# Auth0
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/sso-1/auth0
To enable SSO with Auth0, complete the following:
1. Contact [support@sprig.com](mailto:sso@sprig.com) to claim the email domain(s) that your SSO users will use to sign in.
2. Log into your Sprig account and navigate to **Settings >** [**Single Sign-On**](https://app.sprig.com/settings/sso).
3. Select the **SSO Enabled** option, and click **Save**.
4. An **Important Values** section should appear. Copy the value of the **Entity URI** field into the **Issuer URL** field in the **Your Identity Provider** section, and click **Save**. Take note of the Entity URI and the ACS URL values provided. You will use them to configure your Auth0 integration in later steps.
5. Log into your Auth0 admin account. Navigate to the Applications page and click "Create Application."
6. In the "Name" field, enter "Sprig" or whatever you would like the application to be called, select "Single Page Web Application and click Create.
7. Navigate to the Addons tab and click "SAML2 WEB APP."
8. On the Usage tab:
1. Copy the Issuer value and paste it into the Issuer URL field in the Sprig dashboard.
2. Copy the Identity Provider Login URL value and paste it into the Entry Point URL field in the Sprig dashboard.
9. Copy the ACS URL from the Sprig dashboard and paste it into the Application Callback URL field on the Settings tab in the Auth0 admin account.
10. In the Settings field, replace the default payload with the following, filling in the `recipient` and `destination` values with the ACS URL. At the bottom of the modal, click Enable.
```
{
"audience": "https://app.userleap.com/saml", // Entity URI
"recipient": "", // ACS URL
"destination": "", // ACS URL
"nameIdentifierProbes": [
"http://schemas.xmlsoap.org/ws/2005/05/identity/claims/emailaddress"
],
"signatureAlgorithm": "rsa-sha256",
"mapUnknownClaimsAsIs": true,
"includeAnyClaimInAssertion": false,
"mappings": {
"name": "name"
}
}
```
11. Click on Settings > Advanced Settings > Certificates.
1. Copy the contents of the Signing Certificate, paste it into the X.509 Certificate field in the Sprig dashboard, and click Save.
12. At the top of the Application page, copy the Client ID. It will be used in step 14.
13. In the left-hand sidebar, click on Actions > Triggers > post-login > Create Action.
1. In the "Name" field, enter "Map SAML Attributes" or whatever you would like the action to be called.
2. Trigger should already be populated with "Login / Post Login."
3. For Runtime, choose "Node 22." Click Create.
14. In the new action, paste the following code into the code editor. Make sure to replace `CLIENT_ID` with the Client ID from step 12. Click Deploy.
```
exports.onExecutePostLogin = async (event, api) => {
if (event.client.client_id === 'CLIENT_ID') {
// Get name
const fullName = event.user.name || "";
// Get role from metadata
let userRole = (event.user.app_metadata && event.user.app_metadata.role)
? event.user.app_metadata.role
: 'viewer';
// Set name and role attributes to be mapped to Sprig
api.samlResponse.setAttribute('name', fullName);
api.samlResponse.setAttribute('role', userRole.toLowerCase());
}
};
```
15. Now that the SSO integration is set up, a `role` will need to be added to the profile of users who will use SSO to login to Sprig. If a role is not added to a user, it will default to `viewer` when they login for the first time. The available roles are `admin`, `developer`, `editor`, `editor-lite`, and `viewer`. For more information about the access permissions associated with each role, see our documentation on [Member Permissions](/docs/account-and-settings/team-management-roles/roles-permissions).
1. To add a role to a user, click on User Management > Users and click on a particular user. Under "App Metadata (app\_metadata)," enter the role as follows:
When using the Auth0 SSO integration, Sprig member permissions are controlled by Auth0. Any role changes will need to be made within the Auth0 admin account.
Users that are assigned to the Auth0 application integration will now be able to sign in using the Sprig [SSO login page](https://app.sprig.com/login/sso).
# Google Workspace
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/sso-1/google-workspace
To enable SSO with Google Workspace, complete the following:
1. Contact [support@sprig.com](mailto:sso@sprig.com) to claim the email domain(s) that your SSO users will use to sign in.
2. **Set up SSO with Google Workspace:** log in to the Google Admin console and navigate to Apps > Web and mobile apps > Add app > Add custom SAML app
3. Proceed through the custom SAML app creation steps, first entering an App Name and description.
4. **Download Metadata:** In the "Google Identity Provider details" window, download the IDP metadata file or copy the SSO URL, Entity ID, and Certificate
5. Log in to your Sprig account and navigate to **Settings >** [**Single Sign-On**](https://app.sprig.com/settings/sso).
6. Select the **SSO Enabled** option, and click **Save**.
7. Navigate to the **Your Identity Provider** section at the bottom of the page.
8. Set the value of **Entry Point URL** to be the **SSO URL** from your Google metadata
9. Set the **Issuer URL** to be the same value as the **Entity URI** from the **Important Values** section (this should be [https://app.userleap.com/saml](https://app.userleap.com/saml)).
10. Finally, copy the Certificate from your Google metadata into your Sprig SSO settings and click **Save**.
11. Take note of the **Entity URI** and the **ACS URL** values provided by the **Important Values** section, as you will use them in your Google Workspace client configuration.
12. Back in your Google Workspace SAML App setup, enter the **Important Values** from your Sprig SSO settings.
# Single Sign-On (SSO)
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/sso-1/index
Sprig supports Single Sign-On (SSO) via SAML 2.0. This allows you to integrate with most SAML-compliant Identity Providers (IdPs).
Note: SAML SSO is available for customers on Sprig Enterprise plans.
Use the links below to find configuration guides for popular IdPs:
* [Auth0](/docs/account-and-settings/account-and-login/sso-1/auth0)
* [Google Workspace](/docs/account-and-settings/account-and-login/sso-1/google-workspace)
* [KeyCloak](/docs/account-and-settings/account-and-login/sso-1/keycloak)
* [Microsoft Entra ID](/docs/account-and-settings/account-and-login/sso-1/microsoft-entra-id)
* [Okta](/docs/account-and-settings/account-and-login/sso-1/okta)
* [OneLogin](/docs/account-and-settings/account-and-login/sso-1/onelogin)
# Keycloak
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/sso-1/keycloak
To enable SSO with KeyCloak, complete the following:
1. Contact [support@sprig.com](mailto:sso@sprig.com) to claim the email domain(s) that your SSO users will use to sign in.
2. Log into your Sprig account and navigate to **Settings >** [**Single Sign-On**](https://app.sprig.com/settings/sso).
3. Select the **SSO Enabled** option, and click **Save**.
4. An **Important Values** section should appear. Copy the value of the **Entity URI** field into the **Issuer URL** field in the **Your Identity Provider**, and click **Save** button for both sections. Take note of both values provided by the **Important Values** section, as you will use it in your KeyCloak client configuration in the next step.
5. Log into your KeyCloak administration console. Navigate to the **Clients** page. Click **Create** and an **Add Client** page should appear. In the **Add Client** page enter the Entity URI from Step 4 into the **Client ID** field, and select **SAML** for the **Client Protocol**. Click **Save**.
6. A new configuration page for the newly created Sprig client should appear. Click on the **Settings** tab. Switch the **Enabled** and **Sign Document** toggles to the ON position. All other toggles should be OFF. Select **RSA\_256** for the Signature Algorithm, and enter the ACS URL from Step 4 into the **Valid Redirect URIs** field. The values of all other fields can be as the default value or blank. Click the **Save** button.
7. Click on the **Mappers** tab for the Sprig client you created. Add two mappers that will evaluate the values that will be used by the Sprig application for each user’s name and role. The SAML attribute names must be \_name\_and *role*, respectively. Name values must be less than 255 characters, and valid values for role are *admin*, *developer*, or *viewer*. Sprig roles are described [here](/docs/account-and-settings/team-management-roles/roles-permissions).
8. Click on the **Realm Settings** tab on the left. Click on the **Keys** tab in the Realm page under which your Sprig client was created. On that page, under the **Active** tab you should see a set of rows for each key. Find the one that has type RSA and click on the **Certificate** button on the right side of the row. A long string value should appear. Enter this value into the **X.509 Certificate** field in the **Your Identity Provider** section of the Sprig [SSO Settings Page](https://app.sprig.com/settings/sso). Click **Save**.
Users that are assigned to the KeyCloak application integration will now be able to sign in using the Sprig [SSO login page](https://app.sprig.com/login/sso).
# Microsoft Entra ID
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/sso-1/microsoft-entra-id
To enable SSO with Microsoft Entra ID, complete the following:
1. Contact [support@sprig.com](mailto:sso@sprig.com) to claim the email domain(s) that your SSO users will use to sign in.
2. Log into your Sprig account and navigate to **Settings >** [**Single Sign-On**](https://app.sprig.com/settings/sso).
3. Select the **SSO Enabled** option, and click **Save**.
4. An **Important Values** section should appear. Copy the value of the **Entity URI** field into the **Issuer URL** field in the **Your Identity Provider** section, and click **Save**. Take note of the Entity URI and the ACS URL values provided by the **Important Values** section, as you will use them in your Microsoft Entra ID client configuration.
5. Log into your Microsoft Entra admin center. Navigate to the Enterprise app page. Click “+ New application” at the top of the page and then “+ Create your own application” in the window that opens on the right.
6. In the “What’s the name of your app?” field, enter “Sprig” or whatever you would like the application to be called, and select “Integrate any other application you don’t find in the gallery (Non-gallery)” and click Create.
7. Under “Set up single sign on,” click “Get started” and choose SAML.
8. In the Basic SAML Configuration section, click Edit, and:
1. Paste the Entity URI from the Sprig dashboard into the Identifier (Entity ID) field
2. Paste the ACS URL into the Reply URL (Assertion Consumer Service URL) field.
9. Copy the Login URL from section 4 in the Microsoft Entra admin center and paste it into the Entry Point URL field in the Sprig dashboard.
1. Then, click download next to Certificate (Base64) from section 3 in the Microsoft Entra admin center to download the X.509 certificate.
2. Open the downloaded certificate in a text editor.
3. Copy the contents of the certificate, paste it into the X.509 Certificate field in the Sprig dashboard, and click Save.
10. Back in the Microsoft Entra admin center, navigate to the “Users and groups” page to add users or groups to the application. The users or groups that you add will determine which users will be able to use SSO to login to Sprig.
Users that are assigned to the Microsoft Entra ID application integration will now be able to sign in using the Sprig [SSO login page](https://app.sprig.com/login/sso).
# Okta
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/sso-1/okta
To enable SSO with Okta, complete the following:
1. Contact [support@sprig.com](mailto:support@sprig.com) to claim the email domain(s) that your SSO users will use to sign in.
2. Log into your Sprig account and navigate to the **Settings >** [**Single Sign-On**](https://app.sprig.com/settings/sso).
3. Select **SSO Enabled** and click **Save**.
4. An **Important Values** section should appear. Take note of the values provided. You will use them to configure your Okta integration in Step 10.
5. Log into your Okta account and go to the **Admin** section. Open the side menu with the hamburger button in the top left corner, and navigate to **Applications > Applications**.
6. Click on **Create App Integration**.
7. A modal window should appear. Select **SAML 2.0** for the sign-in method. Then click **Next**.
8. Enter **Sprig** for the App Name, and click **Next**.
9. The next screen is where you will input the SAML settings. Use the values you were provided on the Sprig SSO settings page in Step 4 to enter the **ACS URL** into the **Single sign on URL** field, and the **Entity URI** into the **Audience URI (SP Entity ID)** field. Select **EmailAddress** from the **Name ID format** dropdown, then select **Email** from the **Application username** dropdown. Do not edit the checkboxes under the **Single sign on URL** field.
10. In the attributes section add an attribute so that there are two. Enter “name” and “role” for the **Name** fields. Leave the **Name format** fields as **Unspecified**. In the **Value** fields enter [Okta Expression Language](https://developer.okta.com/docs/reference/okta-expression-language/) expressions that will provide the name and role for your Sprig users. The “role” field needs to evaluate to one of: `admin` , `editor` , `developer` , or `viewer` . Sprig roles are described [here](/docs/account-and-settings/team-management-roles/roles-permissions). If you are not sure what to enter here you can add `String.join(" ", user.firstName, user.lastName)` for **name** and `admin` for **role**.
11. Leave the **Group Attribute Statements** section blank. Scroll down to the bottom of the page and click **Next**.
12. Fill out the necessary fields in the **Feedback** section and click **Finish**.
13. You should now be taken to your new app’s integration page. Make sure you're on the **Sign On** tab, then scroll down and click **View SAML Setup Instructions**
14. A new tab will open with configuration values. You will be using these values to configure Sprig SSO in the next step.
15. Navigate to the Sprig [SSO Settings Page](https://app.sprig.com/settings/sso). Copy the values from the previous step into the corresponding fields in the “Your Identity Provider” section
* **Identity Provider Single Sign-On URL → Entry Point URL**
* **Identity Provider Issuer → Issuer URL**
* **X.509 Certificate → X.509 Certificate**
16. Click the **Save** button in the **Your Identity Provider section**. You now can assign users in the **Assignments** tab of your Okta application integration.
Users that are assigned to the Okta application integration will now be able to sign in using the Sprig [SSO login page](https://app.sprig.com/login/sso).
# OneLogin
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/sso-1/onelogin
To enable SSO with OneLogin, complete the following:
1. Contact [support@sprig.com](mailto:sso@sprig.com) to claim the email domain(s) that your SSO users will use to sign in.
2. Log in to Sprig and go to [Settings > Single Sign On](https://app.sprig.com/settings/sso).
3. Select **SSO Enabled** option, and click **Save**.
4. An *Important Values* section will appear. Take note of the values provided. You will use them to configure your OneLogin integration in step 8.
5. Log in to your OneLogin account and go to the **Administration** section. Navigate to the **Applications** page.
6. Click the **Add App** on the right side of the page. In the search field, enter *Saml Custom Connector*. Choose SAML Custom Connector (Advanced) provided by *OneLogin Inc*:
7. In the **Display Name** field, enter a name and click **Save**.
8. Click **Configuration**. Use the *Important Values* you were provided in step 4 to cut and paste the *Entity URI* into the **Audience (EntityID)** field, and the *ACS URL* into both the **ACS (Consumer) URL Validator** field and the **ACS (Consumer) field**.
9. Click **Parameters**. Click to add a parameter.
10. Enter `name` in the Field name field. Select the **Include in SAML assertion** option. Click **Save**.
10. In the **Value** drop-down list select **Name**.
12. Click again on **Parameters**. Click to add another parameter.
13. Enter `role` in the **Field name** field. Select the **Include in SAML assertion** option. Click **Save**.
14. In the **Value** drop-down list select **- Macro -** . Either enter `admin` , `editor`, `developer` , or `viewer` in the field. Sprig roles are described [here](/docs/account-and-settings/team-management-roles/roles-permissions). Roles can be configured on a per-user basis using [user attribute macros](https://onelogin.service-now.com/kb_view_customer.do?sysparm_article=KB0010609). If you don’t have the appropriate attribute configured for users yet, you can choose “- Macro -” again and enter `admin`, and all assigned users will receive “admin” permissions.
15. You will configure the SAML settings. Click on the **SSO** tab. In the SAML Signature Algorithm dropdown, select **SHA-256**.
16. Navigate to the Sprig's [**Settings>Single Sign-On**](https://app.sprig.com/settings/sso). Copy the values from the SSO tab in the previous step into the corresponding fields in the **Your Identity Provider** section:
* **Issuer URL → Issuer URL**
* **SAML 2.0 Endpoint → Entry Point URL**
15. Now in the OneLogin **SSO** tab, click **View Details** link under the **X.509 Certificate** field. A new page will appear. Copy the text inside the X.509 Certificate field and paste it into the **X.509 Certificate** field in Sprig's [**Settings>Single Sign-On**](https://app.sprig.com/settings/sso). Click “Save”.
Users that are assigned to the OneLogin application integration will now be able to sign in using the Sprig [SSO login page](https://app.sprig.com/login/sso).
# Domain-Based Team Discovery
Source: https://docs.sprig.com/docs/account-and-settings/account-and-login/team-discovery
Allow team members to automatically join your Sprig workspace
Domain-based team discovery is an easy way to help your team get started in Sprig, allowing your colleagues to automatically join your team based on their email domain. Alternatively, if your company uses single sign-on (SSO) and you have a Sprig Enterprise plan, you can use SAML-based SSO instead. For more information, visit [Single Sign-On (SSO)](/docs/account-and-settings/account-and-login/sso-1/index).
# Getting Started with Team Discovery
Please contact [support@sprig.com](mailto:support@sprig.com) to add your domain as a discoverable domain for your team. Once that's done, navigate to [Settings > Domains](https://app.sprig.com/settings/domains) in your team Admin account and confirm the domain was added. There, you can:
1. Set the default role new users will have.
1. We recommend Editor to empower your colleagues to create and launch studies, as well as create new dashboards, but feel free to choose any role depending on your team's needs. You can see and adjust role permissions for each user in [Settings > Team > Members](https://app.sprig.com/settings/team).
2. Determine whether users with matching email domains can automatically join your team or whether they must issue a request for you to approve or reject.
Note: Team discovery only supports one domain.
# Team Discovery as a New Sprig User
## Automatically Join a Team
*If **"Immediately"** is selected as the access setting for your team:* When a colleague with a matching domain signs up for Sprig at [app.sprig.com/signup](https://app.sprig.com/signup) or any redirect from an authenticated dashboard page, they'll be prompted to join your team before setting up their password. They'll automatically see your team's account dashboard when they log in to Sprig.
## Request to Join a Team
*If **"Require Approval"** is selected as the access setting for your team:* When a colleague with a matching domain signs up for Sprig, they'll be prompted to "Request to join" your team. Then, team Admins will be sent an email notification about the request, which they'll be able to approve from [Settings > Team > Members](https://app.sprig.com/settings/team) in the Sprig dashboard. The new team member will then be notified via email that their request to join has been approved, and they'll see your team's account dashboard when they log in to Sprig.
# Admin Configuration
Source: https://docs.sprig.com/docs/account-and-settings/configure
In [**Settings > Configure**](https://app.sprig.com/*/settings/configure), you can:
* Change the Product Name.
* Configure whether or not to Auto Accept Events.
* For web-based single-page applications, dismiss the study on page change.
* Define the Recontact Waiting Period.
* Allow Manual Study Display from the command line.
* Control Open Text Question footer content across all surveys as new questions are added and surveys are edited.
## Product Name
Use this option to change the name of the product.
## Auto Accept Events
Sprig will automatically accept unregistered events from your websites or apps to your list of triggered events.
## Dismiss on Page Change
For web-based single-page applications (SPA), there is an option to dismiss (close) the study on page change. Note: after the waiting period, for page URL-based events, the study is only shown if the page URL still exactly matches the URL as originally defined.
For mobile applications, this operates the same way. The study will not show to the user if their app view changes.
## Recontact Waiting Period
[Recontact Waiting Period](/docs/sprig-studies/in-product-surveys/survey-creation/resurvey-waiting-period) sets the minimum number of days across all In-Product Surveys to wait before delivering a study to the same person.
## Allow Manual Study Display
Enable the manual [displaySurvey](/docs/Installation/introduction-web/web-javascript#browser-console) function for testing purposes, which makes studies publicly accessible by numeric ID.
## Set Open Text Question Footer
This setting allows you to automatically add standard footer content to all Open Text Questions that appear in In-Product Surveys, Surveys, and Feedback studies. This helps ensure consistency across surveys, saves time, and makes it easy to include important reminders such as not to share personally identifiable information in responses.
### How it works
Once you save text in this field, all new and edited Open Text Questions will get this content automatically. This applies to surveys regardless of their state, for example, if you edit an in-progress study after enabling this setting, any existing footer content for Open Text Questions in the study will be replaced with content from this setting. Once this setting is enabled, editing footer content from within a survey will be disabled. The content can be translated along with the rest of the survey content using the standard [multi-language functionality](/docs/shared-study-foundations/main-tasks/multi-language-support).
To stop applying footer content automatically, delete all of the content from this setting and save. Footers for Open Text Questions will retain the last version of the content from the setting but it will be editable from within each survey again.
# Plans and Billing
Source: https://docs.sprig.com/docs/account-and-settings/plans-teams-and-billing
As of June 2024, Sprig is rolling out a new pricing & usage model based on individual study units (Survey responses, Feedback responses, Replay clips, and Heatmap captures) and Monthly Unique Users to support a broader diversity of customers better. Learn more [here](https://dash.readme.com/project/userleap/v6.0/docs/usage-muu)
# Plans
Sprig supports three plans: Free, Starter, and Enterprise. The Sprig [Website](https://sprig.com/plans#feature_table) provides more details on the differences between the three plans. You can verify your current Plan by going to the [Settings > Plans](https://app.sprig.com/settings/plans) page in the Sprig app.
The main differences between the three plans are Product Access, the number of individual study units (Survey responses, Feedback responses, Replay clips, and Heatmap captures), and Monthly Unique Users - for [legacy plans](/docs/account-and-settings/usage-muu/usage) this is Study Credits and Monthly Tracked Users (MTUs) - you can use each month, as well as the delivery platforms available to you. The Enterprise Plan also features greater design customization options and increased customer support.
[Plan changes: FAQ](/docs/account-and-settings/plans-teams-and-billing#plan-changes-faqs-1)
## Enterprise Plan
The **Enterprise Plan** is designed for organizations scaling their product development, so it can be completely tailored to your needs. Depending on your contract, your package includes access to products, individual study units (Survey responses, Feedback responses, Replay clips, and Heatmap captures), and a Monthly Unique Users (MUU) bundle.
The Enterprise Plan gives you access to all Delivery Methods (Mobile or Web), custom limits for Surveys, Replays, Heatmaps and Feedback, GPT-powered AI Analysis, API access, and customizable study look and feel. Plan pricing varies based on needs.
## Starter Plan
The [**Starter Plan**](https://sprig.com/plans) is designed for professionals and teams collecting user insights from a small user base.
The Starter Plan provides (monthly):
* Replays: 400 Clips
* In-Product Surveys: 200 Responses
* Surveys: 100 Responses
* Heatmaps: 1000 Captures
* Feedback: 100 Responses
* Up to 50k MUUs
* Mobile Delivery is available as an add-on
Additionally, it provides access to native [integrations](https://sprig.com/integrations/featured) with top-rated panel providers. Check out the [Plans and Pricing page](https://sprig.com/pricing#feature_table) for more details.
## Free Plan
The [**Free Plan**](https://sprig.com/plans) is designed for individuals and teams just getting started with capturing quick and easy user insights.
The Free Plan provides (monthly):
* Replays: 50 Clips
* In-Product Surveys: 25 Responses
* Surveys: 25 Responses
* Heatmaps: 100 Captures
* Feedback: 10 Responses
* Up to 5k MUUs
Consider upgrading to a Starter or Enterprise Plan if you'd like Surveys, mobile-delivered surveys, integrations, as well as more robust Sprig AI Analysis. To upgrade, click [here](https://sprig.com/trial) to book a call.
# Overage Enforcement
Limits are enforced across the two primary billing dimensions:
* Study Units - Replay Clips, Heatmap Captures, Survey Responses, and Feedback Responses
* MUUs
Overage enforcement can behave differently, based on your plan type
**Free & Starter Plans**: Hard Limits
* Study Units: Studies of the particular type will stop collecting user data
* MUUs: All study types will stop collecting data
**Enterprise Plans**: Two-month grace period before Hard limits are invoked (see Hard Limit behavior above)
Your usage resets at the beginning of the calendar month after which any *In Progress* study will resume collecting data.
## Teams and Products
The Team contains all the Members or users who can access the Sprig app with their email addresses. The Team is often described as your Sprig account. The Plan you choose and the Billing each month are associated with the Team. You can add multiple Products to a Team. All Products in a Team are accessible to Members of that Team. You cannot share Member information or any other information between Teams. Sprig determines which Team you are placed into based on your login credentials. You will need a different email if you want to log into other Teams.
Some customers may decide to have all their Products in one Team. Other customers may choose to have multiple Teams with multiple Products. Before adding a Team or a Product, contact us so that we can review the options to determine if you should create a new Team or join an existing Team. If you need help locating your company's Sprig app, contact Sprig at [support@sprig.com](mailto:support@sprig.com).
## Billing
Sprig's billing is based on the number of individual study units (Survey responses, Feedback responses, Replay clips, and Heatmap captures) and Monthly Unique Users in your contract. Please note that your team may incur additional charges if you exceed your allotted usage for MUUs in a given calendar month. You can view your team's billing information by navigating to [Settings > Plans](https://app.sprig.com/settings/plans).
Sprig will invoice your company according to the service terms expressed in the agreement. For all billing questions, please contact [**support@sprig.com**](mailto:support@sprig.com).
# Plan Changes FAQs
### How can I upgrade?
Free and Starter Plan customers who are interested in upgrade options can [click here](https://app.sprig.com/pricing/) to explore our plans or go to [Settings > Plans](https://app.sprig.com/settings/plans) to set up a consultation with a Sprig Specialist.
Enterprise Plan customers can contact your account team or email Sprig Support at [support@sprig.com](mailto:support@sprig.com) if you have questions or would like to upgrade your plan to add Surveys, Replays, or Heatmaps.
### How can I downgrade?
If you want to discuss downgrade options, please email Sprig Support at [support@sprig.com](mailto:support@sprig.com).
### How can I cancel my Starter Plan?
To cancel your Starter plan, head to Settings > Billing & Plans > Manage plan and log into the billing system with the email used to set up billing. From there, you will be able to cancel your plan.
Your plan will revert to a Free Plan after the current billing cycle ends.
# Team Management & Roles
Source: https://docs.sprig.com/docs/account-and-settings/team-management-roles/index
Sprig believes that product experience insights are the most powerful when an entire team is empowered to learn from them and take action. That's why we offer unlimited seats, so there are no additional costs to collaborate with your colleagues.
This section covers:
* Organizing [Sprig product workspaces and understanding environments](/docs/account-and-settings/team-management-roles/products-and-environments)
* [Sprig roles and user permissions](/docs/account-and-settings/team-management-roles/roles-permissions)
# Products and Environments
Source: https://docs.sprig.com/docs/account-and-settings/team-management-roles/products-and-environments
## Products
If you have multiple services, products, or websites and would rather assign a single domain for each product, you might consider adding additional *Products* to Sprig. *Products* have distinct data flows, studies, and events in one environment. Adding a Product to Sprig is supported on Enterprise Plans.
### Adding a Product
Adding a Product to Sprig is supported on Enterprise Plans only and allows you to partition your account to support multiple Products.
Limits such as MUUs, Survey Responses, Feedback Responses, Heatmap Captures, and Replay Clips are partitioned *per Product* and are unable to be allocated across Products.
Contact [support@sprig.com](mailto:support@sprig.com) to add a product to your Sprig account.
#### Things to Consider
Sprig identifies users by a unique identifier, `visitorids`, and then determines whether or not they should be eligible to receive another Sprig study. Users that are tracked through the new product are treated as **new users** and will carry unique `visitorids`. So in this case it is possible for the same user to receive more than one study within the same day.
**Warning:** Warning
As with environments, you cannot share user identities across product boundaries
### Workflow
Select **Account > Product > + Add New Product**.
### Deleting a Product
Deleting a product requires contacting Sprig customer support. Contact [support@sprig.com](mailto:support@sprig.com) to remove a product from your Sprig account.
## Environments
There are 2 environments for each product in your Sprig account: the Development and Production environment. These have distinct data flows, studies, and events in one environment cannot be used in or moved to the other environment.
In the following example, the current Environment, **Production**, is shown under the Product name in the **Account** menu.
To change from the Production to Development Environment, select **Account > Environment**, then select **Development**.
### Development and Production
The Development and Production environments have two distinct but similar purposes.
The purpose of your development environment is to test study delivery and appearance. The environment operates and appears like the production environment, with some exceptions.
The Production environment is where you should keep all studies you intend to collect data from. The production environment has fully functioning recontact periods, so after a visitor is shown a study, they will not receive another until the default period expires or the override period for the study is completed. For more information, see [Recontact Waiting Period](/docs/sprig-studies/in-product-surveys/survey-creation/resurvey-waiting-period).
The main differences between the Development and Production environments are:
1. There is no Recontact Period in the Development environment. This is intended to allow for rapid testing of Events and Question logic.
2. Studies launched in the Development environment do not count against your monthly limit. This allows additional launches during testing cycles.
### SDKs
In addition, when setting up an [SDK](/docs/developer-center/sprig-sdk/features-by-sdk-version#sdk-diagnostics) based event, be aware that the Production and Development IDs are different. They must be correctly configured with the corresponding ID for that environment to receive events. You can find the IDs at:
* **Integrations > JavaScript >Get Code**
* **Integrations > iOS > Get Environment ID**
* **Integrations > Android > Get Environment ID**
The Production and Development IDs are the same for JavaScript, iOS, and Android.
# Roles & Permissions
Source: https://docs.sprig.com/docs/account-and-settings/team-management-roles/roles-permissions
How to help your team sign up for Sprig
## Sprig Permission Sets
Sprig offers 5 different access permissions, listed below ranked from highest to lowest access:
1. Admin
2. Developer
3. Editor
4. Editor Lite
5. Viewer
For more information on user roles & permissions, see below:
| | Admin | Developer | Editor | Editor Lite | Viewer |
| :- | :- | :- | :- | :- | :- |
| **SSO** | | | | | |
| Log In using SSO | ✅ | ✅ | ✅ | ✅ | ✅ |
| **Dashboards Page** | | | | | |
| Create New Dashboard | ✅ | ❌ | ✅ | ✅ | ❌ |
| Edits to Dashboards Page | ✅ | ✅ | ✅ | ✅ | ❌ |
| View Pinned Results | ✅ | ✅ | ✅ | ✅ | ✅ |
| Use Help Chat | ✅ | ✅ | ✅ | ✅ | ❌ |
| **Studies Page** | | | | | |
| View Studies | ✅ | ✅ | ✅ | ✅ | ✅ |
| Edit Studies | ✅ | ✅ | ✅ | ✅ | ❌ |
| View Study Results | ✅ | ✅ | ✅ | ✅ | ✅ |
| View Study Templates | ✅ | ✅ | ✅ | ✅ | ✅ |
| Create a Study | ✅ | ✅ | ✅ | ✅ | ❌ |
| Launch a Study | ✅ | ✅ (Dev Env only) | ✅ | ❌ | ❌ |
| Edit Live Survey | ✅ | ✅ (Dev Env only) | ✅ | ❌ | ❌ |
| Pause a Study | ✅ | ✅ | ✅ | ✅ | ❌ |
| Complete a Study | ✅ | ✅ | ✅ | ✅ | ❌ |
| **Users Page** | | | | | |
| Access Users Page | ✅ | ✅ | ✅ | ✅ | ✅ |
| View Visitor Timeline | ✅ | ✅ | ✅ | ✅ | ✅ |
| Contact User | ✅ | ✅ | ✅ | ✅ | ✅ |
| **Events Page** | | | | | |
| View Events | ✅ | ✅ | ✅ | ✅ | ✅ |
| Add an Event | ✅ | ✅ | ✅ | ✅ | ❌ |
| Edit/Delete Event | ✅ | ✅ | ✅ | ✅ | ❌ |
| Filter Events | ✅ | ✅ | ✅ | ✅ | ✅ |
| **Settings / Look & Feel** | | | | | |
| Edit Product Name | ✅ | ✅ | ❌ | ❌ | ❌ |
| Add/Change Logo | ✅ | ✅ | ❌ | ❌ | ❌ |
| Add/Change Brand Color | ✅ | ✅ | ❌ | ❌ | ❌ |
| Adjust Study Placement | ✅ | ✅ | ❌ | ❌ | ❌ |
| Remove Signature | ✅ | ✅ | ❌ | ❌ | ❌ |
| **Settings / Integrations** | | | | | |
| Add and Configure Integrations | ✅ | ✅ | ✅ | ❌ | ❌ |
| **Settings / Team** | | | | | |
| Add Team Member\* | ✅ | ✅ | ✅ | ✅ | ✅ |
| Edit Team Member | ✅ | ❌ | ❌ | ❌ | ❌ |
| Configure SSO | ✅ | ✅ | ❌ | ❌ | ❌ |
| Manage Billing | ✅ | ❌ | ❌ | ❌ | ❌ |
\*Admins can add any role. Other roles can only add their level or below.
If you have any questions please email us at [**support@sprig.com**](mailto:support@sprig.com) or use the in-product help chat.
# Usage
Source: https://docs.sprig.com/docs/account-and-settings/usage-muu/index
Learn about how Sprig tracks usage and how it impacts your plan limits
In June 2024, Sprig moved a new pricing and usage model based on individual Study Units (responses, clips and Heatmap captures) and Monthly Unique Users to better support a broader diversity of customers.
If you are still on the legacy MTU & study model plan, please see relevant information [here](https://docs.sprig.com/docs/account-and-settings/usage-muu/usage#study-usage).
# Overview
Sprig's Enterprise billing and usage model has two main components:
* A platform fee that incorporates monthly usage
* as measured by Monthly Unique Users
* Product access & per product bundles
# Product Usage
## How is Survey, Replay, Heatmap, and Feedback Usage tracked?
* **Replay Clips:** The number of Replay clips captured in a calendar month. Clips can be captured as part of standalone Replay studies, or captured alongside Feedback and Survey responses, or Heatmap captures
* **Heatmap Captures:** Heatmap usage is tracked based on the number of visitor captures in a Heatmap report in a calendar month. A capture is a visitor that visited the page on which the study is configured and had their clicks or scrolls recorded in the study
* **Feedback:** The number of Feedback responses collected in a calendar month. A response is counted if a visitor answers at least one question of your Feedback study. Feedback responses are tracked separately from Survey responses
* **Surveys:** The number of Survey responses collected in a calendar month. A response is counted if a visitor answers at least one question of your survey
Your monthly usage allowance for each study type will be renewed at the start of each calendar month.
# Monthly Unique Users (MUU) Usage
## What is an MUU?
Monthly Unique Users (MUUs) are a measure of the number of unique Visitors within a month that have visited your web page or interacted with your application. It is important to note that an MUU is not necessarily a person that has seen a Survey or Feedback Study, or been captured as part of a Replay or Heatmap.
MUUs are an important factor in billing, as exceeding your monthly usage limit may result in being unable to launch additional studies or your active studies being unable to collect responses. Enterprise Plans offer a customizable number of MUUs, Starter Plans & Free plans currently subscribe to our [Legacy MTU model.](https://dash.readme.com/project/userleap/v6.0/docs/usage)
To estimate how many MUUs you'll need for your Sprig plan, you can use your monthly active user (MAU) count from your product analytics tool as a starting point. If you would like to increase your MUU limits or upgrade your plan, please reach out to [Sales](https://sprig.com/sales-demos)
**Note:** Certain customers may be grandfathered into a [MTU model](/docs/account-and-settings/usage-muu/usage)
## How is MUU usage tracked and how can I monitor usage?
MUU allocation is shared across all [Products](/docs/account-and-settings/team-management-roles/products-and-environments) within a Team and across all [Environments](/docs/account-and-settings/team-management-roles/products-and-environments#environments). To monitor your team's MUU usage throughout the month, head over to [Settings > Usage](https://app.sprig.com/settings/usage) in the Sprig app. Additionally, you will be proactively alerted at various usage milestones as you approach MUU limits.
Accurate tracking requires a common identity provided for each unique visitor. Users tracked without a common ID, such as anonymous visitors to a website, may be counted multiple times for each session. See the [Installation Guide](/docs/Installation/introduction-web/index) for more information.
## When do monthly MUU usage limits reset?
Your monthly usage allowance for studies will be renewed at the start of each calendar month.
## How can I reduce my team's MUU usage?
If you're looking to avoid MUU overages, consider one or more of the following options:
1. Track User IDs: Manage user identity consistently to limit the number of “anonymous” users who may be counted multiple times during a month. This is especially important if you’re using Sprig SDK with other Integrations like Segment or Google Tag Manager. See [installation guide](/docs/Installation/introduction-web/index) for best practices.
2. Upgrade your plan and/or Increase MUU limits by talking with [Sales](https://sprig.com/sales-demos)
3. MUU Sampling: (Not recommended) Admins can request Sprig Customer Success to implement sampling to control the amount of traffic sent to Sprig from your App.
# Overage Enforcement
Limits are enforced across the two primary billing dimensions:
* Study Units - Replay Clips, Heatmap Captures, Survey Responses, and Feedback Responses
* MUUs
Overage enforcement can behave differently, based on your plan type
**Free & Starter Plans**: Hard Limits
* Study Units: Studies of the particular type will stop collecting user data
* MUUs: All study types will stop collecting data
**Enterprise Plans**: Two-month grace period before Hard limits are invoked (see Hard Limit behavior above)
Your usage resets at the beginning of the calendar month after which any *In Progress* study will resume collecting data.
# Other Usage FAQs
## Can I allocate MUUs across products or environments?
MUUs are provisioned by [product](/docs/account-and-settings/team-management-roles/products-and-environments) and admins are unable to selectively allocate MUUs across products. Please reach out to Support if you are interested in adding an additional Sprig Product to your Team.
## Why is my MUU count different from that provided by other tools?
Each tool counts users under different conditions. Different ingestion methods and data processings will naturally generate different results. As a reminder, Sprig tracks MUUs that due to qualifying occurrences in app or are exposed to a link survey.
## Is there a limit to the number of Events & Attributes I can collect about Users?
While you might be tempted to send any and all of your user Events & Attributes over to Sprig, there are some limitations that you'll want to keep in mind.
Sprig allows for a maximum average of 100 Events & Attributes per MUU on a monthly basis. If this limit is exceeded, a Sprig customer success person will reach out to discuss how you can reduce the number of Events & Attributes per MUU.
# Usage - Legacy MTU & Study Model
Source: https://docs.sprig.com/docs/account-and-settings/usage-muu/usage
Learn about how Sprig tracks usage and how it impacts your account limits
In June 2024, Sprig moved a new pricing and usage model based on individual Study Units (responses, clips and Heatmap captures) and Monthly Unique Users to better support a broader diversity of customers. Learn [more](https://docs.sprig.com/docs/account-and-settings/usage-muu/index).
# Study Usage
## How is my Study usage tracked?
Any study (Heatmap, Replay, Survey or Feedback) that receives one or more pieces of user data (capture, replay clip, Survey response or Feedback response) in a calendar month is considered is considered *Active* and will counts towards your Active Monthly Study limit. Only studies launched in Production environments count towards your monthly limits
An in product survey, feedback study or heatmap study with an attached Replay will only be counted as an active survey
## When do monthly Active Study usage limits reset?
Your monthly usage allowance for studies will be renewed at the start of each calendar month. You can see your team's Turnover Date in the Sprig app by going to [Settings > Usage](https://app.sprig.com/settings/usage).
# Monthly Tracked Users (MTUs) Usage
## What is an MTU?
Monthly Tracked Users (MTUs) is a measure of the number of unique Visitors within a month that have visited your web page or interacted with your application *and you've decided to send their events/attributes to Sprig*. It is important to note that an MTU is not necessarily a person that been captured in a study.
MTUs are an important factor in billing, as exceeding your monthly usage limit may result in being unable to launch additional studies or your active studies being unable to collect responses. Enterprise Plans offer a customizable number of MTUs, Starter Plans have a hard limit of 25,000 MTUs, and Free Plans have a hard limit of 5,000 MTUs.
To estimate how many MTUs you'll need for your Sprig plan, you can use your monthly active user (MAU) count from your product analytics tool as a starting point. If you would like to increase your MTU limits or upgrade your plan, please reach out to [Sales](https://sprig.com/sales-demos)
## How is MTU usage tracked and how can I monitor usage?
MTU allocation is shared across all [Products](/docs/account-and-settings/team-management-roles/products-and-environments) within a Team and across all [Environments](/docs/account-and-settings/team-management-roles/products-and-environments#environments). To monitor your team's MTU usage throughout the month, head over to [Settings > Usage](https://app.sprig.com/settings/usage) in the Sprig app. Additionally, you will be proactively alerted at various usage milestones as you approach MTU limits.
[Settings > Usage](https://app.sprig.com/settings/usage) allows you to display usage by user identify (anonymous vs identified) or platform.
To avoid exceeding your MTU limit, it is critical to practice good user identity hygiene to understand where, when, and how you want to track users.
Accurate tracking requires a common identity provided for each unique visitor. Users tracked without a common ID, such as anonymous visitors to a website, may be counted multiple times for each session. See the [Installation Guide](/docs/Installation/introduction-web/index) for more information.
## What are Events & Attributes?
[Events](/docs/shared-study-foundations/events/index) - Events are behaviors tracked in your application about a user and are used to trigger (display) studies after the user performs a specific action (e.g. *Dashboard - Clicked - Download CSV*)
[Attributes](/docs/shared-study-foundations/attributes) - Attributes are information tracked about a user and are used to refine the target users and filter the response data. Example attributes include (*language, role, plan\_type, browser etc)*
## How do Events & Attributes impact MTU accounting?
Tracking events that are not triggers for an active survey could lead to users that are counted as an MTU:
* For example, if you are tracking the event *Dashboard - Clicked - Download CSV* but you don't have an active survey that will trigger on that event, you will still accumulate MTUs from users that trigger the event.
Additionally, Sprig allows for a maximum average of 100 Events & Attributes per MTU on a monthly basis.
As of September 1st, 2023, Sprig no longer counts an MTU due to attribute setting towards visitor limits. Counts reflected in your Usage charts prior to that date reflect accounting by the previous accounting system whereby MTUs could be attributed to event triggering, attribute setting or study seen.
Some customers will be kept on the legacy MTU counting system. Please reach out to your customer success rep with any questions.
## When do monthly MTU usage limits reset?
Your monthly usage allowance for MTUs will be renewed on your Turnover Date each month. You can see your team's Turnover Date in the Sprig app by going to [Settings > Usage](https://app.sprig.com/settings/usage).
## How can I reduce my team's MTU usage?
If you're looking to avoid MTU overages and want to reduce your MTU count, consider one or more of the following options:
1. Track User IDs: Manage user identity consistently to limit the number of “anonymous” users who may be counted multiple times during a month. This is especially important if you’re using Sprig SDK with other Integrations like Segment or Google Tag Manager. See [installation guide](/docs/Installation/introduction-web/index) for best practices.
2. Archive unused Events: Events you’ve asked Sprig to track could result in a qualifying event that may count towards your MTU usage. Navigate to [Events](https://app.sprig.com/events) to view and archive unused Events.
3. Upgrade your plan and/or Increase MTU limits by talking with [Sales](https://sprig.com/sales-demos)
4. [MTU Sampling](/docs/account-and-settings/usage-muu/usage#mtu-sampling): (Not recommended) Admins can request Sprig Customer Success to implement sampling to control the amount of traffic sent to Sprig from your App.
# Other Usage FAQs
## What are some reasons that my MTUs are higher than expected?
**There could be a few reasons why you might be seeing higher MTUs usage than expected:**
* MTUs can include visitors that are not exposed to a study based on satisfying visitor tracking events. See How do Events & Attributes impact usage?
* Sprig generated visitor IDs are not correctly being coupled with the unique user IDs assigned to users within your platform’s internal authentication framework resulting in multiple MTUs for the same users. See [Installation Guide](/docs/Installation/introduction-web/index) for best practices for user ID management.
* Though it is rare, a user can be counted multiple times towards MTU limits. This can happen when a user accesses your website or application from one browser, but later opens your app anonymously on a different device or platform. Double counting can also happen if a user has two unlinked user IDs and uses both of them in a single month.
## Can I allocate MTUs across products or environments?
At this time, admins are unable to selectively allocate MTUs across products or environments. We recommend monitoring MTU usage throughout the month. You can filter Usage charts by Product under Settings > Usage.
## Why is my MTU count different from that provided by other tools?
Each tool counts users under different conditions. Different ingestion methods and data processings will naturally generate different results. As a reminder, Sprig only tracks MTUs that due to qualifying occurrences in app or are exposed to a link survey.
## Is there a limit to the number of Events & Attributes I can collect?
While you might be tempted to send any and all of your user Events & Attributes over to Sprig, there are some limitations that you'll want to keep in mind.
Sprig allows for a maximum average of 100 Events & Attributes per MTU on a monthly basis. If this limit is exceeded, a Sprig customer success person will reach out to discuss how you can reduce the number of Events & Attributes per MTUs.
## What happens when I hit my Study Limits?
For Free and Starter Plans, your active studies will continue to collect responses, but you will be unable to launch additional studies. Enterprise customers will be able to launch studies, but will be contacted by Success/Sales to discuss plan upgrade options.
## What happens when I hit my MTU Limits?
For Free and Starter Plans, you will be unable to launch additional studies and your active studies will no longer collect responses. Enterprise customers will be able to launch studies and collect responses, but will be contacted by Success/Sales to discuss plan upgrade options.
# Android Changelog
Source: https://docs.sprig.com/docs/developer-center/sdk-changelog/android-changelog
**How to read this changelog:** [Understanding SDK changelog urgency and impact](/docs/developer-center/sdk-changelog)
## v2.30.1
**Recommended if you use:** Session Replays
* add: \[impact: performance] `turnOffSessionReplayCapture()` turns session replay off for the rest of the app session. It replaces `stopRecording()`, now deprecated, which no longer stops only the recording in progress.
* fix: \[impact: performance] Session replay now stops for the rest of the app session under sustained memory pressure or when capture costs the main thread more than the configured threshold, rather than restarting on the next request.
## v2.30.0
**Recommended if you use:** URL Prompt Question Type
* chore: Updated the bundled Web SDK to [v2.53.0](https://docs.sprig.com/docs/developer-center/sdk-changelog/web-changelog#v2-53-0), which carries survey enhacements into this release.
* add: \[impact: behavior] Added the ability to launch an in-app web browser for URL Prompt question types.
* add: Added new lifecycle event displayInAppBrowser which fires when the in-app experience is triggered.
## v2.29.0
**Recommended if you use:** survey lifecycle events, or apps with multiple Activities
* chore: Updated the bundled Web SDK to [v2.51.0](/docs/developer-center/sdk-changelog/web-changelog#v2-51-0), which carries its survey and Session Replay fixes into this release.
* add: \[impact: behavior] Refactor of the survey lifecycle events for better accuracy with the addition of the new surveyReturned event, the removal of surveyWillPresent, a change to when the surveyAppeared emits and the addition of the new surveyDidNotAppear event.
* add: Passing the surveyId of the previous survey when a previousSurveyReady state is returned.
* fix: \[impact: performance] Memory leak fix for multiple Activities.
## v2.28.0
**Recommended if you use:** Session Replay
* add: Wireframe session replay recording (optional)
## v2.27.2
* chore: Updated WebSDK to v2.49.0
## v2.27.1
* chore: Removal of unnecessary library dependency
* chore: Logging improvements
## v2.27.0
* chore: Updated WebSDK to v2.48.2
## v2.26.2
* chore: Changes to error logging
## v2.26.1
* add: Updated WebSDK to v2.46.1
* fix: Single select answer selection color for Conversational UI in Dark Mode
## v2.26.0
* add: Updated WebSDK to v2.46.0
* fix: Survey sliding animation issue with text field questions under Material 1.10+
## v2.25.0
* add: Updated WebSDK to v2.45.0
* add: JIT survey web view creation for improved long-term reliability
* fix: Survey text fields were covered by the keyboard in certain React Native environments
* chore: Error logging optimizations
## v2.24.0
* add: Updated WebSDK to v2.44.0
* add: New function to override device light/dark mode in surveys
* fix: Ensure light/dark mode is always enabled for current activity
* fix: Certain lifecycle events are no longer reported twice
* chore: The surveyId in SprigSurveyResult is no longer optional, keeping in parity with iOS
## v2.23.0
* add: Updated WebSDK to v2.43.0
* add: Survey ID provided in track callbacks via new SprigSurveyResult
* add: New PREVIOUS\_SURVEY\_READY state to indicate pending surveys
* add: New SURVEY\_STATE\_RETURNED and SURVEY\_COMPLETED lifecycle events
* add: Light/dark mode support with custom CSS
* fix: Pending surveys now cause newly tracked surveys to be ignored
## v2.22.1
* fix: Conversational UI surveys having incorrect height in landscape
## v2.22.0
* add: Updated WebSDK to v2.41.3
* add: Support for the new AI Follow-up question type
* add: Display Logic support
## v2.21.3
* fix: Ensures the active UI context is used for surveys in multi-activity apps
* fix: Corrects a bounded memory leak during configuration
## v2.21.2
* fix: Delays set for surveys had stopped working
* fix: Surveys were getting cut off in landscape mode
## v2.21.1
* fix: Memory leak with ConnectivityManager
## v2.21.0
* add: Updated WebSDK to v2.40.3
* add: Support for Attribute Piping
## v2.20.0
* add: Ability to pause and unpause displaying of surveys
* add: Dismissing active surveys also dismisses any pending surveys
## v2.19.7
* add: Keyboard height override
## v2.19.6
* add: Call to configure is now thread and coroutine safe
* fix: Crash that could occur during replays with complex composite views
## v2.19.5
* add: Launch time configuration
## v2.19.4
* add: Updated WebSDK to v2.39.3
* add: Support for new Conversational Survey format
* add: Support for SURVEY\_WILL\_PRESENT lifecycle event
* add: Support for SURVEY\_PRESENTED lifecycle event
* add: Support for SURVEY\_WILL\_CLOSE lifecycle event
* add: Support for SURVEY\_CLOSED lifecycle event
* add: Support for SURVEY\_HEIGHT lifecycle event
* fix: Removed SURVEY\_DIMENSIONS lifecycle event no longer being emitted
## v2.19.3
* fix: Passing an Activity when presenting surveys is now optional
## v2.19.2
* fix: Corrected the stopRecording function
* fix: Addressed a minor memory leak
## v2.19.1
* fix: Memory leak when presenting surveys from multiple activities
## v2.19.0
* add: Updated WebSDK to v2.37.1
* add: Support for new Rank Order question type
* add: Response piping support
* fix: Improved keyboard behavior for text input questions
* fix: Improved survey dismiss behavior under certain app state changes
* fix: Improved Android activity management for multiple app activities
## v2.18.5
* add: Updated WebSDK to v2.34.0
* add: New property to add space on screen below surveys
* fix: Improved keyboard behavior for text input questions
* fix: Improved survey dismiss behavior under certain app state changes
## v2.18.4
* fix: Improved low-memory handling for session replays
## v2.18.3
* fix: Crash that could occur during replays and device rotation
* fix: Surveys are now masked during replays
## v2.18.2
* add: Made the SDK version available to host applications
* fix: Improved replay masking performance
## v2.18.1
* add: Modals are now included in session replay recordings
## v2.18.0
* add: Additional Sprig lifecycle events available to monitor
* add: Web views are now included in session replay recordings
* fix: Session replay attached to surveys are only uploaded after a question has been answered
* fix: Increase display size of tap gesture
* fix: Start-up performance optimizations
## v2.17.8
* fix: Fix for survey closing on screen rotation.
## v2.17.7
* fix: Fix for bug that was keeping surveys displayed after the user tapped close.
## v2.17.6
* fix: Improve memory performance by recycling bitmaps, only start Session Replay when event tracked
## v2.17.5
* fix: update SURVEY\_CLOSED callback to provide initiator 'close.click' if dismissed by tapping out of study
## v2.17.4
* add: support for matrix questions
* fix: clear activity reference in onActivityPaused
## v2.17.3
* fix: application context fallback for WebView when activity context is unavailable
## v2.17.2
* add: reactFragmentActivity to configure method to better support React Native
## v2.17.1
* fix: Prevent web sdk reset on initial load
* chore: Improved internal logging
* chore: Update web sdk to 2.30.1
## v2.17.0
* add: Session Replay support
## v2.16.6
* chore: Update web sdk to 2.28.1
## v2.16.5
* fix: Escape single quotes in event names
## v2.16.4
* add: None of the Above question option for MCMS questions
## v2.16.3
* add: `x-ul-package-version` header to report mobile SDK plugin versions
* fix: Add network status listener to handle disconnects
## v2.16.2
* fix: reduce delay in subsequent survey presentations
* fix: hold weak reference to provided activity for improved memory management
## v2.16.0
* add: Add `dismissActiveSurvey()` function to dismiss any visible surveys
* add: Add a `QUESTION_ANSWERED` event that is emitted after the user answers a question
* chore: Update LICENSE
## v2.15.2
* fix: Improve right-to-left language formatting
## v2.15.1
* fix: Load `shouldDismissOnPageChange` before notifying listeners that the SDK is ready
* fix: Resolve race condition with `shouldDismissOnPageChange` when event is tracked before the SDK is ready
* fix: `setPreviewKey` was not working because of old web sdk version
* chore: Update web sdk to 2.24.4
## v2.15.0
* fix: Prevent a crash if loading the bundled JS fails. Only fixes the crash on Android 26+
* add: Add support for SDK event listeners
* add: Add `setPreviewKey` method deep linking
* chore: Update the test app to allow setting the user ID and properly log the user out
## v2.14.0
* add: Add a callback to `EventPayload` that allows surveys to be suppressed
* chore: Update web sdk to 2.24.0
## v2.13.1
* fix: Handle multiple events being tracked with \`dismissOnPageChange\`\` in user navigation
* chore: Update web sdk to 2.23.2
## v2.13.0
* add: Add support for \`dismissOnPageChange\`\` to not show surveys after navigation
* chore: Update web sdk to 2.21.7
## v2.12.1
* fix: Prevent the SDK from crashing when running on a known bad version of Chrome
* chore: Update web sdk to 2.21.6
## v2.12.0
* fix: Update the publishing action to use the correct publishing plugin
* add: Add new optional parameter to configure function
* chore: Update gradle plugin version to 7.2.0
* chore: Updated auto publishing steps in automation
* chore: Update web sdk version to 2.21.3
## v2.11.0
* fix: Prevent a crash when attempting to show a second survey with an initial survey still showing
## v2.10.0
* fix: Gracefully handle process death
* add: Optimizely Integration
* chore: Updated web sdk to 2.20.0
## v2.9.0
* chore: Updated web sdk to 2.19.5
## v2.8.0
* fix: Handle no callback provided on track event
* add: Support for required questions
* chore: Updated web sdk to 2.19.1
## v2.7.0
* add: Support event properties
## v2.6.10
* chore: Updated web sdk to 2.17.5
## v2.6.9
* chore: Updated Material and AppCompat libraries
## v2.6.8
* chore: Improved release automation
## v2.6.7
* fix: Check that activity is active before presenting survey
## v2.6.6
* chore: Updated web sdk to 2.17.2
## v2.6.5
* fix: Gracefully handle empty attributes
## v2.6.4
* add: Support for identifyAndSetVisitorAttributes
* add: Support Other Specify and rating scale questions
* chore: Updated web sdk to 2.17.1
## v2.6.3
* add: setPartnerAnonymousd, setVisitorAttributes and removeVisitorAttributes
* fix: Edge case where queued up function calls were being cleared near initialization
## v2.6.2
* chore: Updated web sdk to 2.16.20
## v2.6.1
* fix: Set webview background color to transparent
* fix: Reset webview after presenting a survey
* add: Handle device rotation
* chore: Removed coroutine dependencies
## v2.6.0
* chore: Updated LICENSE
* chore: Updated web sdk to 2.15.5
# Flutter Changelog
Source: https://docs.sprig.com/docs/developer-center/sdk-changelog/flutter-changelog
# SDK Changelog
Source: https://docs.sprig.com/docs/developer-center/sdk-changelog/index
Explore records of changes made to your specific Sprig SDK platform, including bug fixes, new features, etc.
Changelogs:
1. [Web Changelog](/docs/developer-center/sdk-changelog/web-changelog)
2. [Android Changelog](/docs/developer-center/sdk-changelog/android-changelog)
3. [iOS Changelog](/docs/developer-center/sdk-changelog/ios-changelog)
4. [React Native Changelog](/docs/developer-center/sdk-changelog/react-native-changelog)
5. [Flutter Changelog](https://pub.dev/packages/sprig_flutter_plugin/changelog)
6. [Segment iOS Changelog](https://github.com/UserLeap/analytics-swift-sprig/releases)
7. [Segment Android Changelog](https://github.com/UserLeap/analytics-kotlin-sprig/releases)
8. [Segment React Native Changelog](https://github.com/UserLeap/analytics-react-native-plugin-sprig/releases)
## Understanding SDK changelog urgency and impact
Sprig SDK release notes use three related signals so you can decide whether and how soon to upgrade:
| Signal | Answers | Where it appears |
| :- | :- | :- |
| **Recommended if you use** | Does this release affect me at all? | Once per release, directly under the version number (August 2026 onward) |
| **Upgrade urgency** | How soon should I upgrade? | Once per release |
| **Impact** | What happens if I stay on the old version? | On meaningful change bullets, and as a short summary on higher-urgency releases |
They often move together, but they are not the same. **Recommended if you use** describes who is affected. **Impact** describes the blast radius. **Urgency** describes when to act.
New features appear frequently. A new feature alone does **not** usually mean you must upgrade.
Here is where each signal appears on an SDK changelog:
1. **Recommended if you use** — who the release applies to, shown under the version number.
2. **Upgrade urgency** — Critical, High, or Low, shown once per release.
3. **Impact tag** — security, behavior, or performance, shown on the change it affects.
### Recommended if you use
Releases carry one **Recommended if you use** line under the version number, naming the features, question types, or integration surfaces that release touches. It is a filter, not a rating: if nothing in that line is part of your setup, the release almost certainly does not need your attention.
| Example line | Read it as |
| :- | :- |
| **Recommended if you use:** Session Replay | Only relevant if you have Session Replay enabled |
| **Recommended if you use:** Carry Forward, Validated Text questions, or Feedback studies | Relevant if any one of the three applies to you |
| **Recommended if you use:** Session Replay in SwiftUI apps on iOS 26 or later | Narrowed to a platform and integration method, not just a feature |
| **Recommended if you use:** all customers | No filtering; everyone should upgrade |
Pair it with urgency: the line tells you **whether** a release applies, and urgency tells you **when** to act on it.
This line is published on releases from August 2026 onward. Older releases do not carry it, so for those, fall back to the change bullets and impact tags.
### Upgrade urgency
Every release has one urgency rating. If a release includes several changes, the rating reflects the **most serious** change in that release.
| Urgency | Meaning | What you should do |
| :- | :- | :- |
| **Critical** | Security exposure; data loss or corruption; crash; a generally available feature fully broken | Upgrade as soon as practical |
| **High** | Incorrect survey logic or progression; host-app or host-page regression; a major feature broken for many customers | Upgrade in your next planned release window |
| **Low** | Visible defects with a workaround or a narrow blast radius; polish; opt-in or coming-soon features | Upgrade when convenient |
#### Examples
| Change | Urgency | Why |
| :- | :- | :- |
| XSS prevention on Button URLs | Critical | Security exposure |
| Consent/legal or Skip Logic evaluation corrected | High | Wrong questions may have been shown; collected responses may be affected |
| SDK overwrites host page body background | High (web embeds) | Can break styling on your site |
| Dependency updates with no practical embed exposure | Low | Hygiene; low need to act immediately |
### Impact tags
Impact tags highlight changes that affect **behavior, data quality, security, host integration, or noticeable performance**. Most changelog bullets have **no** impact tag. That usually means polish or presentation.
| Tag | Means the change involves… | Example |
| :- | :- | :- |
| `[impact: security]` | XSS, CSP, embed isolation, or actionable security dependency fixes | Prevent XSS for Button URLs |
| `[impact: behavior]` | Wrong survey flow; missing or wrong questions; response capture; host-app or host-page breakage; crashes | Consent/legal Skip Logic correction |
| `[impact: performance]` | Replay/heatmap performance, memory, battery, extra network calls, or UI freezes | Duplicate replay captures prevented |
| *(no tag)* | Spacing, alignment, hover states, copy, or presentation | Alignment of selection boxes in Multiple Choice |
Some releases also include a one-line **Impact** summary, for example:
**Impact:** Surveys with Skip Logic could advance incorrectly. This release corrects evaluation for consent/legal and Multiple Choice logic.
That sentence is written for **Critical**, **High**, and **Low** releases.
### Impact vs urgency
| | **Impact** | **Urgency** |
| :- | :- | :- |
| Question | What happens if I don’t upgrade? | How soon should I upgrade? |
| About | Nature of the change and the blast radius | When to act |
| Values | security / behavior / performance / none | Critical / High / Low |
The same change can matter differently depending on how you use the SDK:
* A body-background fix may be **High** for web page embeds, but less urgent inside a native WebView.
* A self-host packaging change may be **High** for customers who mirror SDK assets, and **Low** if you load from the Sprig CDN.
### New features
Sprig releases new functionality frequently, upgrade when you want to take advantage of improvements:
* Plain `add:` entries (new question types, capabilities marked coming soon, features you must enable) are usually **Low**.
* Upgrade for a feature when *you* want that capability, the timeline is up to you.
* If a release mixes a new feature with a meaningful fix, follow the **urgency** and **impact** of the fix.
### How to use this when upgrading
1. Scan **Recommended if you use** on releases newer than your current version, and skip the ones that name nothing you use.
2. Read **Upgrade urgency** on the releases that remain.
3. Skim **Impact tags** (security, behavior, performance) and the Impact summary on Critical and High releases.
4. Plan **Critical/High** upgrades into your next release window.
# iOS Changelog
Source: https://docs.sprig.com/docs/developer-center/sdk-changelog/ios-changelog
**How to read this changelog:** [Understanding SDK changelog urgency and impact](/docs/developer-center/sdk-changelog)
## v4.36.1
**Recommended if you use:** Surveys on iPad
* fix: Fix for survey layout issue when resizing the host app on iPad.
## v4.36.0
**Recommended if you use:** URL Prompt question type
* chore: Updated the bundled Web SDK to [v2.53.0](/docs/developer-center/sdk-changelog/web-changelog#v2-53-0), which carries survey enhacements into this release.
* add: \[impact: behavior] Added the ability to launch an in-app web browser for URL Prompt question types.
* add: Added new lifecycle event displayInAppBrowser which fires when the in-app experience is triggered.
## v4.35.0
**Recommended if you use:** survey lifecycle events
* chore: Updated the bundled Web SDK to [v2.51.0](/docs/developer-center/sdk-changelog/web-changelog#v2-51-0), which carries its survey and Session Replay fixes into this release.
* add: \[impact: behavior] Refactor of the survey lifecycle events for better accuracy with the addition of the new surveyReturned event, the removal of surveyWillPresent, a change to when the surveyAppeared emits and the addition of the new surveyDidNotAppear event.
* add: Passing the surveyId of the previous survey when a previosSurveyAvailable state is returned.
## v4.34.0
**Recommended if you use:** Session Replay in SwiftUI apps on iOS 26 or later
* add: Added SwiftUI support for text and image capture in session replays when running on iOS26 or above.
## v4.33.1
* chore: Updated WebSDK to v2.49.0.
## v4.33.0
* chore: Updated WebSDK to v2.48.2.
* add: questionAnswered lifecycle event added.
## v4.32.3
* chore: Changes to error logging.
## v4.32.2
* chore: Removed WebSDK logging.
## v4.32.1
* chore: Updated WebSDK to v2.46.1.
## v4.32.0
* chore: Updated WebSDK to v2.46.0.
## v4.31.0
* chore: Updated WebSDK to v2.45.0.
* fix: Fix for issue that was causing a white bar at the bottom of surveys when in dark mode.
* fix: Fix for survey height and animation issues.
## v4.30.0
* chore: Updated WebSDK to v2.44.0.
## v4.29.0
* chore: Updated WebSDK to v2.43.0.
## v4.28.0
* chore: Updated WebSDK to v2.42.1.
* add: Returning new previousSurveyReady survey state.
* add: Logging enhancements.
## v4.27.3
* add: Added additional survey state logging.
## v4.27.2
* add: Additional debug logging for surveys.
## v4.27.1
* fix: For for sliding surveys when the keyboard is displayed.
## v4.27.0
* chore: Updated WebSDK to v2.41.3.
* add: Updates to survey transition animations.
* add: Support for Display Logic.
## v4.26.2
* chore: Changed the minimum supported iOS version to 15.0.
## v4.26.1
* add: Survey animation enhancements.
* add: Updated WebSDK to v2.40.3.
## v4.26.0
* add: Support to pause and unpause surveys.
## v4.25.2
* add: Updated WebSDK to v2.39.3.
* add: Support for Conversational surveys.
## v4.25.1
* add: Updated WebSDK to v2.37.1.
* chore: Changed the mimimum supported iOS version to 16.0.
* fix: Fixed issue where backgrounds for tab bars and alert views did not display in replays for iOS26
## v4.25.0
* add: Updated WebSDK to v2.36.1.
* add: Support for new Rank Order question type.
* add: Response piping support.
* add: Removal of native modals coming from WKWebViews in Sprig replays.
* fix: Visual and stability improvements to the Sprig Replays experience.
* fix: Fix for surveys partially loading.
## v4.24.7
* add: Updated WebSDK to v2.34.0.
* add: Added the ability to capture SwiftUI text and images as images for Session Replays.
* add: Added the SDK version to the debug logging output.
* fix: Removed surveyDimensions lifecycle event that was not being emitted.
* fix: Change to the way images are fed to the video writer for Session replays rendering.
## v4.24.6
* fix: Fix for issue that prevented surveyClosed event from firing.
* fix: Fix for issue where SDK would crash if passed a non String, Int or Bool value in the properties of a track event call.
## v4.24.5
* fix: Fix for issue that was causing irregular survey height for initial question.
* fix: Fix for issue where surveys would become partially dismissed if the keyboard was initially showing.
* add: Made the SDK version available to host applications.
* add: Added the ability for host applications to subscribe to a logging event for more detailed messages from the SDK.
## v4.24.4
* fix: Changed logic in replays to only truncate text if it is masked.
## v4.24.3
* fix: Fix for issue where dismiss on page change was executed when the current view controller could not be retrieved.
* fix: Fix for issue where two track events in rapid succession could cause a survey to dismiss.
* fix: Fix for issue where a session replay could be stopped if the user quickly answered a question and then closed the survey.
## v4.24.2
* add: Uploading of partial session replay clips after capture has been stopped due to time on main thread exceeding the threshold.
## v4.24.1
* add: Added new trackAndPresent and present public functions that allow client apps to present surveys without passing in a view controller.
* add: Added retrying to configure the SDK when there is not initially connectivity.
* add: Added respecting of content mode for images in session replays.
* fix: Added masking of images captured by the device camera in session replays.
* fix: Fixed issue that was preventing the passed block from being called when calling trackAndPresent.
## v4.24.0
* add: Allow capturing of WKWebViews in session replays when unmasked.
* fix: Prevent potential retain cycle if track event is called but config is never called.
* fix: Fix for scenario where dismissing a second survey stops session replay capture triggered from an initial survey.
## v4.23.10
* add: Support for the new session replay privacy controls (basic / moderate / strict / mask classes / unmask classes).
* fix: Fix race condition which prevents surveys from displaying when calling presentSurvey after a delay
## v4.23.9
* fix: Fix for bug that was keeping surveys displayed after the user tapped the close button.
## v4.23.8
* fix: Fix for race condition that could potentially cause blank surveys.
## v4.23.7
* fix: Fix for session replays ignoring max duration value from server.
## v4.23.6
* fix: Fix for session replays rendering issue.
## v4.23.5
* add: Baseline support for SwiftUI in session replays.
## v4.23.4
* fix: Fixed issues with session replays.
## v4.23.3
* Interface fix
## v4.23.2
* add: Functionality for React Native iOS replays
## v4.23.1
* fix: Fix for threading issue triggered by config being called multiple times
## v4.23.0
* add: Support for accordion display matrix questions.
## v4.22.3
* add: Check for available disk space before initiating session replay.
## v4.22.2
* add: Support for rendering of server images in session replays.
* fix: Fix for crash when calling multiple SDK functions from background threads.
## v4.22.1
* add: Session Replay fidelity enhancements around tinting symbols and text layout.
## v4.22.0
* add: Stability and performance enhancements for Session Replays.
## v4.21.9
* fix: Support survey delays greater than 2 seconds due to WebView limitations
## v4.21.8
* fix: Added thread validation when calling track event.
## v4.21.7
* add: Replays: Added the ability to change SPS in the server config.
## v4.21.6
* add: Replays: Added the ability to mask views based on class names.
* fix: Replays: Stop touch capture on keyboard when displaying.
## v4.21.5
* add: Ability to turn off session replay capture.
* fix: Duplicate event listener callbacks fixed.
## v4.21.4
* add: Privacy Manifest.
* fix: Added logic to dimiss active survey if it is never presented.
## v4.21.3
* fix: Revert top level UIViewController check.
## v4.21.2
* fix: Small bug fixes.
## v4.21.1
* fix: Fix for endpoint issue.
## v4.21.0
* add: Session replays.
* fix: Prevent config from happening if it has already been called.
* fix: Escape single quotes in eventName.
## v4.20.2
* add: `x-ul-package-version` header to report mobile SDK plugin versions
* fix: set default `cssString` in getBackgroundColor to prevent regex match failing
## v4.20.1
* fix: Added missing JS files
## v4.19.2
* fix: calling track() from background thread would sporadically cause a SIGSEGV
* chore: still on web sdk 2.24.4
## v4.19.1
* fix: `setPreviewKey` was not working because of old web sdk version
* chore: update web sdk to 2.24.4
## v4.19.0
* add: add `setPreviewKey` interface method for customer to set previewKey via deep link
* fix: execution order of custom lifecycle event handlers
* fix: dismissOnPageChange event race condition for events fired before `sdkReady`
* fix: Webview bottom background color based on custom styles configured for survey
* chore: update web sdk to 2.24.2
## v4.18.0
* add: support for isOverride flag to allow overriding experiments while integrating with Optimizely
* add: support for survey lifecycle events
## v4.17.0
* add: added a showSurveyCallback to allow dynamically manage whether to show the survey or not
* fix: fixed a issue that results in a UI blocking routine introduced from 4.15.0
* chore: update web sdk to 2.24.0
## v4.16.0
* add: add integrateOptimizelyExperiments in the public SprigAPI
* chore: update to web sdk 2.23.2
## v4.15.0
* add: add dismissOnPageChange functionality to iOS
* add: add private interface methods for importing LaunchDarkly flag to variation index mapping
* chore: update to web sdk 2.23.0
## v4.14.0
* add: add additional interface for boolean and number types for setVisitorAttribute
* fix: fix an issue preventing scrolling after answering an open text question
* chore: update to web sdk 2.21.7
## v4.13.0
* add: Add new optional parameter to configure function
* chore: remove storage.swift
* chore: add ios legacy build automation
* chore: update to web sdk 2.21.3
## v4.12.1
* New EventPayload object to simplify calling track methods available for ObjC projects
* Allows public methods (excluding displaySurvey and other UI methods) to be called from a background thread
* Uses web 2.19.7
## v4.12.0
* New EventPayload object to simplify calling track methods
* Uses web 2.19.7
## v4.11.1
* Fixed an issue in text url prompt that prevents opening in external browser
## v4.11.0
* Added mobile trigger delay and optimizely integration
* Bug fixes and improvements
## v4.10.0
* Added required questions in the sdk
* Bug fixes and improvements
## v4.9.0
* Added event properties in the sdk
* Bug fixes and improvements
## v4.8.6
* Built using xcode 14. Bitcode is removed in xcode 14, please update your build environment for compatibility. Xcode 13 compatible builds will be available in a later release.
* Bug fixes and improvements
## v4.8.5
* Bug fixes and improvements
## v4.8.4
* Added a public api method trackAndPresentWithEventName that allows presenting survey immediately after tracking an event
* Bug fixes and improvements
## v4.8.3
* Added a public api method setVisitorAttributes that allows setting user id and partner anonymous id
## v4.8.2
* Added a public api method to track event with optional parameters userId and partner anonymous id
* Gracefully handle configure from being called multiple times
## v4.8.1
* Added an additional public api for setting the anonymous id from partner's integration
## v4.8.0
* Added support for new question types, functionalities and bug fixes
* removed presentDebugSurvey
* deprecated the NSNumber visitorIdentifier in preference to the String visitorIdentifierString
## v4.7.0
* license update
* bug fixes and improvements
## v4.6.0
* support SPM
## v4.5.0
* built sdk using xcframework
## v4.4.4
* fixed an sdk versioning issue that omitted the change in 4.4.3
## v4.4.3
* removed arm64 from excluded architecture to support simulator builds
## v4.4.2
* Fixed reported SDK version
* Security improvements
## v4.4.1
* Built with Xcode 13.0 (13A233)
## v4.4.0
* New Sprig namespace, you can now import and use the Sprig singleton
* Built with Xcode 12.5.1 (12E507)
## v4.4.0-beta
* New Sprig namespace, you can now import and use the Sprig singleton
* Built with Xcode 13.0 beta (13A5155e)
## v4.3.0-beta
* Built with Xcode 13.0 beta (13A5155e) which fixes the "Unable to use malformed module source info" build error
## v4.3.0
* Added support for text url prompt, a new question type that allows external link with informational title and body text.
## v4.2.1
* Fixes bug: When visitor id changes when a survey is in progress, the responses for that survey should be associated with the visitor id at the time the survey was delivered.
## v4.2.0
* Added support for multiple choice multi-select skip logic
## v4.1.1
* Bug fixes and improvements
## v4.1.0
* Added the ability to dynamically control the question text and thanks card text from dashboard settings
## v3.2.0
* Support visitorId as string type
* Improved network performance when app is backgrounded
## v3.1.1
* Included i386 architecture to framework
## v3.1.0
* Added setVisitorAttributes(\_ attributes: \[String: String]) which allows setting multiple attributes at a time, saving network round trips
* Added removeVisitorAttributes(\_ attributes: \[String])
## v3.0.0
* Updated UserLeap class to be visible to Objective-C projects
* UserLeap.visitorIdentifier type has been changed from Int? to NSNumber?
* Reachability class which was erroneously public is now private
* Calling UserLeap init() is no longer allowed, please access through the singleton shared method
## v2.3.3
* Build with Xcode 12A6163b
## v2.3.3
* Fixed bug with multiple choice routing logic
* Built with Xcode 12 beta 2, Swift 5.3
## v2.3.2
* Improved implementation of UserLeap.shared.setLocale()
## v2.3.1
* Added UserLeap.shared.setLocale() so clients can override static text localization
## v2.3.0
* Added localization for ja, ko, fr, ru, zh, de, hi
## v2.2.0
* Allow visitors to see and respond to the same survey if the customers wants (done through the dashboard)
## v2.1.0
* Added NPS question type support
## v2.0.0
* Change framework name to UserLeapKit so it doesn't conflict with class UserLeap
## v1.1.0
* Enabled Module Stability
* Added disableNetworkAccess parameter
## v1.0.2
* Bump, no changes
## v1.0.1
* Fixed: Presenting the debug survey before the SDK finishes initializing can cause non-main-thread UI operations
## v1.0.0
* The first version
# React Native Changelog
Source: https://docs.sprig.com/docs/developer-center/sdk-changelog/react-native-changelog
**How to read this changelog:** [Understanding SDK changelog urgency and impact](/docs/developer-center/sdk-changelog)
## v4.4.0
**Recommended if you use:** URL Prompt question type
* chore: Updated the bundled iOS SDK to [v4.36.1](/docs/developer-center/sdk-changelog/ios-changelog#v4-36-1) and Android SDK to [v2.30.1](/docs/developer-center/sdk-changelog/android-changelog#v2-30-1)
* add: \[impact: behavior] Added the ability to launch an in-app web browser for URL Prompt question types.
* add: Added new lifecycle event displayInAppBrowser which fires when the in-app experience is triggered.
## v4.3.0
**Recommended if you use:** survey lifecycle events
* chore: Updated the bundled iOS SDK to [v4.35.0](/docs/developer-center/sdk-changelog/ios-changelog#v4-35-0) and Android SDK to [v2.29.0](/docs/developer-center/sdk-changelog/android-changelog#v2-29-0)
* add: \[impact: behavior] Refactor of the survey lifecycle events for better accuracy with the addition of the new surveyReturned event, the removal of surveyWillPresent, a change to when the surveyAppeared emits and the addition of the new surveyDidNotAppear event.
* add: Passing the surveyId of the previous survey when a previousSurveyReady state is returned.
## v4.2.0
**Recommended if you use:** Session Replay
* chore: Updated the bundled iOS SDK to [v4.34.0](/docs/developer-center/sdk-changelog/ios-changelog#v4-34-0) and Android SDK to [v2.28.0](/docs/developer-center/sdk-changelog/android-changelog#v2-28-0), adding SwiftUI Session Replay capture on iOS 26 and wireframe replay recording on Android
## v4.1.1
* chore: Upgrade iOS SDK to 4.33.1
* chore: Upgrade Android SDK to 2.27.2
* fix: Fix for crash on iOS related to Sprig lifecycle events.
## v4.1.0
* chore: Upgrade to React Native New Architecture.
* add: Support for Sprig events.
## v4.0.0
* chore: Upgrade to React Native .85 and React 19.2.3.
## v3.3.0
* chore: Upgrade to React Native .83 and React 19.2.
## v3.2.1
* chore: Upgrade iOS SDK to 4.32.3
* chore: Upgrade Android SDK to 2.26.2
## v3.2.0
* chore: Upgrade iOS SDK to 4.32.2
* chore: Upgrade Android SDK to 2.26.1
## v3.1.0
* chore: Upgrade iOS SDK to 4.30.0
* chore: Upgrade Android SDK to 2.24.0
* Fix: Text not being reflected in session replays.
## v3.0.0
* chore: Update React Native to .81.
* fix: Removed support for lifecycle events.
## v2.21.0
* chore: Upgrade iOS SDK to 4.29.0
* chore: Upgrade Android SDK to 2.23.0
## v2.20.0
* chore: Upgrade iOS SDK to 4.27.3
* chore: Upgrade Android SDK to 2.22.1
## v2.19.2
* chore: Upgrade iOS SDK to 4.26.2
* chore: Upgrade Android SDK to 2.21.2
## v2.18.9
* chore: Upgrade iOS SDK to 4.25.2
* chore: Upgrade Android SDK to 2.19.5
## v2.18.8
* chore: Upgrade Android SDK to 2.19.3
## v2.18.7
* chore: Upgrade iOS SDK to 4.25.1
* chore: Upgrade Android SDK to 2.19.0
## v2.18.6
* chore: Upgrade iOS SDK to 4.24.7
* chore: Upgrade Android SDK to 2.18.4
## v2.18.5
* chore: Upgrade iOS SDK to 4.24.3
* chore: Downgrade Android SDK to 2.17.8
## v2.18.4
* chore: Upgrade iOS SDK to 4.24.1
* chore: Upgrade Android SDK to 2.18.0
## v2.18.3
* chore: Upgrade iOS SDK to 4.23.10
* chore: Upgrade Android SDK to 2.17.8
## v2.18.2
* chore: Upgrade iOS SDK to 4.23.7
* chore: Upgrade Android SDK to 2.17.6
## v2.18.1
* chore: Upgrade iOS SDK to 4.23.7
* chore: Upgrade Android SDK to 2.17.6
## v2.18.0
* add: Session replay functionality.
## v2.17.1
* fix: new arch crash
* chore: Upgrade iOS SDK to 4.23.0
## v2.17.0
* add: Matrix question support
* chore: Upgrade Android SDK to 2.17.4
## v2.16.2
* chore: Upgrade iOS SDK to 4.22.1
* chore: Upgrade Android SDK to 2.17.3
## v2.16.1
* chore: remove method overloads from Android code
* chore: Upgrade Android SDK to 2.17.2
## v2.16.0
* add: Session Replay support for React Native
* chore: Upgrade iOS SDK to 4.21.8
* chore: Upgrade Android SDK to 2.17.0
## v2.15.6
* chore: Upgrade iOS SDK to 4.21.4
## v2.15.5
* chore: Upgrade Android SDK to 2.16.5
* chore: Upgrade iOS to 4.21.1
## v2.15.4
* add: `x-ul-package-header` support for plugins
* chore: Upgrade Android to 2.16.4
* chore: Upgrade iOS to 4.20.1
* chore: Update LICENSE
## v2.15.3
* fix: Calling iOS track() from background thread would sporadically cause a SIGSEGV
* chore: Upgrade iOS to 4.19.2
## v2.15.2
* chore: Bumped because 2.15.1 was incorrectly published
## v2.15.1
* add: `setPreviewKey` method to enable test a study on React Native
* chore: Bumped iOS version to 4.19.1
* chore: Bumped Android version to 2.15.1
## v2.15.0
* fix: (ios) Fix an issue preventing scrolling after answering an open text question
* fix: (android) Prevent the SDK from crashing when running on a known bad version of Chrome
* fix: (ios) Fixed a issue that results in a UI blocking routine introduced from 4.15.0
* add: (ios) Add additional interface for boolean and number types for setVisitorAttribute
* add: (ios/android) Add `dismissOnPageChange` functionality to iOS and android
* add: (ios) Add private interface methods for importing LaunchDarkly flag to variation index mapping
* add: (ios) Add integrateOptimizelyExperiments in the public SprigAPI
* add: (ios) Added a showSurveyCallback to allow dynamically manage whether to show the survey or not
* add: Add a callback to `EventPayload` that allows surveys to be suppressed
* chore: Updated the example app to be able to depend on the local ios build
* chore: Bump ios version to 4.17.0 and Android version to 2.14.0
## v2.14.1
* chore: Improved release process
## v2.14.0
* chore: Improved release process
## v2.13.0
* chore: Updated iOS version to 4.12.1
* chore: Updated Android version to 2.9.0
## v2.12.1
* chore: Updated iOS Version to 4.11.1
## v2.12.0
* fix: Fix stringifying attributes
## v2.11.0
* chore: Updated iOS Version to 4.11.0
## v2.10.0
* add: Support event properties
* chore: Updated Android Version to 2.8.0
## v2.9.0
* chore: Updated iOS version to 4.9.0
* chore: Updated Android Version to 2.7.0
## v2.8.4
* add: Improved typings
## v2.8.3
* fix: More permissive react and react-native version peerDependencies
## v2.8.2
* chore: Updated iOS Version to 4.8.6
* chore: Updated Android Version to 2.6.10
## v2.8.1
* chore: Updated react-native peer dependency to 0.68.2
## v2.8.0
* chore: Updated react-native peer dependency to 0.67.4
## v2.7.0
* fix: Removed RCTBridgeModule.h import for expo compatibility
* chore: Updated Android Version to 2.6.0
## v2.6.0
* chore: Updated LICENSE
* chore: Updated iOS Version to 4.7.0
# Segment Android Changelog
Source: https://docs.sprig.com/docs/developer-center/sdk-changelog/segment-android-changelog
# Segment iOS Changelog
Source: https://docs.sprig.com/docs/developer-center/sdk-changelog/segment-ios-changelog
# Segment React Native Changelog
Source: https://docs.sprig.com/docs/developer-center/sdk-changelog/segment-react-native-changelog
# Web Changelog
Source: https://docs.sprig.com/docs/developer-center/sdk-changelog/web-changelog
**How to read this changelog:** [Understanding SDK changelog urgency and impact](/docs/developer-center/sdk-changelog)
## v2.54.0
* chore: Upgrade Session Replay recorder (@rrweb/record) to v2.1.4
* chore: Update dependencies to address security vulnerabilities
## v2.53.0
* add: Option to display links in-app instead of in the mobile browser for In-Product Surveys (coming soon)
* add: Setting for allowing backwards navigation in Surveys and In-Product Surveys (coming soon)
* add: Rich text formatting available for Thank you screens (coming soon)
## v2.52.0
* add: Images for response options in Multiple Choice Multi-Select questions (coming soon)
## v2.51.3
**Recommended if you use:** Default Dark mode theme
* fix: \[impact: behavior] Dark mode default text color
## v2.51.2
**Recommended if you use:** Carry Forward
* fix: Carry Forward polish
## v2.51.1
**Recommended if you use:** Session Replay
* fix: \[impact: performance] Session Replay memory leak for link\[rel="preload"] elements
## v2.51.0
**Recommended if you use:** Validated Text questions, Feedback studies
* add: Carry Forward functionality (coming soon)
* add: Validated Text question enhancements (coming soon)
* fix: Improve presentation of the Feedback button border
## v2.50.0
* add: Add new Validated Text question type (coming soon)
## v2.49.1
* add: Allow custom text for Conjoint question "None of the above" option
* fix: UI adjustments for Conjoint questions
## v2.49.0
* add: Conjoint question type (coming soon)
* add: Dark mode support (coming soon)
* fix: In-Product Survey border issue with host application CSS
## v2.48.2
* fix: Improve presentation of NPS and Likert questions that use stars or smileys
## v2.48.1
* fix: Update alignment of selection box in Multiple Choice Single and Multi-Select questions
* fix: Improve presentation of NPS and Likert questions on mobile
* fix: Adds border radius to images in questions
* fix: Improve disabled/hover button colors and shade
## v2.48.0
* add: Update layout and navigation of Surveys
* fix: "Other" error state in Multi-Choice questions
* fix: Fixes for the setting to hide custom branding on Surveys
* fix: Alignment for answer options when they go beyond 1 line in Multiple Choice questions
* fix: Moved the survey close button for In-Product Surveys to accommodate images
* fix: Conversation format minor visual fixes
## v2.47.0
* add: Support for Survey Quotas (coming soon)
* add: Support for Image in Question (coming soon)
* add: Option to hide branding on Surveys (coming soon)
* fix: Remove CTAs on answered questions in Conversation surveys
* fix: Matrix questions in Surveys now expand horizontally if space is available when on desktop
* fix: In-Product Surveys now advance correctly honoring both Display Logic and AI Follow-up questions
## v2.46.1
* fix: Body background color is not transparent for SDK
## v2.46.0
* add: Display optional persona text beneath questions in Conversational surveys
* add: AI Follow-up Questions added to Rating scale, Single select, Multi select, NPS, Matrix, Rank Order questions
* add: Skip Logic now available for questions that have AI Follow-up Questions attached
* fix: Increased font size for text inputs in Conversational Surveys
* fix: Placeholder for Display Logic questions with attributes in the side-by-side preview
* fix: Likert/Rating Scale question visual and usability issues
## v2.45.0
* add: Support for complex logic evaluation in Display Logic and Skip Logic
## v2.44.1
* fix: Matrix question accordian format - page jumping when user interacts with list
* fix: Mobile hover state for Rating Scale questions
* fix: Rating Scale question responsiveness
* fix: Conversation format - AI Follow-up question format for submitted Open Text questions
* fix: Conversation format - Input styling for "Other" option in Multiple Choice Multi-Select questions
## v2.44.0
* add: AI Dynamic Questions
* fix: Conversational format close button padding
* fix: "Powered by Sprig" footer padding on In-Product Surveys
* fix: Race condition for Session Replay scheduling
* chore: Update vulnerabilites in transient dependencies
## v2.43.0
* fix: Consent/legal Skip Logic check correction
* fix: Multiple Choice Skip Logic correction
* fix: Multiple Choice Display Logic for skipped values
## v2.42.1
* fix: Survey padding on wide monitors
* fix: Display Logic for AI Follow-up Questions
* fix: Send "previous survey ready" event instead of "no survey" event when a survey is open
* fix: Performance enhancements for AI Follow-up Questions
* chore: Update vulnerabilities in transient dependencies
## v2.42.0
* fix: Last question too close to the bottom in Long-Form Surveys with multiple questions on a page
* fix: Rank order not auto-advancing to next question Long-Form Surveys with multiple questions on a page
* fix: Preview mode for AI Follow-up Questions
* chore: Remove calls to `window` in `Sprig.configure`
## v2.41.3
* fix: Captcha footer overlaps with "Powered by Sprig" line
* fix: AI Follow-up Questions not always presented
## v2.41.2
* add: Translation for "Other" options placeholder text
* fix: Study preview behavior for In-Product Surveys
* fix: Endpoint for preview of AI Follow-up Questions in In-Product Surveys
## v2.41.1
* fix: Alignment of Video/Voice buttons in Conversational UI
* fix: AI Follow-up question type fix for preview.
* fix: Spacing for LFS surveys with prototype URLs for mobile.
## v2.41.0
* add: Display Logic for attributes and Long-Form Surveys
* add: Support for the new AI Follow-up question type
## v2.40.4
* add: Re-initialization for Dashboard Previews
* fix: Conversational UI not loading or reset in Previews
## v2.40.3
* fix: Rank Order Question footer for Conversational UI for Android
## v2.40.2
* fix: Global scope environment creep
* fix: Mobile specific SDK builds
## v2.40.1
* add: Display Logic for surveys
* fix: Fix survey height for missing question types
## v2.40.0
* add: Attribute Piping for In-Product Surveys and Feedback Studies
* add: Make Long-Form Survey footer on mobile non-sticky
* fix: Fix survey height race condition
## v2.39.4
* add: Display asterisk for required Long-Form Survey questions
* add: Support `addResponseGroupMeta` config that allows adding metadata before submits
* add: Support `enableCspTrustedTypes` config that allows compatibility with CSP trusted-types directives
* fix: Add support for Android Play and Apple App Store links in Text/URL questions
* fix: Layout and interactions for MaxDiff questions on mobile (Long-Form Surveys only)
* fix: Layout of Long-Form Surveys on mobile
* fix: Matrix question accordions now collapse correctly on desktop
* fix: Prototype url not visible on mobile due to insufficient bottom padding on mobile
## v2.39.3
* fix: Fix continue button for rank order question
## v2.39.2
* fix: Build new deployment
## v2.39.1
* fix: Drag and drop for Web, iOS, and Android web
* fix: Conversational UI matrix, consent, text/URL question type fixes
* fix: Minor conversational UI fixes
## v2.39.0
* add: Conversational Surveys for Long-Form Surveys, In-Product Surveys, and Feedback Surveys
* fix: skip logic question type comparison
## v2.38.1
* chore: new combined release of sprig browser and sprig bundled
## v2.38.0
* add: MaxDiff Question Type (Long-Form Surveys only)
* fix: Open Text button behavior for non-required questions in Long-Form Surveys
## v2.37.1
* fix: Skip logic optimization for Long-Form Surveys
## v2.37.0
* add: Validation logic to Multiple Choice Multi-Select questions
* fix: Session Replay performance improvement
## v2.36.1
* fix: Consent legal card response piping fix
* fix: Better tracking for clicks of non-html elements in heatmaps
* fix: Whitespace regex for response piping
* fix: Improvements for drag and drop experienece in rank order questions on mobile
## v2.36.0
* add: question response piping for all survey types
* fix: add footer to open text questions in Long-Form Surveys
* fix: moved footer for open text questions above button for In-Product Surveys
## v2.35.0
* add: New Rank Order question type support
* add: Visual enhancements for Rating Scale and Text/URL questions
* add: Configuration for outstanding IndexedDB transactions limit for fine-grained memory control in Session Replay
* add: Long-form survey support
* fix: Ensure matrix usability on various screen widths/configurations
## v2.34.0
* add: Support pause/resume session replay functionality
## v2.33.3
* fix: Fix uncaught ResizeObserver error on closing survey
* fix: Extraneous network calls should not be made from subsequent surveys
* fix: Remove console.error invocations when IndexedDB operations fail
## v2.33.2
* fix: displaySurvey was not working in some cases
* add: Support for recording cross origin iframes
## v2.33.1
* fix: Race condition uploading heatmaps on page change.
* fix: Prevent SDK from sometimes unnecessarily uploading empty always-on replays
## v2.33.0
* add: Always-on replay support
## v2.32.11
* fix: consecutive mc dropdown would freeze screen
* fix: Video response questions would size incorrectly
* fix: Heatmaps on MPA was not uploading after page navigation
## v2.32.10
* fix: Prevent XSS for Button URLs
* fix: Check for IndexedDB supported by browser
## v2.32.9
* add: New config setting forceDirectEmbed
* fix: Fix for using the sdk in a sandboxed iframe
## v2.32.7
* fix: Sizing issue in sandboxed iframed and after matrix questions.
## v2.32.6
* fix: Address sizing issue, make question body scrollable
## v2.32.5
* fix: Properly compare past URLs for sandboxed instances
* fix: Revert question restyling
## v2.32.4
* fix: Fix dev environment banner overlap, open text centering, close button alignment
## v2.32.3
* chore: Add logs to checkPendingHeatmapsUrl
* fix: Don't resend attributes already sent in existing session
* fix: Fix skipping unanswered multiple choice single select questions if it has "answered" skip-logic rules
* fix: Fixes issue with clicks not being recorded for some elements on mobile safari.
* fix: Make question body scrollable, fix header and footer positions
* fix: Upload ready Heatmaps on initialization
## v2.32.2
* fix: Use trackPageUrl provided URL for sandboxed installations
* fix: Remove deprecated Upchunk console warning
## v2.32.1
* fix: add webpackIgnore for dynamic replay library import
## v2.32.0
* add: Support for mobile web and accordion display matrix questions.
## v2.31.6
* chore: updates import of rrweb to use dynamic import and removes usage of window\.Sprig.replayNonce
## v2.31.5
* chore: Improve debugging logs
## v2.31.4
* fix: Handle missing survey id when creating iframe
## v2.31.3
* fix: Address some indexedDB quota issues
* fix: Don't emit survey.willClose if no survey is displayed
* add: survey.id to more survey lifecycle events
## v2.31.2
* fix: Enable DOM metric thresholds even when not sampling for reporting
* fix: Improve replay storage error capturing
* fix: Prevent resize observer infinite loop
## v2.31.1
* fix: Update style instead of creating a new element if one already exists
* fix: Use Promise.all in replay cleanup for wider compatibility
## v2.31.0
* add: Renamed IndexedDB table and adds new store indices
* fix: Return early in initialization of recording fails to start
* refactor: Replaces IndexedDB package and shrink bundle size by half
## v2.30.4
* add: New performance metrics
## v2.30.3
* fix: take full snapshot to minimize look-back in heatmaps
## v2.30.2
* fix: track seen event only when survey view is visible
* fix: removed open text aria-label, added describedby
* fix: improve nps and rating scale button semantics
* fix: update styling for mobile feedback button studies
## v2.30.1
* add: preview banner to call out when viewing a preview mode study
* add: replayLibraryURL and upchunkLibraryURL config options enabling self-hosted dependencies
* fix: metadata href returning empty string
* refactor: Separates replay module with its own entry point.
## v2.30.0
* fix: NPS question iframe height after Matrix question
* add: trackPageView sends URL to view
* add: Add heatmaps capture when object received from events
* add: Sprig\_Scroll custom replay event
## v2.29.0
* add: Add method to customize feedback surveys
## v2.28.1
* fix: View CSS should accept from product config instead of global value
## v2.28.0
* add: FeedbackButtonLoaded lifecycle event
* add: hideRecordPrompt option for Video & Voice questions
* fix: Memory leak when closing survey
* fix: Improve Feedback animation and UI
* fix: Rebuild replay Dexie approach, improve cleanup
* chore: Reduce size of the view bundle
## v2.27.0
* add: Support for multiple choice questions with dropdown
* add: Support for rich text headers, descriptions and open text footers
* add: Show feedback button when received from pageURL event
* add: Call events/batch if survey opened while event tracked
* add: Adds properties accessible to mobile sdks for metrics reporting
* fix: Stop logging error when window\.parent.Intercom is inaccessible
* fix: Live preview restarts on first question when survey finished/closed
* chore: Add size limit validator to the build process
## v2.26.6
* fix: Mark Intercom data argument optional
## v2.26.5
* add: Clean up custom event info for replay analysis
* fix: setAttribute types to match what Sprig accepts for attribute values
* chore: Improve sentry error reporting
## v2.26.4
* add: SDK performance metrics
* add: Timed code block metrics
* add: Replay killswitch from performance limits
## v2.26.3
* add: Adds SDK logging
* fix: Add back support for cjs exports
* fix: Responsive display in sandboxed iframe
* fix: Show gradient and arrow when matrix has columns offscreen
* fix: Handle undefined tagName
* chore: Allow local cdn configurations
## v2.26.2
* add: none of the above multiselect option support
* fix: Add bundled version to the headers for diagnostics
* fix: Check browser quota before collecting replay events
* fix: Update thank you card footer styling
* fix: Fix build issues
* fix: Fix mobile SDK scaling in preview
* fix: Add right padding to matrix questions
* chore: Strip un-needed code from the sprig bundled package
* chore: Adds replay config info to sdk events
* chore: Port tests to different testing framework
* chore: Remove old testing framework
* chore: Better error reporting
* chore: Shrink down size for the shim bundle
## v2.26.1
* fix: Retrieve parent href if available, or fallback to view frame href
## v2.26.0
* fix: Requests canceled before being resolved when survey has been finished
* fix: Make SDK window height and width have smoother transition inbetween cards
* fix: Do not save html attributes in replay data
* add: Adds more custom event info for replay analysis
* chore: Remove cjs exports for build
## v2.25.1
* fix: Undo view parent href change to fix link preview
## v2.25.0
* add: Add new Matrix question type card
* add: Support SVG elements in no code CSS selector events
* add: surveyId to SurveyPresented and SurveyAppeared payloads
## v2.24.11
* chore: Update LICENSE
## v2.24.10
* fix: Pass headers in \_completeSessionReplay
* fix: Do not send trackPageUrl events when no url events are configured
## v2.24.9
* fix: More improvements to RTL formatting
* fix: Add try-catch to replay recordCustomEvent
## v2.24.8
* add: Add support for previewing language translations if passed through the SDK config
* add: Improves formatting/layout of RTL languages
## v2.24.7
* fix: Prevent retries requests when prior SDK request violates CSP
* add: Update Sprig brand logos for free plans
## v2.24.6
* fix: revert "add rrweb & upchunk to the bundle"
* add: Add public function \_generateVideoUploadUrl to allow mobile to generate URL
* add: Add public function \_completeSessionReplay to allow mobile to send completed mobile session replays
* add: Return surveyId and responseGroupUid after displaying questions
## v2.24.5
* chore: add rrweb & upchunk to the bundle
## v2.24.4
* fix: Fixes error from tracking custom events without recording active
* fix: QuestionAnswered event wasn't emitting because we weren't using the internal binded event emitter
* add: Exposes trackPageView function for triggering no-code events
* chore: Fix trackPageView error stacktrace and send page view storage in extraInfo parameter instead
## v2.24.3
* fix: Fixes bug with corrupted replays in Chrome when duplicating tabs
* fix: Fixes bug that caused replays to lose up to the most recent 30 seconds of data.
* fix: Improve accuracy of replay durations
* fix: During survey dismiss, remove survey container from its parent node, instead of document body
* chore: Add skip button css for voice + video skip button
* add: Pass userAgent info along with replay
* add: Inject custom sprig events into replay
* add: Upload replay events for IPS after question has been answered
* add: Emits question and its response after question submission
## v2.24.2
* fix: improved showSurveyCallback to send tracked events during the callback to the batch endpoint
* chore: centered text prompt question card to center buttons
* chore: updated the build/release process to upload source-maps to sentry
## v2.24.1
* fix: prevent additional pendingCaptures while waiting
* fix: batch events fetch to reduce memory load
* fix: catch uncaught transaction errors
* chore: updated testing env to test replay image capture
## v2.24.0
* fix: add and remove event listener for survey fading out
* add: Accepts new skip logic format
* add: New comparator types for mcss, mcms, and open text questions
## v2.23.6
* fix: wrap deletes and chunkUpload fetch in transactions
## v2.23.5
* fix: block reporting specific errors, return earlier in initializeReplay
## v2.23.4
* fix: remove non-actionable error report of storage init failure
## v2.23.3
* fix: capture failures when initializing indexedDB for replayStorage
* fix: delete previous db if found
## v2.23.2
* fix: send previewKey during /history and /submit endpoint calls
* fix: use Dexie for IndexedDB interactions, update tests
## v2.23.1
* fix: Add catches to indexDB interactions
* add: Accept Optimizely client to add notification listener
## v2.23.0
* fix: Renames rrweb script
* fix: Fixes shorter-than intended recordings
* add: Send replayDuration on replay upload
* add: Ability to integrate LaunchDarkly with Sprig SDK
* add: Track events with LaunchDarkly metadata, if integration is enabled
* add: Adds storage usage information to error reports
* add: Support for "after" and "before and after" replay captures
## v2.22.4
* fix: Prevent uploads of replays below duration threshold
* fix: Improves usage of indexedDB storage for replay info. Better handles storage limit errors
* add: Attempt to compress replays before uploading
## v2.22.3
* fix: Prevent uploads of replays below duration threshold
* fix: Fix whitespace calculation to include border and margin space
* fix: Emit the calculated height instead of the client height on SURVEY\_HEIGHT event
* fix: fix an issue when selector is invalid and sdk fails to process the no code events
## v2.22.2
* fix: Fix negative whitespace calculation for frame height
## v2.22.1
* fix: Improve performance of replay capture
* fix: Clear replay data when user logs out or visitor ID changes
* add: Add Electron support to open external url based on user's default browser
## v2.22.0
* fix: Handle invalid regex gracefully
* fix: Prioritize locally set config over dashboard provided config
* add: Session Replay: Controller and network/upload module. replaySettings config object. Capture session.
* add: Ability to test a new or draft study's trigger logic
* add: Add Electron support to open external url based on user's default browser
## v2.21.7
* fix: Prevent unintentionally skipping question if user cancel screen or AV permission mid-question
* fix: Set properties like UPDATES synchronously in sprig initialization
* fix: Handle invalid regex gracefully
## v2.21.6
* fix: Prevent share screen button to be clicked on multiple times
* add: Enable optional survey callback function when tracking events for an eligible survey to determine whether or not survey should be shown to visitor
* add: Add skip button on Start Task page for recorded tasks if the question is optional
## v2.21.5
* fix: Update typings generation to handle external modules
* chore: Cleaned up some browser package descriptions
* chore: Improve typings generation and validation
## v2.21.4
* fix: Updated typings for Sprig.dismissActiveSurvey() call to allow for no arguments
* fix: Fixed typings for previewSurvey and added fix for module resolution NodeNext
## v2.21.3
* fix: Progress bar on surveys was incorrect in some situations
* chore: skip rc tag creation if the release tag is already public
* chore: CSP blocked websocket / devserver connection which disable hot reloading
* chore: update the release merge to main process to run only when there's newer diffs than dev
* chore: added LICENSE.md and CHANGE\_LOG.md to sprig-browser as a build step
## v2.21.2
* chore: Cleaned up android automation errors and outdated files
* chore: Updates to build and release automation
* chore: Removed redundant styles.css file
## v2.21.1
* fix: styles.css was missing
## v2.21.0
* fix: Progress bar indicator showed incorrect progress
* fix: Consent legal red highlight did not show
* fix: "View Document" button missing on mobile surveys
* fix: Link preview wasn't showing properly
* add: Allow Text URL question type to have skipped button customized text
* chore: Periodically check for webcam/audio permissions when applicable
## v2.20.1
* fix: "Seen" event was not being sent which affected resurvey window
## v2.20.0
* add: UI framework rewritten to Preact 10.11.2 (from Hyperapp)
## v2.19.7
* fix: Check Optimizely.get() function is defined before invoking
## v2.19.6
* fix: When SDK is disabled, should return a valid config object
## v2.19.5
* fix: Surveys were not showing for NPM installs because of a faulty event listener
## v2.19.4
* fix: Pressing the spacebar was toggling Other:specify question types
## v2.19.3
* fix: When a survey with a delay is delivered, use the events/batch endpoint so subsequent events do not trigger surveys
## v2.19.2
* add: Support nonce for style tags
## v2.19.1
* fix: Voice & Video skip logic wasn't working because of faulty comparison
## v2.19.0
* add: Support required questions
## v2.18.3
* add: If enabled, read the Optimizely singleton and include experiments when tracking events
## v2.18.2
* fix: Provide default for event properties
## v2.18.1
* chore: Include preview mode in request headers
## v2.18.0
* add: Support event properties
## v2.17.5
* fix: Improve ontouchstart and ontouchend handling for multiple select options
## v2.17.4
* fix: Add wordbreak for very long words
* fix: Remove height restriction for multiple choice questions with lots of options
## v2.17.3
* fix: Likert number turned white on Safari browser after completing a likert star question
## v2.17.2
* fix: Prevent touchend() from being called twice which skipped a question on Android
## v2.17.1
* fix: Remove visual flicker in select components
* chore: Remove unused import
## v2.17.0
* add: Support for 'Other' options with text entry for single-select and multi-select questions
## v2.16.28
* add: Support likert question with stars and smiley labels
## v2.16.27
* fix: Recorded tasks events were not being emitted for websurveys
## v2.16.26
* fix: Properly destroy event listeners to better support multiple surveys showing in a single session
## v2.16.25
* add: Allow text entry for Consent/Legal questions
## v2.16.24
* fix: Revert change that made select box in Consent/Legal questions not selectable
## v2.16.23
* add: Allow Option (Specify) to be configurable
* chore: Disable error reporting with response JSON parsing fails
## v2.16.22
* chore: Automatically convert attributes with email key to !email
## v2.16.21
* add: Support 7-pt likert and more options
## v2.16.20
* add: Height update notification to event listeners
## v2.16.19
* fix: SDK installed via NPM had incorrect document heights
* add: Github actions support for deploying SDKs
## v2.16.18
* fix: Reset scroll position when moving to next question
* add: Internal SURVEY\_COMPLETED event for event listeners
## v2.16.17
* add: `showQuestionIdx` int into SDK config to show a specific question index (if exist)
* add: `useDesktopPrototype` boolean into SDK config to use the desktop version of embedded questions for link/email platforms
## v2.16.16
* fix: Transitioning from a "Screen only" permissions question to a "Screen + Audio" permission wasn't being detected properly
* fix: Stream wasn't terminating properly when going from a "Screen + Audio" to a "Screen + Audio + Video" question
## v2.16.15
* chore: Add `npm install` to build script
## v2.16.14
* fix: Autosizing of open text questions wasn't working properly on NPM installs
## v2.16.13
* fix: Wrong questionId was being passed to video player event listeners during response submission
* add: "View Prototype" button to recorded question type
## v2.16.12
* add: Upload spinner for video uploads
* add: Show permissions request when permissions type changes between questions
## v2.16.11
* fix: avStream wasn't stopping when it was the last question
* fix: Record UUID was not being updated properly
* fix: Subsequent recording questions weren't working
* fix: Various polishes and tweaks
## v2.16.10
* fix: Skip logic for recorded task when user gives up
## v2.16.9
* fix: Text entry boxes would lose focus shortly after being displayed
## v2.16.8
* fix: Video codec issue that was not working on safari/firefox
* fix: Video permission screen state transition now will skip to the next page for audio only, and will always show the video preview even if permission is previously given
* add: Upload card before thank you card when videos are uploading
* add: "Try again" button for retry permissions
## v2.16.7
* fix: Skip logic for multiple choice questions wasn't working
## v2.16.6
* fix: Addressed several issues with consecutive recorded task states
* add: Recorded task now can record and uploads multiple tasks with different permission settings
## v2.16.5
* add: Internal events for recorded task permission screen and recorded task start
## v2.16.4
* add: Log analytics events for video recorder
## v2.16.3
* fix: Add passthrough data to provide required fields
* fix: Fix check for video tracks
# Features by SDK Versions
Source: https://docs.sprig.com/docs/developer-center/sprig-sdk/features-by-sdk-version
## SDK Overview
Ensure that the Sprig SDK is up to date to take advantage of new features and bug fixes
**Note:** In the case of mobile SDKs, your end-users will need to update to the version of your mobile app that includes the SDK with the Sprig functionality you want to be available. Usually this means that you will need to release an updated version of your app on the Apple App Store or Google Play.
For more details about what's included in each version, see our [SDK Changelogs](https://docs.sprig.com/docs/developer-center/sdk-changelog/index).
## Features and SDK Versions
Not all product updates require updating SDKs but certain functionality, especially related to Replay recording, question types, and the survey-taking experience, usually does.
#### SDK Versions by Feature
Make sure to scroll to the right to see all major SDK types.
| Feature | Date | Web SDK | iOS SDK | Android SDK | React Native SDK | Flutter |
| :- | :- | :- | :- | :- | :- | - |
| Use in-app browser for links | Sept 2026 | v2.53.0 | v4.36.0 | v2.30.0 | Coming soon | Coming soon |
| Rich text on thank you cards | Sept 2026 | v2.53.0 | v4.36.0 | v2.30.0 | Coming soon | Coming soon |
| Carry Forward | Aug 2026 | v2.51.0 | v4.35.0 | v2.29.0 | v4.3.0 | 0.10.0 |
| Validated Text | Aug 2026 | v2.51.0 | v4.35.0 | v2.29.0 | v4.3.0 | 0.10.0 |
| Built-in Dark Mode (default CSS) | July 2026 | v2.49.0 | v4.33.1 | v2.27.2 | v4.33.1 | v0.9.1 |
| Image in Question | June 2026 July 2026 (mobile) | v2.48.0 | v4.33.0 | v2.27.0 | v4.1.1 | v0.8.0 |
| Updated question styling for Surveys, Feedback studies, and IPS | June 2026 July 2026 (mobile) | v2.48.0 | v4.33.0 | v2.27.0 | v4.1.1 | v0.8.0 |
| AI Follow-ups for more question types | June 2026 | v2.46.0 | v4.32.0 | v2.26.0 | v3.2.0 | v0.8.0 |
| Updated Conversation format styling | June 2026 | v2.46.0 | v4.32.0 | v2.26.0 | v3.2.0 | v0.7.0 |
| Complex Display Logic | May 2026 June 2026 (RN) | v2.45.0 | v4.31.0 | v2.25.0 | v3.2.0 | v0.7.0 |
| AI Dynamic Questions | April 2026 | v2.44.0 | v4.30.0 | v2.24.0 | v3.1.0 | v0.6.0 |
| AI Follow-up Questions | February 2026 | v2.41.0 | v4.27.0 | v2.22.0 | v2.20.0 | v0.4.0 |
| Display Logic | February 2026 | v2.41.0 | v4.27.0 | v2.22.0 | v2.20.0 | v0.4.0 |
| Attribute Piping | Jan 2026 (web) Feb 2026 (mobile) | v2.40.0 | v4.26.1 | v2.21.0 | v2.19.2 | v0.3.1 |
| Conversational Surveys | November 2025 | v2.39.1 | v4.25.2 | v2.19.4 | v2.18.9 | - |
| Validation for Multi-Select | October 2025 | v2.37.0 | v4.25.0 | v2.19.0 | v2.18.7 | - |
| Response Piping | Sept 2025 (web) Oct 2025 (mobile) | v2.36.0 | v4.25.0 | v2.19.0 | v2.18.7 | - |
| Rank Order Questions | Sept 2025 (web) Oct 2025 (mobile) | v2.35.0 | v4.25.0 | v2.19.0 | v2.18.7 | - |
| Always On Replays | Mar 2025 | v2.33.0 | Not supported | Not supported | Not supported | Not supported |
| Survey Card Styling Updates | Nov 2024 | v2.32.4 | v4.23.1 | v2.17.5 | v.2.18.1 | - |
| Matrix Accordion | Oct 2024 | v2.32.0 | v4.23.0 | v2.17.4 | v2.17.0 | - |
| Mobile Session Replays | Aug 2024 (iOS/Android) Dec 2024 (RN) | N/A | v4.22.2 | v2.17.6 | v2.18.0 | Not supported |
| Heatmaps GA | Sept 2024 | v2.30.3 | Not supported | Not supported | Not supported | Not supported |
| CSS Styling (Feedback) | Late May 2024 | v2.29.0 | Not supported | Not supported | Not supported | Not supported |
| Study Creation Improvements | May 2024 | v2.28.0 | v4.21.7 | v2.16.6 | v2.16.0 | - |
| Feedback Studies | April 2024 | v2.27.0 | Not supported | Not supported | Not supported | Not supported |
| None of the Above (Multi-Select) | January 2024 | v2.26.2 | v4.20.2 | v2.16.3 | v2.15.4 | - |
| Replay Analysis | January 2024 | v2.26.0 | Not supported | Not supported | Not supported | - |
| Matrix Questions | January 2024 | v2.25.1 | Not supported | Not supported | Not supported | - |
| Test a Study | June 2023 (web) Oct 2023 (mobile) | v2.22.0 | v4.19.1 | v2.15.0 | v2.15.2 | - |
| Advanced Skip Logic | July 2023 | v2.24.0 | v4.17.0 | v2.14.0 | v2.15.0 | - |
| Replay "Before/After" | May 2023 | v2.23.0 | Not supported | Not supported | Not supported | - |
| Session Replay | April 2023 | v2.22.0 | Not supported | Not supported | Not supported | - |
| Mobile Trigger Delay | October 2022 | N/A | v4.11.0 | v2.9.0 | v2.12.0 | - |
| Required Questions | October 2022 | v2.19.1 | v4.10.0 | v2.8.0 | v2.10.0 | - |
| Event Properties | October 2022 | v2.18.2 | v4.9.0 | v2.7.0 | v2.10.0 | - |
| Rating Scale | September 2022 | v2.17.3 | v4.8.5 | v2.6.4 | v2.8.0 | - |
| Other (Specify) Option | August 2022 | v2.17.0 | v4.8.5 | v2.6.4 | v2.8.0 | - |
| Recorded Task Question | May 2022 | v2.16.0 | Not supported | Not supported | Not supported | - |
| "Skipped" Skip Logic | April 2022 (web) Aug 2022 (mobile) | v2.15.14 | v4.8.5 | v2.6.1 | v2.8.0 | - |
| Consent/Legal Question | April 2022 (web) Aug 2022 (mobile) | v2.15.10 | v4.8.5 | v2.6.1 | v2.8.0 | - |
| Enrich URL Prompts | March 2022 (web) Aug 2022 (mobile) | v2.15.2 | v4.8.5 | v2.6.3 | v2.8.0 | - |
| Video & Voice Question | August 2022 | v2.2.4 | Not supported | Not supported | Not supported | - |
| Text/URL Prompt | June 2021 | v1.13.1 | v4.3.0 | v2.3.0 | v2.4.0 | - |
| Multi-select Skip Logic | March 2021 | v1.11.0 | v4.2.0 | v2.2.0 | v2.2.0 | - |
| Customized Description | February 2021 | v1.8.0 | v4.1.0 | v2.1.2 | v2.1.3 | - |
| Customized Continue Button | February 2021 | v1.8.0 | v4.1.0 | v2.1.2 | v2.1.3 | - |
| Open Text Placeholder | February 2021 | v1.8.0 | v4.1.0 | v2.1.2 | v2.1.3 | - |
| Customized Thank You Card | February 2021 | v1.8.0 | v4.1.0 | v2.1.2 | v2.1.3 | - |
| NPS Question Type | July 2020 | v1.3.0 | v2.1.0 | v1.1.0 | v1.1.0 | - |
## Upgrading SDKs
We adhere to [Semver](https://semver.org/) for versioning our SDKs so upgrading between minor versions or patches (e.g. 2.0.0 -> 2.1.0 or 3.1.0 > 3.2.1) should not present any breaking changes. You can view the release logs [here](/docs/developer-center/sdk-changelog/index)
## How do I upgrade my Sprig SDK to the latest version?
If you installed with [HTML](/docs/Installation/introduction-web/web-javascript), Segment, or Google Tag Manager your SDK will be automatically upgraded.
For [npm and Yarn](/docs/account-and-settings/team-management-roles/products-and-environments) install methods, reach out to your development team to upgrade the SDK to the latest version. Please note that if utilize additional [Products and Environments](/docs/account-and-settings/team-management-roles/products-and-environments) you will need to update the in each place that the SDK is installed.
Mobile SDK installs, including [iOS](/docs/Installation/introduction-mobile/ios-sdk-installation), [Android](/docs/Installation/introduction-mobile/android-sdk-installation/index) and [React Native](/docs/Installation/introduction-mobile/react-native-module), will require developer help to upgrade versions. Additionally, if bundled with an app store release, users will need to update to the latest version of\_your companies mobile application\_ in order to be eligible for a Sprig survey (or Replay) that requires a minSDK version.
# Sprig SDK
Source: https://docs.sprig.com/docs/developer-center/sprig-sdk/index
In this section, you can review Sprig SDK information such as:
* [Reviewing SDK versions and traffic](/docs/developer-center/sprig-sdk/sdk-traffic)
* [Features by SDK versions](/docs/developer-center/sprig-sdk/features-by-sdk-version)
* [Sprig's SDK end of life (EOL) policies](/docs/developer-center/sprig-sdk/sdk-end-of-life-eol-policy#overview)
# SDK End of Life (EOL) Policy
Source: https://docs.sprig.com/docs/developer-center/sprig-sdk/sdk-end-of-life-eol-policy
*Effective as of November 5, 2023*
## Overview
Keeping your Sprig SDK updated to the latest version ensures that you have access to all of Sprig’s newest features, bug fixes and security patches.
Sprig will support an SDK for 18 months after initial release date, after which the SDK will be deprecated and your ability to target users, conduct in product Surveys, or record Replay clips may be impacted.
Generally, if Sprig is installed into your application via Javascript, Google Tag Manager, or Segment, your SDKs will automatically update to the latest version. npm/yarn or native mobile installs will likely require your development team to manually upgrade to the newest SDK version - often this change takes only takes a few minutes, plus any testing and QA.
## SDK Deprecation
All SDKs will be deprecated 18 months after the initial release date. This policy applies 18 months from the release date for any major or minor version change.
* All users with Admin or Developer [roles](/docs/account-and-settings/account-and-login/index) will receive proactive in-app and email alerts stating that their SDK will be no longer supported
* Deprecated SDK version may be blocked from connecting to the service resulting in the inability to route visitor data to Sprig, or inhibit the ability to send Surveys to visitors or record Replay clips
At the time of a new release, Sprig will update the changelog to reflect what was modified.
## Critical SDK Upgrade
In the case that Sprig must release a new SDK version in order to remediate security and/or data protection or loss issues, a **critical** SDK upgrade may be necessary.
If a critical upgrade is required for an SDK, the old versions will be immediately deprecated at the time of release of the new version. A critical SDK upgrade will be limited to changes that are required to remediate security and/or data protection or loss issues.
* All users with Admin or Developer [roles](/docs/account-and-settings/account-and-login/index) will receive proactive in app and email alerts stating that their SDK will be no longer supported
* Additionally our support teams will proactively work with all impacted teams until resolved
# SDK & Traffic
Source: https://docs.sprig.com/docs/developer-center/sprig-sdk/sdk-traffic
See most recent SDK releases & visitor traffic by SDK version in app
## Overview
Sprig has in-app functionality to help you understand what Sprig SDK version your users have loaded on their device or browser. This information helps admins and developers determine the visitor traffic that might be impacted by a Sprig SDK that has reached end of life, or that won't have access to recent feature releases. See [SDK Versions by Feature](https://dash.readme.com/project/userleap/v6.0/docs/debugging) for more details.
As a reminder, **if Sprig is installed into your application via Javascript, Google Tag Manager, or Segment, your SDKs will automatically update to the latest version**. npm/yarn or native mobile installs will likely require your development team to manually upgrade to the newest SDK version - often this change takes only takes a few minutes, plus any testing and QA.
Keeping your Sprig SDK updated to the latest version ensures that you have access to all of Sprig’s newest features, bug fixes and security patches.
## SDK Version Table
SDK Traffic Tables display SDK initializations detected for Sprig and the associated visitor traffic by SDK version, by Product. In other words, these tables show the version of the Sprig SDK that end users have loaded on their device or browser.
Distribution is calculated as % of traffic with an SDK initialized over a 24 hour period, by platform, by product:
## Current SDK Releases
Easily see a list of Current SDK Releases, by platform and installation method.
For more details, visit the [SDK Changelog](/docs/developer-center/sdk-changelog/index)
# Enabling Dark Mode
Source: https://docs.sprig.com/docs/developer-center/styling/dark-mode
Sprig In-Product Studies can ship with a default dark appearance: turn it on and a respondent's study matches whatever light or dark setting their device or browser is using. It's a self-serve, product-wide setting in your Sprig team's settings. This is separate from writing your own `prefers-color-scheme` CSS, which you could always do (and still can on top of it). This page covers how the default works, how to brand it, and how it interacts with your custom CSS.
Already have your own `prefers-color-scheme` CSS covering dark mode? **Don't enable this toggle.** It loads Sprig's own dark stylesheet underneath your custom CSS, and that stylesheet applies everywhere you haven't explicitly overridden a Sprig selector or variable. Any element your own CSS doesn't already cover can pick up Sprig's default dark colors instead of staying in light mode.
This toggle is best used to start from scratch, utilizing Sprig's default styles as the baseline.
Default CSS dark mode shipped in Web SDK v2.49.0, and studies rendered in a mobile SDK need a version built against it: see [Minimum SDK versions](#minimum-sdk-versions) below.
## Turning it on
Only Admins and Developers can modify survey appearance. Go to Settings > Surveys > Look & Feel and switch on **Enable Default Dark Mode CSS**. This one toggle covers both surfaces: turning it on here enables the default dark theme for Feedback studies alongside In-Product Surveys.
Same story for the Brand Color fields below, set once in Surveys > Look & Feel and they apply to Feedback too. Custom CSS is the one thing that stays separate: to override built-in styles for Feedback specifically, use its own editor at Settings > Feedback > Look & Feel > CSS.
Once the toggle is on, a second **Brand Color** field appears for dark mode next to the existing light mode one. Each drives the `--sprig-brand-color` variable in its mode, controlling the default survey border, button background, radio fills, and other accent details, no CSS required.
## How it works
Sprig loads a second stylesheet that responds to the respondent's operating system or browser appearance setting via the standard CSS media query:
```css theme={null}
@media (prefers-color-scheme: dark) {
/* Sprig's dark palette */
}
```
Once enabled, there's no per-survey switch and no toggle inside the survey itself. Every respondent gets whichever version matches their own device or browser setting, instantly, on their end.
Sprig's styles are built on CSS custom properties (variables). The light values are declared once, and the dark stylesheet re-declares the same variable names with dark values. Every Sprig selector reads from those variables, so changing one variable updates every place that color is used.
```css theme={null}
/* Light (always loaded) */
html {
--background-color: #fff;
--text-color: #2f2e2c;
}
/* Dark */
@media (prefers-color-scheme: dark) {
:root {
--background-color: #1c1c1e;
--text-color: #fff;
}
}
```
### Load order and specificity
How the CSS is applied:
1. Your custom CSS is injected after Sprig's stylesheets. Your rules win at equal specificity. You do not need `!important` for ordinary overrides.
2. Sprig's dark values are declared on `:root`, not `html`. Since `:root` has higher specificity than `html`, a variable you set on `html` will apply in light mode but be overridden by Sprig in dark mode.
The commented reference block in the CSS editor is light-mode only: a snapshot of Sprig's selectors with hardcoded light colors, no variables or dark palette listed. Use the [variable reference](#css-variable-reference) below when you're working on dark mode.
## Choosing an approach
| Goal | Best when | Effort | Approach |
| :- | :- | :- | :- |
| **Set your Brand Color fields** | You only want to set Sprig's accent color for dark and light mode. No other custom styles. | None | [Study Style settings](/docs/sprig-studies/in-product-surveys/microsurvey-look-and-feel#study-style) |
| **Do nothing (CSS)** | Your customizations are structural (spacing, radius, font, layout) and don't set colors. | None | Approach 1 |
| **Override selectors directly** | You want plain CSS with no variables, or you're only restyling a few elements. | Low | Approach 2 |
| **Override Sprig's variables** | You want Sprig's dark behavior, just in more of your brand colors than the Brand Color fields cover. | Low | Approach 3 |
| **Define your own tokens** | You have a real design system with light/dark pairs to mirror. | Medium | Approach 4 |
Variables are a convenience, not a requirement: because every Sprig selector reads from them, changing one value updates everywhere that color is used. A plain `@media (prefers-color-scheme: dark)` block with ordinary selector overrides works just as well, and is often clearer for a handful of elements. Use whichever fits your stylesheet.
### Approach 1: Do nothing (color-free customizations)
If your custom CSS only changes layout, spacing, typography, or border radius, it already works in both modes. Sprig's colors keep flowing through the variables.
```css theme={null}
/* Safe in both light and dark: no color declarations */
.ul-card__container--desktop {
border-radius: 12px;
box-shadow: none;
padding: 24px;
}
.ul-question {
font-family: 'Inter', sans-serif;
font-size: 20px;
font-weight: 700;
}
```
A hardcoded color applies in both modes. `.ul-question { color: #1f2937; }` means dark text on Sprig's default dark card. Pair a foreground color with its matching background, or move both into variables.
### Approach 2: Override selectors directly
No variables involved. Write your light-mode rules as usual, then re-declare whatever needs to change inside a `@media (prefers-color-scheme: dark)` block. Your custom CSS is injected after Sprig's, so at equal specificity your rules win in both modes.
```css theme={null}
/* Applies in both modes */
.ul-card__container {
border-radius: 12px;
}
.ul-question {
color: #1f2937;
}
.ul-card-text__button {
background-color: #0075de;
color: #ffffff;
}
/* Dark only */
@media (prefers-color-scheme: dark) {
.ul-card__container {
background: #252525;
border-width: 0;
box-shadow: 0 2px 10px rgba(0, 0, 0, 0.35);
}
.ul-question {
color: #ffffff;
}
.ul-caption {
color: #9b9a97;
}
.ul-card-text__button {
background-color: #0075de;
color: #ffffff;
}
}
```
A selector you override only affects that selector, unlike a variable. Step through every question type in both light and dark mode before saving.
### Approach 3: Override Sprig's variables
The lowest-effort way to brand both modes. Set Sprig's own variable names on `:root` for light, then re-declare the ones that need to change inside a dark media query. Every Sprig selector picks the new values up automatically.
```css theme={null}
/* Light */
:root {
--text-color: #1f2937;
--text-color-light: #4b5563;
--background-color: #ffffff;
--selection-background-color: #f3f0ff;
--selection-border-color: #7c5cff;
}
/* Dark */
@media (prefers-color-scheme: dark) {
:root {
--text-color: #f5f5f7;
--text-color-light: #a1a1aa;
--background-color: #16161a;
--selection-background-color: #2a2440;
--selection-border-color: #a78bfa;
}
}
```
### Approach 4: Define your own tokens
If your company already maintains light/dark color pairs, declare them all up front, point a set of "active" tokens at the light values, and remap only the active tokens in the dark block. Your selectors then reference the active tokens and never need duplicating.
```css theme={null}
:root {
/* Full palette: both modes declared once */
--brand-text-light: #000000;
--brand-text-dark: #ffffff;
--brand-text-inverse-light: #ffffff;
--brand-text-inverse-dark: #000000;
--brand-button-light: #820076;
--brand-button-dark: #f0a0ff;
/* Active tokens default to light */
--brand-text: var(--brand-text-light);
--brand-text-inverse: var(--brand-text-inverse-light);
--brand-button: var(--brand-button-light);
}
@media (prefers-color-scheme: dark) {
:root {
/* Remap only the active tokens */
--brand-text: var(--brand-text-dark);
--brand-text-inverse: var(--brand-text-inverse-dark);
--brand-button: var(--brand-button-dark);
}
}
/* Selectors are written once and work in both modes */
.ul-question,
.likert-number {
color: var(--brand-text);
}
.ul-card-text__button {
background: var(--brand-button);
color: var(--brand-text-inverse);
border-radius: 20px;
padding: 12px 40px;
font-weight: 600;
}
```
## CSS variable reference
These are the variables Sprig's stylesheets read from, with the default value in each mode. Override any of them on `:root`. You only need this for Approach 3 or Approach 4 above; skip it otherwise.
This reference reflects Web SDK v2.49.0. Sprig may add variables in later versions; anything not listed here should be overridden by selector instead.
| Variable | Light | Dark |
| :- | :- | :- |
| `--background-color` | `#fff` | `#1c1c1e` |
| `--background-color-darker` | `#faf9f8` | `#2c2c2e` |
| `--text-color` | `#2f2e2c` | `#fff` |
| `--text-color-light` | `#575653` | `#8f8f8f` |
| `--text-color-lighter` | `#858481` | `#a8a8a8` |
| `--border-color` | `#ececec` | `#3a3a3c` |
| `--border-color-heavy` | `#ebebeb` | `#2c2c2e` |
| Variable | Light | Dark |
| :- | :- | :- |
| `--button-disabled-background` | `#f2f2f2` | `#2c2c2e` |
| `--button-disabled-text-color` | `#a8a8a8` | `#8f8f8f` |
| `--progress-bar-background` | `rgba(0, 0, 0, 0.1)` | `rgba(255, 255, 255, 0.1)` |
| `--prototype-button-background` | `rgba(0, 0, 0, 0.01)` | `rgba(255, 255, 255, 0.01)` |
| `--thank-you-link-background` | `rgba(0, 0, 0, 0.01)` | `rgba(255, 255, 255, 0.01)` |
| `--thank-you-link-background-hover` | `rgba(0, 0, 0, 0.03)` | `rgba(255, 255, 255, 0.03)` |
| Variable | Light | Dark |
| :- | :- | :- |
| `--selection-border-color` | `#c2c2c2` | `#3a3a3c` |
| `--selection-background-color` | `#f2f2f2` | `#2c2c2e` |
| `--selection-background-color-hover` | `#e6e6e6` | `#3a3a3c` |
| `--selection-indicator-color` | `#a8a8a8` | `#8f8f8f` |
| `--selection-indicator-color-selected` | `#000` | `#fff` |
| `--select-border` | `#e6e6e6` | `#3a3a3c` |
| `--select-border-hover` | `#dddcd9` | `#4a4a4c` |
| `--select-background` | `#fff` | `#1c1c1e` |
| `--select-background-hover` | `#f2f2f2` | `#2c2c2e` |
| Variable | Light | Dark |
| :- | :- | :- |
| `--matrix-header-background` | `#f7f7f7` | `#121212` |
| `--nps-unselected` | `#fcfcfc` | `#2c2c2e` |
| `--nps-unselected-border` | `#e6e6e6` | `#3a3a3c` |
| `--nps-selected-color-low` | `#b06d6d` | `#f44336` |
| `--nps-selected-color-high` | `#95a779` | `#4caf50` |
| `--likert-symbol-color` | `transparent` | `#8f8f8f` |
| `--rank-order-background` | `#f2f2f2` | `#2c2c2e` |
| `--rank-order-border` | `#e6e6e6` | `#3a3a3c` |
| `--rank-order-border-hover` | `#d9d9d9` | `#4a4a4c` |
| `--rank-order-number-background` | `#fff` | `#1c1c1e` |
| `--record-task-background` | `#f2f2f2` | `#2c2c2e` |
| `--record-task-border` | `#e6e6e6` | `#3a3a3c` |
| `--record-task-border-hover` | `#d9d9d9` | `#4a4a4c` |
| `--record-task-number-background` | `#fff` | `#1c1c1e` |
| `--voice-video-background` | `#f2f2f2` | `#2c2c2e` |
| `--voice-video-border` | `#e6e6e6` | `#3a3a3c` |
| `--voice-video-border-hover` | `#d9d9d9` | `#4a4a4c` |
| `--voice-video-icon-color` | `#a8a8a8` | `#8f8f8f` |
### Conversational UI
Conversational studies load an additional dark stylesheet with its own variables for the chat transcript and inputs, overridden the same way: inside a `@media (prefers-color-scheme: dark)` block on `:root`. The most commonly overridden:
| Variable | Controls |
| :- | :- |
| `--chat-right-bg` | Respondent message bubble background |
| `--chat-left-bg` | Sprig message bubble background |
| `--chat-msg-no-response` | Skipped/unanswered message text |
| `--chat-end-text` | End-of-conversation text |
| `--chat-footer` | Footer text |
| `--chat-choice-bg` | Choice option background |
| `--text-card-input-bg` | Open text input background |
| `--text-card-border` | Open text input border |
| `--select-checkbox-bg` | Checkbox fill |
| `--select-checkbox-border` | Checkbox border |
| `--select-radio-bg` | Radio button fill |
| `--consent-input-bg` | Consent card name input background |
## Testing your CSS
Because custom CSS applies to all studies in a product, including active ones, test both modes before you save. A Product's CSS is one stylesheet shared by its development and production environments, so saving updates both at once.
A sun/moon switcher is available in two places:
One sits above the preview in the custom CSS editor (Settings > Surveys > Look & Feel > Add Custom Styles), a sandbox: nothing here goes live until you hit save.
The other sits next to **Preview Study** in the study builder's sidebar preview, and renders your actual survey questions, so you can confirm what respondents will see in each mode.
1. Iterate in the CSS editor's preview first: unsaved, useful for a sandbox.
2. Once you save, confirm the result in the study builder's sidebar preview against your real questions.
3. Toggle your OS appearance (macOS: System Settings > Appearance; Windows: Settings > Personalization > Colors) only if you're checking the survey somewhere neither switcher covers, like a live link.
4. In Chrome DevTools you can also force the media query without changing your OS: open the Command Menu (`Cmd/Ctrl + Shift + P`), run **Show Rendering**, and set **Emulate CSS media feature prefers-color-scheme**.
5. Step through every question type in the preview, not just the first card. Matrix, NPS, Rank Order, and Open Text have the most mode-specific styling.
## Common issues
You most likely declared your variables on `html` instead of `:root`. Sprig's dark values are on `:root`, which has higher specificity, so it wins regardless of source order. Change your selector to `:root`.
You have a hardcoded foreground color with no matching background, or vice versa. Search your CSS for any literal hex value on a `color`, `background`, or `border-color` property and either move it into a variable pair or wrap the dark variant in a `@media (prefers-color-scheme: dark)` block.
Something in the card's ancestry still has a light background. Reset the wrappers to transparent so the host page shows through:
```css theme={null}
html,
body,
#ul-app,
.ul-app--overlay,
.ul-app--visible,
.ul-app__container {
background: transparent !important;
}
```
Some Sprig icons are inline SVG data URIs with a fixed stroke color. Sprig's dark stylesheet replaces the affected ones, but if you've overridden a background shorthand you may have wiped the replacement. Set `background-color` rather than `background`, or re-declare the `background-image` in your dark block.
Confirm three things: **Enable Default Dark Mode CSS** is switched on in Look & Feel settings (it's off by default), you're on Web SDK v2.49.0 or later or a mobile SDK version built against it (see [Minimum SDK versions](#minimum-sdk-versions)), and the test device's OS appearance is actually set to Dark.
The toggle applies per Product, not per environment: a Product's development and production environments share one setting. If dark mode works in one place and not another, check whether you're comparing two different Products rather than two environments of the same one. Both the study builder's preview and the custom CSS editor's preview have their own sun/moon switcher, see [Testing your CSS](#testing-your-css), so you can rule out an OS-level mismatch by checking either one directly.
## Mobile SDKs
Studies rendered in the iOS, Android, React Native, and Flutter SDKs use the same web stylesheets inside a web view, so everything on this page applies there as well.
Native light/dark support (the SDK letting the web view render dark at all) landed earlier than the default CSS work, which is why some customers were already shipping their own dark mode CSS before v2.49.0.
The mobile SDKs also expose APIs to force a study into light or dark mode regardless of the device setting: all include a method called `overrideUserInterfaceMode`, which takes `dark`, `light`, or `unspecified`. This lets an app align the survey's theme with its own custom settings; passing `unspecified` resets it to match the device again.
### Minimum SDK versions
These are the first mobile SDK releases built against Web SDK v2.49.0, and therefore the first to include the default CSS dark mode styles.
These versions gate only Sprig's default dark stylesheet. You don't need any of them to write your own `prefers-color-scheme` CSS, that's plain custom CSS and always has worked on any SDK version. The default just gives you a baseline dark setting to start from or override.
| SDK | Minimum version |
| :- | :- |
| Web | v2.49.0 |
| iOS | v4.33.1 |
| Android | v2.27.2 |
| React Native | v4.1.1 |
| Flutter | v0.9.1 |
| Segment iOS | v1.10.1 |
| Segment Android | v1.10.1 |
| Segment React Native | v0.9.1 |
For the full list of selectors and non-color customization options, see [Styling Studies with Custom CSS](/docs/developer-center/styling/styling-your-studies-with-custom-css).
# Styling
Source: https://docs.sprig.com/docs/developer-center/styling/index
In this section, you can review how to control the look and feel of your Sprig studies, from dashboard settings like brand color to custom CSS:
* [Styling studies with custom CSS](/docs/developer-center/styling/styling-your-studies-with-custom-css)
* [Dark mode](/docs/developer-center/styling/dark-mode)
# Styling Studies with Custom CSS
Source: https://docs.sprig.com/docs/developer-center/styling/styling-your-studies-with-custom-css
**You can add and override the CSS applied to Sprig In-Product Surveys and Feedback to completely re-work its appearance to match your branding guidelines and requirements.**
Some look and feel styling is built into the Sprig dashboard by default. Other customizations require CSS styling. The guidance here is a deeper dive into how the CSS editor works and how to safely override default rules.
Custom CSS styling is done separately for In-Product Surveys and Feedback, and can be done in:
* Settings > Surveys > Look & Feel > CSS OR
* Settings > Feedback > Look & Feel > CSS
**Note:** currently Sprig only supports 1 CSS styling theme per Sprig Product. Per study styling is coming soon!
**Styling for dark mode?** Turn on **Enable Default Dark Mode CSS** in Look & Feel settings first, self-serve, no need to contact Sprig. The code shown in the editor below is a **light-mode-only snapshot**: no variables, no dark palette. See [Dark Mode](/docs/developer-center/styling/dark-mode) before adding any color rules.
### Introduction
A single CSS file applies to all survey question types, although some CSS selectors only apply to HTML elements on specific survey types. **Any un-commented out CSS you add will override the default styling to all surveys when saved, including any in-progress studies. Do proceed with caution when applying.**
When you open the Custom CSS editor, you’ll see a block of commented-out code. These aren’t “extra” styles you need to delete or modify, they’re simply the default Sprig styles shown for reference. You can ignore them if you like or choose to clear the window.
### Basic instructions:
* **Add your own CSS below the comments, or replace selectors with your own.**
* The default file is organized by general styles and question-type-specific styles.
* You can make modifications directly in this editor or paste in your own CSS.
* **Use the preview panel to test changes across question types.**
* The preview will update with the changes you make to your CSS. You can select each of the question types from underneath the preview to see how your custom CSS changes their appearance. Note that not all changes will be shown in previews until the CSS styling configurations are saved. Use this unsaved preview to get your styling right first: a Product's CSS is one value shared by its development and production environments, so once you save, it applies everywhere at once, there's no separate dev copy to promote afterward.
* If dark mode is enabled for the product, a sun/moon switcher above the preview lets you flip it between light and dark on demand, so you can check both without changing your OS or browser setting.
* Defaults will remain unless overridden.
* Custom CSS applies to all surveys within a product, including active surveys.
### CSS variables
Underneath the selectors shown in the editor, Sprig's stylesheets are built on **CSS custom properties** (variables) for color, e.g. `--text-color`, `--background-color`, `--selection-background-color`. Every selector below reads its color from one of these variables rather than a hardcoded value.
You don't need to touch variables to use custom CSS; overriding a selector directly (as shown throughout this page) works fine. Variables matter once you want the same color change to apply automatically in both light and dark mode, since a variable you set once is picked up everywhere Sprig uses it.
The full variable reference, and the three patterns for using them, live on the [Dark Mode](/docs/developer-center/styling/dark-mode#css-variable-reference) page rather than duplicated here.
## The Practical Guide
The 600+ lines of default CSS have JSDoc style comments that organize all the selectors.
* [Base Typography](#base-typography)
* [Universal Elements](#universal-elements)
* [Card Component](#card-component)
* [Rich Text](#rich-text)
* [Choice Elements](#choice-elements)
* [Buttons](#buttons)
* [Matrix Questions](#matrix-questions)
* [One to Five Scale (Likert)](#one-to-five-scale-likert)
* [NPS Question](#nps-question)
* [Open Text Card](#open-text-card)
* [Text or URL Prompt](#text-or-url-prompt)
* [Consent or Legal Card](#consent-or-legal-card)
* [Rank Order](#rank-order)
* [AI Follow-Up & AI Dynamic Question](#ai-follow-up-and-ai-dynamic-question)
* [Thank You Card](#thank-you-card)
* [Feedback Button & Container](#feedback-button-and-container)
Sprig has also curated 2 different quick "Choose-your-own-theme" [recipes](#quick-recipes), shown below!
#### Base Typography
What it controls: global text feel.
```css Try: theme={null}
/* Brand font */
html, body { font-family: 'Georgia', serif; }
```
`html`, `body`, `b`
#### Universal Elements
What it controls: the little bits around the card (footers, dots, close button).
```css Try: theme={null}
/* Increased footer spacing & add color */
.ul-footer { margin-top: 12px; background-color: #e97451; }
/* Increase size of the close icon */
.close-btn { height: 18px; width: 18px;}
```
`.ul-footer`, `.ul-footer-bubble`, `.close-container`, `.close-btn`
#### Card Component
What it controls: the survey “card”, padding, shadow, radius.
```css Try: theme={null}
/* Rounded, no heavy shadow */
.ul-card__container--desktop, .ul-card__container--mobile {
border-radius: 10px;
box-shadow: none;
}
/* Headline + subcopy tone */
.ul-question { font-size: 20px; font-weight: 700; color: #1f2937; }
```
`.ul-card`, `.ul-card__container--desktop`, `.ul-card__container--mobile`, `.ul-card__container`, `.ul-card-main-content`, `.ul-question`, `.ul-caption`
#### Rich Text
What it controls: paragraphs and lists in rich text cards.
```css Try: theme={null}
/* Visual focus on rich text */
.ul-rich-text-body p, .ul-rich-text-body li {
text-align: center;
padding: 5px;
border: #b18187 3px solid;
}
```
`.ul-rich-text-body`, `.ul-rich-text-body p`, `.ul-rich-text-body li`
#### Choice Elements
What it controls: option "buttons," spacing, radio dots, labels (multiple choice, multi-select, matrix options).
```css Try: theme={null}
/* Space the list a bit */
.ul-card__choices--desktop { margin-top: 16px; }
/* Button-like options */
.choice { background: #f9f9f8; border-radius: 12px; }
/* Hide radio circles for a cleaner look */
.select-radio { display: none; }
```
`.ul-card--multiple`, `.ul-card__choices--desktop`, `.ul-card__choices--mobile`, `.ul-card__choices`, `.choice--mobile`, `.choice--desktop` (has `:hover`/`:active` states), `.choice`, `.select-label`, `.select-radio`, `.ul-select-active-dynamic-style .select-radio`
#### Buttons
What it controls: primary/secondary actions (finish/submit). Buttons appear across nearly every question type, not just one, so this section sits with the other general-purpose selectors above.
```css Try: theme={null}
/* Rounded (pill-shape) primary action */
.ul-card-text__button {
border-radius: 20px;
background: #e97451;
color: #fff;
}
```
`.ul-card-text__button`, `.ul-card-text__button:disabled`, `.ul-card__button-wrapper`, `.ul-card-skip__button`
#### Matrix Questions
What it controls: row/column labels and cells.
```css Try: theme={null}
/* Colorful matrix background & label text */
.ul-matrix-option-wrapper {
background-color: #e97451;
margin: 4px;
border-radius: 3px;
}
.ul-matrix-row-label, .ul-matrix-column-label {
background: white;
color: #e97451;
}
```
`.ul-card--matrix_grid`, `.ul-card--matrix_container`, `.ul-matrix-column-label`, `.ul-matrix-option-wrapper`, `.ul-matrix-last-option`, `.ul-matrix-row-label`
#### One to Five Scale (Likert)
What it controls: the row of numbers and labels beneath.
```css Try: theme={null}
/* Dotted borders on each number & mauve labels */
.likert-number--desktop { border: 2px #f1e1e7 dotted; }
.ul-card--likert__labels { color: #b18187; }
```
`.ul-card--likert`, `.ul-card--likert__numbers`, `.likert-number--mobile`, `.likert-number--desktop` (has `:hover`/`:active` states), `.likert-number`, `.ul-card--likert__labels`
#### NPS Question
What it controls: the number grid and label row.
```css Try: theme={null}
/* Same visual language as Likert */
.ul-card--nps__numbers { border: 2px #f1e1e7 dotted; }
.ul-card--nps__labels { color: #b18187; }
```
`.ul-card--nps`, `.ul-card--nps__numbers`, `.nps-number--mobile`, `.nps-number--desktop` (has `:hover`/`:active` states), `.nps-number`, `.ul-card--nps__labels`
#### Open Text Card
What it controls: text areas and their container.
```css Try: theme={null}
/* Peach background, rounder corners */
.ul-card-text__input { background: #fad6c3; border-radius: 8px; }
```
`.ul-card--text`, `.ul-card-text`, `.ul-card-text__container`, `.ul-card-text__input--mobile`, `.ul-card-text__input--desktop` (has a `:hover` state), `.ul-card-text__input` (has `::placeholder`/`:focus` states)
#### Text or URL Prompt
What it controls: the prompt button styling.
```css Try: theme={null}
/* Make prompt feel like a primary action */
.ul-card__text-url-prompt-button { background-color: #e97451 }
```
`.ul-card__text-url-prompt`, `.ul-card__text-url-prompt-button`
#### Consent or Legal Card
What it controls: name input and consent choices.
```css Try: theme={null}
/* Peach background, rounder corners */
.ul-consent-legal__name-input { background: #fad6c3; border-radius: 6px; }
```
`.ul-consent-legal__name-input--mobile`, `.ul-consent-legal__name-input--desktop` (has a `:hover` state), `.ul-consent-legal__name-input` (has `::placeholder`/`:focus` states), `.ul-card__consent-legal .choice`, `.ul-card__consent-legal .choice--desktop` (has `:hover`/`:active` states), `.ul-card__consent-legal .choice--mobile` (has an `:active` state)
#### Rank Order
What it controls: draggable rows, drag handle, and the rank select dropdown.
```css Try: theme={null}
/* Rounder rows with a colored drag handle */
.ul-card-rank__option { border-radius: 12px; border-color: #b18187; }
.ul-card-rank__drag-btn { color: #b18187; }
/* Custom-colored rank select */
.ul-card-rank__select { border-color: #b18187; border-radius: 8px; }
```
`.ul-card-rank__labels`, `.ul-card--rank__question-inner-container`, `.ul-card-rank__list`, `.ul-card-rank__option` (has an `:active` state, plus `.is-dragging` and `.is-drop-target` modifier classes), `.ul-card-rank__option.is-drop-target select, .ul-card-rank__option.is-drop-target span, .ul-card-rank__option.is-drop-target button`, `.ul-card-rank__drag-btn` (has an `:active` state), `.ul-card-rank__option svg`, `.ul-card-rank__option span`, `.ul-card-rank__select`, `.ul-card-rank__select.ul-card-rank__select--placeholder`
#### AI Follow-Up & AI Dynamic Question
What it controls: the loading indicator shown while an AI Follow-Up or AI Dynamic Question is generated. Everything else on these question types shares styling with the [Open Text Card](#open-text-card).
```css Try: theme={null}
/* Slower, brand-colored shimmer */
.ul-card-text__input__loading {
background-image: linear-gradient(70deg, #b18187 0%, #f1e1e7 50%, #b18187 100%);
animation-duration: 3s;
}
```
`.ul-card-text__input__loading`
#### Thank You Card
What it controls: closing screen layout and text.
```css Try: theme={null}
/* Colored checkmark, tighter closing copy */
.ul-thanks-check { color: #21522e; }
.ul-card--thanks .ul-question { font-weight: 700; }
.ul-card--thanks .ul-caption { color: #575653; }
```
Want to replace the checkmark with your own image entirely — a logo, an icon, an illustration? Hide the default SVG and inject your own via a `content: url(...)` data URI:
```css Try: theme={null}
/* Custom image instead of the checkmark */
.ul-thanks-check svg { display: none; }
.ul-thanks-check::before {
content: url('data:image/svg+xml;base64,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');
}
```
Keep your image close to 64×64px to match the default icon's footprint, or set explicit `width`/`height` on `.ul-thanks-check::before` if it needs different dimensions.
`.ul-card--thanks`, `.ul-thanks-check`, `.ul-card--thanks-content`, `.ul-card--thanks .ul-question`, `.ul-card--thanks .ul-caption`
#### Feedback Button & Container
What it controls: the floating Feedback button and the container it opens into. These selectors are only relevant to the Feedback tab's CSS editor, not surveys.
```css Try: theme={null}
/* Rounder floating button */
#sprig-feedback-button { border-radius: 24px; }
```
**`.sprig-feedback-button-light` / `.sprig-feedback-button-dark` are not the same as the dark mode covered on the [Dark Mode](/docs/developer-center/styling/dark-mode) page.** These two classes correspond to the Feedback button's own **Light/Dark theme** setting in Look & Feel — a manual choice you make once for the button, not something that responds to the respondent's system appearance. If you want the Feedback button itself to follow `prefers-color-scheme`, you'll need to write that media query yourself against these selectors.
`#sprig-feedback-button`, `.sprig-feedback-button-label`, `.sprig-feedback-button-right`, `.sprig-feedback-button-bottom`, `.sprig-feedback-button-light`, `.sprig-feedback-button-dark`, `#sprig-feedback-container`, `.sprig-feedback-container-left`, `.sprig-feedback-container-center`, `.sprig-feedback-container-bottom`
## Quick Recipes
“Choose-Your-Own-Theme” recipes designed to help you tailor the look and feel of your studies.
These recipes are light-mode only. If dark mode is enabled for your product, pair them with a `@media (prefers-color-scheme: dark)` block — see [Dark Mode](/docs/developer-center/styling/dark-mode) for the patterns to use.
```css Minimal Branded Look theme={null}
body { font-family: Optima; }
.ul-card__container { border: #5a6b5f 2px solid; border-radius: 0; box-shadow: none; }
.ul-question { font-weight: 700; color: #21522e; text-align: center}
.choice { background: white; border-radius: 24px; }
.select-radio { display: none; }
.ul-card-text__button { border-radius: 16px; padding: 8px;}
```
```css High Contrast for Accessibility theme={null}
.ul-question { font-weight: 700; font-family: Verdana; color: #25283D; font-size: 22px; }
.choice { background: white; font-size: 16px; border: 2px solid #25283D; }
.ul-card-text__button { background: #25283D; color: #fff; border-radius: 16px; }
```
# Android SDK
Source: https://docs.sprig.com/docs/installation/introduction-mobile/android-sdk-installation/index
## Getting Started
### Overview
The Sprig Android SDK, when installed in your native Android app, allows you to track your customer’s in-product behavior and display Sprig studies when they perform certain actions.
### Requirements
* Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/android-sdk).
* Ensure you have access to your Android codebase, and can deploy to a development and/or production environment
* The Sprig Android SDK is designed to work with Android SDK 21 (Android Lollipop, OS 5.0) and above. If using minSdk below 21, you can override the library in your main AndroidManifest:
```markup theme={null}
....
```
To see all official releases of the Sprig Android SDK, visit the [repository](https://search.maven.org/artifact/com.userleap/userleap-android-sdk).
## Install SDK
### Install via Gradle
You can install the Sprig SDK via [maven central](https://search.maven.org/artifact/com.userleap/userleap-android-sdk):
```groovy theme={null}
dependencies {
implementation "com.userleap:userleap-android-sdk:2.17.8"
}
```
Add Java 8 support to your project (if not added already):
```groovy theme={null}
android {
...
compileOptions {
sourceCompatibility JavaVersion.VERSION_1_8
targetCompatibility JavaVersion.VERSION_1_8
}
// For Kotlin projects
kotlinOptions {
jvmTarget = "1.8"
}
}
```
If you experience build issues like "Failed to find the generated class", try adding this to your proguard rules:
```text theme={null}
-keep class com.userleap.** { *; }
-keep class sprig.** { *; }
```
Your app will also need to maintain the following dependencies:
* [Kotlin](https://developer.android.com/kotlin) (1.5.31)
* [Gradle](https://developer.android.com/studio/releases/gradle-plugin) (7.2.0)
* [Android X](https://developer.android.com/jetpack/androidx)
* [Material Components](https://github.com/material-components/material-components-android) (1.5.0-alpha04) (used for bottom sheet dialog for surveys)
* ConstraintLayout (1.1.3) (used for flat view hierarchies for surveys)
### Obtain an Environment ID
After you've installed, you must obtain an environment ID from Sprig. Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [Integrations > Android SDK](https://app.sprig.com/integrations/installation/android-sdk)).
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Initialize the SDK
Initializing and using the SDK revolves around a singleton named `Sprig`. The singleton must be configured before it can be used; a common pattern is to configure Sprig in your class that extends [Application](https://developer.android.com/reference/android/app/Application), but follow the best practices for your team and application.
Make sure to check the [OS system version](https://developer.android.com/training/basics/supporting-devices/platforms#version-codes) before calling Sprig:
```java theme={null}
if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.LOLLIPOP) {
Sprig.configure(context, "ENVIRONMENT_ID")
}
/**
* You can test your study easily (bypass all filters and resurvey windows) by
* using Sprig's new testing feature. This requires installing Sprig v2.15.0 and
* adding the following code to pass the study's unique previewKey to the Sprig
* instance.
**/
class DeepLinkActivity : AppCompatActivity() {
override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState)
intent?.data?.getQueryParameter("sprigPreviewKey")?.let { previewKey ->
Sprig.setPreviewKey(previewKey)
}
finish()
}
}
```
Be sure to swap in the correct ENVIRONMENT\_ID. Note that `configure` will only accept 1 environment ID, and calling it multiple times with different IDs will have no effect.
**Warning:** Additional action recommended for customers that completed SDK install before October 2023 to enable in app testing feature
In order to [test your study](/docs/sprig-studies/in-product-surveys/study-testing) directly in your production application, you must first update your application’s install code to include additional snippet below ⬇️
### Study Previews
```java theme={null}
/**
* You can test your study easily (bypass all filters and resurvey windows) by
* using Sprig's new testing feature. This requires installing Sprig v2.15.0 and
* adding the following code to pass the study's unique previewKey to the Sprig
* instance.
**/
class DeepLinkActivity : AppCompatActivity() {
override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState)
intent?.data?.getQueryParameter("sprigPreviewKey")?.let { previewKey ->
Sprig.setPreviewKey(previewKey)
}
finish()
}
}
```
Alternatively, you can overwrite the previously added install code with the version [here](/docs/Installation/introduction-mobile/android-sdk-installation/index#initialize-the-sdk) that includes the required changes. Be sure to swap in the correct ENVIRONMENT\_ID
## Identify Users
Identifying users ensures that a user’s actions are all associated with the same profile so they can be targeted.
Properly identifying users helps ensure:
* Your users have a consistent experience across platforms, and do not see the same study multiple times
* You can accurately target the right users
* You are billed for the correct number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index)
### Set User ID
Sprig allows you to differentiate users by setting a unique USER\_ID. You may want to ensure consistency between the User IDs sent to Sprig and the ones in your internal database, product analytics/CDP, or data warehouse. You can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is…
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
Users that do not have a User ID set are considered unauthenticated.
You can use `setUserIdentifier` to identify a user with any string less than 256 characters. This function can be called multiple times safely, and stores the identifier locally. We recommend you set the User ID whenever the user logs in to your app, as well as after configuring Sprig (if the user is already logged in).
```java theme={null}
Sprig.setUserIdentifier("USER_ID")
```
### Logout
When a user logs out of your app, make sure to log that user out of the Sprig SDK. This will prevent any new activity from being associated with the wrong user. Note that if you call `logout()` on an unauthenticated user, Sprig will assign them a new profile and count this new user separately toward your MTU limit.
```java theme={null}
Sprig.logout()
```
## Track Events
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
Once you’ve installed the Sprig SDK, the next step is to configure the tracking of events that you would like to use to trigger or filter a study. For mobile SDKs, you must configure [Code](/docs/shared-study-foundations/events/code-events) events. (Sprig also offers [No-Code](/docs/shared-study-foundations/events/no-code-events) events, but these are only available on web platforms.)
To track a Code event, use:
```java theme={null}
val payload = EventPayload(event = "EVENT_NAME", properties = mapOf("key" to "value"))
Sprig.trackAndPresent(payload, YOUR_FRAGMENT_ACTIVITY)
```
After sending a new Code event to Sprig, you must [approve the new event request](/docs/shared-study-foundations/events/index#adding-events) on the [Events page](https://app.sprig.com/events) before it can be used to trigger or filter surveys.
Alternatively, after sending each tracking event, you can check if a new survey is ready for the user. If a survey is ready, you can decide to present the survey to the user. The survey will be presented on a [modal bottom sheet](https://material.io/develop/android/components/bottom-sheet-dialog-fragment/).
```java theme={null}
val payload = EventPayload(event = "EVENT_NAME", properties = mapOf("key" to "value")) { surveyState ->
when (surveyState) {
SurveyState.READY -> {
// We received a survey for the event, present it to the user
Sprig.presentSurvey(activity)
}
SurveyState.NO_SURVEY -> {
// No survey available based on event
}
SurveyState.DISABLED -> {
// Sprig has been disabled remotely
}
}
}
Sprig.track(payload)
```
These events will also be available as filters for your studies. For example, you may want to only display a study to users who have performed the "checkout" event at least 3 times.
## Track Attributes
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#survey-filter) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the Users page, and are recorded and attached to any surveys response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
To set a user’s attribute, provide key-values pairs where:
* `ATTRIBUTE_NAME` must be a string less than 256 characters, and cannot start with an `!` (these names are reserved for use by Sprig)
* `ATTRIBUTE_VALUE` must be a number, boolean, or string less than 256 characters
```java theme={null}
Sprig.setVisitorAttributes(mapOf("key" to "value", "plan" to "enterprise"))
```
### Set Email Address
Setting the user’s email address is **optional**. Setting emails is not required for web or mobile studies, but can be used to target users or create a Group of users based on their email. Check your organization's guidelines around personally-identifiable information before sending email addresses to Sprig.
```java theme={null}
Sprig.setEmailAddress("EMAIL_ADDRESS")
```
## Test & Deploy
To verify your SDK is configured properly, we recommend testing with your development `ENVIRONMENT_ID`.
1. Create a survey in your Sprig Development Environment
2. Choose an approved event as a trigger for your study
3. \[For testing purposes only] Allow users to retake the survey and set the recontact waiting period to 0 days
4. Track the approved event from your app and confirm that the survey appears
Congratulations! Your installation is complete and you can begin deploying.
## Advanced Customization
### Study Lifecycle Notifications
Sprig exposes updates throughout the study lifecycle. Here is a sample code block for listening to SDK events in real time:
```kotlin theme={null}
val listener = EventListener {
Log.d("Sprig Event Tracking", it.toString())
}
Sprig.addEventListener(eventName, listener)
```
| Lifecycle Event | Data | Min SDK Version |
| - | - | - |
| SDK\_READY | `null` | 2.15.0 |
| VISITOR\_ID\_UPDATED | `{"visitorId": UUID }` | 2.15.0 |
| ~~SURVEY\_WILL\_PRESENT~~ | `{name: "survey.will.present", "survey.id": Integer}` | removed in 2.29.0 |
| SURVEY\_RETURNED | `{name: "survey.returned", "survey.id": Integer}` | 2.29.0 |
| ~~SURVEY\_PRESENTED~~ | `{name: "survey.presented", "survey.id": Integer}` | removed in 2.29.0 |
| SURVEY\_APPEARED | `{name: "survey.appeared", "survey.id": Integer}` | 2.16.1 |
| SURVEY\_HEIGHT | `{"name":"survey.height","contentFrameHeight": Integer}` | 2.15.0 |
| SURVEY\_WILL\_CLOSE | `{"name":"survey.willClose","initiator":"close.click"}` `{"name":"survey.willClose","initiator":"survey.completed"}` | 2.15.0 |
| SURVEY\_CLOSED | `{"name":"survey.closed","initiator":"close.click"}` `{"name":"survey.closed","initiator":"survey.completed"}` | 2.15.0 |
| SURVEY\_DID\_NOT\_APPEAR | `{ name: survey.did.not.appear' , 'reason': String }` | 2.29.0 |
### Set Locale
Sprig supports setting the locale for default caption and button text. The following locales are supported:
* de
* en
* es-es
* fr
* hi
* ja
* ko
* pt-br
* ru
* zh
To set the locale to Chinese:
```java theme={null}
Sprig.setLocale('zh')
```
Setting the locale will only affect static text, and is only available for the iOS and Android SDKs (not React Native).
### App size impact
The Sprig SDK AAR size is **211 KB**.
The impact to an Android App Bundle is around **650 KB**. Note: The Sprig SDK uses the common dependencies listed above. The actual size impact will be smaller if these dependencies are already used by the app.
Methodology: Build a ProGuarded release Android App Bundle in Android Studio with an Empty Activity project. Then compare size after adding the Sprig SDK.
# Android and React Native Android Session Replay Wireframes Implementation Guide
Source: https://docs.sprig.com/docs/installation/introduction-mobile/android-session-replay-wireframes-implementation-guide
# Background
Historically, Android session replays have been based on snapshots of the entire screen that are then used as the frames for the session replay.
Starting with version v2.28.0 of the Android SDK, developers can now opt to capture their screens as wireframes. This generally allows for better performance on the main thread as well as more control over PII elements.
# Native Android Implementation
To make this change, host app developers simply need to pass the `WIREFRAME` value to the `setReplaySessionRecordingFormat() `method on the Android SDK instance:
```kotlin theme={null}
var recordReplaysAsWireframes = true
Sprig.setReplaySessionRecordingFormat(
if (recordReplaysAsWireframes) ReplaySessionRecordingFormat.WIREFRAME
else ReplaySessionRecordingFormat.SCREENSHOT
)
```
# React Native Android Implementation
The same flag needs to be set on React Native Android in order to record replays as wireframes:
```kotlin theme={null}
const recordReplaysAsWireframes = true;
Sprig.setAndroidReplaySessionRecordingFormat(
recordReplaysAsWireframes
? Sprig.ReplaySessionRecordingFormat.wireframe
: Sprig.ReplaySessionRecordingFormat.screenshot,
);
```
# Flutter Plugin
Source: https://docs.sprig.com/docs/installation/introduction-mobile/flutter_plugin
# Getting Started
### Overview
The Sprig Flutter plugin, when installed in app, allows you to track your customer’s in-product behavior and display Sprig studies when they perform certain actions.
### Requirements
* Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/react-native-module).
* Ensure you have access to your Flutter codebase, and can deploy to a development and/or production environment
* Please check the platform-specific requirements:
* [iOS](/docs/Installation/introduction-mobile/ios-sdk-installation#requirements): iOS 15 or above; Xcode 16
* [Android](/docs/Installation/introduction-mobile/android-sdk-installation/index#requirements): Android 5.1(22): Android Studio 2024.2.2
# Setup
### Obtain an Environment ID
Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [any of the installation methods](https://app.sprig.com/integrations/installation)).
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Add a reference to flutter-sprig
The Sprig Flutter plugin ([flutter-sprig](https://github.com/UserLeap/flutter-sprig/)) is hosted in a [github repository](https://github.com/UserLeap/flutter-sprig/) where it can be easily referenced from within your Flutter application.
In your **pubspec.yaml** file, add a reference to Sprig in your dependancies. The entry should look like this when you are done:
```yaml theme={null}
dependencies:
flutter:
sdk: flutter
sprig_flutter_plugin:
git:
url: https://github.com/UserLeap/flutter-sprig
```
One that is in place, in a CLI that has a path to the Flutter SDK, run at the root of the plugin example project:
```bash theme={null}
flutter pub get
```
When installing for iOS, you need to do `pod install`. And if you are updating, it's best to remove the `Podfile.lock` and run `pod repo update` first. So from your app top-level directory, run the following commands:
```bash theme={null}
cd example
cd ios
rm Podfile.lock
pod repo update
pod install
```
### Full main.dart example
Following is a full example of a main.dart file that includes initializing the plugin, checking the version and calling trackAndPresent with an event code to display a survey.
```cplusplus Dart theme={null}
import 'package:flutter/material.dart';
import 'dart:async';
import 'package:flutter/services.dart';
import 'package:sprig_flutter_plugin/sprig_flutter_plugin.dart';
import 'package:sprig_flutter_plugin/sprig_types.dart';
void main() {
runApp(MaterialApp(home: MyApp()));
}
class MyApp extends StatefulWidget {
const MyApp({super.key});
@override
State createState() => _MyAppState();
}
class _MyAppState extends State {
String _sdkVersion = "";
final _sprigFlutterPlugin = SprigFlutterPlugin();
@override
void initState() {
super.initState();
initPlatformState();
}
Future initPlatformState() async {
String sdkVersion = "";
try {
_sprigFlutterPlugin.configure(environment: "", configuration: null);
sdkVersion = await _sprigFlutterPlugin.sdkVersion() ?? "";
_sprigFlutterPlugin.registerEventListener(SprigLifecycleEvent.sdkReady, (Map eventData) async {
print("SDK is ready");
});
} on PlatformException catch (e) {
print('PlatformException: ${e.message}');
}
if (!mounted) return;
setState(() {
_sdkVersion = sdkVersion;
});
}
@override
Widget build(BuildContext context) {
return MaterialApp(
home: Scaffold(
appBar: AppBar(
title: const Text('A Flutter App'),
),
body: Container(
margin: const EdgeInsets.only(left: 16.0),
child: ListView(
padding: const EdgeInsets.all(8),
children: [
Text('Sprig SDK version: $_sdkVersion'),
// Spacer
SizedBox(height: 20),
// Button to present a survey by supplied ID
SizedBox(
width: double.infinity,
child: ElevatedButton(
onPressed: () {
_sprigFlutterPlugin.trackAndPresent(eventName: "");
},
child: Text("Call trackAndPresent"),
),
),
],
),
)
),
);
}
}
```
Be sure to swap in the correct environment ID for YOUR\_ENVIRONMENT\_ID. Note that `configure()` will only accept 1 environment ID, and calling it multiple times with different IDs will have no effect.
# Additional Functionality
Note that the remaining examples use **\_sprigFlutterPlugin** when calling the plugin, assuming you have set **\_sprigFlutterPlugin** to **SprigFlutterPlugin()** as in the above code.
## Identify Users
Identifying users ensures that a user’s actions are all associated with the same profile so they can be targeted.
Properly identifying users helps ensure:
* Your users have a consistent experience across platforms, and do not see the same study multiple times
* You can accurately target the right users
* You are billed for the correct number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index)
### Set User ID
Sprig allows you to differentiate users by setting a unique USER\_ID. You may want to ensure consistency between the User IDs sent to Sprig and the ones in your internal database, product analytics/CDP, or data warehouse. You can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is…
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
Users that do not have a User ID set are considered unauthenticated.
You can use `setUserIdentifier()` to identify a user with any string less than 256 characters. This function can be called multiple times safely, and stores the identifier via local storage. We recommend you set the User ID whenever the user logs in to your app, as well as after the installation snippet (if the user is already logged in).
```cplusplus Dart theme={null}
_sprigFlutterPlugin.setUserIdentifier(identifier: "");
```
### Logout
When a user logs out of your app, make sure to log out of Sprig. This will prevent new activity from being associated with an incorrect user. Note that if you call `logout()` on an unauthenticated user, Sprig will assign them a new profile and count this new user separately toward your MTU limit.
```cplusplus Dart theme={null}
_sprigFlutterPlugin.logout();
```
## Track Events
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
Once you’ve installed the Sprig SDK, the next step is to configure the tracking of events that you would like to use to trigger a study. For mobile SDKs, you must configure [Code](/docs/shared-study-foundations/events/code-events) events. (Sprig also offers [No-Code](/docs/shared-study-foundations/events/no-code-events) events, but these are only available on web platforms.)
To track a Code event, use:
```cplusplus Dart theme={null}
SizedBox(
width: double.infinity,
child: ElevatedButton(
onPressed: () {
_sprigFlutterPlugin.track(eventName: "", onCompletion: (surveyState) {
debugPrint("Track completed with survey state: $surveyState");
if (surveyState == SprigSurveyState.ready) {
_sprigFlutterPlugin.present();
}
});
},
child: const Text('Track with callback and then present'),
),
),
```
After sending a new Code event to Sprig, you must [approve the new event request](/docs/shared-study-foundations/events/index#adding-events) on the [Events page](https://app.sprig.com/events) before it can be used to trigger or filter surveys.
These events will also be available as filters for your studies. For example, you may want to only display a study to users who have performed the "checkout" event at least 3 times.
## Track Attributes
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#survey-filter) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the Users page, and are recorded and attached to any surveys response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
To set user attributes, provide the SDK with a key-value pairs:
* `ATTRIBUTE_NAME` must be a string less than 256 characters, and cannot start with an `!` (these names are reserved for use by Sprig)
* `ATTRIBUTE_VALUE` must be a number, boolean, or string less than 256 characters
```cplusplus Dart theme={null}
_sprigFlutterPlugin.setVisitorAttribute(key: "", value: "");
// if attributes no longer apply to the user,
// you can delete multiple at a time
_sprigFlutterPlugin.removeVisitorAttributes(attributes:["", ""]);
```
### Set Email Address
Setting the user’s email address is **optional**. Setting emails is not required for web or mobile studies, but can be used to target users or create a Group of users based on their email. Check your organization's guidelines around personally-identifiable information before sending email addresses to Sprig.
```cplusplus Dart theme={null}
_sprigFlutterPlugin.setEmailAddress(emailAddress: );
```
## Test & Deploy
To verify your SDK is configured properly, we recommend testing with your development `ENVIRONMENT_ID`.
1. Create a survey in your Sprig Development Environment
2. Choose an approved event as a trigger for your study
3. \[For testing purposes only] Allow users to retake the survey and set the recontact waiting period to 0 days
4. Track the approved event from your app and confirm that the survey appears
Congratulations! Your installation is complete and you can begin deploying.
# iOS SwiftUI Session Replay Implementation Guide
Source: https://docs.sprig.com/docs/installation/introduction-mobile/i-os-swift-ui-session-replay-implementation-guide
# Background
Sprig Session Replays for iOS are schematic; each frame is a rough representation of what the user is seeing on the screen of the app. They are not screen shots of the UI itself.
To achieve this, the Sprig iOS SDK traverses the UIKit view hierarchy, collecting element details of the screen and then recreating them into an image, using the image as the basis for each video frame. This allows us to filter out text or images when customers select the Strict replay capture mode.
Starting with iOS26, some SwiftUI text and image elements no longer appear in the UIKit view hierarchy. In order to capture these elements in replays, we have created SwiftUI modifiers that host app developers can place in their code on elements that they would like rendered in session replays.
This content capture method also enables the capture of custom UI elements that could not previously be captured (a custom chart view, for example).
This replay capture enhancement is available starting with the Sprig iOS SDK v4.34.0.
# The Sprig SwiftUI session replay modifiers
Following are the modifiers you can add to SwiftUI elements in order to capture them in schematic session replays.
`.sprigSnapshotText()` - Views with this modifier will be captured as an image unless the privacy settings require masking of text, in which case they will not be captured, and instead placeholder text will be rendered in the same frame.
`.sprigSnapshotImage()` - Views with this modifier will be captured as an image unless the privacy settings require masking of images, in which case they will be rendered as a rectangle shape in the same frame with an image icon in the middle.
`.sprigSnapshotPlaceholder()` - Views with this modifier will be rendered as a rectangle shape in the same frame as the View.
`.sprigSnapshot()` - Views with this modifier will be captured as an image regardless of the current privacy settings. Use this only if you want to capture a custom View that is not being captured by the UIKit capture and does not contain PII.
# Example code and images
Following is an example of implemented modifiers in some basic SwiftUI:
```swift theme={null}
struct ExampleView: View {
var body: some View {
VStack(spacing: 20) {
Text("This is a Text element.")
.sprigSnapshotText()
Rectangle()
.fill(Color.green)
.frame(width: 200, height: 200)
.sprigSnapshotPlaceholder(color: Color.green)
Image("puppy")
.resizable()
.frame(width: 100, height: 100)
.cornerRadius(20)
.sprigSnapshotImage()
Image("puppy")
.resizable()
.frame(width: 100, height: 100)
.cornerRadius(20)
.sprigSnapshot()
}
}
}
```
Below are screenshots of the app itself (running the code above), a frame of the replay without masking and a frame of the replay with privacy set to Strict.
Note that the second puppy image used the`.sprigSnapshot()`modifier, which did *not* adhere to the privacy settings, and thus still fully rendered even when the privacy setting was on Strict.
# Considerations
When implementing the Sprig SwiftUI modifiers in your SwiftUI app, please keep the following in mind:
## Test first
Many SwiftUI elements *do* get translated down to UIKit elements and *will* show up in Sprig session replays without any additional code. Before adding the Sprig SwiftUI modifiers, you should run a replay capture on the user paths of your app that you would like captured and note any UI elements that are already being captured (and thus don’t need the modifiers).
## Smaller is better (most of the time)
The modifiers use`UIGraphicsImageRenderer`to capture the content of the View they are modifying. This happens on the main thread; as such you should use them sparingly and apply them to the smaller pieces that you want to capture. In other words, if you have a view that is made up of 5 text elements, rather than capture the entire view with one modifier, capture each text element with a modifier. Adding a modifier to each element rather than a parent View decreases the chance that you will accidentally capture an element with PII and decreases the total area that needs to be captured.
Having said that, due to the extreme complexity around SwiftUI rendering, if an element you are trying to capture is not showing up in the replay after adding a modifier, go up a level to the parent View and apply the modifier there.
## Think about PII
The Sprig SwiftUI replays modifiers are designed to respect the privacy settings that customers select in the Sprig dashboard. In order for this to work, developers need to use the modifier designed for the element they are trying to capture.
* Text elements should be captured with the`.sprigSnapshotText() `modifier.
* Image elements should be captured with the`.sprigSnapshotImage() `modifier.
Note that the`.sprigSnapshot()`modifier will capture everything in the view being modified, regardless of the privacy setting in the dashboard. It is designed to be used with UI elements that are not normally captured in the UIKit view hierarchy but should be rendered in a replay (for example, a custom chart view).
Use the`.sprigSnapshotPlaceholder()`modifier to put a placeholder colored box where PII content exists that you do not want to capture. This allows viewers of the replay to recognize that something is in that location without showing potential PII contained in that element.
## View snapshots are cached
In order to be as efficient as possible with our session replay capture, snapshots of elements are cached until the replay itself has been rendered. As such, dynamic elements in your UI that are being captured will only reflect their initial state in replays.
## Capturing complex stacked layouts
Given the nature of SwiftUI rendering of text and images, it is impossible for the SprigSDK to know the Z-index of an element being captured. Therefore, if you have multiple elements that live on top of each other that you would like to capture, you should pass a z-index value as a parameter in the modifier. This will allow the SprigSDK to render the elements in the proper order in the replay itself.
For example:
```swift theme={null}
ZStack {
// Bottom Layer: A large blue square.
Rectangle()
.fill(.blue)
.frame(width: 200, height: 200)
.sprigSnapshotPlaceholder(zIndex: 0, color: .blue)
// Middle Layer: A smaller green square.
Rectangle()
.fill(.green)
.frame(width: 130, height: 130)
.sprigSnapshotPlaceholder(zIndex: 1, color: .green)
// Top Layer: Text on top of everything.
Text("Front Layer")
.foregroundColor(.white)
.fontWeight(.bold)
.sprigSnapshotText(zIndex: 2)
}
```
## Gaining visibility into capture time on the main thread
In order to give host app developers visibility into how long screen captures are taking, we have provided the ability to subscribe to loggingEvents that contain the details of each UIKit and SwiftUI element capture.
To receive the capture details, simply pass a value of`true`to the`showReplayCaptureLogging`method on the Sprig singleton, and register to listen to logging events, like so:
```swift theme={null}
Sprig.shared.showReplayCaptureLogging(true)
Sprig.shared.registerEventListener(for: .loggingEvent) { data in
print(data["message"] ?? "(none)")
}
```
# Mobile
Source: https://docs.sprig.com/docs/installation/introduction-mobile/index
## Overview
Installing Sprig on your mobile applications allows you to:
* Ask the right questions, to the right users, at the right time with [Sprig Surveys](/docs/sprig-studies/in-product-surveys/index)
* Monitor your customer's interactions and behavior with [Sprig Replays](/docs/sprig-studies/replays/replay-creation/mobile-replays)
Install Sprig in hours or days (not months) and configure studies based on [Events](/docs/shared-study-foundations/events/index) and [Attributes](/docs/shared-study-foundations/attributes) associated with users as they use your app.
## Installation Options
To launch a Sprig study on your mobile app, you'll need to install one of the following:
* Native [iOS](/docs/Installation/introduction-mobile/ios-sdk-installation) and [Android](/docs/Installation/introduction-mobile/android-sdk-installation/index) SDKs
* [React Native Module](/docs/Installation/introduction-mobile/react-native-module) (if your apps are built using React Native)
* [Segment iOS](/docs/Installation/introduction-mobile/segment-ios), [Segment Android](/docs/Installation/introduction-mobile/segment-android), or [Segment React Native](/docs/Installation/introduction-mobile/segment-react-native) (if Segment is installed in your apps)
# iOS SDK
Source: https://docs.sprig.com/docs/installation/introduction-mobile/ios-sdk-installation/index
## Getting Started
### Overview
The Sprig iOS SDK, when installed in your native iOS app, allows you to track your customer’s in-product behavior and display Sprig studies when they perform certain actions.
### Requirements
* Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/ios-sdk).
* Ensure you have access to your iOS codebase, and can deploy to a development and/or production environment
* The Sprig iOS SDK only supports iOS 16 and above.
* Xcode 14: If you have not updated to the Xcode 14, you may experience build issues since [Xcode 14 removes bitcode](https://developer.apple.com/documentation/xcode-release-notes/xcode-14-release-notes). Check out Sprig's [legacy release](https://github.com/UserLeap/userleap-ios-sdk-releases/releases?q=legacy\&expanded=true) for Xcode 13 compatibility.
To see all official releases of the Sprig iOS SDK, visit the [repository](https://github.com/UserLeap/userleap-ios-sdk-releases/releases).
## Install SDK
There are three ways you can include Sprig in your application: SPM, CocoaPods, or manually.
### Install via SPM
To install using SPM, use our [release repository](https://github.com/UserLeap/userleap-ios-sdk-releases/releases) and install the package from main branch:
### Install via CocoaPods
To install via CocoaPods, add the following statement to your Podfile:
```bash theme={null}
pod 'UserLeapKit'
```
Then run this command in the same directory that contains your Podfile:
```bash theme={null}
pod install
```
### Install manually
If you’re unable to use Cocoapods or Carthage, you can also install Sprig manually. Download the latest framework as a zip from our [Releases](https://github.com/UserLeap/userleap-ios-sdk-releases/releases). Unzip the downloaded file and drag the UserLeap.framework folder into your project directory.
Open Xcode and select your project in the “Project Navigator” pane, select your app under “TARGETS”. In the “Frameworks, Libraries, and Embedded Content” section, press “+”, “Add Other…”, “Add Files…” and select the UserLeap.framework folder.
Be sure that UserLeap.framework is in your project settings “Framework Search Paths” or Xcode will throw the “no such module UserLeap” error.
### Obtain an Environment ID
After you've installed, you must obtain an environment ID from Sprig. Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [Integrations > iOS SDK](https://app.sprig.com/integrations/installation/ios-sdk)).
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Initialize the SDK
Usage is simple and revolves around a singleton, conveniently named `Sprig`. The singleton must be configured before it can be used. A common pattern is to configure this in your `ApplicationDelegate`, but follow the best practices for your team and application.
```swift theme={null}
import UserLeapKit
class AppDelegate: UIResponder, UIApplicationDelegate {
func application(_ application: UIApplication, didFinishLaunchingWithOptions launchOptions: [UIApplication.LaunchOptionsKey: Any]?) -> Bool {
//your app setup
Sprig.shared.configure(withEnvironment: "ENVIRONMENT_ID")
return true
}
}
/**
* You can test your study easily (bypass all filters and resurvey windows) by
* using Sprig's new testing feature. This requires installing Sprig v4.19.0 and
* adding the following code to pass the study's unique previewKey to the Sprig
* instance.
**/
func application(_ app: UIApplication, open url: URL, options: [UIApplication.OpenURLOptionsKey : Any] = [:]) -> Bool {
URLComponents(url: url, resolvingAgainstBaseURL: false)?.queryItems?.forEach {
if let value = $0.value, $0.name == Sprig.previewKeyName {
Sprig.shared.setPreviewKey(value)
}
}
return true
}
```
Be sure to swap in the correct ENVIRONMENT\_ID. Note that `configure` will only accept 1 environment ID, and calling it multiple times with different IDs will have no effect.
**Warning:** Additional action recommended for customers that completed SDK install before October 2023 to enable in app testing feature
In order to [test your study](/docs/sprig-studies/in-product-surveys/study-testing) directly in your production application, you must first update your application’s install code to include additional snippet below ⬇️
### Study Previews
```swift theme={null}
/**
* You can test your study easily (bypass all filters and resurvey windows) by
* using Sprig's new testing feature. This requires installing Sprig v4.19.0 and
* adding the following code to pass the study's unique previewKey to the Sprig
* instance.
**/
func application(_ app: UIApplication, open url: URL, options: [UIApplication.OpenURLOptionsKey : Any] = [:]) -> Bool {
URLComponents(url: url, resolvingAgainstBaseURL: false)?.queryItems?.forEach {
if let value = $0.value, $0.name == Sprig.previewKeyName {
Sprig.shared.setPreviewKey(value)
}
}
return true
}
```
Alternatively, you can overwrite the previously added install code with the version [here](/docs/Installation/introduction-mobile/ios-sdk-installation#initialize-the-sdk) that includes the required changes. Be sure to swap in the correct ENVIRONMENT\_ID
Sprig is not thread-safe, so please invoke all methods on the main thread. Rest assured that all network and I/O requests are made asynchronously.
## Identify Users
Identifying users ensures that a user’s actions are all associated with the same profile so they can be targeted.
Properly identifying users helps ensure:
* Your users have a consistent experience across platforms, and do not see the same study multiple times
* You can accurately target the right users
* You are billed for the correct number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index#monthly-unique-users-muu-usage)
### Set User ID
Sprig allows you to differentiate users by setting a unique USER\_ID. You may want to ensure consistency between the User IDs sent to Sprig and the ones in your internal database, product analytics/CDP, or data warehouse. You can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is…
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
Users that do not have a User ID set are considered unauthenticated.
You can use `setUserIdentifier` to identify a user with any string less than 256 characters. This function can be called multiple times safely, and stores the identifier locally. We recommend you set the User ID whenever the user logs in to your app, as well as after the configuring Sprig (if the user is already logged in).
```swift theme={null}
Sprig.shared.setUserIdentifier("USER_ID")
```
### Logout
When a user logs out of your app, make sure to log that user out of the Sprig SDK. This will prevent any new activity from being associated with the wrong user. Note that if you call `logout()` on an unauthenticated user, Sprig will assign them a new profile and count this new user separately toward your MTU limit.
```swift theme={null}
Sprig.shared.logout()
```
## Track Events
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
Once you’ve installed the Sprig SDK, the next step is to configure the tracking of events that you would like to use to trigger or filter a study. For mobile SDKs, you must configure [Code](/docs/shared-study-foundations/events/code-events) events. (Sprig also offers [No-Code](/docs/shared-study-foundations/events/no-code-events) events, but these are only available on web platforms.)
An event’s properties can be used to further filter an event trigger for a survey. To set an event's properties, provide key-values pairs where:
* `KEY` must be a string less than 256 characters, and cannot start with an `!` (these names are reserved for use by Sprig)
* `VALUE` can be string|number|boolean that is less than 256 characters
To track a Code event, use:
```swift theme={null}
let payload = EventPayload(eventName: "EVENT_NAME", properties:["key": "value"])
Sprig.shared.trackAndPresent(payload: payload, from: YOUR_VIEW_CONTROLLER)
```
If you are using SwiftUI and don't want to create UIViewController, you can call trackAndPresent without passing a UIViewController. The SDK will look for the root or host UIViewController and present the survey from there.
```swift SwiftUI theme={null}
let payload = EventPayload(eventName: "EVENT_NAME", properties:["key": "value"])
Sprig.shared.trackAndPresent(payload: payload)
```
After sending a new Code event to Sprig, you must [approve the new event request](https://sprig.mintlify.app/docs/shared-study-foundations/events/index#adding-events) on the [Events page](https://app.sprig.com/events) before it can be used to trigger or filter surveys.
Alternatively, after sending each tracking event, you can check if a new survey is ready for the user. If a survey is ready, you can decide to present the survey to the user. The survey will be presented onto the provided viewController from the bottom of the screen.
```swift theme={null}
let payload = EventPayload(eventName: "EVENT_NAME", properties:["key": "value"]) { state in
switch state {
case .ready:
Sprig.shared.presentSurvey(from: viewController)
case .noSurvey, .disabled:
break
}
}
Sprig.shared.track(payload: payload)
```
These events will also be available as filters for your studies. For example, you may want to restrict a study to users who performed the "checkout" event at most 3 times.
## Track Attributes
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#survey-filter) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the Users page, and are recorded and attached to any surveys response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
To set a user’s attribute, provide key-values pairs where:
* `KEY` must be a string less than 256 characters, and cannot start with an `!` (these names are reserved for use by Sprig)
* `VALUE` can be string|number|boolean that is less than 256 characters
```swift theme={null}
// for a single attribute
Sprig.shared.setVisitorAttribute(key: "KEY", value: "VALUE")
// for multiple attributes
// saves multiple round-trips and reduces data usage
Sprig.shared.setVisitorAttributes([
"KEY1": "VALUE1",
"KEY2": "VALUE2"
])
// if attributes no longer apply to the user,
// you can delete multiple at a time
Sprig.shared.removeVisitorAttributes(["KEY1", "KEY2"])
```
### Set Email Address
Setting the user’s email address is **optional**. Setting emails is not required for web or mobile studies, but can be used to target users or create a Group of users based on their email. Check your organization's guidelines around personally-identifiable information before sending email addresses to Sprig.
```swift theme={null}
Sprig.shared.setEmailAddress("EMAIL_ADDRESS")
```
## Test & Deploy
To verify your SDK is configured properly, we recommend testing with your development `ENVIRONMENT_ID`.
1. Create a survey in your Sprig Development Environment
2. Choose an approved event as a trigger for your study
3. \[For testing purposes only] Allow users to retake the survey and set the recontact waiting period to 0 days
4. Track the approved event from your app
Congratulations! Your installation is complete and you can begin deploying.
## Advanced Customization
### Study Lifecycle Notifications
Sprig exposes updates throughout the study lifecycle. Here is a sample code block for listening to SDK events in real time:
```swift Swift theme={null}
Sprig.shared.registerEventListener(for: .surveyReturned) { eventData in
let surveyId = eventData["surveyId"]
}
```
| Lifecycle Event | Data | Min SDK Version |
| :- | :- | :- |
| sdkReady | `{ name: 'sdkReady' }` | 4.18.0 |
| visitorIdUpdated | `{ name: 'visitorIdUpdated' }` | 4.18.0 |
| ~~surveyWillPresent~~ | `{ name: 'surveyWillPresent', 'surveyId': String }` | removed in 4.35.0 |
| ~~surveyPresented~~ | `{ name: 'surveyPresented' }` | removed in 4.35.0 |
| surveyReturned | `{ name: 'surveyReturned' , 'surveyId': String }` | 4.35.0 |
| surveyAppeared | `{ name: 'surveyAppeared' }` | 4.18.0 |
| surveyClosed | `{ name: 'surveyClosed' }` | 4.18.0 |
| surveyWillDismiss | `{ name: 'surveyWillDismiss' }` | 4.18.0 |
| surveyDidNotAppear | `{ name: surveyDidNotAppear' , 'surveyDidNotAppearReason': String }` | 4.35.0 |
### Sprig Replays Lifecycle Notifications
Sprig exposes updates throughout the Sprig Replay lifecycle. Here is a sample code block for listening to replay events in real time:
```swift Swift theme={null}
Sprig.shared.registerEventListener(for: .replayCaptureStarted) { eventData in
}
```
| Sprig Replay Lifecycle Event | Min SDK Version |
| :- | :- |
| replayCaptureStarted | 4.23.4 |
| replayCaptureStopped | 4.23.4 |
| replayCaptureCompleted | 4.23.4 |
| replayRenderingCompleted | 4.23.4 |
| replayUploadCompleted | 4.23.4 |
| replayEventsUploadCompleted | 4.23.4 |
### Set Locale
Sprig supports setting the locale for default caption and button text. The following locales are supported:
* de
* en
* es-es
* fr
* hi
* ja
* ko
* pt-br
* ru
* zh
To set the locale to Chinese:
```swift theme={null}
Sprig.shared.setLocale('zh')
```
Setting the locale will only affect static text, and is only available for the iOS and Android SDKs (not React Native).
### App size impact
Sprig only uses `Foundation`, `UIKit`, `SystemConfiguration`, and `CoreGraphics` with no third-party frameworks to provide the smallest disk footprint on your app binary.
The SDK size is **234 KB** compressed and **592 KB** uncompressed.
Note: Compressed is equivalent to the additional size downloaded from the App Store, and uncompressed is the additional size on an iPhone after installation
Methodology: Created a fresh Xcode project with and without UserLeapKit.framework and used the App Size Report tool ([Apple docs](https://developer.apple.com/documentation/xcode/reducing_your_app_s_size#//apple_ref/doc/uid/DTS40014195-CH1-MEASURE))
# React Native SDK
Source: https://docs.sprig.com/docs/installation/introduction-mobile/react-native-module
Easily install Sprig into your React Native mobile apps via Segment to track behavior and send targeted In-Product Surveys based on your users' characteristics and actions they take in your product.
## Getting Started
### Overview
The Sprig React Native SDK, when installed in app, allows you to track your customer’s in-product behavior and display Sprig studies when they perform certain actions.
### Requirements
* Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/react-native-module).
* Ensure you have access to your React Native codebase, and can deploy to a development and/or production environment
* Please check the platform-specific requirements:
* [iOS](/docs/Installation/introduction-mobile/ios-sdk-installation#requirements): iOS 13 or above; Xcode 14
* [Android](/docs/Installation/introduction-mobile/android-sdk-installation/index#requirements): Android SDK 21 (Lollipop, OS 5.0) and above
## Install React Native Module
### Obtain an Environment ID
Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [Integrations > React Native Module](https://app.sprig.com/integrations/installation/react-native-module)).
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Install with npm/Yarn
Use the following shell command to install the Sprig SDK through [npm](https://en.wikipedia.org/wiki/Npm_\(software\)) or [YARN](https://en.wikipedia.org/wiki/Yarn_\(package_manager\)).
Note that you will have to update the SDK manually to receive the latest functionality. We recommend you update the package monthly for improved functionality and bug fixes.
```shell NPM theme={null}
npm install --save react-native-userleap
```
```shell Yarn theme={null}
yarn add react-native-userleap@latest
```
When installing for iOS, you need to do `pod install`. And if you are updating, it's best to remove the `Podfile.lock` and run `pod repo update` first. So from your app top-level directory, run the following commands:
```bash theme={null}
cd ios
rm Podfile.lock
pod repo update
pod install
```
### Initialize the SDK
Then, in your application, initialize Sprig with your ENVIRONMENT\_ID:
```javascript theme={null}
import { Linking } from 'react-native';
import Sprig from 'react-native-userleap'
Sprig.configure('ENVIRONMENT_ID');
/**
* You can test your study easily (bypass all filters and resurvey windows) by
* using Sprig's new testing feature. This requires installing Sprig v2.15.0 and
* adding the following code to pass the study's unique previewKey to the Sprig
* instance.
**/
Linking.getInitialURL().then(url => {
let urlObj = new URL(url);
let previewKey = urlObj.searchParams.get('sprigPreviewKey');
if (previewKey) {
Sprig.setPreviewKey(previewKey)
}
}).catch(error => { console.log(error)})
// This handles URLs when the app is already open, but not foregrounded.
Linking.addEventListener('url', (event) => {
let urlObj = new URL(event.url);
let previewKey = urlObj.searchParams.get('sprigPreviewKey');
if (previewKey) {
Sprig.setPreviewKey(previewKey)
}
})
```
Be sure to swap in the correct ENVIRONMENT\_ID. Note that `configure()` will only accept 1 environment ID, and calling it multiple times with different IDs will have no effect.
Note: If an installation error occurs on incompatible react versions, you may need to use the `--legacy-peer-deps` option
```bash theme={null}
npm i --legacy-peer-deps
```
Note: If this error occurs on Android `
Attempt to invoke virtual method'boolean com.facebook.react.uimanager.FabricViewStateManager.hasStateWrappper()`, you can either update your `react-native` dependency to version `0.68.2` or higher, or you can add the following snippet to the dependencies in the `build.gradle` file under the app directory. The version block is necessary in the snippet.
```groovy theme={null}
implementation ("androidx.appcompat:appcompat:1.3.1") {
version {
strictly '1.3.1'
}
}
```
**Warning:** Additional action recommended for customers that completed SDK install before October 2023 to enable in app testing feature
In order to[ test your study](/docs/sprig-studies/in-product-surveys/study-testing) directly in your production application, you must first update your application’s install code to include additional snippet below ⬇️
### Study Previews
```javascript theme={null}
/**
* You can test your study easily (bypass all filters and resurvey windows) by
* using Sprig's new testing feature. This requires installing Sprig v2.15.0 and
* adding the following code to pass the study's unique previewKey to the Sprig
* instance.
**/
import { Linking } from 'react-native';
Linking.getInitialURL().then(url => {
let urlObj = new URL(url);
let previewKey = urlObj.searchParams.get('sprigPreviewKey');
if (previewKey) {
Sprig.setPreviewKey(previewKey)
}
}).catch(error => { console.log(error)})
// This handles URLs when the app is already open, but not foregrounded.
Linking.addEventListener('url', (event) => {
let urlObj = new URL(event.url);
let previewKey = urlObj.searchParams.get('sprigPreviewKey');
if (previewKey) {
Sprig.setPreviewKey(previewKey)
}
})
```
Alternatively, you can overwrite the previously added install code with the version [here](/docs/Installation/introduction-mobile/react-native-module#initialize-the-sdk) that includes the required changes. Be sure to swap in the correct ENVIRONMENT\_ID
## Identify Users
Identifying users ensures that a user’s actions are all associated with the same profile so they can be targeted.
Properly identifying users helps ensure:
* Your users have a consistent experience across platforms, and do not see the same study multiple times
* You can accurately target the right users
* You are billed for the correct number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index)
### Set User ID
Sprig allows you to differentiate users by setting a unique USER\_ID. You may want to ensure consistency between the User IDs sent to Sprig and the ones in your internal database, product analytics/CDP, or data warehouse. You can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is…
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
Users that do not have a User ID set are considered unauthenticated.
You can use `setUserIdentifier()` to identify a user with any string less than 256 characters. This function can be called multiple times safely, and stores the identifier via local storage. We recommend you set the User ID whenever the user logs in to your app, as well as after the installation snippet (if the user is already logged in).
```javascript theme={null}
Sprig.setUserIdentifier('USER_ID');
```
### Logout
When a user logs out of your app, make sure to log out of Sprig. This will prevent new activity from being associated with an incorrect user. Note that if you call `logout()` on an unauthenticated user, Sprig will assign them a new profile and count this new user separately toward your MTU limit.
```javascript theme={null}
Sprig.logout();
```
## Track Events
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
Once you’ve installed the Sprig SDK, the next step is to configure the tracking of events that you would like to use to trigger a study. For mobile SDKs, you must configure [Code](/docs/shared-study-foundations/events/code-events) events. (Sprig also offers [No-Code](/docs/shared-study-foundations/events/no-code-events) events, but these are only available on web platforms.)
To track a Code event, use:
```javascript theme={null}
Sprig.trackWithProperties(
'EVENT_NAME',
'USER_ID',
null, // ignore this parameter
{
property1: 'value',
},
state => {
if (state === Sprig.SurveyState.READY) {
Sprig.presentSurvey();
}
},
);
```
After sending a new Code event to Sprig, you must [approve the new event request](/docs/shared-study-foundations/events/index#adding-events) on the [Events page](https://app.sprig.com/events) before it can be used to trigger or filter surveys.
These events will also be available as filters for your studies. For example, you may want to only display a study to users who have performed the "checkout" event at least 3 times.
## Track Attributes
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#survey-filter) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the Users page, and are recorded and attached to any surveys response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
To set user attributes, provide the SDK with a key-value pairs:
* `ATTRIBUTE_NAME` must be a string less than 256 characters, and cannot start with an `!` (these names are reserved for use by Sprig)
* `ATTRIBUTE_VALUE` must be a number, boolean, or string less than 256 characters
```javascript theme={null}
Sprig.setVisitorAttribute('ATTRIBUTE_NAME', 'ATTRIBUTE_VALUE');
// you can set multiple at a time
// to save on network round trips
Sprig.setVisitorAttributes({'ATTRIBUTE_NAME', 'ATTRIBUTE_VALUE'});
// if attributes no longer apply to the user,
// you can delete multiple at a time
Sprig.removeVisitorAttributes({'ATTRIBUTE_NAME', 'ATTRIBUTE_VALUE'});
```
### Set Email Address
Setting the user’s email address is **optional**. Setting emails is not required for web or mobile studies, but can be used to target users or create a Group of users based on their email. Check your organization's guidelines around personally-identifiable information before sending email addresses to Sprig.
```javascript theme={null}
Sprig.setEmailAddress('EMAIL_ADDRESS');
```
## **Listening to Lifecycle Events**
Sprig emits **lifecycle events** as the SDK initializes and as surveys are presented, answered, and closed. You can subscribe to these to run your own logic — for example, pausing background media while a survey is on screen, or logging when a survey completes.
Subscribe with `addEventListener`, which returns a subscription you can later remove:
```javascript theme={null}
const subscription = Sprig.addEventListener(
Sprig.SprigEventName.surveyPresented,
(event) => {
console.log('A survey was presented', event);
}
);
// Later, when you no longer need it:
subscription.remove();
```
The event name can be passed as a string or via the `Sprig.SprigEventName` constants. The callback receives an `event` object that always includes the event `type`, plus any fields relevant to that event (for example, `surveyId` on survey events).
**Commonly used events**
* `sdkReady` — the SDK has finished initializing
* `surveyWillPresent` / `surveyPresented` / `surveyAppeared` — a survey is being shown
* `surveyCloseRequested` / `surveyWillClose` / `surveyClosed` — a survey is closing
* `surveyCompleted` — the user completed a survey
* `visitorIdUpdated` — the visitor ID changed
* `questionAnswered` — the user answered a question within a survey
* `loggingEvent` — SDK diagnostic logs, useful for debugging
See the `Sprig.SprigEventName` enum for the full list of events.
**Removing listeners**
```javascript theme={null}
// Remove all listeners for a single event
Sprig.removeAllEventListeners(Sprig.SprigEventName.surveyPresented);
// Remove all lifecycle event listeners
Sprig.removeAllEventListeners();
```
## **Test** & Deploy
To verify your SDK is configured properly, we recommend testing with your development `ENVIRONMENT_ID`.
1. Create a survey in your Sprig Development Environment
2. Choose an approved event as a trigger for your study
3. \[For testing purposes only] Allow users to retake the survey and set the recontact waiting period to 0 days
4. Track the approved event from your app and confirm that the survey appears
Congratulations! Your installation is complete and you can begin deploying.
## Advanced Customization
### App size impact
See more information about the [iOS app size impact](/docs/Installation/introduction-mobile/ios-sdk-installation#app-size-impact) and [Android app size impact](/docs/Installation/introduction-mobile/android-sdk-installation/index#app-size-impact).
# Segment Android
Source: https://docs.sprig.com/docs/installation/introduction-mobile/segment-android
Leverage the Segment Android CDP to easily install Sprig into your Android mobile app. This integration makes it easy to send targeted In-Product Surveys based on your users' characteristics and actions they take in your product.
## Getting Started
### Overview
Segment is a Customer Data Platform (CDP) that collects and processes data from the users of your digital platforms and products. You can also use Segment to direct that data to other tools, making it a powerful tool for driving product experience insights with Sprig.
If your team is already leveraging Segment in your digital properties, you can use Segment to install the Sprig SDK as well as send the data Sprig needs to trigger and filter studies (like events and attributes).
This is an effective low-to-no-code option because it requires minimal code changes to deploy in-product Sprig studies. Even many of Sprig’s advanced features also require no changes to your codebase as long as you know what Segment functions your organization is already deploying.
**Warning:** Segment Actions vs Segment Classic
This install method leverages [Segment Actions](https://segment.com/docs/connections/destinations/actions/) both to install the Sprig SDK and to send events and attributes to Sprig from Segment. In most cases, we recommend integrating Sprig with Segment Actions over Segment Classic, although certain use cases may require Segment Classic, such as passing data to Sprig from your product's backend. For more information, consult with your Segment administrator or our [Segment Classic](/docs/Integrations/data-sources-introduction/segment-classic) documentation.
### Requirements
1. Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/segment-android).
2. You will either need to access your team’s Segment account, or work with your team’s Segment administrator.
3. If you are planning to use Segment as a source for certain events and attributes, you may wish to consult with a developer on your team who has knowledge of how these events and attributes are expressed in the codebase.
## Install SDK
If you are running Segment and wish to integrate your Segment instance with Sprig, you will first need to follow these steps to install the Sprig SDK.
### Obtain a Sprig Environment ID
Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [Integrations > Segment Android](https://app.sprig.com/integrations/installation/segment-android)).
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Set up Sprig as a Segment Destination
In Segment, you will be connecting your app as a Source to Sprig as a Destination. This will enable the Segment SDK to pass data to the Sprig SDK.
To do this, follow these steps (or follow [this video](https://www.loom.com/share/f6858cc78d2f4132965e853ec4d0b80d)):
1. In Segment, click **Connections**, then click **Destinations**.
2. Search for “Sprig” and select the **Sprig** destination.
3. Click **Configure Sprig**.
4. Select your data source (e.g. your app).
5. Enter an identifiable destination name and ensure **Actions** is selected.
6. Copy your **Environment ID** from your [Sprig Dashboard](https://app.sprig.com/integrations) and paste it into the **Environment ID** field.
7. Turn on **Enable Destination** and save your changes.
### Install the Sprig Plugin via Gradle
Next, you will need to install the Sprig plugin.
1. Add mavenCentral() to your project's root build.gradle repositories block
2. In your application module's build.gradle file, add the dependency:
```gradle theme={null}
dependencies {
implementation "com.userleap:segment-analytics-kotlin-destination:$version"
}
```
Note the Sprig Android SDK will be installed as an additional dependency.
### Initialize the Sprig Plugin
Add the Sprig destination where Segment is configured.
If you are initializing the Analytics class in your Application class:
```gradle theme={null}
analytics = Analytics(BuildConfig.SEGMENT_WRITE_KEY, this) {
// Automatically track Lifecycle events
trackApplicationLifecycleEvents = true
flushAt = 3
flushInterval = 10
}.add(SprigDestination(application = this))
```
If you are initializing the Analytics class in your Activity class:
```gradle theme={null}
analytics = Analytics(BuildConfig.SEGMENT_WRITE_KEY, this) {
// Automatically track Lifecycle events
trackApplicationLifecycleEvents = true
flushAt = 3
flushInterval = 10
}.add(SprigDestination(application = applicationContext))
```
And that's it! All Users, Events, and Attributes that you send to the Segment SDK will automatically be forwarded to the Sprig SDK. Surveys will be presented on the top activity.
## Identify Users
Each time a user is tracked by Sprig on an app with the SDK installed, they are assigned a unique visitor ID in Sprig that allows users to be targeted with studies when they perform specified behaviors.
While this is a requirement for targeting users with Sprig studies, these are still considered unauthenticated users until their Sprig visitor IDs are coupled with the unique USER\_IDs assigned to users within your platform’s internal authentication framework.
We recommend that you follow this best practice when installing Sprig:
* This ensures consistency between the visitor IDs generated by Sprig and the ones in your internal database, product analytics/CDP, or data warehouse, allowing more effective targeting of studies.
* Your users have a consistent experience across platforms, and do not see the same study multiple times.
* **It also optimizes the number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index) sent to Sprig, which impacts your billing**.
If necessary, you can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is:
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
Once you've configured Sprig as a Segment destination above, users tracked from Segment's [Identify method](https://segment.com/docs/connections/spec/identify/) will be sent into Sprig:
```kotlin theme={null}
Analytics.with(context).identify("userId123", Traits().putName("James Gibbson"), null);
```
You can view these users in Segment in the **Debugger**, or in Sprig on the Users page.
### Logout
When a user logs out of your app, make sure to log out of Sprig. This will prevent new activity from being associated with an incorrect user. Note that if you call `analytics.track("SOME_EVENT")` on an unauthenticated user, Sprig will assign them a new profile and count this new user separately toward your MTU limit.
```kotlin theme={null}
Analytics.with(context).track("Signed Out");
```
**Warning:** Logging out your users correctly
You must make the above call to log out your users and accurately track users in Sprig. Existing calls to Segment's `analytics.reset()` in your codebase will log the user out of Segment but **not** out of Sprig, creating discrepancies in your data if an accompanying `"Signed Out"` event is not tracked.
## Track Events
If you are already leveraging Segment's [Track method](https://segment.com/docs/connections/spec/track/), your events in Segment will automatically be passed to Sprig, and you do not need to do additional work.
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
To track an event, use:
```kotlin theme={null}
Analytics.with(context).track("Clicked Button", new Properties().putValue("plan", "Pro Annual");
```
Now, go to your source site or app's Debugger page on Segment, and check to see if it has registered the `Clicked Button` event. If it appears here, in Sprig's [Events page](https://app.sprig.com/events), you will also see a banner showing that you have an event request to review. Click **Manage Requests** to see the event.
## Track Attributes
If you are already leveraging [traits](https://segment.com/docs/connections/spec/identify/#traits) in Segment, your traits in Segment will automatically be passed to Sprig (as Attributes), and you do not need to do additional work.
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#survey-filter) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the Users page, and are recorded and attached to any surveys response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
In Segment, the equivalent of attributes are [traits](https://segment.com/docs/connections/spec/identify/#traits), and these are treated as a subset of the Identify spec.
## Test & Deploy
To verify your SDK is configured properly, we recommend testing with your development `ENVIRONMENT_ID`.
1. Create a survey in your Sprig Development Environment
2. Choose an approved event as a trigger for your study
3. \[For testing purposes only] Allow users to retake the survey and set the recontact waiting period to 0 days
4. Track the approved event from your app
Congratulations! Your installation is complete and you can begin deploying.
# Segment iOS
Source: https://docs.sprig.com/docs/installation/introduction-mobile/segment-ios
Easily install Sprig into your iOS app via Segment to track your users' behavior and send targeted In-Product Surveys based on your users' characteristics and actions they take in your product.
## Getting Started
### Overview
Segment is a Customer Data Platform (CDP) that collects and processes data from the users of your digital platforms and products. You can also use Segment to direct that data to other tools, making it a powerful tool for driving product experience insights with Sprig.
If your team is already leveraging Segment in your digital properties, you can use Segment to install the Sprig SDK as well as send the data Sprig needs to trigger and filter studies (like events and attributes).
This is an effective low-to-no-code option because it requires minimal code changes to deploy in-product Sprig studies. Even many of Sprig’s advanced features also require no changes to your codebase as long as you know what Segment functions your organization is already deploying.
**Warning:** Segment Actions vs Segment Classic
This install method leverages [Segment Actions](https://segment.com/docs/connections/destinations/actions/) both to install the Sprig SDK and to send events and attributes to Sprig from Segment. In most cases, we recommend integrating Sprig with Segment Actions over Segment Classic, although certain use cases may require Segment Classic, such as passing data to Sprig from your product's backend. For more information, consult with your Segment administrator or our [Segment Classic](/docs/Integrations/data-sources-introduction/segment-classic) documentation.
### Requirements
1. Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/segment-ios).
2. You will either need to access your team’s Segment account, or work with your team’s Segment administrator.
3. If you are planning to use Segment as a source for certain events and attributes, you may wish to consult with a developer on your team who has knowledge of how these events and attributes are expressed in the codebase.
4. You have Segment's [Swift](https://github.com/segmentio/analytics-swift) library installed
## Install SDK
If you are running Segment and wish to integrate your Segment instance with Sprig, you will first need to follow these steps to install the Sprig SDK.
### Obtain a Sprig Environment ID
Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [Integrations > Segment iOS](https://app.sprig.com/integrations/installation/segment-ios)).
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Set up Sprig as a Segment Destination
In Segment, you will be connecting your app as a Source to Sprig as a Destination. This will enable the Segment SDK to pass data to the Sprig SDK.
To do this, follow these steps (or follow [this video](https://www.loom.com/share/f6858cc78d2f4132965e853ec4d0b80d)):
1. In Segment, click **Connections**, then click **Destinations**.
2. Search for “Sprig” and select the **Sprig** destination.
3. Click **Configure Sprig**.
4. Select your data source (e.g. your app).
5. Enter an identifiable destination name and ensure **Actions** is selected.
6. Copy your **Environment ID** from your [Sprig Dashboard](https://app.sprig.com/integrations) and paste it into the **Environment ID** field.
7. Turn on **Enable Destination** and save your changes.
Next, you will need to install the Sprig plugin via SPM or via Package.swift.
**Warning:** Installing via SPM or via Package.swift
These are equivalent options — simply choose the installation method that you are more comfortable or familiar with.
### Install the Sprig Plugin via SPM
1. In Xcode > File > Add Packages, search for `https://github.com/UserLeap/analytics-swift-sprig` (you can view or star the [plugin repository on Github](https://github.com/UserLeap/analytics-swift-sprig))
2. Click **Add Package**
### Install the Sprig Plugin via Package.swift
Open your Package.swift file and add the following to the dependencies section:
```swift theme={null}
dependencies: [
// ... other dependencies
.package(
url: "https://github.com/UserLeap/analytics-swift-sprig.git",
from: "1.2.1"
),
]
```
If you have not migrated to Xcode 14 and need an Xcode 13 compatible version, you will need to use our legacy build:
```swift theme={null}
dependencies: [
// ... other dependencies
.package(
url: "https://github.com/UserLeap/analytics-swift-sprig.git",
exact: Version(1, 2, 1, prereleaseIdentifiers: ["legacy"]) // the version number are in sequence: major, minor, patch, prereleaseIdentifier without '-'.
),
]
```
Then specify the name of the package:
```swift theme={null}
targets: [
.target(
name: "YourPackageName",
dependencies: [
.product(name: "SegmentSprig", package: "analytics-swift-sprig"),
]
)
]
```
Note the Sprig iOS SDK will also be installed as an additional dependency.
### Initialize the Sprig Plugin
Go to your file that sets up your Segment Installation and add the following import:
```swift theme={null}
import Segment
import SegmentSprig // <-- Add this line
```
Add the following after you have initialized your `Analytics` object:
```swift theme={null}
Analytics.add(plugin: SprigDestination())
```
And that's it! All Users, Events, and Attributes that you send to the Segment SDK will automatically be forwarded to the Sprig SDK. Surveys will be presented on the top ViewController.
## Identify Users
Each time a user is tracked by Sprig on an app with the SDK installed, they are assigned a unique visitor ID in Sprig that allows users to be targeted with studies when they perform specified behaviors.
While this is a requirement for targeting users with Sprig studies, these are still considered unauthenticated users until their Sprig visitor IDs are coupled with the unique USER\_IDs assigned to users within your platform’s internal authentication framework.
We recommend that you follow this best practice when installing Sprig:
* This ensures consistency between the visitor IDs generated by Sprig and the ones in your internal database, product analytics/CDP, or data warehouse, allowing more effective targeting of studies.
* Your users have a consistent experience across platforms, and do not see the same study multiple times.
* **It also optimizes the number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index) sent to Sprig, which impacts your billing**.
If necessary, you can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is:
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
Once you've configured Sprig as a Segment destination above, users tracked from Segment's [Identify method](https://segment.com/docs/connections/spec/identify/) will be sent into Sprig:
```swift theme={null}
Analytics.shared().identify("userId123", traits: ["firstName": "James", "lastName": "Gibbson"])
```
You can view these users in Segment in the **Debugger**, or in Sprig on the Users page.
### Logout
When a user logs out of your app, make sure to log out of Sprig. This will prevent new activity from being associated with an incorrect user. Note that if you call `analytics.track("SOME_EVENT")` on an unauthenticated user, Sprig will assign them a new profile and count this new user separately toward your MTU limit.
```swift theme={null}
Analytics.shared().track("Signed Out")
```
**Warning:** Logging out your users correctly
You must make the above call to log out your users and accurately track users in Sprig. Existing calls to Segment's `analytics.reset()` in your codebase will log the user out of Segment but **not** out of Sprig, creating discrepancies in your data if an accompanying `"Signed Out"` event is not tracked.
## Track Events
If you are already leveraging Segment's [Track method](https://segment.com/docs/connections/spec/track/), your events in Segment will automatically be passed to Sprig, and you do not need to do additional work.
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
To track an event, use:
```swift theme={null}
Analytics.shared().track("Clicked Button", properties: ["plan": "Pro Annual", "accountType": "Wick"])
```
Now, go to your source site or app's Debugger page on Segment, and check to see if it has registered the `Clicked Button` event. If it appears here, in Sprig's [Events page](https://app.sprig.com/events), you will also see a banner showing that you have an event request to review. Click **Manage Requests** to see the event.
## Track Attributes
If you are already leveraging [traits](https://segment.com/docs/connections/spec/identify/#traits) in Segment, your traits in Segment will automatically be passed to Sprig (as Attributes), and you do not need to do additional work.
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#survey-filter) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the Users page, and are recorded and attached to any surveys response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
In Segment, the equivalent of attributes are [traits](https://segment.com/docs/connections/spec/identify/#traits), and these are treated as a subset of the Identify spec.
## Test & Deploy
To verify your SDK is configured properly, we recommend testing with your development `ENVIRONMENT_ID`.
1. Create a survey in your Sprig Development Environment
2. Choose an approved event as a trigger for your study
3. \[For testing purposes only] Allow users to retake the survey and set the recontact waiting period to 0 days
4. Track the approved event from your app
Congratulations! Your installation is complete and you can begin deploying.
# Segment React Native
Source: https://docs.sprig.com/docs/installation/introduction-mobile/segment-react-native
Leverage the Segment React Native CDP to easily install Sprig into your React Native mobile app. This integration makes it easy to send targeted In-Product Surveys based on your users' characteristics and actions they take in your product.
## Getting Started
### Overview
Segment is a Customer Data Platform (CDP) that collects and processes data from the users of your digital platforms and products. You can also use Segment to direct that data to other tools, making it a powerful tool for driving product experience insights with Sprig.
If your team is already leveraging Segment in your digital properties, you can use Segment to install the Sprig SDK as well as send the data Sprig needs to trigger and filter studies (like events and attributes).
This is an effective low-to-no-code option because it requires minimal code changes to deploy in-product Sprig studies. Even many of Sprig’s advanced features also require no changes to your codebase as long as you know what Segment functions your organization is already deploying.
**Warning:** Segment Actions vs Segment Classic
This install method leverages [Segment Actions](https://segment.com/docs/connections/destinations/actions/) both to install the Sprig SDK and to send events and attributes to Sprig from Segment. In most cases, we recommend integrating Sprig with Segment Actions over Segment Classic, although certain use cases may require Segment Classic, such as passing data to Sprig from your product's backend. For more information, consult with your Segment administrator or our [Segment Classic](/docs/Integrations/data-sources-introduction/segment-classic) documentation.
### Requirements
1. Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/segment-react-native).
2. You will either need to access your team’s Segment account, or work with your team’s Segment administrator.
3. If you are planning to use Segment as a source for certain events and attributes, you may wish to consult with a developer on your team who has knowledge of how these events and attributes are expressed in the codebase.
## Install SDK
If you are running Segment and wish to integrate your Segment instance with Sprig, you will first need to follow these steps to install the Sprig SDK.
### Obtain a Sprig Environment ID
Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [Integrations > Segment React Native](https://app.sprig.com/integrations/installation/segment-react-native)),
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Set up Sprig as a Segment Destination
In Segment, you will be connecting your app as a Source to Sprig as a Destination. This will enable the Segment SDK to pass data to the Sprig SDK.
To do this, follow these steps (or follow [this video](https://www.loom.com/share/f6858cc78d2f4132965e853ec4d0b80d)):
1. In Segment, click **Connections**, then click **Destinations**.
2. Search for “Sprig” and select the **Sprig** destination.
3. Click **Configure Sprig**.
4. Select your data source (e.g. your app).
5. Enter an identifiable destination name and ensure **Actions** is selected.
6. Copy your **Environment ID** from your [Sprig Dashboard](https://app.sprig.com/integrations) and paste it into the **Environment ID** field.
7. Turn on **Enable Destination** and save your changes.
### Install the Sprig Plugin with npm/Yarn
Next, use the following shell command to install the Sprig SDK through [npm](https://en.wikipedia.org/wiki/Npm_\(software\)) or [YARN](https://en.wikipedia.org/wiki/Yarn_\(package_manager\)).
Note that you will have to update the SDK manually to receive the latest functionality. We recommend you update the package monthly for improved functionality and bug fixes.
```shell npm theme={null}
npm install --save @sprig-technologies/analytics-react-native-plugin-sprig react-native-userleap
```
```shell Yarn theme={null}
yarn add @sprig-technologies/analytics-react-native-plugin-sprig react-native-userleap
```
When installing for iOS, you need to do `pod install`. And if you are updating, it's best to remove the `Podfile.lock` and run `pod repo update` first. So from your app top-level directory, run the following commands:
```bash theme={null}
cd ios
rm Podfile.lock
pod repo update
pod install
```
### Initialize the Sprig Plugin
In your code where you initialize the analytics client call the `.add({ plugin })` method with a SprigPlugin instance.
```javascript theme={null}
// App.js
import { createClient } from '@segment/analytics-react-native';
import { SprigPlugin } from '@sprig-technologies/analytics-react-native-plugin-sprig';
const segmentClient = createClient({
writeKey: 'SEGMENT_WRITE_KEY'
});
const plugin = new SprigPlugin();
segmentClient.add({ plugin });
```
And that's it! All Users, Events, and Attributes that you send to the Segment SDK will automatically be forwarded to the Sprig SDK. Surveys will be presented on the top activity.
## Identify Users
Each time a user is tracked by Sprig on an app with the SDK installed, they are assigned a unique visitor ID in Sprig that allows users to be targeted with studies when they perform specified behaviors.
While this is a requirement for targeting users with Sprig studies, these are still considered unauthenticated users until their Sprig visitor IDs are coupled with the unique USER\_IDs assigned to users within your platform’s internal authentication framework.
We recommend that you follow this best practice when installing Sprig:
* This ensures consistency between the visitor IDs generated by Sprig and the ones in your internal database, product analytics/CDP, or data warehouse, allowing more effective targeting of studies.
* Your users have a consistent experience across platforms, and do not see the same study multiple times.
* **It also optimizes the number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index) sent to Sprig, which impacts your billing**.
If necessary, you can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is:
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
Once you've configured Sprig as a Segment destination above, users tracked from Segment's [Identify method](https://segment.com/docs/connections/spec/identify/) will be sent into Sprig:
```javascript theme={null}
const { identify } = useAnalytics();
identify('userId123', {
firstName: 'James',
lastName: 'Gibbson',
});
```
You can view these users in Segment in the **Debugger**, or in Sprig on the Users page.
### Logout
When a user logs out of your app, make sure to log out of Sprig. This will prevent new activity from being associated with an incorrect user. Note that if you call `analytics.track("SOME_EVENT")` on an unauthenticated user, Sprig will assign them a new profile and count this new user separately toward your MTU limit.
```javascript theme={null}
const { track } = useAnalytics();
track('Signed Out');
```
**Warning:** Logging out your users correctly
You must make the above call to log out your users and accurately track users in Sprig. Existing calls to Segment's `analytics.reset()` in your codebase will log the user out of Segment but **not** out of Sprig, creating discrepancies in your data if an accompanying `"Signed Out"` event is not tracked.
## Track Events
If you are already leveraging Segment's [Track method](https://segment.com/docs/connections/spec/track/), your events in Segment will automatically be passed to Sprig, and you do not need to do additional work.
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
To track an event, use:
```javascript theme={null}
const { track } = useAnalytics();
track('Clicked Button', {
plan: "Pro Annual",
accountType: "Wick"
});
```
Now, go to your source site or app's Debugger page on Segment, and check to see if it has registered the `Clicked Button` event. If it appears here, in Sprig's [Events page](https://app.sprig.com/events), you will also see a banner showing that you have an event request to review. Click **Manage Requests** to see the event.
## Track Attributes
If you are already leveraging [traits](https://segment.com/docs/connections/spec/identify/#traits) in Segment, your traits in Segment will automatically be passed to Sprig (as Attributes), and you do not need to do additional work.
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#survey-filter) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the Users page, and are recorded and attached to any surveys response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
In Segment, the equivalent of attributes are [traits](https://segment.com/docs/connections/spec/identify/#traits), and these are treated as a subset of the Identify spec.
## Test & Deploy
To verify your SDK is configured properly, we recommend testing with your development `ENVIRONMENT_ID`.
1. Create a survey in your Sprig Development Environment
2. Choose an approved event as a trigger for your study
3. \[For testing purposes only] Allow users to retake the survey and set the recontact waiting period to 0 days
4. Track the approved event from your app
Congratulations! Your installation is complete and you can begin deploying.
# Web
Source: https://docs.sprig.com/docs/installation/introduction-web/index
## Overview
Installing Sprig allows you to monitor your customer's interactions and generate triggers to launch a Sprig Survey or Replay, so you can ask just the right question and capture just the right moments--all at just the right time.
Installing Sprig in your website or web app allows you to send [Events](/docs/shared-study-foundations/events/index) and [Attributes](/docs/shared-study-foundations/attributes) associated with users as they use your Website or Web App.
## Installation Options
To launch a Sprig study on your Website or Web App, you'll need to install one of the following:
* [JavaScript SDK](/docs/installation/introduction-web/web-javascript)
* [Google Tag Manager](/docs/Installation/introduction-web/web-google-tag-manager) (if Google Tag Manager is installed on your site)
* [Segment Web](/docs/Installation/introduction-web/segment-web) (if Segment is installed on your site)
* npm/yarn
## More Information
### Performance
Performance is a critical part of any successful website, and Sprig ensures you can get deep insights about your users without sacrificing your site’s performance.
#### Files
The script is loaded asynchronously, so it does not impact website load times or scroll performance.
The Sprig JS SDK is broken up into 2 JS files: a controller and a view.
controller.js: 89kB (28kb gzipped)
The controller is responsible for keeping track of your users and your interface to track events and set attributes and identities. A vast majority of sessions are not shown studies, so we separated the view into a separate file, reducing data usage for your users.
view\.js: 171kB (users only download this when a study is presented to them)
The view contains the code to show the study and send the responses to Sprig.
You may notice that our [npm package](https://www.npmjs.com/package/@sprig-technologies/sprig-browser) shows a size of \~800kb. This is double of what is mentioned above because it includes both `.js` and `.cjs` exports. Sprig JS is intended only for web browser use so the `.cjs` files won't be included in your bundle and thus will be half of what is mentioned on the npm webpage
#### Availability and load time
The Sprig client-side script is hosted on a leading global CDN powered by AWS CloudFront. This allows for the fastest load times by hosting the script as close to the users as possible.
#### Supporter browser versions
The Sprig client-side script is tested against all modern browsers. These are our minimum supported versions:
* Chrome 87
* Firefox 78
* Safari 14
* Edge 88
As Chrome and Firefox are on 6-week release cycles, best-effort support is given to older releases.
#### Impact on Page Load
##### Methodology
We performed an A/B test of the Sprig marketing page ([https://sprig.com](https://sprig.com)) with the Sprig SDK Snippet installed and not-installed. We used Lighthouse and configured it to throttle the network to "Slow 4G" and CPU to "4x slowdown". We measured 3 metrics:
* FCP (First Contentful Paint)
* LCP (Last Contentful Paint)
* DCL (DOM Content Loaded)
We ran each variant 20 times and both the average and median values showed no difference
# Segment Web
Source: https://docs.sprig.com/docs/installation/introduction-web/segment-web
Leverage the Segment Web CDP to easily install Sprig into your web product. This integration makes it easy to send targeted In-Product Surveys based on your users' characteristics and actions they take in your product.
## Getting Started
### Overview
Segment is a Customer Data Platform (CDP) that collects and processes data from the users of your digital platforms and products. You can also use Segment to direct that data to other tools, making it a powerful tool for driving product experience insights with Sprig.
If your team is already leveraging Segment in your digital properties, you can use Segment to install the Sprig SDK as well as send the data Sprig needs to trigger and filter studies (like events and attributes).
This is an effective low-to-no-code option because it requires no changes to your codebase to deploy in-product Sprig studies. Even many of Sprig’s advanced features also require no changes to your codebase as long as you know what Segment functions your organization is already deploying.
**Warning:** Segment Actions vs Segment Classic
This install method leverages [Segment Actions](https://segment.com/docs/connections/destinations/actions/) both to install the Sprig SDK and to send events and attributes to Sprig from Segment. In most cases, we recommend integrating Sprig with Segment Actions over Segment Classic, although certain use cases may require Segment Classic, such as passing data to Sprig from your product's backend. For more information, consult with your Segment administrator or our [Segment Classic](/docs/Integrations/data-sources-introduction/segment-classic) documentation.
### Requirements
* You must be on Segment [Analytics.js 2.0](https://segment.com/docs/connections/sources/catalog/libraries/website/javascript/)
* Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/segment-web).
* You will either need to access your team’s Segment account, or work with your team’s Segment administrator.
* If you are planning to use Segment as a source for certain events and attributes, you may wish to consult with a developer on your team who has knowledge of how these events and attributes are expressed in JavaScript.
## Install SDK
If you are running Segment and wish to integrate your Segment instance with Sprig, you will first need to follow these steps to install the Sprig SDK.
### Obtain a Sprig Environment ID
Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [Integrations > Segment Web](https://app.sprig.com/integrations/installation/segment-web)).
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Set up Sprig as a Segment Destination
In Segment, you will be connecting your digital platform or product as a Source to Sprig as a Destination. This will both install the Sprig SDK in your digital platform and allow events and attributes to be passed back to Sprig for the purpose of triggering and filtering studies.
To do this, follow these steps (or follow [this video](https://www.loom.com/share/f6858cc78d2f4132965e853ec4d0b80d)):
1. In Segment, click **Connections**, then click **Destinations**.
2. Search for “Sprig” and select the **Sprig** destination.
3. Click **Configure Sprig**.
4. Select your data source (e.g. your website or app).
5. Enter an identifiable destination name and ensure **Actions** is selected.
6. Copy your **Environment ID** from your [Sprig Dashboard](https://app.sprig.com/connect) and paste it into the **Environment ID** field.
7. Turn on **Enable Destination** and save your changes.
That’s it! As well as the Sprig SDK, your events, attributes and other user data (e.g. userIDs) are automatically configured to be forwarded to Sprig. (See the **Mappings** tab for more details)
### Verify Installation
To verify your Sprig installation, go to your Segment-enabled product and “hard refresh” the page to ensure the Segment destinations are updated. Next, open the console by holding `Control+Shift+I` on Chrome for Windows or `Option+Command+I` on Chrome and Safari for Mac, clicking on the Console tab. Once there, execute either or both of the following commands:
* Type `Sprig._segment`. If the value 1 is returned, Sprig has been successfully installed via Segment.
* Retrieve your Sprig visitor ID with `Sprig.visitorId`. This is the unique ID assigned by Sprig to visitors loading the SDK, so the value that is returned indicates Sprig is installed. You can then add this value to the following URL to view your activity in the Sprig Users page: `https://app.sprig.com/users/`
For the following sections on identifying users and tracking events, you will need to ensure your Sprig Mappings are enabled in Segment. These are enabled by default, but if you want to review these settings in Segment, go to Destinations > Sprig > Mappings > Edit Mapping.
## Identify Users
Each time a user is tracked by Sprig on a webpage with the SDK installed, they are assigned a unique visitor ID in Sprig that allows users to be targeted with studies when they perform specified behaviors.
While this is a requirement for targeting users with Sprig studies, these are still considered unauthenticated users until their Sprig visitor IDs are coupled with the unique USER\_IDs assigned to users within your platform’s internal authentication framework.
We recommend that you follow this best practice when installing Sprig:
* This ensures consistency between the visitor IDs generated by Sprig and the ones in your internal database, product analytics/CDP, or data warehouse, allowing more effective targeting of studies.
* Your users have a consistent experience across platforms, and do not see the same study multiple times.
* **It also optimizes the number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index#monthly-unique-users-muu-usage) sent to Sprig, which impacts your billing**.
If necessary, you can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is:
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
Once you've configured Sprig as a Segment destination above, users tracked from Segment's [Identify method](https://segment.com/docs/connections/spec/identify/) will be sent into Sprig. If you want to test user identification, open the web page or app in your browser and run this command in your web console:
```javascript theme={null}
analytics.identify('userId123', {
firstName: 'James',
lastName: 'Gibbon'
});
```
In Segment, go to the corresponding source and click **Debugger**. You should see something similar to the following:
Once Identify events are being triggered in your users' browsers and successfully forwarded to Sprig, you can view visitors being created on your Sprig Users dashboard. You'll be able to see visitor emails if being set, and when clicking on a specific visitor, you'll be able to see their User ID and any attributes set for them.
### Logout
When a user logs out of your webpage, make sure to log out of Sprig. This will prevent new activity from being associated with an incorrect user. Note that if you call `analytics.track("SOME_EVENT")` on an unauthenticated user, Sprig will assign them a new profile and count this new user separately toward your MTU limit.
```javascript theme={null}
analytics.track("Signed Out")
```
> **Warning:** Logging out your users correctly
>
> You must make the above call to log out your users and accurately track users in Sprig. Existing calls to Segment's `analytics.reset()` in your codebase will log the user out of Segment but **not** out of Sprig, creating discrepancies in your data if an accompanying `"Signed Out"` event is not tracked.
## Track Events
If you are already leveraging Segment's [Track method](https://segment.com/docs/connections/spec/track/), your events in Segment will automatically be passed to Sprig, and you do not need to do additional work.
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
If you want to test that events are passing from your source to Sprig through Segment, you can follow a similar process as testing that you are [identifying users](#identify-users). In the console, copy and paste the following script to stage a mock event:
```javascript theme={null}
analytics.track('Clicked Button', {
plan: "Pro Annual",
accountType: "Wick"
})
```
Now, go to your source site or app's Debugger page on Segment, and check to see if it has registered the `Clicked Button` event. If it appears here, in Sprig's [Events page](https://app.sprig.com/events), you will also see a banner showing that you have an event request to review. Click **Manage Requests** to see the event.
### No-Code Events
No-Code events let teammates without access to the codebase or to Segment create events in Sprig based on the page’s URL, HTML elements, or CSS, which can then be used to trigger or filter Web studies. No-Code events tend to be used to define more straightforward user actions, like viewing a page or clicking a button. For more information, see [No-Code events](/docs/shared-study-foundations/events/no-code-events).
## Track Attributes
If you are already leveraging [traits](https://segment.com/docs/connections/spec/identify/#traits) in Segment, your traits in Segment will automatically be passed to Sprig (as Attributes), and you do not need to do additional work.
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#survey-filter) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the Users page, and are recorded and attached to any surveys response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
In Segment, the equivalent of attributes are [traits](https://segment.com/docs/connections/spec/identify/#traits), and these are treated as a subset of the Identify spec.
## Filter Attributes through Segment
Segment offers the ability to define rules, so that only a subset of your data can be automatically sent to Sprig, through [Destination Filters](https://segment.com/docs/connections/destinations/destination-filters/). This is often used for limiting which PII is sent to Sprig, and does not require any additional engineering work to implement.
The ability to use Destination filters within Segment, for reducing the scope of which data is sent to Sprig, is currently limited to Segment Business Tier customers.
### Enable Destination Filters for your Segment Source
As part of the Segment Data Source you are using, you will need to ensure that the ability to use `Destination Filters` is enabled, under `Settings > Analytics.js` and toggling the `Destination Filters` setting on:
### Create the Destination Filter on your Segment Destination
As part of your Sprig destination within Segment, you'll now need to create the filter. In the example below, we can define certain traits that should not be sent to Sprig, such as the `!email` associated with this visitor:
Once your conditions have been set, you will then need to name your filter and save it.
## Screen Calls (Mobile)
Segment allows clients to take advantage of Screen calls, which allow you to record whenever a user sees a Screen, which is the mobile app equivalent of a Page in Segment. Screen calls tracked via[ Segment’s Screen method](https://segment.com/docs/connections/spec/screen/) can be used in Sprig to trigger a Code Event when building out a Study’s targeted audience. For example, if there are specific user interactions in your mobile app that you would like to tie to a Study in Sprig, you can use an attribute in your Segment Screen call to trigger your Sprig Study.
## Test & Deploy
To confirm everything is working as expected with survey delivery, you can create a survey and manually trigger delivery from the Developer Console.
1. You'll first need to create a Study and set the delivery method to Web. If you're testing in the Development environment, you'll need to create the Study in Development.
2. In the Sprig app, go to [Settings > Configure](https://app.sprig.com/settings/configure) and select **Allow Manual Study Display** (on by default for the Development environment)
3. Open the developer console and run `Sprig('displaySurvey', SURVEY_ID);`. The SURVEY\_ID of a study can be found at the end of its URL (`https://app.sprig.com/surveys/SURVEY_ID`).
4. If the Sprig snippet is already installed on that page, your browser will display the study.
1. If the questions are not rendering correctly or responses aren’t uploaded, check your browser console for any errors. You may have to work with your engineering and security teams to update your installation or CSP settings to resolve the errors.
After you have finished your testing, consider returning to [Settings > Configure](https://app.sprig.com/settings/configure) and select Disable Manual Study Display. This will prevent any other visitor from using displaySurvey in your environment.
Congratulations! Your installation is complete and you can begin deploying.
# Google tag Manager
Source: https://docs.sprig.com/docs/installation/introduction-web/web-google-tag-manager
## Getting Started
### Overview
[Google Tag Manager](https://tagmanager.google.com/) (GTM) is a free tool that allows you to manage and deploy tags (snippets of code or tracking pixels) on your website, browser-based app, or mobile app without having to modify the code. It requires little to no coding and is deployed in minutes.
If your organization is already running Google Tag Manager, or if you wish to install Google Tag Manager, you can use it to install Sprig on your website or browser-based app, as well as send events and attributes to Sprig.
This is an effective low-to-no-code option because it requires no changes to your codebase to deploy in-product Sprig studies. Even many of Sprig’s advanced features also require no changes to your codebase as long as you know what Google Tag Manager functions your organization is already deploying.
> **Are you already running Google Tag Manager?**
>
> If you don't have the Chrome [Tag Assistant](https://chrome.google.com/webstore/detail/tag-assistant-legacy-by-g/kejbdjndbnbjgmefkgdddjlbokphdefk) extension installed, you can check if GTM is installed by invoking the `inspect` option in your web browser while viewing your team's website or application.
>
> 1. To open the **Inspect** window in Chrome, Firefox and Edge, press `Control+Shift+I` (or `Option+Command+I` on Chrome and Safari for Mac).
> 2. Make sure you are on the **Elements** tab (or **Inspector** tab in Firefox), then press `Control+F` (or `Command+F` for Mac) to open the search field. Firefox displays the search field by default.
> 3. Search for the string *GTM*. If GTM is already deployed, you should get results similar to the following:``. The container id XXXXXX-X is specific to your deployment.
### Requirements
* Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/google-tag-manager).
* If you have not already installed Google Tag Manager, and wish to do so, you will need access to your web codebase, and be able to deploy to a development and/or production environment. You will also need to [sign up for a Google Tag Manager account](https://support.google.com/tagmanager/answer/6103696?hl=en) and set up Google Tag Manager on all pages where you plan to trigger Sprig studies.
* If your organization is already running Google Tag Manager, you will need administrator access to the account. Google Tag Manager administrators can [follow these steps](https://support.google.com/tagmanager/answer/6107011?hl=en) to add new users.
* If you are planning to use Google Tag Manager as a source for certain events and attributes, you may wish to consult with a developer on your team who has knowledge of how these events and attributes are expressed in JavaScript.
## Install SDK
Assuming that you are already running Google Tag Manager, you will first need to install the Sprig SDK following these steps.
### Obtain an Environment ID
Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [Integrations > Google Tag Manager](https://app.sprig.com/integrations/installation/google-tag-manager)).
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Create a Variable with the Sprig Environment ID
Variables in Google Tag Manager are placeholders that populate the code on your website with specific values. To install Sprig with Google Tag Manager, you will first need to create a variable specifying your Sprig Environment ID. This will then be used to populate the Sprig Installation Tag (see below), and specify which Sprig Environment it should target.
Here are the steps for creating a variable with your Sprig Environment ID:
1. Open Google Tag Manager app and click **Variables**.
2. In **User-Defined Variables**, click **New**.
3. In the **Untitled Variable** field, give the variable an appropriate name, like SPRIG\_PROD\_ENV\_ID (if you are installing for your **Production** environment) or SPRIG\_DEV\_ENV\_ID (if you are installing for your **Development** environment).
4. Click anywhere on the **Variable Configuration** box, and scroll down the new sidebar to find **Constant** (under the **Utilities** subheading).
5. Paste your Sprig Environment ID into the **Value** field and click **Save**.
### Add the Sprig Installation Tag to your Google Tag Manager Account
A Tag in Google Tag Manager is a snippet of code that executes on web pages with Google Tag Manager installed. Sprig has created an installation tag, called **Sprig Tag**, which can be found in Google Tag Manager’s Community Template Gallery, and which you will now add to your Google Tag Manager account. This will execute the Sprig SDK on all pages on your website where you have Google Tag Manager installed.
Here are the steps for adding the Sprig Installation Tag to your account:
1. Open Google Tag Manager and click **Tags**.
2. Click **New** to create a new tag.
3. In the **Untitled Tag** field, give the tag an appropriate name, like Sprig Install Tag.
4. Click anywhere on the **Tag Configuration** box, and click on **Discover more tag types in the Community Template Gallery** in the new sidebar. Search for **Sprig**, click on **Sprig Tag**, and then click **Choose Template** to confirm your selection.
5. Click and select the Environment **Variable** you created earlier (for example, SPRIG\_PROD\_ENV\_ID or SPRIG\_DEV\_ENV\_ID).
6. Make sure the **Action Type** is set to **Install**.
7. Click anywhere on the **Triggering** box below and select **All Pages** in the new sidebar.
8. Click **Save**.
9. Click **Submit** and then **Publish** to push your changes out to your website.
> **Using the Sprig Tag in Google Tag Manager**
>
> Throughout this page, we will be leveraging the Sprig Tag to execute a number of Sprig functions, including configuring Events, Attributes, User IDs, and Data Layer variables. For each function, you will begin by creating a new Sprig Tag as outlined in Steps 1-5 above, and then changing the action type.
### Verify Installation
1. As you did before to check for the installation of GTM, open the **Inspect** window in your browser.
2. Make sure you are on the **Elements** tab (or **Inspector** tab in Firefox), then open the search field.
3. Search for the string *sprig*. If Sprig is installed, you should get results similar to the following:``, where XXX-XXXXX is your Environment ID. Sprig has now been successfully installed using GTM.
## Identify Users
Each time a user is tracked by Sprig on a webpage with the SDK installed, they are assigned a unique visitor ID in Sprig that allows users to be targeted with studies when they perform specified behaviors.
While this is a requirement for targeting users with Sprig studies, these are still considered unauthenticated users until their Sprig visitor IDs are coupled with the unique USER\_IDs assigned to users within your platform’s internal authentication framework.
We recommend that you follow this best practice when installing Sprig:
* This ensures consistency between the visitor IDs generated by Sprig and the ones in your internal database, product analytics/CDP, or data warehouse, allowing more effective targeting of studies.
* Your users have a consistent experience across platforms, and do not see the same study multiple times.
* **It also optimizes the number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index#monthly-unique-users-muu-usage) sent to Sprig, which impacts your billing**.
If necessary, you can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is:
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
We can use the same Sprig Installation Tag described above to couple the Sprig visitor ID with your system’s internal USER\_ID or EMAIL\_ADDRESS in Google Tag Manager:
1. Follow [Steps 1-5 in the instructions for adding the Sprig Installation Tag](#add-the-sprig-installation-tag-to-your-google-tag-manager-account) to Google Tag Manager, though when naming the tag, choose a different name, like Sprig User ID Tag.
2. Under **Action Type**, use the dropdown menu to select “User ID” (or, if adding email address, “User Email”).
3. Enter your internal USER\_ID string to the **User ID** field.
4. Click anywhere on the **Triggering** box below and select **All Pages** in the new sidebar.
5. Click **Save**, then click **Submit** and then **Publish** to push your changes out to your website.
**Warning:** Identifying Users in the Data Layer
If your team is leveraging Google Tag Manager's Data Layer, user IDs may be information stored there. Sending information from the Data Layer to Sprig is treated below under [Track Attributes](#track-attributes).
## Track Events
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
Once you’ve installed the Sprig SDK via Google Tag Manager, the next step is to configure the tracking of events that you would like to use to trigger a study. You can configure events either through Google Tag Manager, or by configuring [No-Code](/docs/shared-study-foundations/events/no-code-events) events within Sprig.
### No-Code Events
No-Code events let teammates without access to the codebase create events in Sprig based on the page’s URL, HTML elements, or CSS, which can then be used to trigger or filter Web studies. No-code events tend to be used to define more straightforward user actions, like viewing a page or clicking a button. For more information, see [No-Code events](/docs/shared-study-foundations/events/no-code-events).
### Configuring Events as Google Tags
For more complex user actions, Google Tag Manager contains a library of common triggers that you can use to configure events in Sprig. Some common triggers in the Google Tag Manager trigger library include:
* scroll depth
* form submission
* element clicks
For more information on Google Tag Manager triggers, click [here](https://support.google.com/tagmanager/answer/7679316?hl=en).
There are four main steps in configuring Google Tag Manager to generate triggers that can be used by Sprig to display a study:
1. Create and configure the Trigger in Google Tag Manager
2. Create a new Sprig Tag associated with the Trigger
3. Publish your changes to the server
4. Approve the event when it appears in Sprig’s Events page
The next section describes this workflow in greater detail, using [Scroll Depth](https://support.google.com/tagmanager/answer/7679218?hl=en) as an example Trigger.
### Sending an example Event to Sprig
In this example, we want the user to scroll to certain depth on the webpage in order to trigger the study. This example will use the Google Tag Manager built-in trigger [Scroll Depth](https://support.google.com/tagmanager/answer/7679218?hl=en).
1. In the Google Tag Manager app, click **Triggers**
2. Click **New** on the Triggers dashboard.
3. Click **Untitled Tag** and give the trigger an appropriate name, for example Scroll Depth.
4. Click anywhere on the **Trigger Configuration** card and select **Scroll Depth** from the sidebar that appears.
5. Configure the trigger (for example, the direction & percentage of scroll depth you want for the trigger) and click **Save**.
6. Follow [Steps 1-5 in the instructions for adding the Sprig Installation Tag](#add-the-sprig-installation-tag-to-your-google-tag-manager-account) to Google Tag Manager, though when naming the tag, choose a different name, like Sprig Scroll Depth Tag.
7. Under **Action Type**, use the dropdown menu to select “Event”.
8. Under **Event Name**, enter the name of the event as you would like it to appear in Sprig (for example, Scroll Depth).
9. Click anywhere on the **Triggering** card to bring up the sidebar where you can select the **Scroll Depth** trigger you configured earlier.
10. Click **Save** then click **Submit** and **Publish** to push the changes to the server.
11. In the target site, go to a page with Google Tag Manager installed and scroll to trigger the event. Then, in Sprig, open the **Events**, where you will see a prompt to approve a new event under review. Click **Manage Requests** to add this event.
For more information, Google also provides [documentation](https://support.google.com/tagmanager/answer/6107056?hl=en) describing methods and tools to diagnose variables, tags, and triggers.
## Track Attributes
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#survey-filter) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the Users page, and are recorded and attached to any surveys response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
In Google Tag Manager, there are two methods by which you can pass attributes to Sprig:
1. Determine if your organization already leverages Google Tag Manager **Data Layers**, and identify variables stored in the Data Layer you wish to send to Sprig.
2. Configure a **discrete attribute** and use the Sprig Install Tag to pass the attribute
If you are setting attributes with Google Tag Manager, it is likely your team is leveraging the Data Layer. The following section describes how to send these attributes to Sprig, with some further information on individual attributes following.
**Configuring Attributes in Sprig**
If your team is not already tracking user attributes in Google Tag Manager, you will likely require some knowledge of JavaScript to configure these attributes and direct to Sprig. Note that in order for Sprig to receive attributes, your website or web app must also be able to parse that information to the JavaScript layer. You may have to engage your Web engineering team to find out which attributes are visible to JavaScript and ask them to enable visibility for those attributes that are not.
### Sending Data Layer Variables to Sprig
Google Tag Manager's [Data Layer](https://developers.google.com/tag-manager/devguide#datalayer) is a JavaScript array that stores data which you can process and pass from your website to other applications. If your team is leveraging the Data Layer to supply data to your analytics tool about the details of your website visitor (such as login status, user ID, and location), you can also use these details as attributes to filter your studies in Sprig.
The most likely use case for leveraging the Data Layer as a source for Sprig is therefore if your organization is already storing user data there that would be useful for targeting studies. To **check your current Data Layer**, follow these steps:
1. Make sure Google Tag Manager is installed.
2. Go to a page where you wish to check the Data Layer, and open up the browser JavaScript console with `Ctrl + Shift + J` (`command + option + J` on Mac).
3. Enter `window.dataLayer` in the console prompt. Note: The dataLayer name is case-sensitive, meaning that only dataLayer will work, not for example, datalayer.
If you are running a Data Layer on this page, you will see the data it is storing. If you are not, the console will return an 'undefined' response.
#### Example Data Layer Variable
Once you have determined that a Data Layer is present, the next step is to identify some information to send to Sprig. In this example, we are going to send information about which plan a user purchased when the checkout event occurred. This example will just treat this information as static data; in the real world a developer would generate this information dynamically for each checkout event.
Data is stored in the Data Layer in key-value pairs. The key is a variable name in string format, and values can be any allowed JavaScript type. At our example checkout event, we might store the following information in the Data Layer:
| Key | Value |
| :- | :- |
| event | checkout |
| planid | 99 |
| costPerMonth | 79 |
| planName | Enterprise |
| userid | 12345 |
In JavaScript, this would be described as follows:
```javascript theme={null}
'event': 'checkout',
'planid': 99,
'costPerMonth': 79,
'planName': 'Enterprise',
'userid': 12345
```
#### Instructions
In order to pass this information to Sprig, we first need to add the following code snippet to the `` of the webpage before the Google Tag Manager snippet as follows:
```html theme={null}
...
```
Next, we will need to go to Google Tag Manager to create a variable that points to the Data Layer and identifes `planid` as the key we wish to select to pass to Sprig.
1. In Google Tag Manager, click **Variables**.
2. In **User-Defined Variables**, click **New**.
3. Click **Untitled Variable** and give the variable an appropriate name, for example, DL-planid.
4. In **Variable Configuration**, click anywhere on the card to choose the variable type, and select **Data Layer Variable** as the variable type in the sidebar.
5. In the Data Layer Variable Name field type `planid`. The Data Layer Variable Name field is case-sensitive.\
Click **Save**.
Finally, you need to create a Sprig tag that fires at the appropriate time to send `planid` to Sprig:
1. Follow [Steps 1-5 in the instructions for adding the Sprig Installation Tag](#add-the-sprig-installation-tag-to-your-google-tag-manager-account) to Google Tag Manager, though when naming the tag, choose a different name, like Sprig DL.
2. Under **Action Type**, select **User Attribute**. This will allow you to define a custom attribute.
3. In **Attribute Key** type in the name your attribute as you wish it to appear in Sprig; in this case, 'PlanID'. Don't forget to put single quotes around the attribute key name.
4. Select the Custom JavaScript variable you created in the last step; in the previous example it was called, DL-planid.
5. Click anywhere on the **Triggering** box below and select **All Pages** in the new sidebar.
6. Click **Save**, then click **Submit** and then **Publish** to push your changes out to the server.
Whenever a user clicks **Finish** to return a Study to Sprig, the current value of `planid` will be associated with the Study response. In the Sprig app, click **Users**, then click on the last **User ID**. If you look under **Profile**, you will be able to see the custom attribute that you defined.
In addition, if you go to **Studies > YOUR\_STUDY\_NAME > Responses**, then click on **Download CSV**. In the CSV file that you download there will be one column containing all the custom attributes.
### Using GTM to Trigger Dismissal of an Active Survey
Using Sprig’s tag, you can configure the action of dismissing an Active Sprig Survey directly through GTM. Here are the steps for creating a trigger to dismiss an active Sprig Survey given a set of criteria.
1. Open Google Tag Manager and click Tags
2. Click New to create a new tag
3. Find the Sprig Tag and select the Action Type **Dismiss Active Survey**
4. Click and select the appropriate Environment Variable (for example, SPRIG\_PROD\_ENV\_ID or SPRIG\_DEV\_ENV\_ID)
5. In the Triggering section, select the set of criteria that will dictate when an Active Sprig Survey will be automatically dismissed.
### Triggering Logout User using GTM
While using Sprig to track user behaviors there may be a need to have Sprig reset a users status to track a different user’s behavior across your website or application. Some common reasons this may be necessary include:
1. A user is accessing your app or website on a shared device
2. A user has multiple accounts across your website or application
If it becomes necessary to reset a user via Sprig in either of those scenarios, configuring the Sprig tag to trigger a Logout User Action. You can set this up by following the typical tag and trigger configuration steps and selecting **Logout User** as the action type.
### Sending Discrete Attributes to Sprig
The simplest way to send attributes to Sprig individually is to create a custom variable containing the Javascript identifying the attribute, then configuring the Sprig Tag in a similar manner as above. Simply follow the steps, but when identifying the **Variable Configuration**, select **Custom Javascript** (instead of Data Layer Variable). Supply your attribute's Javascript call here, then follow the remaining steps to action the User Attribute in the Sprig Tag as with the Data Layer Variable.
## Test & Deploy
To confirm everything is working as expected with survey delivery, you can create a survey and manually trigger delivery from the Developer Console.
1. You'll first need to create a Study and set the delivery method to Web. If you're testing in the Development environment, you'll need to create the Study in Development.
2. In the Sprig app, go to [Settings > Configure](https://app.sprig.com/settings/configure) and select **Allow Manual Study Display** (on by default for the Development environment)
3. Open the developer console and run `Sprig('displaySurvey', SURVEY_ID);`. The SURVEY\_ID of a study can be found at the end of its URL (`https://app.sprig.com/surveys/SURVEY_ID`).
4. If the Sprig snippet is already installed on that page, your browser will display the study.\
4a. If the questions are not rendering correctly or responses aren’t uploaded, check your browser console for any errors. You may have to work with your engineering and security teams to update your installation or CSP settings to resolve the errors.
After you have finished your testing, consider returning to [Settings > Configure](https://app.sprig.com/settings/configure) and select Disable Manual Study Display. This will prevent any other visitor from using displaySurvey in your environment.
Congratulations! Your installation is complete and you can begin deploying.
# JavaScript SDK
Source: https://docs.sprig.com/docs/installation/introduction-web/web-javascript
## Getting Started
### Overview
The Sprig Javascript SDK, when installed in your website or web app, allows you to track your customer’s in-product behavior and display Sprig studies when they perform certain actions. To learn more about SDKs and web installation options provided by Sprig, click [here](/docs/Installation/introduction-web/index).
### Requirements
* Join your teammates on [Sprig](https://app.sprig.com) (check with your Sprig admin whether team discovery is on, or simply have a team member invite you via your email address). This will give you access to your team’s environment IDs, as well as the [interactive Installation Guide](https://app.sprig.com/integrations/installation/javascript-sdk).
* Ensure you have access to your web codebase, and can deploy to a development and/or production environment
## Install SDK
If you are installing the Sprig Javascript SDK, we recommend installing Sprig via the HTML code snippet. This installation method automatically ensures you have the latest version of our SDK, reducing the workload on your engineering team since they won’t have to fetch and deploy an update every time Sprig releases a new version of the SDK. You will automatically have access to the latest features on the latest SDKs.
For teams that prefer to use a package manager, Sprig can also be installed via npm or Yarn. Note that your engineering team will need to do some additional work to update in order to access the latest features and bug fixes.
### Obtain an Environment ID
Sprig provides two environments, Development and Production, each with its own corresponding ENVIRONMENT\_ID (which can be found in [Integrations > Javascript SDK](https://app.sprig.com/integrations/installation/javascript-sdk)).
The Development environment is recommended for initially setting up and verifying your installation. Then, you can use the Production environment to deploy studies to real users.
### Install with HTML (recommended)
Add the following JavaScript snippet to every page on your website where you want Sprig to track your users. You can paste the snippet anywhere on the page, but preferably at the [bottom](https://gtmetrix.com/put-javascript-at-bottom.html) of the document, before the `` tag. Be sure to swap in the correct ENVIRONMENT\_ID.
```html theme={null}
```
This snippet fetches the latest version of the SDK asynchronously when the page is loaded. Click [here](/docs/Installation/introduction-web/index#performance) for more information on performance.
### Install with npm/Yarn
Use the following shell command to install the Sprig SDK through [npm](https://en.wikipedia.org/wiki/Npm_\(software\)) or [YARN](https://en.wikipedia.org/wiki/Yarn_\(package_manager\)). With this installation method, Sprig will be bundled with the rest of your front-end application and be immediately accessible on page load.
Note that you will have to update the SDK manually to receive the latest functionality. We recommend you update the package monthly for improved functionality and bug fixes.
```shell npm theme={null}
npm install --save @sprig-technologies/sprig-browser
```
```shell Yarn theme={null}
yarn add @sprig-technologies/sprig-browser --latest
```
Then, in your application, initialize Sprig with your ENVIRONMENT\_ID:
```javascript theme={null}
import { sprig } from '@sprig-technologies/sprig-browser';
// Starting with version 2.42.0 released on 2026-03-16
sprig.configure({
environmentId: 'ENVIRONMENT_ID',
})
// For versions 2.41.3 and earlier
export const Sprig = sprig.configure({
environmentId: 'ENVIRONMENT_ID',
})
```
Other parameters for `configure` can be found below in the [Customize Appearance](/docs/Installation/introduction-web/web-javascript#customize-appearance) section.
#### Usage with Next.js (Sprig SDK v2.42.0 or higher)
The Sprig SDK is a client side SDK that should only be run in [client components in Next.js applications](https://nextjs.org/docs/app/getting-started/server-and-client-components). Former versions of the Sprig SDK relied on the browsers global `window`. Starting with v2.42.0 of the SDK, calls to `window` have been transitioned to `globalThis` with optional chaining so calls fail silently if Sprig does not exist. If you are still using a previous version of the SDK, please skip to [Usage with Next.js (Sprig SDK v.2.41.3 or lower)](/docs/Installation/introduction-web/web-javascript#usage-with-next-js-sprig-sdk-v2-41-3-or-lower) for the recommended implementation of Sprig with your Next.js application.
After installing the Sprig SDK through npm or YARN, initialize Sprig with your ENVIRONMENT\_ID:
```javascript theme={null}
import { sprig } from '@sprig-technologies/sprig-browser';
sprig.configure({
environmentId: 'ENVIRONMENT_ID',
})
```
Use Sprig across your application in client components:
```javascript theme={null}
'use client';
import { Sprig } from '@sprig-technologies/sprig-browser';
export const Button = ({ children, click }: { children: React.ReactNode, click?: () => unknown }) => {
const handleClick = () => {
Sprig.track('btn-clicked');
click?.();
}
return
}
```
#### Usage with Next.js (Sprig SDK v2.41.3 or lower)
The Sprig SDK is a client side SDK that relies on the browsers global `window` and other client side APIs, meaning that the Sprig SDK should only be run in [client components in Next.js applications](https://nextjs.org/docs/app/getting-started/server-and-client-components). We recommend creating a client side [context](https://react.dev/learn/passing-data-deeply-with-context) for the Sprig SDK to ensure that only one instance of the Sprig SDK is configured.
Create the Sprig Context and load the Sprig SDK dynamically in a `useEffect`:
```typescript theme={null}
'use client';
import { createContext, useContext, useEffect, useRef, useMemo, ReactNode } from 'react';
import { type WindowSprig } from '@sprig-technologies/sprig-browser';
const SprigNoop = (() => {}) as unknown as WindowSprig;
export const SprigContext = createContext({ Sprig: SprigNoop });
export const useSprigContext = () => useContext<{ Sprig: WindowSprig }>(SprigContext);
export const SprigContextProvider = ({ children }: { children: ReactNode }) => {
const SprigRef = useRef(SprigNoop);
useEffect(() => {
import('@sprig-technologies/sprig-browser').then(({ sprig }) => {
SprigRef.current = sprig.configure({ environmentId: 'ENVIRONMENT_ID' });
});
}, []);
const value = useMemo(() => ({
Sprig: SprigRef.current,
}) , [])
return {children}
}
```
Include the newly created `SprigContextProvider` within your application:
```typescript theme={null}
'use client';
import { SprigContextProvider } from './SprigContext';
export const Providers = ({ children }: { children: React.ReactNode }) => {
return {children}
}
```
Use the newly created context across your application in client components:
```typescript theme={null}
'use client';
import { useSprigContext } from './SprigContext';
export const Button = ({ children, click }: { children: React.ReactNode, click?: () => unknown }) => {
const { Sprig } = useSprigContext();
const handleClick = () => {
Sprig('track', 'btn-clicked');
click?.();
}
return
}
```
#### Updating the Sprig SDK with npm or Yarn
When using npm or Yarn, you should regularly update your Sprig installation with the latest features by running the following command:
```shell npm theme={null}
npm update @sprig-technologies/sprig-browser
```
```shell YARN theme={null}
yarn update @sprig-technologies/sprig-browser
```
### CSP Configuration
Using Sprig for Web studies may require you to update your web application's [Content Security Policy](https://en.wikipedia.org/wiki/Content_Security_Policy) (CSP). This may be required because Sprig uses third-party libraries to support JavaScript.
The following list of sources is required to use Video & Voice questions:
* Base64 SVGs and fonts.
* Connecting to Mux (for streaming and short video uploads).
* Connecting to Google APIs (for long video uploads).
Examples are shown in the following CSP source list:
```text Sprig CSP theme={null}
```
```text Sprig CSP for Voice/Video theme={null}
```
> **Info**
>
> As every company has different security policies, the example may not reflect the complete configuration. You may need to add additional keys and values in order to comply with your own organization’s policies.
### Verify Installation
1. Load a page from your website/web app that has the Sprig SDK installed
2. Open the developer console to the **Network** tab
3. Find a network request named `config` that hits `https://api.sprig.com/...`
4. Check the status code of the request. If it’s 200 or 304, your install is working correctly and you can move on.
## Identify Users
Each time a user is tracked by Sprig on a webpage with the SDK installed, they are assigned a unique visitor ID in Sprig that allows users to be targeted with studies when they perform specified behaviors.
While this is a requirement for targeting users with Sprig studies, these are still considered unauthenticated users until their Sprig visitor IDs are coupled with the unique USER\_IDs assigned to users within your platform’s internal authentication framework.
We recommend that you follow this best practice when installing Sprig:
* This ensures consistency between the visitor IDs generated by Sprig and the ones in your internal database, product analytics/CDP, or data warehouse, allowing more effective targeting of studies.
* Your users have a consistent experience across platforms, and do not see the same study multiple times.
* **It also optimizes the number of [Monthly Unique Users (MUUs)](/docs/account-and-settings/usage-muu/index#monthly-unique-users-muu-usage) sent to Sprig, which impacts your billing**.
If necessary, you can also use an [anonymizing function or hash](https://docs.google.com/document/d/1qMO3DaXklt9csAPfWNolBpPecAiQ55350ke2_nwFSAs/edit).
A good User ID is…
* Unique: Two users should not share the same User ID.
* Mappable: User IDs sent to Sprig should map back to your internal User IDs, either directly or anonymously.
* Static: Once assigned, a User ID should not change.
Users that do not have a User ID set are considered unauthenticated.
### Set User ID
You can use `setUserId` to identify a user with any string less than 256 characters. This function can be called multiple times safely, and stores the identifier via local storage. We recommend you set the User ID whenever the user logs in to your website, as well as after the installation snippet (if the user is already logged in).
```html HTML script tag theme={null}
```
```javascript npm theme={null}
// import the client returned from your Sprig.configure call
import { Sprig } from 'utils/sprig'
Sprig.setUserId('USER_ID');
```
### Logout
When a user logs out of your webpage, make sure to log out of Sprig. This will prevent new activity from being associated with an incorrect user. Note that if you call `logoutUser()` on an unauthenticated user, Sprig will assign them a new profile and count this new user separately toward your MTU limit.
```html HTML script tag theme={null}
```
```javascript npm theme={null}
// import the client returned from your Sprig.configure call
import { Sprig } from 'utils/sprig'
Sprig.logoutUser();
```
## Track Events
Sprig uses events to **trigger** (display) studies after the user performs a specific action. They can also be used as a **filter** to target users who have previously performed an action.
Once you’ve installed the Sprig SDK, the next step is to configure the tracking of events that you would like to use to trigger a study. Sprig provides two types of Events for triggering and filtering your studies, [Code](/docs/shared-study-foundations/events/code-events) and [No-Code](/docs/shared-study-foundations/events/no-code-events) events.
### No-Code Events
No-Code events let teammates without access to the codebase create events in Sprig based on the page’s URL, HTML elements, or CSS, which can then be used to trigger or filter Web studies. No-code events tend to be used to define more straightforward user actions, like viewing a page or clicking a button. For more information, see [No-Code events](/docs/shared-study-foundations/events/no-code-events).
### Code Events
Sometimes No-Code events may not provide visibility into a particular event that you would like to track. For example, you may want to study users who, in the previous month, have downgraded their account status from *premium* to *standard*. It may be preferable to generate the event directly from the webpage.
To track a Code event, you will need the following snippet. You can also optionally attach properties to your event.
```html HTML script tag theme={null}
```
```javascript npm theme={null}
// import the client returned from your Sprig.configure call
import { Sprig } from 'utils/sprig'
// Note: all of these functions make a network call, so be sure to give them enough time to complete
// RECOMMENDED: Track event with event payload. Only eventName is required.
Sprig.identifyAndTrack({
eventName: 'EVENT_NAME',
userId: 'some_user_id',
properties: { property1: 'value'}
});
// ALTERNATIVES
// Track event with string
Sprig.track('EVENT_NAME');
// Optionally include properties
Sprig.track('EVENT_NAME', { property1: 'value' };
```
After sending a new Code event to Sprig, you must [approve the new event request](/docs/shared-study-foundations/events/index#adding-events) on the [Events page](https://app.sprig.com/events) before it can be used as a trigger or filter.
These events will also be available as filters for your studies. For example, you may want to only display a study to users who have performed the "checkout" event at least 3 times.
Alternatively, after sending each tracking event, you can decide if a survey should be shown for the user if there is an eligible survey. The optional parameter accepts an async function that expects a boolean. We include the eligible survey ID as the parameter.
```javascript theme={null}
```
## Track Attributes
Sprig allows you to track **attributes**, which can provide more context about the user to help you better understand their feedback. You can also use these attributes to [filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#/user-filters---attributes-group-or-event-history-optional) your audience and target specific kinds of users. Some example attributes that can be tracked are:
* Plan type
* Super users / power users
* Company
A user’s attributes can be seen on their profile in the People page, and are recorded and attached to any response they submit. For more information, see [Attributes](/docs/shared-study-foundations/attributes).
To set a user’s attribute, provide the SDK with a key-value pair:
* `ATTRIBUTE_NAME` must be a string less than 256 characters, and cannot start with an `!` (these names are reserved for use by Sprig)
* `ATTRIBUTE_VALUE` must be a number, boolean, or string less than 256 characters
```html HTML script tag theme={null}
```
```javascript npm theme={null}
// import the client returned from your Sprig.configure call
import { Sprig } from 'utils/sprig'
Sprig.setAttribute('ATTRIBUTE', 'VALUE');
// for multiple attributes
// saves multiple round-trips and reduces data usage
Sprig.setAttributes({
ATTRIBUTE1: 'VALUE1',
ATTRIBUTE2: 'VALUE2'
});
// if attributes no longer apply to the user,
// you can delete multiple at a time
Sprig.removeAttributes(['ATTRIBUTE1', 'ATTRIBUTE2']);
```
### Set Email Address
Setting the user’s email address is **optional**. Setting emails is not required for web or mobile studies, but can be used to target users or create a Group of users based on their email. Check your organization's guidelines around personally-identifiable information before sending email addresses to Sprig.
```html HTML script tag theme={null}
```
```javascript npm theme={null}
import { Sprig } from 'utils/sprig'
Sprig.setEmail('EMAIL_ADDRESS');
```
## Test & Deploy
To confirm everything is working as expected with survey, you can create a survey and manually trigger delivery from the Developer Console.
1. You'll first need to create a Study and set the delivery method to Web. If you're testing in the Development environment, you'll need to create the Study in Development.
2. In the Sprig app, go to [Settings > Configure](https://app.sprig.com/settings/configure) and select **Allow Manual Study Display** (on by default for the Development environment)
3. Open the developer console and run `Sprig('displaySurvey', SURVEY_ID);`. The SURVEY\_ID of a study can be found at the end of its URL (`https://app.sprig.com/surveys/SURVEY_ID`).
4. If the Sprig snippet is already installed on that page, your browser will display the study.
1. If the questions are not rendering correctly or responses aren’t uploaded, check your browser console for any errors. You may have to work with your engineering and security teams to update your installation or CSP settings to resolve the errors.
After you have finished your testing, consider returning to [Settings > Configure](https://app.sprig.com/settings/configure) and select Disable Manual Study Display. This will prevent any other visitor from using displaySurvey in your environment.
Congratulations! Your installation is complete and you can begin deploying.
## Advanced Customization
### Customize Appearance
You can set a hard limit on the height of your study with the `maxHeight` parameter, which sets the `maxHeight` property of the iframe.
For custom installations, if Sprig is installed within an iframe that initially has 0 width, by default, studies will render with desktop styling and a width of 360px. In these cases, to make use of mobile styling and full-width studies on mobile web, you can provide your window dimensions when Sprig is initialized, and when the window is resized, with the `setWindowDimensions` function.
Example of configuring `maxHeight` and using `setWindowDimensions`:
```html HTML script tag theme={null}
```
```javascript npm theme={null}
import Sprig from '@sprig-technologies/sprig-browser';
// or with require() syntax:
// const sprig = require('@sprig-technologies/sprig-browser');
export const Sprig = sprig.configure({
environmentId: '[[ENVIRONMENT_ID]]',
maxHeight: '50%', // sets maxHeight property of the iframe to 50% of page height.
});
// during initialization, and when the window is resized
Sprig.setWindowDimensions([[WIDTH]], [[HEIGHT]]) // [[WIDTH]] and [[HEIGHT]] are pixel numbers
```
You can further customize study placement and appearance in our dashboard: [**Settings > Look and Feel**](https://app.sprig.com/settings/look-and-feel). See [Study look and feel documentation](/docs/sprig-studies/in-product-surveys/microsurvey-look-and-feel#microsurvey-appearance) for more details.
### Sandbox implementation
A common use case from our customers is to place the UserLeapKit in a sandbox iframe that's hosted by a hosting frame with an initial size of 0. The sandboxed frame will observe the `survey.height` events and the `survey.closed` events to manage the size and appearance of the hosting frame.
[See a gist of the implementation](https://gist.github.com/earlsprig/76e13e54b01f29af55d789219ca96f28)
### Inject CSS to your studies
For more fine-tuned control of how your study looks, Sprig supports injecting CSS into the survey. Sprig creates a `` tag in the `` of the iframe and sets the CSS string as the text content.
```html HTML script tag theme={null}
```
```javascript npm theme={null}
import Sprig from '@sprig-technologies/sprig-browser';
Sprig.styleNonce = 'YOUR_NONCE'; // Optional if your CSP requires nonces
Sprig.applyStyles('.ul-question {color: red}'); // Example: changes question text color to red
```
| Element | CSS Selector |
| :- | :- |
| Container | `.ul-card__container` |
| Main question title | `.ul-question` |
| Question subtitle | `.ul-caption` |
| Progress bar | `.ul-progress-bar-container` |
You may call this method at any time (even when a study is already presented) to override the existing CSS rules. Note that calls to this are not additive, you must include all the CSS changes in one call.
### Study Event Lifecycle Notifications
Sprig exposes updates throughout the study lifecycle. Here is a sample code block for listening to SDK events in real time:
```html HTML script tag theme={null}
```
```javascript npm theme={null}
// import the client returned from your Sprig.configure call
import { Sprig } from 'utils/sprig'
//import SprigEvent from the Sprig NPM package
import { SprigEvent } from '@sprig-technologies/sprig-browser';
// an example of a simple listener
const listener = function (e) {
// does work with data
console.log(e);
};
// to subscribe to Sprig study presented event
Sprig.addListener(SprigEvent.SurveyPresented, listener);
// to remove a study presented event listener
Sprig.removeListener(SprigEvent.SurveyPresented, listener);
```
The following supported events are available on `Sprig.UPDATES` if using the JS snippet, and `SprigEvent` if using the NPM package:
| UPDATES name | SprigEvent name | Data | Trigger | Min SDK version |
| - | - | - | - | - |
| `QUESTION_ANSWERED` | `QuestionAnswered` | `{ answeredAt?: number; questionIndex?: number; value: unknown }` | Question was submitted by visitor. See table below for possible value type per question type. | 2.24.3 |
| `SDK_READY` | `SdkReady` | `{ name: 'sdk.ready' }` | SDK is loaded and initialized | 2.10.0 |
| `VISITOR_ID_UPDATED` | `VisitorIDUpdated` | `{ name: 'visitor.id.updated' }` | Visitor ID is updated | 2.10.0 |
| `SURVEY_DIMENSIONS` | `SurveyDimensions` | `text { name: 'survey.dimensions', contentFrameHeight: int, contentFrameWidth: int } ` | Dimension is changed | 2.9.0 |
| `SURVEY_HEIGHT` | `SurveyHeight` | `text { name: 'survey.height', contentFrameHeight: int } ` | Height is changed | 1.9.0 |
| `SURVEY_WIDTH` | `SurveyWidth` | `{ name: 'survey.width', contentFrameWidth: int }` | Width is changed | 2.25.0 |
| `SURVEY_WILL_PRESENT` | `SurveyWillPresent` | `text { name: 'survey.will.present', "survey.id": number } ` | Immediately before study will be presented | 2.15.15 |
| `SURVEY_PRESENTED` | `SurveyPresented` | `{ name: 'survey.presented' }` | Study is presented (animations have not yet completed) | 1.9.0 |
| `SURVEY_APPEARED` | `SurveyAppeared` | `{ name: 'survey.appeared' }` | Study has appeared on screen (animations have completed) | 2.10.0 |
| `SURVEY_WILL_CLOSE` | `SurveyWillClose` | `text { name: 'survey.willClose', initiator: 'survey.completed', studyType: 'feedbackButton' \| 'inProductSurvey' } ` | Immediately before study frame is dismissed `initiator` will be `close.click` if study is closed, or `survey.completed` if study is completed | 2.5.0 |
| `SURVEY_CLOSED` | `SurveyClosed` | `text { name: 'survey.closed', studyType: 'feedbackButton' \| 'inProductSurvey' } ` | Study frame is dismissed (either submitted or closed) | 1.9.0 |
| `FEEDBACK_BUTTON_LOADED` | `FeedbackButtonLoaded` | `{ name: 'feedback.button.loaded', "survey.id": number}` | Feedback button was loaded on the page | 2.28.0 |
| `SURVEY_LIFE_CYCLE` | `SurveyLifeCycle` | `{ state: 'presented' }` or `{ state: 'dismissed' }` | Study is presented, or study is closed | deprecated |
For the event when a question is answered, it will return the value the user submitted. See below for each question type and its possible value. There are mainly two types of value, the user can either submit an answer or skip it. Please be aware of all possible outcome of survey responses.
| Question Type | Input | Value(s) |
| :- | :- | :- |
| Text/URL | Clicked | `value: undefined` |
| Text/URL | Skipped | `value: {skipped: true}` |
| Consent/Legal Form | Submitted | `value: {submitted: boolean, name?: string}` |
| Consent/Legal Form | Skipped | `value: null` |
| Rating Scale | Submitted | `value: number` |
| Rating Scale | Skipped | `value: null` |
| Open Text | Submitted | `value: string` |
| Open Text | Skipped | `value: ''` |
| Multiple-Choice Single Choice | Submitted | `value: { [optionId]: string }` |
| Multiple-Choice Single Choice | Skipped | `value: {}` |
| Multiple-Choice Multiple Choice | Submitted | `value: { [optionId1]: boolean, [optionId2]: boolean, ... }` |
| Multiple-Choice Multiple Choice | Skipped | `value: { [optionId1]: boolean, [optionId2]: boolean, ... }` (same as submitted but all false value) |
| NPS | Submitted | `value: number` |
| NPS | Skipped | `value: null` |
| Voice and Video | Submitted | `value: { mediaRecordingUid: string }` |
| Voice and Video | Skipped | `value: null` |
| Recorded Task | Submitted | `value: {taskStatus: “completed”} ` |
| Recorded Task | Given up | `value: {taskStatus: “given.up”}` |
| Recorded Task | Skipped | `value: {taskStatus: “abandoned”}` |
### Installing without Session Replay Code
For installations and use cases where you do not want session replay code bundled, you can do this only via npm by installing `@sprig-technologies/sprig-browser` and changing the import as shown below
```javascript theme={null}
import { sprig } from '@sprig-technologies/sprig-browser/core'; //note the /core path addition
export const Sprig = sprig.configure({
environmentId: 'ENVIRONMENT_ID',
})
```
## Web Replays: Pause and Resume Recording
### Overview
Use these functions to pause and resume the capture of recordings within web Replays. This granular control allows for additional privacy protection while maintaining session continuity for those viewing Replays.
Requires: [v2.34.0](/docs/developer-center/sdk-changelog/web-changelog) of the web SDK or higher.
### Pause Recording
`pauseReplayRecording()`
Temporarily pauses all replay recording activity without ending the session. This function stops the recording of DOM events, user interactions (clicks, scrolls, keystrokes), and any other Replay data until recording is resumed.
**How to use**\
`Sprig.pauseReplayRecording();`
**When to use**
* When users are entering sensitive information (passwords, credit card numbers, personal data)
* During privacy-sensitive workflows or screens
* When temporarily switching to content that shouldn't be recorded
* To comply with privacy regulations during specific user flows
**Behavior**
* Records a "pause" event marker before stopping recording
* Maintains the existing replay session (doesn't create a new session when resumed)
* All subsequent user activity is ignored until resumeReplayRecording() is called
* Safe to call multiple times (subsequent calls are ignored if already paused)
* Pause state persists across page refreshes within the same session
Returns: `void`
### Resume Recording
`resumeReplayRecording()`
Resumes Replay recording after it was paused with pauseReplayRecording(). This function re-enables the capture of user interactions.
**How to use**\
Sprig.resumeReplayRecording();
**When to use**
* After users complete entering sensitive information
* When exiting privacy-sensitive workflows or screens
* To resume normal replay recording after a temporary pause
**Behavior**
* Resumes capture of all user interactions and DOM changes
* Safe to call multiple times (subsequent calls are ignored if not currently paused)
Returns: `void`
### **Example Usage**
`// Pause recording before sensitive input`\
`Sprig.pauseReplayRecording();`
`// User enters password or sensitive data`\
`// ... user activity not recorded ...`
`// Resume recording after sensitive input is complete`\
`Sprig.resumeReplayRecording();`
### Watching Replays that were Paused and Resumed
When watching a recording that was paused a gray background will appear with a message letting the user know the recording was paused. This way the passing of time is clear and the resumption of the recording, which might take place on a different screen than where the recording was paused, is less confusing.
# Data Collection
Source: https://docs.sprig.com/docs/integrations/data-collection/index
## Collection Integrations
Sprig offers an integration with [User Interviews](/docs/integrations/data-collection/user-interviews) to assist in data collection from panel participants.
# User Interviews
Source: https://docs.sprig.com/docs/integrations/data-collection/user-interviews
Integrate Sprig and User Interviews to collect real-time insights from the right users.
### Sprig & User Interviews' integration enables you to:
* Find the right participants for your study. Recruit your own users via Sprig or source from User Interviews’ 2.1 million+ panel with detailed consumer and professional targeting.
* Build a Prototype Test or Survey within Sprig, send it to participants, and capture user insights. Automate the entire flow from invite to incentives.
* Manage progress and access task recordings from a single place. Let our integration do the work of tracking participants across platforms.
### Connecting User Interviews & Sprig:
1. In the Sprig dashboard, navigate to Integrations > Study creation > Panels > User Interviews and click "Connect."
1. If you are not already logged in to User Interviews, click "Sign In" and login to your account.
1. Once logged in, click on your username in the bottom left corner and choose "Account settings."
2. On the Integrations tab, find Sprig and click "Connect" and login to your Sprig account.
3. If the connection is successful, the "Connect" button should now say "Disconnect."
2. If you are already logged in to User Interviews, find Sprig on the Integrations tab and click "Connect" and login to your Sprig account.
1. If the connection is successful, the "Connect" button should now say "Disconnect."
### Make Sprig Survey Available in User Interviews:
1. Build a [Survey](/docs/sprig-studies/long-form-surveys/index) or [Prototype Test](/docs/sprig-studies/prototype-studies/index) within Sprig.
2. On the Audience tab under Delivery Platform, toggle on the button that says “Share to a panel in User Interviews.”
3. Launch your survey.
For a Sprig survey to show up in User Interviews, the “Share to a panel in User Interviews” button must be toggled on and the survey must be in progress. All Sprig studies across all of your team's [Products](https://docs.sprig.com/docs/account-and-settings/team-management-roles/products-and-environments) that meet the above criteria will show up in User Interviews.
### Connect Sprig Survey to User Interviews Project:
1. In User Interviews, create a new Project.
1. Give the project an internal project name. Optionally, add an internal project description.
2. On the Recruitment tab, select the appropriate participant source and configure recruitment criteria as needed.
3. On the Research activity tab, select Unmoderated as the research activity.
1. Under Task Platform, select Integrations and add a task by clicking the "Add" button.
1. Click "Use your Sprig account” to select Sprig.
2. In the dropdown menu, select the name of the Sprig study you want to connect to your User Interviews project and click "Save."
4. Finish setting up your project by outlining incentive information on the Participant number & incentives tab and configuring communication details on the Participant communications tab. When ready, you can then launch the project.
5. Once the project is launched, you can monitor its progress by viewing the project, allowing you to see a link to task, start-time, duration, and status (not started, incomplete, complete).
6. Once the participant has completed the survey, view Sprig completion data and pay out incentives automatically in User Interviews once completion is confirmed.
Please see this article for more information about [using Sprig with User Interviews](https://www.userinterviews.com/support/sprig-integration).
# Amplitude
Source: https://docs.sprig.com/docs/integrations/data-destinations/amplitude
The Sprig and Amplitude integration enables you to get the full picture of your product experience by uniting your user insights and product analytics in one platform. This integration automatically sends your Sprig survey data to Amplitude in real time, so you can analyze product metrics alongside customer sentiment to uncover the “why” behind your users’ behavior. By pairing your qualitative and quantitative data, your team can surface and solve customer issues, deeply understand users' needs, and make product decisions with conviction.
Here are some of the many ways your team can use the Sprig & Amplitude integration to elevate your product development process:
✔️ Continuously track your critical user journeys to surface pain points and understand how to solve them.\
✔️ Collect continuous user feedback and analyze results by segment or use to build new cohorts.\
✔️ Detect a drop-off point in your conversion or onboarding flow and pinpoint the exact reason behind it.
## FAQs
### How do I connect Sprig and Amplitude?
*This integration is available to Sprig Starter and Enterprise Plan users and all Amplitude users.*
1. Log into Amplitude and go to **Settings**
2. Under Organization Settings, click **Projects**, and click into the project you'd like to integrate with Sprig
3. Copy the **API Key**
4. Log into [Sprig](https://app.sprig.com/) and visit the [**Integrations**](https://app.sprig.com/integrations/analytics) page
5. Click into the [**Amplitude**](https://app.sprig.com/integrations/analytics/amplitude) card, and select the tab corresponding to the environment you'd like to set up (Development or Production)
6. Paste your Amplitude API Key and click **Save**
7. Sprig study responses will begin flowing into Amplitude under the event name `sprig_study_response`
### Are there any factors I should consider before using this integration?
1. To analyze your Sprig data alongside your other data in Amplitude, you must identify users on both platforms in the same way. A user's User ID in Sprig must match the user\_id in Amplitude.
2. Ensure that integrating Sprig will not push you over your Amplitude usage limits. Every response to an individual question will be sent to Amplitude as a specific event.\
For example, if you have a 3-question survey and 5 users respond to all questions, Amplitude will receive 15 events from Sprig. If you are close to your monthly event limit for a project, enabling the Sprig integration may push you over the limit. If you have additional questions, reach out to Customer Success.
# Data destinations
Source: https://docs.sprig.com/docs/integrations/data-destinations/index
Integrate Sprig insights with your company's processes and workflows
## Destination Integrations
Sprig offers integrations with popular services so that you can export study results and findings into your company's processes and business workflows. Sprig currently supports the following integrations:
* [Amplitude](/docs/integrations/data-destinations/amplitude)
* [Segment Streams](/docs/integrations/data-destinations/segment-streams)
* [Slack](/docs/integrations/data-destinations/slack)
* [Mixpanel](/docs/integrations/data-destinations/mixpanel)
* [Webhooks](/docs/integrations/data-destinations/webhooks)
* [Zapier](/docs/integrations/data-destinations/zapier)
## Data Format
When using official Sprig methods to export data, the following information will be included in each first-party export method:
| Attribute | Amplitude | Mixpanel | Segment Stream | Webhooks | Zapier |
| :- | :- | :- | :- | :- | :- |
| Survey ID | Yes | Yes | Yes | Yes | Yes |
| Survey Name | Yes | Yes | Yes | Yes | Yes |
| Visitor ID | Yes | Yes | Yes | Yes | Yes |
| Created at | Yes | Yes | Yes | Yes | Yes |
| User ID | Yes | Yes | Yes | Yes | Yes |
| Custom Attributes | Yes | Yes | Yes | Yes | Yes |
| Survey received href | Yes | Yes | Yes | Yes | Yes |
| os | Yes | Yes | Yes | Yes | Yes |
| browser | Yes | Yes | Yes | Yes | Yes |
| userAgent | Yes | Yes | Yes | Yes | Yes |
| customMetadata | Yes | Yes | Yes | Yes | Yes |
| triggeringEvent | Yes | Yes | Yes | Yes | Yes |
| eventProperties | Yes | Yes | Yes | Yes | Yes |
| Question text | Yes | Yes | Yes | Yes | Yes |
| Question response | Yes | Yes | Yes | Yes | Yes |
| Question response option value | Yes | Yes | Yes | Yes | Yes |
| Question response theme | N/A | N/A | Yes | N/A | N/A |
| Environment ID | Yes | Yes | Yes | Yes | Yes |
| Group all responses in a responseGroup | N/A | N/A | N/A | Yes | N/A |
| Response Group UID | Yes | Yes | Yes | Yes | :white\_check\_mark: |
## Other Data Export Methods
Alongside the integrations listed above, Sprig supports a couple other data export methods:
* [Export API](/reference/sprig-api/v1/get-v1-responses-1): Leverage our Public API to retrieve survey response data and more.
* [CSV Download](/docs/shared-study-foundations/export-survey-data): Sprig sends an email with a link to download all responses for a survey in CSV format.
## Requesting an Integration
If there is a product that you would like to see integrated with Sprig, please let us know through our [Request an Integration Survey](https://a.sprig.com/U0pjVmZxLTdRUX5zaWQ6NGIyNGM5MmMtNTAxOC00MmNkLWEzNGMtMzFhYmJlZWZkYjAw)!
## Joining the Partner Network
If you're a company that is looking to integrate with Sprig, feel free to [Join our Partner Network](https://sprig.com/partnership-application). Let's build something great together!
# Mixpanel
Source: https://docs.sprig.com/docs/integrations/data-destinations/mixpanel
With the Sprig and Mixpanel integration, you can easily combine your user insights and product analytics into a single platform to capture a comprehensive view of your users’ product experience. The integration sends Sprig survey response data into Mixpanel so that product teams can uncover the 'why' behind how users behave in their product by digging into Sprig’s user insights alongside Mixpanel’s product data.
Here are some of the many ways your team can use the Sprig & Mixpanel integration to elevate your product development process:
✔️ Detect a drop off in your conversion or onboarding flow and pinpoint the root cause of it.\
✔️ Learn what your power users want to see next in your product.\
✔️ Understand how to retain cohorts that are likely to churn.
## Sprig x Mixpanel use cases
**Detect a drop off in your conversion or onboarding flow with Mixpanel analytics data and pinpoint the root cause of it.**
1. Leverage this Sprig “Reduce Onboarding Drop-Off” [template](https://sprig.com/template/reduce-onboarding-drop-off) to get started collecting insights, after users have completed Event A.
2. Create a funnel report in Mixpanel to evaluate conversion Event A to Event B, a key step in your onboarding flow.\
View drop-off and create a new cohort of users who dropped off before completing Event B. View drop-off and create a new cohort of users who dropped off before completing Event B.
3. Create an Insight report in Mixpanel and select the specific Sprig survey event, filter by the cohort of users who dropped off, and breakdown by response to see exactly why they dropped.
**Learn what your power users want to see next in your product**
1. Leverage this Sprig “Prioritize Feature Development” [template](https://sprig.com/template/prioritize-feature-development) to start gathering insights on new product features.
2. To prioritize features based on product usage, create a cohort identifying your power users who also responded to the in-product survey.
3. Create an Insights report selecting the “Power Users” cohort created and breakdown by “response” to understand demand for new features and product improvements.
**Understand how to retain cohorts that are likely to churn**
1. Leverage this Sprig “Gauge Feature Satisfaction” [template](https://sprig.com/template/gauge-feature-satisfaction) to understand potential areas for improvement.
2. Create a cohort identifying users that have signaled potential churn risk (low usage).
3. Create an Insights Report selecting the “At Risk” Cohort and breakdown by “response” to understand how you can improve the user experience for users who might churn and proactively reach out with product updates based on their feedback.
**Analyze how different use properties affect product sentiment**
1. Create a cohort based on Sprig survey respondents that expressed positive sentiment.
2. Create an Insights Report and select the Sprig survey as the event.
3. Filter by the cohort of happy respondents, and breakdown by location or another user property to understand how various user properties affect product sentiment.
## How to set up the Mixpanel and Sprig integration
This integration is available to Sprig Starter and Enterprise Plan users, and all Mixpanel users.
1. Log into Mixpanel and select the project you'd like to integrate with Sprig
2. Click on the gear icon in the right hand corner and go to Project Settings
1. You'll need to copy over three credentials from Mixpanel to Sprig to connect your accounts.
3. Within **Project Details**, copy the Project ID
4. Within **Project Details**, click Service Accounts in the left hand menu and click Add a Service Account found in the navigation bar on the left hand side (which can also be managed under “Organization Settings”)
5. Create a **Service Account** with the following settings:
1. Enter a **Name** for the account
2. Assign the **Project Role** to **Admin**
3. We recommend setting **Expiration** to **Never** (if you set an expiration date, the integration will no longer work u
6. Once the Service Account is created, copy both credentials: **Username** and **Secret**
7. Log into Sprig and visit the [**Integrations**](https://app.sprig.com/integrations/analytics) page
8. Click into the Mixpanel card, and select the tab corresponding to the environment you'd like to set up (Development or Production)
9. Paste your Mixpanel **Project ID**, **Username**, and **Secret** in the Mixpanel Integration Card and click **Save**
10. Sprig study responses will begin flowing into your Mixpanel account under the event name `Sprig: Your Survey Name`
## Once Mixpanel and Sprig are connected, what is the best way to view Sprig data within Mixpanel?
Prior to viewing your Sprig data in Mixpanel, make sure the following steps are complete:
* A [survey](/docs/sprig-studies/in-product-surveys/index) to collect insights is live in Sprig
* The Mixpanel \<> Sprig integration is [set up](/docs/Integrations/data-destinations/mixpanel#how-do-i-connect-sprig-and-mixpanel) with the correct projectId
* Sprig response events are being ingested in Mixpanel. Below is an example response event in Mixpanel.
**Start evaluating Sprig data in Mixpanel in a few different ways:**
1. Create a Mixpanel Insight Report and analyze survey response data by key user attributes. Select the event \[**Sprig**: Survey Name] and filter by a cohort based on attributes like usage, plan type, etc.
2. Create a Mixpanel Funnel Report and analyze a critical user journey (defined by completing Event A and Event B). Next, create a Sprig cohort based on survey response data (see cohort creation steps below) and look at conversion for users with positive sentiment versus negative sentiment, then dig into open end responses to understand ways to optimize and increase conversion.
**How to create a cohort in Mixpanel**
Cohorts are groups of users defined by a chosen set of criteria, like a shared property or sequence of events. When you define a cohort, you can use it to group and filter data in the Analysis reports. Mixpanel Cohorts combined with Sprig survey responses allow you to create detailed journeys of customer behavior, with an overlay of customer attitudinal data.
1. Navigate to the Data icon in the top navigation bar and click on “Cohorts”
2. Click on “**Create a Cohort**”
3. Name and define the Cohort
1. Suggestion: create two cohorts - one for “happy path” and the other for “not happy path”. Be sure to provide a distinguishable naming convention for each cohort.
2. Remember for additional event property filters, like questionType and response, you must use the three dots drop down on the far right and then click on “filter”. Do not use the “+ Filter”
4. Click "Create Cohort"
## Are there any factors I should consider before using this integration?
1. To analyze your Sprig data alongside your other data in Mixpanel, you must identify users on both platforms in the same way. A user's User ID in Sprig must match the user\_id in Mixpanel.
2. Ensure that integrating Sprig will not push you over your Mixpanel usage limits. Every response to an individual question will be sent to Mixpanel as a specific event.
*For example, if you have a 3-question survey and 5 users respond to all questions, Mixpanel will receive 15 events from Sprig. If you are close to your monthly event limit for a project, enabling the Sprig integration may push you over the limit. If you have additional questions, reach out to Customer Success.*
# Segment Streams
Source: https://docs.sprig.com/docs/integrations/data-destinations/segment-streams
Export data to Segment
## Overview
Sprig supports sending study responses to Segment (via Segment Streams) each time a response is received. These responses can then be exported to one or more of Segment's [Destination integrations](https://segment.com/docs/connections/destinations/catalog/).
First, you will need to create the Sprig Source in Segment, and then you can configure one or more Segment destinations.
### Connecting Sprig to Segment
1. Sprig currently does not appear as a Source in Segment, but you can set an HTTP endpoint as a source in Segment’s workspace to receive Sprig’s data as a stream. In Segment, click **Connections**, then click **Sources**.
2. Search for **HTTP** in the Sources Catalog and click **Add Source**.
3. Next, type in a Source name. As well as project-specific labels, consider incorporating the Sprig production and development environments in your naming convention.
4. Type in the URL of your website and click **Add Source**.
5. Click **Copy Snippet** and paste the code so that it is referenced in the `` section of all the pages that can display Studies.
6. Click **Settings** and **API Keys**.
7. Click **Copy** next to **Write Key**.
8. In the Sprig app, click **Integrations > Segment Stream**.
9. Click Add Key and paste the Write Key into the field.
10. Click **Save**.
11. Returning to the Source you just created in the Segment app, click **Overview > Add Destination** and follow the steps for creating a destination where you'd like to send study response data.
### Troubleshooting installation
The Segment Write Key is unique to each source connected to Segment, so please check to make sure you add the right one, and that the environment in the Sprig Integrations page in which the Write Key is set matches the Segment Source for that Write Key. For example, a source for your app's Production environment should be added to Sprig's Integrations page viewed in Production.\
A User ID is required to receive Sprig data in Segment. Sprig cannot respond to Segment if the study taker is anonymous: if the visitor does not have a User ID.
### Integration data fields
This table describes the data that will be sent from Sprig's Segment Stream to your destination integrations.
This table describes the data that will be sent from Sprig's Segment Stream to your destination integrations.
| Name | Description |
| - | - |
| userId (required) | Also known as \`externalUserId\`, \`userId\` is required by the Segment Stream. This value should be consistent across all data flowing through Segment (\[more details]\([https://segment.com/docs/partners/streams/#userid](https://segment.com/docs/partners/streams/#userid))) |
| event | Name of the action that a user has performed. We will use \`SDK - Submitted - Survey Response\` as a default value |
| properties.surveyName | Name of the survey |
| properties.surveyId | Uuid of the survey |
| properties.createdAt | Timestamp when the survey was created (ISO-8061 format) |
| properties.question | Question text |
| properties.questionType | Question type |
| properties.visitorId | Uuid of the visitor who submitted the response |
| properties.oldVisitorId | **deprecated** Legacy identifier of a visitor. Different from visitorId (uuid), oldVisitorId is a number |
| properties.responseGroupId | A response group is a set of responses for a visitor for a given survey |
| properties.response | The survey response to the question |
| properties.email | Visitor's email |
| properties.attributes | Other attributes of the visitor, like plan, company, role etc. |
| properties.triggeringEvent | The label of the event that triggered this survey. Can be NULL |
| context | Dictionary of extra information that provides useful context about a message. Each call is required to contain a \`context.integration\` object in the call body that identifies where the call is coming from |
| sentAt | Timestamp of when a message is sent to Segment |
| receivedAt | Automatically set by Segment, the timestamp of when a message is received by Segment |
| timestamp | Timestamp when the message itself took place, defaulted to the current time by the Segment Tracking API, as a ISO-8601 format date string |
| type | Type of message, corresponding to the Segment API method: \`identify\`, \`group\`, \`track\`, \`page\`, \`screen\`, or \`alias\`. Sprig will call Segment’s track API to publish the events to destinations, so the type will be \`track\` |
# Slack
Source: https://docs.sprig.com/docs/integrations/data-destinations/slack
Sprig’s Slack integration allows customers to receive notifications about Sprig studies in their desired Slack workspace channels. Some highlights about the integration include:
* Per study configuration of Slack channels
* Three notification types: Study Connected, Study Responses, Study Completed
* Public and Private channels access
* Default catch-all Slack configuration
## Before getting started
* The Sprig Slack integration is available to all plans.
* Only a Sprig Admin, Developer, or Editor role can enable the Slack integration in Sprig, while in Slack, channel creation and application integration are determined by your [Slack administrator](https://slack.com/help/articles/201314026-Permissions-by-role-in-Slack).
* You may need to add your Slack administrator to the Sprig account so that they can install the integration. If you have added more than one product in Sprig, you may configure separate Slack channels for each product.
* Only completed survey responses will be sent to Slack through this integration. A user must click the "finish" button at the end of a survey to be considered a complete survey response, though they may skip questions within the survey.
* Users that close a survey without finishing or leave the browser tab without finishing the active survey will not have their responses sent to Slack.
Once you have the right Slack channels available and have verified the permissions for integrating Slack, you can map specific studies to specific Slack channels, or send all your study notifications to a single Slack channel for a given environment. Listed below are some general recommendations:
* Study-level channels: a channel with a working group or stakeholders who are interested in responses for a specific study
* Default channel for all study notifications: a channel with your whole product team or stakeholders to see when any study is connected to Slack, completed, or receives a response. This is set at an environment level.
## Connecting Sprig with Slack
There are three ways to grant Sprig authorization to your Slack Workspace.
### Method 1: Integrations > Slack
1. In the Sprig app, navigate to the Slack Integrations page (Integrations > Collaboration > Slack) and click the **Connect** button.
2. Slack will ask for permission to connect with Sprig. Please make sure you have the intended workspace selected and then click **Allow.**
1. Sprig will request the following bot scopes: `channels:read`, `chat:write`, `team:read`, `chat:write.public`
2. If you’d like Sprig to send notifications to a private channel, toggling “Private channel access”, will also request the `groups:read` and `group:write` scopes.
3. For more information on Slack Oauth2 scopes, please feel free to refer to the [Slack documentation](https://api.slack.com/scopes).
3. Once authorized, you will be redirected to the **Slack Integration page.** To turn on study-level notifications, navigate to an in-progress study’s Connect tab to choose a channel.
### Method 2: Study launch modal
1. Once a study is launched, click **Connect** on the launch modal’s Slack banner.
2. Slack will ask for permission to connect with Sprig. Please make sure you have the intended workspace selected, then click **Allow.**
3. Once authorized, you will be redirected to the **Connect tab** for your recently launched study. From here, you can set one or more Slack channels to receive response notifications.
### Method 3: Results page
1. For any in-progress study, navigate to the study’s results page and click on the **Connect tab**. From here, click **Connect.**
2. Slack will ask for permission to connect with Sprig. Please make sure you have the intended workspace selected, then click **Allow.**
3. Once authorized, you will be redirected back to the **Connect tab** for your recently launched study. From here, you can set one or more Slack channels to receive response notifications.
## Connect to private Slack channels
The Sprig bot must be invited to any private Slack channel that you wish to receive notifications.
1. In Slack, navigate to the private channel and click on the channel name to **Get channel details.**
2. In the modal that appears, select the **Integrations** tab, and click **Add an App.**
3. **Sprig** should be listed in the **In your workspace** section. Click **Add** to invite the Sprig bot to your private channel.
4. In Sprig, you will now see your private channel as an option in the Select Channel dropdown. Private channels are denoted with a lock icon.
* Note: If you have trouble connecting private Slack channels, your Slack connection may not have Private Channel Access enabled. This setting must be enabled prior to connecting your Slack workspace to Sprig. In order to fix this, on the Slack Integrations page, you must disconnect Slack, toggle on **Private Channel Access**, and re-connect Slack.
## Notification settings
### Default Channel (Optional)
You can set a **Default channel for all study notifications**. This channel will receive a notification when any study is connected to Slack, completed, or receives a response. This is set at an **environment** level. If you do not wish to receive messages across all studies, leave it as Not Set.
### User Emails (Optional)
You can include a respondent’s email address in study response notifications by toggling it on under Notification Settings. The email address is populated from visitor attributes. This is set at an environment level.
## Disconnecting Slack
To remove the Slack integration, click the **Disconnect** button on the Slack Integration page, and on the modal, choose whether to save your channel settings and click **Disconnect**. This will remove the Sprig App from your workspace and stop all Sprig notifications from being sent to Slack.
For more information, visit the [Sprig Privacy Policy](https://sprig.com/privacy-policy).
# Webhooks
Source: https://docs.sprig.com/docs/integrations/data-destinations/webhooks
Customer Data Platform
## What is a Webhook?
A [webhook](https://en.wikipedia.org/wiki/Webhook) is an HTTP request triggered by an event in a source system (in this case, Sprig) and sent to a destination system with a payload of data. Webhook requests are automatically sent out when their event is triggered in Sprig.
#### **What Webhook Events Does Sprig Support?**
Sprig supports webhooks triggered by the following events:
* Answer submitted - a user submits an answer to a specific question in a study.
* Study submitted - a user completes and submits a study.
* Study sent - Sprig has triggered and delivered a study.
* Study seen - a user has viewed a study.
* Theme identified - Sprig identifies a new [theme](/docs/shared-study-foundations/responses-and-insights#2-review-responses) associated with a study.
* Study status changed - a study becomes paused, completed, etc.
Currently, Sprig supports [Bearer Tokens](https://oauth.net/2/bearer-tokens/) for webhook authentication. The webhook is sent as an HTTP POST request to the specified endpoint, in JSON format.
You can have different Webhook configurations for each *Product* and *Environment*.
## Configuring Webhooks in Sprig
To receive webhooks from Sprig to a destination system:
1. Navigate to **Integrations > Destinations > Webhook** and click **Configure**.
2. Select the **Production** or **Development** environment.
3. Enter the destination system's Payload URL.
4. Enter the Bearer Token **API Secret** (*Bearer\_is automatically prepended to the\_authorization:* header field).
5. Check which events in Sprig you want to trigger a Webhook request.
6. Click **Test Webhook** to see if the request posts to the destination system.
7. Click **Save** to save the configuration.
#### Example cURL equivalent of the Test Webhook request
```curl theme={null}
curl -X 'POST' 'https://webhook.site/96255364-4d38-4be5-a6e4-795881dc5b6b?' -H 'connection: close' -H 'host: webhook.site' -H 'content-length: 92' -H 'user-agent: axios/0.21.2' -H 'authorization: Bearer APIsecret' -H 'content-type: application/json' -H 'accept: application/json, text/plain, */*' -d $'{"id":1,"environmentId":"abc123","surveyId":1,"surveyName":"TEST_SURVEY","eventType":"TEST"}'
```
## Example Payloads for Each Event
### Answer Submitted
| Property | Type | Description | | | |
| :- | :- | :- | - | - | - |
| id | Integer | Webhook ID | | | |
| environmentId | String | Internal Environment ID | | | |
| createdAt | Datetime | Creation date and time | | | |
| responseGroupUid | String | UUID for the Group of Responses sent by a User | | | |
| response | String \\ | Integer \\ | List \\ | Object | Response Text or Option to the Question. This can be an Integer, String, or List, or Object. |
| surveyId | Integer | Unique Survey ID | | | |
| surveyName | String | Survey name/title | | | |
| question | String | Question wording | | | |
| questionType | String | Question type (open, nps, multipleselect, matrix, etc.) | | | |
| visitorId | String | Visitor ID | | | |
| oldVisitorId | integer | Legacy Vistor ID | | | |
| userId | String | User ID | | | |
| anonymousId | String | Segment data not used by Sprig | | | |
| triggeringEvent | String | Event name of event that initiated study for visitor | | | |
| timestamp | Timestamp | Time of response in UTC unix milliseconds epoch | | | |
| email | String | Email address of the user | | | |
| attributes | map | A key-value map of custom attributes you can set on the user | | | |
| href | String | URL where study was activated if web study | | | |
| os | String | Operating system of device if collected from SDK | | | |
| browser | String | Browser that study was activated if web study | | | |
| userAgent | String | Information about platform visitor used if collected from SDK | | | |
| customMetadata | Object | A key-value map of custom metadata you can set on the url of link studies, empty map otherwise | | | |
| selectedIndexes | Integer \\ | List | This field can either be an Integer of a List of Integers, depending on the question type. If the question type is "multiplechoice", this field will be an Integer. If the question type is "multipleselect", this field will be a List of Integers. | | |
| eventType | String | The type of event that triggers the webhook | | | |
| eventName | String | Name of Event under the Event Type | | | |
| eventProperties | Object | A key-value map of event properties that were set to target this visitor, empty map otherwise. | | | |
JSON example
```json theme={null}
{
"id": 234211,
"environmentId": "ENVIRONMENT_ID",
"createdAt": "2022-08-16T17:57:33.603Z",
"responseGroupUid": "3305ee6c-15f4-4a55-a478-2c5f4adb9798",
"response": "[\"SUV\"]",
"surveyId": 11220,
"surveyName": "What Is Your Preferred Transportation Method?",
"question": "What models of car do you prefer?",
"questionType": "multipleselect",
"visitorId": "ba050493-0292-4099-9262-8e18c7406e81",
"oldVisitorId": 0,
"userId": "2603",
"anonymousId": null,
"triggeringEvent": exit_rental_booking,
"timestamp": 1660672653789,
"email": "example@example.com",
"attributes": {
"plan": "Enterprise",
"role": "admin"
},
"href": "https://retails.cars.com/surveys/11220",
"os": "Mac OS X",
"browser": "Chrome",
"userAgent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.0.0 Safari/537.36",
"customMetadata": "{}",
"selectedIndexes": "[2]",
"eventType": "survey_response",
"eventName": "surveyResponse",
"eventProperties": {
"string-event-property": "string"
}
}
```
### Theme Identified
| Property | Type | Description |
| :- | :- | :- |
| themename | string | Theme Name |
| updatedAt | date/time | date and time |
| productId | string | ID of the product |
| environmentId | string | Environment ID |
| questionText | string | Question body text |
| questionType | string | Type of Question |
JSON example
```json theme={null}
{
"themename": "testthemeNew8",
"updatedAt": "2022-02-22T19:31:05.089Z",
"productName": "iOS Test Account",
"productId": 20110,
"environmentId": "RpOLQFy3T",
"questionText": "The iOS Test Account team has a video question for you",
"questionType": "videovoice"
}
```
### Study Submitted
| Property | Type | Description |
| :- | :- | :- |
| visitorId | string | unique ID of the survey respondent |
| platform | string | Study delivery method |
| surveyId | string | ID of the survey |
| timestamp | Time | UTC timestamp of when survey was completed |
| environmentId | string | Enironment ID |
| eventDate | date / time | Datestamp of when survey was completed in UTC |
| recordType | string | Will always be Survey |
| action | string | will always be completed |
| responseGroupUid | integer | UUID of Response Group (used for debugging purposes) |
| productName | string | Name of Sprig Product configured by the Customer |
| productId | integer | Internal Numeric Id of Product (used for debugging) |
| questions | string | All the questions in the survey with responses if available |
| question | string | Question instance |
| response | string | Response to the question |
| order | string | order of question in the survey |
| eventType | string | Event type |
JSON example
```json theme={null}
{
"visitorId": "2341e79f-9b73-49d0-884d-d1f168aa9511",
"platform": "link",
"surveyId": 8529,
"timestamp": 1645562173173,
"environmentId": "RpOLQFy3T",
"eventDate": "2022-02-22T20:36:13.011Z",
"recordType": "survey",
"action": "completed",
"responseGroupUid": "91355295-f316-40f3-85e5-dec3e7b2ec72",
"productName": "iOS Test Account",
"productId": 20110,
"eventName": "surveySubmitted",
"questions": [
{
"question": "I am testing something",
"response": 3,
"order": 1
}
],
"eventType": "product_message"
}
```
### Study Status Changed
| Property | Type | Description |
| :- | :- | :- |
| surveyId | string | unique ID of the survey (used for debugging) |
| surveyName | string | Name of the Survey |
| oldStatus | string | Old status of the survey |
| status | string | Updated status of the survey (possible values are "NEW", "IN\_PROGRESS", "PAUSED", "COMPLETED") |
| environmentId | string | Environment ID |
| productName | string | Name of Sprig Product configured by the Customer |
| productId | integer | Internal Numeric Id of Product (used for debugging) |
| eventName | string | Name of Event under the Event Type |
| questions | string | All the questions in the survey |
| question | string | Question text |
| questionTypeId | integer | Type of question |
| eventType | string | Event type (will always be product message in this json object) |
JSON example
```json theme={null}
{
"surveyId": 77694,
"surveyName": "Test Survey for Webhooks",
"oldStatus": "NEW",
"status": "IN_PROGRESS",
"environmentId": "RpOLQFy3T",
"productName": "iOS Test Account",
"productId": 20110,
"eventName": "surveyStatusChange",
"questions": [
{
"question": "What is one plus one?",
"questionTypeId": "open"
},
{
"question": "How likely are you to recommend iOS Test Account to a friend or colleague?",
"questionTypeId": "nps"
}
],
"eventType": "product_message"
}
```
### Study Sent
| Property | Type | Description |
| :- | :- | :- |
| isUserInterviews | boolean | True if Link Study with User Interviews integration enabled |
| platform | string | Study delivery method |
| timestamp | time | UTC timestamp of when survey was completed |
| recordType | string | record type will always be "survey" |
| eventDate | date/time | Datestamp of when survey was completed in UTC |
| visitorId | string | unique ID of the survey respondent |
| environmentId | string | Environment ID |
| surveyId | integer | survey ID |
| action | string | will always be completed |
| responseGroupUid | integer | UUID of Response Group (used for debugging purposes) |
| productName | string | Name of Sprig Product configured by the Customer |
| productId | integer | Internal Numeric Id of Product (used for debugging) |
| eventName | string | Name of Event under the Event Type |
| triggeringEvent | string | Event name of event that initiated study for visitor |
| surveyName | string | Name of the Sprig Study |
| attributes | object | Object of attributes set on the visitor if available |
| email | string | Email address if set |
| oldVisitorId | null | Deprecated |
| userId | string | User ID if set |
| anonymousId | string | Segment Anonymous ID if set |
| customMetadata | object | Custom metadata if set for Link Study response |
| eventType | string | Event type |
JSON example
```json theme={null}
{
"isUserInterviews": false,
"platform": "web",
"timestamp": 1711987848970,
"recordType": "survey",
"eventDate": "2024-04-01T16:10:48.970Z",
"visitorId": "0209f2ad-27db-4080-bf8b-2fdae11a2649",
"environmentId": "",
"surveyId": 0,
"action": "seen",
"responseGroupUid": "38b1a6fe-13ed-477f-ab04-af53f9ecd499",
"productName": "Earl Test",
"productId": 0,
"teamId": 0,
"eventName": "studySeen",
"triggeringEvent": "sprig",
"surveyName": "Survey Test",
"attributes": {},
"email": "",
"oldVisitorId": null,
"userId": null,
"anonymousId": null,
"customMetadata": "{}",
"eventType": "product_message"
}
```
### Study Seen
| Property | Type | Description |
| :- | :- | :- |
| visitorId | string | unique ID of the survey respondent |
| timestamp | Time | UTC timestamp of when survey was completed |
| environmentId | string | Environment ID |
| platform | string | Study delivery method |
| recordType | string | record type will always be "survey" |
| eventDate | date/time | Datestamp of when survey was completed in UTC |
| surveyId | integer | Will always be Survey |
| action | string | be completed ID |
| responseGroupUid | integer | UUID of Response Group (used for debugging purposes) |
| productName | string | Name of Sprig Product configured by the Customer |
| productId | integer | Internal Numeric Id of Product (used for debugging) |
| eventName | string | Name of Event under the Event Type |
| triggeringEvent | string | Event name of event that initiated study for visitor |
| surveyName | string | Name of the Sprig Study |
| attributes | object | Object of attributes set on the visitor if available |
| email | string | Email address if set |
| oldVisitorId | null | Deprecated |
| userId | string | User ID if set |
| anonymousId | string | Segment Anonymous ID if set |
| customMetadata | object | Custom metadata if set for Link Study response |
| eventType | string | Event type |
JSON example
```json theme={null}
{
"visitorId": "0209f2ad-27db-4080-bf8b-2fdae11a2649",
"timestamp": 1711987848665,
"environmentId": "",
"platform": "web",
"recordType": "survey",
"eventDate": "2024-04-01T16:10:48.665Z",
"surveyId": 0,
"action": "sent",
"responseGroupUid": "38b1a6fe-13ed-477f-ab04-af53f9ecd499",
"productName": "Demo Product",
"productId": 0,
"teamId": 0,
"eventName": "studySent",
"triggeringEvent": "studyEventTrigger",
"surveyName": "Survey Test",
"attributes": {},
"email": "",
"oldVisitorId": null,
"userId": null,
"anonymousId": null,
"customMetadata": "{}",
"eventType": "product_message"
}
```
# Zapier
Source: https://docs.sprig.com/docs/integrations/data-destinations/zapier
Business Workflow Automation
Using Zapier may require access to admin permissions. Please contact your admin if prompted to do so.
## What is Zapier?
Zapier is a workflow automation tool that enables you to connect to thousands of other applications within their connected marketplace. Zapier utilizes “zaps” that run tasks, these tasks are easy to set up and serve highly customizable needs, in minutes. Zapier supports applications including Slack, HubSpot, Salesforce, Intercom, Zendesk, and Gmail.
You can find instructions on how to set up some of the most popular Sprig+Zapier integrations below:
1. [Airtable](#airtable)
2. [Gmail](#gmail)
3. [HubSpot](#hubspot)
4. [Intercom](#intercom)
5. [Salesforce](#salesforce)
6. [Slack](#slack)
7. [Zendesk](#zendesk)
### How to Find Your API Keys
To use Zapier you’ll first need to [create an account](https://zapier.com/sign-up/). Once you’ve signed up, you’ll want to keep your Sprig Zapier API key handy, see below:
1. In the Sprig app, click **[Integrations](https://app.sprig.com/integrations/collaboration)> Zapier > Get API Keys**
2. Confirm which Environment you are in. Based on the current Environment, take note of either the **Development ID** or **Production ID**
3. Copy the Environment ID for use in a later step.
## Airtable
If you have a large team, everyone needs to be able to see the user insights you've collected through Sprig. Set up this integration and Airtable records will be automatically generated from new Sprig study responses. Now, your whole team can view all the responses from one platform that you already use.
* Create a new Zap, and select **Sprig** as the trigger.
* If asked, "Sign in" to Sprig using your [Zapier API Key](#how-to-find-your-api-keys). If you’re unable to locate your Zapier API Key, please contact support.
* Select **New Study Response** as the *Trigger Event*.
* Click **Continue** and then click **Test Trigger** (testing is optional).
* Search for **Airtable** as the action, in other words, where should the data be sent to.
* Add action **Create a Record**. For all available actions supported by Airtable, visit the [Zapier Library](https://zapier.com/apps/airtable/integrations).
* You may be prompted to authenticate/sign in to Airtable.
* Select an existing base and table for data population.
* Once finished **Continue**.
* You have the option to test your Zap or skip and make **live**.
## Gmail
Save time by automating your follow-up process with new respondents to your Sprig study. With this integration, a custom email will be automatically sent from your Gmail account to a specified recipient. Send thank you's, schedule interviews, trigger updates, and more!
* Launch a study using one of the [Recruiting Interview Participants](https://app.sprig.com/templates/recruit-for-research) templates
* Create a filtered workflow in Zapier that emails a pre-built link to anyone that agrees to be part of the study, for example [www.calendly.com](https://www.calendly.com).
* Create a new Zap, and select **Sprig** as the trigger.
* If prompted, sign in to Sprig using your [Zapier API Key](#how-to-find-your-api-keys). If you’re unable to locate your Zapier API Key, please contact support.
* Select **New Study Response** as the Trigger Event.
* Click **Continue** and optionally **Test Trigger**.
* **Add a filter** before selecting an app
* We only want to send an email to participants that have \_accepted \_the opportunity to be part of a study. Here is an idea of how to create the filters, this may vary depending on your study question configuration. This flow will activate when the following two conditions are met:
* This Study Name contains Recruit (make sure you add this to the title)
* There's a response that has someone's email (the "@" symbol)
* Search for Gmail as the action ( e.g. where should the data be sent to)
* Choose the Send Email action. For all available actions supported by Gmail, visit the[ **Zapier Library**](https://zapier.com/apps/gmail/integrations).
* You may be prompted to authenticate/sign in to Gmail.
* Fill out the fields highlighted below (some are optional). You'll notice how you can use Sprig-provided fields to create a more personalized experience.
* Once finished click **Continue**.
* You have the option to test your Zap or skip and make it live.
## HubSpot
Having quick access to your HubSpot contacts' latest comments or satisfaction scores is essential to providing a best-in-class customer experience. This Zap makes it simple and efficient to save your latest study responses to HubSpot.
### Step 1: Create Zap and Define Trigger
* Create a new Zap
* Click Trigger and select **Sprig** as the trigger
* For trigger event, select New Survey Response
* Click sign in to login to Sprig using your [Zapier API Key](#how-to-find-your-api-keys)
* Click continue
* Click test the trigger
* Choose one of the responses and click continue with selected record
### Step 2: Add an Action - Find Contact (optional)
Adding "Find Contact" to your Zap will allow you to tie survey responses to specific contacts within HubSpot. If this is not necessary, you can skip this step.
* Select HubSpot as the App for the action
* For action event, select Find Contact. For all available actions supported by HubSpot, visit the [Zapier Library](https://zapier.com/apps/hubspot/integrations).
* Click sign in to login to HubSpot
* Click continue
* In the first search property name field, locate and select the HubSpot property for email
* For the first search property value, click the plus (+) and select Email
* *Optional: If the email value of a Sprig response does not match the email of an already existing HubSpot contact and you would like a new contact created, check the box to “create HubSpot contact if it doesn’t exist yet”*
* Click continue
* Click test step
### Step 3: Add an Action - Create Custom Object
If you haven’t already, you will need to first create a custom object in HubSpot that you can use to store the Sprig survey responses.
* Add an action and select HubSpot as the App for the action
* For action event, select Create Custom Object
* For account choose HubSpot (should already be selected)
* Click continue
* In the Type of Custom Object field, select the custom object you created in HubSpot
* Below the Type of Custom Object field, find the fields for the custom object and map the corresponding Sprig properties to them
* Click continue
* Click test step
* Click publish to turn on the Zap
### If you don’t have a HubSpot enterprise account and therefore don’t have the ability to create custom objects, an alternative approach of sending Sprig survey responses to HubSpot would be to create a note associated with contacts.
### Step 1: Create Zap and Define Trigger
* Create a new Zap
* Click Trigger and select **Sprig** as the trigger.
* For trigger event, select New Survey Response
* Click sign in to login to Sprig using your [Zapier API Key](#how-to-find-your-api-keys)
* Click continue
* Click test the trigger
* Choose one of the responses and click continue with selected record
### Step 2: Add an Action - Find Contact
* Select HubSpot as the App for the action
* For action event, select Find Contact
* Click sign in to login to HubSpot
* Click continue
* In the first search property name field, locate and select the HubSpot property for email
* For the first search property value, click the plus (+) and select Email
* Optional: If the email value of a Sprig response does not match the email of an already existing HubSpot contact and you would like a new contact created, check the box to “create HubSpot contact if it doesn’t exist yet”
* Click continue
* Click test step
### Step 3: Add an Action - Create Engagement
* Add an action and select HubSpot as the App for the action
* For action event, select Create Engagement
* For account choose HubSpot (should already be selected)
* Click continue
* In the Engagement Type field, select Note
* For the Note Body field, click the plus (+) and select Step Output. This will copy over all the survey response information into a note in HubSpot as a JSON object.
* In the “Emails of the contact objects that should be associated with engagement” field, click the plus (+) and choose the Sprig Email field.
* Click continue
* Click test step
* Click publish to turn on the Zap
## Intercom
Having quick access to your Intercom contacts' latest comments or satisfaction scores is essential to providing a best-in-class customer experience. This Zap makes it simple and efficient to save your latest study responses to Intercom contacts. With this integration, whenever a new Sprig response is received, Zapier will automatically create or update the correlating Intercom contact.
* Create a new Zap, and select **Sprig** as the trigger
* If asked, Sign in to Sprig using your [Zapier API Key](#how-to-find-your-api-keys). If you’re unable to locate your Zapier API Key, please contact support.
* Select **New Study Response** as the Trigger Event.
* Click **Continue** and optionally **Test Trigger**.
* Search for **Intercom** as the action, in other words, where should the data be sent.
* Add action **Create/Update User.** For all available actions supported by Intercom, visit the [Zapier Library](https://zapier.com/apps/intercom/integrations).
* You may be prompted to authenticate to sign in to Intercom.
* Enter **Lookup Email** and **User ID** in the relevant fields.
* Once finished press **Continue**.
* You have the option to test your Zap or skip and make live.
* When complete, you should have this saved to *My Zaps*.
## Salesforce
Having quick access to your Salesforce contacts' latest comments or satisfaction scores is essential to providing a best-in-class customer experience. This Zap makes it simple and efficient to save your latest study responses to Salesforce.
### Step 1: Create Zap and Define Trigger
* Create a new Zap
* Click Trigger and select **Sprig** as the trigger
* For trigger event, select New Survey Response
* Click sign in to login to Sprig using your [Zapier API Key](#how-to-find-your-api-keys)
* Click continue
* Click test the trigger
* Choose one of the responses and click continue with selected record
### Step 2: Add an Action - Create Record
If you haven’t already, you will need to first create a custom object in Salesforce that you can use to store the Sprig survey responses.
* Select Salesforce as the App for the action
* For action event, select Create Record. For all available actions supported by Salesforce, visit the [Zapier Library](https://zapier.com/apps/salesforce/integrations).
* Click sign in to login to Salesforce
* Click continue
* In the Salesforce Object field, select the custom object that you created in Salesforce
* Below the Salesforce Object field, find the fields for the custom object and map the corresponding Sprig properties to them
* Click continue
* Click test step
* Click publish to turn on the Zap!
## Slack
Easily send survey responses into Slack. *Do note that Sprig has an existing integration with Slack as well that can also be harnessed, for more information see [here](/docs/Integrations/data-destinations/slack).*
* Create a new Zap, and select **Sprig** as the trigger.
* Sign in to Sprig using your [Zapier API Key](#how-to-find-your-api-keys).
* After that, select a trigger event. The trigger event will be **New Study Response**. Then click **Continue**.
* Sign in to Sprig using your Zapier API Key.
* After that, select a trigger event. The trigger event will be **New Study Response**. Then click **Continue**.
* Next, we'll want to test our trigger.
* Pick the Slack application. Click **Continue** when finished. Please note that you may be prompted to sign into Slack.
* Select **Send Channel Message in Slack.** For all available actions supported by Slack, visit the [Zapier Library](https://zapier.com/apps/slack/integrations).
* Create your custom message and select a channel to post to.
* You can also opt to update fields like *bot name*, *bot icon*, etc. [Read this](https://zapier.com/apps/slack/integrations?utm_source=google\&utm_medium=cpc\&utm_campaign=gaw-usa-nua-search-partners_one_service-brand_exact\&utm_adgroup=brand-slack\&utm_term=zapier%20slack\&utm_content=_pcrid_417761558105_pkw_zapier%20slack_pmt_e_pdv_c_slid__pgrid_94490332016_ptaid_kwd-381410468867_\&gclid=CjwKCAjw9r-DBhBxEiwA9qYUpbGScwPg-VVQay2hNJ85E6uxFfv3pYr3JE3byApPXuuNoWC6n7cSfxoC2gwQAvD_BwE) for more Zapier x Slack capabilities.
* Scroll to the bottom and click continue, then trigger a test.
* If the test was successful, proceed to "Turn on Zap".
* When completed, it should return "Test was successful!"
## Zendesk
Append study responses to your user notes as study responses come in! This Zap makes it easy, automatically updating your Zendesk users with the details of each new study response in Sprig.
* Create a new Zap, and select **Sprig** as the trigger.
* Sign in to Sprig using your [Zapier API Key](#how-to-find-your-api-keys) .
* After that, select a trigger event. The trigger event will be "New Study Response". Then click **Continue**.
* Add an **Action** and search for Zendesk *(Please note that Zendesk is a Premium integration and requires an upgraded Zapier account)*.
* Add action **Find a User**. For all available actions supported by Zendesk, visit the [Zapier Library](https://zapier.com/apps/zendesk/integrations).
* Authenticate and login with Zendesk.
* The **Query** will work off the email search parameters in Zendesk.
* Once finished press **Continue**. You should then be given the option to either test your trigger or skip testing.
# Census
Source: https://docs.sprig.com/docs/integrations/data-sources-introduction/census
To build better products, you need the right insights from the right users. After all, you’ll always get more actionable feedback when you talk to users who have faced the same problem you’re trying to solve.
With the **Sprig & Census integration**, you can easily capture in-product insights from your exact target audience using 360° user data straight from your warehouse.
With every piece of product, support, and sales data at your fingertips, you can trigger Sprig in-product Surveys or Replays to specific cohorts based on characteristics like lifetime value, NPS & CSAT scores, product engagement, and so much more.
Want to leverage this integration and start making user-informed product decisions, day in and day out? [**Set up a free product demo with a Sprig Specialist today.**](https://sprig.com/sales-demos)
## FAQs
### What are Sprig in-product Surveys and Replays?
Sprig [In-Product Surveys](/docs/sprig-studies/in-product-surveys/index) enable you to target specific users in your product and capture their product experience insights at scale.
In-Product Surveys help teams:
* Capture bite-sized user insights to answer the “why” behind product analytics.
* Learn exactly how users feel about new features.
* Measure core flows and ensure they’re meeting customer needs.
* Quickly discover pain points and prioritize what to work on next.
Sprig Replays enable you to target specific users in your product and capture clips of their real-time product experience.
Replays help teams:
* Easily troubleshoot issues that would otherwise go unnoticed, like confusing navigation, hidden CTAs, and bugs.
* Understand why and how users are dropping off by exploring their journey through your product’s core flows.
* Watch users as they engage with features for the first time and identify areas for optimization to add to your roadmap.
### How do I connect Sprig & Census?
*This integration is available to Sprig Starter and Enterprise Plan users and all Census users.*
[Click here ](https://www.loom.com/share/21fed9cca1924417a5c908b1e5fbdb72)for a video demo of the setup process.
1. First, head over to the [Sprig app](https://app.sprig.com/) and log in.
2. Go to the Sprig [Integrations](https://app.sprig.com/integrations/enrichment) page and select **Data Import API**.
3. Then, copy the relevant **API key** (either production or development).
4. Now, head over to [Census](https://www.getcensus.com/integrations/sprig) and log into your account. If you don't have a Census account, you can try it out for free [here](https://www.getcensus.com/integrations/sprig).
5. Click **Add Service** and select **Sprig** from the menu.
6. Drop in the key you copied from Sprig under **API Key**.
7. Customize the sync to your specifications and click **Create Sync**.
8. To confirm that the sync is working as expected, visit the Sprig [Users page](https://app.sprig.com/users) and check that your Census user data has populated.
And that's it! You'll be well on your way to launching in-product Surveys or Replays with targeting powered by your data warehouse.
### What types of data can I send from Census to Sprig?
| Object Name | Supported? | Identifiers? | Behaviors |
| :- | :- | :- | :- |
| Event | | N/A | Append |
| User | | User ID | Update or Create |
# Data Sources
Source: https://docs.sprig.com/docs/integrations/data-sources-introduction/index
Pull data into Sprig from other products and systems in your organization
## Source Integrations
In addition to installing Sprig in your [web app](/docs/Installation/introduction-web/index) or [mobile app](/docs/Installation/introduction-mobile/index), you can also send supplemental data to Sprig that can be used to filter which users are targeted for your Surveys or Replays.
Sprig offers a variety of ways to import data into Sprig and can connect directly with many of the tools that your organization may already use.
Sprig also allows you to import data via [API](/reference/sprig-api/overview) or [uploading a CSV file](/docs/integrations/data-sources-introduction/uploading-a-csv).
# LaunchDarkly
Source: https://docs.sprig.com/docs/integrations/data-sources-introduction/launchdarkly
Use LaunchDarkly alongside Sprig in order to compare & segment results based on the user’s flag variations.
LaunchDarkly enables product and engineering teams to collaborate more effectively on releases by giving everyone the visibility that they need. By integrating LaunchDarkly with Sprig, you will be able to accomplish the following:
1. Target users based on the LaunchDarkly flag name and variation number.
2. Run cross-tab analysis based on the LaunchDarkly flag name and variation number.
# Supported Plans:
See the table below to see if your plan includes the LaunchDarkly integration. If you would like to upgrade, please reach out to your Sprig representative, or email Sprig Customer Success at [support@sprig.com](mailto:support@sprig.com) for assistance.
| Plan | Availability |
| - | - |
| Free | No |
| Starter | No |
| Enterprise (Concept Test) | No |
| Enterprise (IPS) | Yes |
| Enterprise (Full) | Yes |
# LaunchDarkly SDK Version:
You will need to have a minimum version of **2.24.0** for their [Javascript SDK](https://github.com/launchdarkly/js-client-sdk).
# Sprig Supported SDKs:
Please reference the table below to determine the availability and minimum Sprig SDK version your team will need to adopt in order to integrate LaunchDarkly.
| Platform | Supported | Min. SDK Version |
| - | - | - |
| Web | Yes | 2.23.0 |
| Native iOS | No | N/A |
| Native Android | No | N/A |
| React Native | No | N/A |
# How to Implement:
## Enabling on your Sprig product
The first step in enabling LaunchDarkly for your product is to turn the config on in the Integrations page. See below for steps:
**Step 1**: Head over to Integrations\
**Step 2**: Search for LaunchDarkly and click on the LaunchDarkly card\
**Step 3**: In the How to Connect section, toggle LaunchDarkly on
Once you have toggle the configuration on, you will be able to send LaunchDarkly flag and variations to Sprig and use LaunchDarkly as a runtime filter.
## Web
In order for the Sprig SDK to read your LaunchDarkly, there is some engineering dev work required in order to properly import LaunchDarkly flags and variation for the user over to Sprig in order to target the user appropriately.
The main additional change adding an **inspector** during the LaunchDarkly initialization. You can add to your existing inspector, or create a new inspectors config for your LaunchDarkly client.
```javascript theme={null}
inspectors: [
{
type: 'flag-details-changed',
name: 'my-flag-details-inspector',
method: (details) => {
// When flags have changed, use logic below to map flag to variation
// Mapped object should use flag slug paired with the variation index
const mappedLDFlags = Object.keys(details).reduce((agg, flag) => {
agg[flag] = details[flag].variationIndex;
return agg;
}, {});
// Then import the mapped data to Sprig below
Sprig('importLaunchDarklyData', mappedLDFlags);
},
},
]
```
To see the whole example app implementation, see below for a full code sample of how it will look like during initialization.
```javascript theme={null}
import { sprig } from '@sprig-technologies/sprig-browser';
import * as LDClient from 'launchdarkly-js-client-sdk';
// Configuring Sprig
const Sprig = sprig.configure({
environmentId: 'ENVIRONMENT_ID',
});
// Initializing LaunchDarkly
// Attach inspect during flag detail change
const ldClient = LDClient.initialize(clientSideID, context, {
inspectors: [
{
type: 'flag-details-changed',
name: 'my-flag-details-inspector',
method: (details) => {
// When flags have changed, use logic below to map flag to variation
const mappedLDFlags = Object.keys(details).reduce((agg, flag) => {
agg[flag] = details[flag].variationIndex;
return agg;
}, {});
// Then import the mapped data to Sprig below
Sprig('importLaunchDarklyData', mappedLDFlags);
},
},
],
});
```
# How to Use:
Once you have successfully turned LaunchDarkly on in your product and your development team has inserted the necessary code snippet in your application, you are now ready to launch your first LaunchDarkly targeting survey!
**Step 1**: Create a new study OR edit an existing one\
**Step 2**: Fill out the question form and move on to the audience form\
**Step 3**: In the audience form, select a trigger for “When to Send”\
**Step 4**: Select your LaunchDarkly Experiment attribute\
**Step 5**: Copy and paste the corresponding experimentId from LaunchDarkly to Sprig\
**Step 6**: Copy and paste the corresponding value for the variation and pick a comparison operator
# FAQs
**Question: Can I target multiple flags/variations with a single study?**\
Answer: Yes! You can use the AND/OR targeting to support multiple flags/variations.
**Question: Does this work for mobile platforms?**\
Answer: At this time, only the web implementation is available due to a gap in the LaunchDarkly and Sprig implementation for mobile. Please reach out to your Sprig representative, or email Sprig Customer Success at [support@sprig.com](mailto:support@sprig.com), for a feature request if this is something that interests your team.
**Question: How do I export the flag name and variation number from Sprig?**\
Answer: On your Summary page, navigate to responses and select the CSV download option. You should be able to see each respondent, including all qualifying experiments/variations
# Optimizely
Source: https://docs.sprig.com/docs/integrations/data-sources-introduction/optimizely
Use Optimizely alongside Sprig in order to compare & segment results based on user experiments/variations.
Optimizely is a digital experience & experimentation platform. By integrating Optimizely with Sprig, you will be able to accomplish the following:
1. Target users/segments based on an experiment id and variation name(s)
2. Run cross-tab analysis based on an experiment id and variation name(s)
## Optimizely Supported Products:
| Name | Supported? |
| - | - |
| Experiment | Yes |
| Orchestrate | No |
| Monetize | No |
## Sprig Supported SDKs:
| Platform | Triggers | Filters | Event Properties |
| - | - | - | - |
| Web | Yes | Yes | Yes |
| Native iOS | Yes | Yes | Yes |
| Native Android | Yes | Yes | Yes |
| React Native | No | No | No |
## Sprig Min SDK Versions:
Please reference the table below to determine which version of the Sprig SDK your team will need to adopt in order to integrate Optimizely \<> Sprig
| Platform | Min SDK Version |
| :- | :- |
| Web | 2.18.3 / 2.23.1 |
| Native iOS | 4.11.0 |
| Native Android | 2.10.0 |
| React Native | TBD |
## How to Implement:
### Send all active experiments & variations
### Web
Optimizely offers two different product: Web and Full-Stack Experimentation. Based on the product you want to integrate with, you will follow separate steps to get it installed.
#### Optimizely Web
On web, so long as the client SDK matches or is greater than the min (2.18.3), Optimizely will work without any additional dev effort. If your SDK version does not match, you will need to request your developer to update accordingly.
#### Optimizely Full-Stack
This will require you to have a minimum Sprig SDK version of 2.23.1. Once you have installed that version, you will be able to have access to two new methods that will allow you to integrate.
**Option 1**: Passing in Optimizely Client to our SDK
This is the easiest option as we will add in a notification listener to your Optimizely client for you. What this notification listener will do is that it will listen to every time you activate an experiment, and pass the experiment and variation to Sprig.
```javascript theme={null}
const optimizelyClient = optimizely.createInstance({
sdkKey: "",
});
optimizelyClient.onReady().then(() => {
Sprig.integrateOptimizelyClient(optimizelyClient); // once the client is ready, pass client into Sprig
});
```
**Option 2**: Creating your own notification listeners
This option requires more engineer work, however, there is more flexibility and customization with this option. For this option, you will create your own notification listeners and append to your client. It's important here that you pass in with the correct object format otherwise we will not accept the data. Please see the code snippet below for an example.
You can read more about setting up Optimizely notification listeners [here](https://docs.developers.optimizely.com/full-stack-experimentation/docs/set-up-notification-listener-javascript-node).
```javascript theme={null}
const optimizelyClient = optimizely.createInstance({
sdkKey: "",
});
optimizelyClient.notificationCenter.addNotificationListener(
enums.NOTIFICATION_TYPES.ACTIVATE,
({
experiment,
variation,
}: ActivateListenerPayload) => {
// Create this object and pass it into Sprig in line 20
const insertExperiment = {
experiments: [
{
id: experiment.id,
variation: variation.key,
},
],
};
Sprig.integrateOptimizely(insertExperiment, false); // you pass in the experiment/variation to Sprig and we will store and pass the data every time you track a Sprig event.
};
);
```
### iOS or Android
**Step 1:** Cut & paste the snippet below into your application code base
```swift Swift theme={null}
// iOS code example: Client passed in userId and OptimizelyClient to SDK,
// Sprig SDK will assume the userId is involved in all the experiments, and send
// variations of each experiment to Sprig backend.
let optimizely = OptimizelyClient(sdkKey: "")
try? optimizely.start(datafile: localDatafile,
doUpdateConfigOnNewDatafile: true)
/**
isOverride: if true, previously provided experiments in this session will be cleared and only
the newly provided experiments will be sent to Sprig
**/
Sprig.shared.integrateOptimizely(optimizely, userId: userId, attributes: visitorAttributes, isOverride: isOverride);
```
```Text Android theme={null}
// When Optimizely finish initialization, pass in the Optimizely client to Sprig.
OptimizelyManager.builder().withSDKKey("SDK KEY HERE").build(this).also { optimizelyManager ->
Sprig.integrateOptimizely(optimizelyManager.optimizely)
}
```
**Step 2:** Replace with your Optimizely SDK Key\
**Step 3:** Share your associated customer userId with Sprig (not required, but recommended)
Once you have shared your Optimizely SDK Key and the customer’s userId (not required), Sprig will automatically parse all active experiments & variations that are currently active in your application.
## How to Use:
Prior to in-product targeting, please ensure you reach out to [support@sprig.com](mailto:support@sprig.com) in order to activate the integration for your respective **productId**
Once Optimizely has been configured for your account, you can proceed onwards and create a study OR edit an existing one.
**Step 1:** Enable Optimizely in Sprig's integration gallery\
**Step 2:** Create a new study OR edit an existing one\
**Step 3:** Fill out the question form and move on to the audience form\
**Step 4:** In the audience form, select a trigger for “When to Send”\
**Step 5:** Select your Optimizely Experiment attribute (see below)\
**Step 6:** Copy and paste the corresponding experimentId from Optimizely to Sprig (see below)\
**Step 7:** Copy and paste the corresponding value for the variation and pick a comparison operator (see below)
## FAQs
**Question: Can I target multiple experiments/variations with a single study?**\
**Answer:** Yes! You can use the AND/OR targeting to support multiple experiments/variations. You can also change the comparison operator to “contains” to target more than one variation
**Question: Does this work for React Native?**\
**Answer:** At this time, our Optimizely integration does not support React Native. We expect a target of Q1, 2023 to introduce React Native
**Question:** **How do I export experiment names & variations from Sprig?**\
**Answer:** On your Summary page, navigate to responses and select the CSV download option. You should be able to see each respondent, including all qualifying experiments/variations
# RudderStack
Source: https://docs.sprig.com/docs/integrations/data-sources-introduction/rudderstack
With the **Sprig & RudderStack integration**, you can easily capture in-product insights from your exact target audience with user data sourced across your tech stack.
This code-free **Sprig & RudderStack integration** allows you to leverage Rudderstack event data and trigger Sprig in-product Surveys and Replays to specific user cohorts based on their unique characteristics.
* Track and collect all your customer data from a variety of sources, including web and mobile applications
* Improve the user experience by collecting relevant events and details related to your users leading to more concise insights
* Send Rudderstack events through cloud and devices allowing you to seamlessly add events into Sprig
* Ease time-to-insights without having to ask data teams for integration requests
## How do I connect Sprig & RudderStack?
This integration is available to Sprig Starter and Enterprise Plan users and all RudderStack users.
In Sprig:
1. Copy your Sprig API key by logging in to your Sprig dashboard and going to **Integrations** > **Enrichment** > **Data Import API**.
2. If connecting via web device mode, also copy your Sprig Javascript environment ID by going to **Integrations** > **Installation** > **JavaScript**.
In RudderStack:
1. In your RudderStack dashboard, go to **Directory** > **Destinations** > **Cloud Destinations** and search for Sprig.
2. Connect your source and click **Continue**.
3. Set up Sprig as a destination in RudderStack by configuring the **Name**, **Public API Key**, and if using web device mode, **Environment ID**.
4. Specify how you want to route events from your source to Sprig, either **device mode** or **cloud mode**.
And that's it! You'll be well on your way to launching in-product Surveys or Replays with targeting powered by your data warehouse.
## What connection modes can I use to send events from RudderStack to Sprig?
| Connection mode | Web | Mobile | Server |
| - | - | - | - |
| Device mode | Yes | No | No |
| Cloud mode | Yes | Yes | Yes |
# Segment Classic
Source: https://docs.sprig.com/docs/integrations/data-sources-introduction/segment-classic
### Overview
Segment is a Customer Data Platform (CDP) that collects and processes data from the users of your digital platforms and products. You can also use Segment to direct that data to other tools, making it a powerful tool for driving product experience insights with Sprig.
### Segment Actions vs Segment Classic
If you are trying to deliver in-product Surveys or Replays in your website, web app, or mobile app: **You must use Segment Actions**. Set-up instructions can be found in [Segment Web](/docs/Installation/introduction-web/segment-web), [Segment iOS](/docs/Installation/introduction-mobile/segment-ios), [Segment Android](/docs/Installation/introduction-mobile/segment-android), and [Segment React Native](/docs/Installation/introduction-mobile/segment-react-native).
If you are trying to send **additional data from a backend source** to Sprig to further refine which users are targeted for in-product Surveys or Replays: continue to follow the instructions below to set up Segment Classic. Segment Classic can send users, events, and attributes into Sprig. However, note that any events sent can only be used as study **filters**, not study triggers.
* For example, if you send an event "Checkout" from Segment Classic to Sprig, you will NOT be able to trigger a study when the user checks out. However, you WILL be able to apply a study filter to refine your targeting to users that have checked out fewer than three times in the last month.
**Warning:** Confirm Segment Actions vs Segment Classic
Before proceeding, ensure that you are have reviewed the difference between Segment Actions and Classic above.
Remember that Segment Classic alone **cannot be used to display in-product Surveys or Replays** into your product since it does not install the Sprig SDK. You must install the Sprig SDK through one of the installation methods for [Web](https://docs.sprig.com/docs/Installation/introduction-web/index) or [Mobile](https://docs.sprig.com/docs/Installation/introduction-mobile/index) in order to display studies.
### Set up Sprig as a Segment Classic Destination
In Segment, you will be connecting your backend data source(s) as a Source to Sprig as a Destination. This will allow events and attributes to be passed back to Sprig for the purpose of filtering studies.
To do this, follow these steps:
1. In Segment, click **Connections**, then click **Destinations**.
2. Search for “Sprig” and select the **Sprig** destination.
3. Click **Configure Sprig**.
4. Select your data source (e.g. a backend data source).
5. Enter an identifiable destination name and ensure **Classic** is selected.
6. Copy your **Segment Classic API Key** from your [Sprig Dashboard](https://app.sprig.com/integrations/enrichment/segment-classic) and paste it into the **API Key** field.
7. Turn on **Enable Destination** and save your changes.
That’s it! Your backend data sources will now beginning forwarding data into Sprig.
# Importing a CSV file
Source: https://docs.sprig.com/docs/integrations/data-sources-introduction/uploading-a-csv
The CSV Import features support:
* Bulk uploading of user attributes - useful when targeting study respondents.
* Bulk uploading of Users for creating [Manual Groups](/docs/shared-study-foundations/main-tasks/groups#creating-a-manual-group) .
#### Prerequisites
The CSV file must have a column corresponding to the User ID field that can be seen on a visitor's page in the users tab. If you do not add a User ID, a random number will be generated for the User ID.
Steps to import user attributes into Sprig:
1. In the Navigation Pane, click **Users** and click **Upload CSV**.
2. Optionally, click **Download sample CSV** to download a file showing an example of the file format required by Sprig.
| user\_id | email | list\_name | Country | Plan |
| :- | :- | :- | :- | :- |
| 970340 | [lbenson@company.com](mailto:lbenson@company.com) | Email Campaign 1 | Canada | 1 |
| 971933 | [jmurray@company.com](mailto:jmurray@company.com) | Email Campaign 1 | Canada | 2 |
| 251486 | [nhall@company.com](mailto:nhall@company.com) | Email Campaign 1 | United States | 15 |
| 429211 | [pterry@company.com](mailto:pterry@company.com) | Email Campaign 2 | United States | 20 |
| 346380 | [sshelton@company.com](mailto:sshelton@company.com) | Email Campaign 2 | United States | 1 |
*Example CSV File*
If you used the example CSV file to start with, don't forget to change the column headers to match your attribute labels.
3. Once you have created your CSV, drag the file to the target or click **Browse files**.
4. After you have selected the file to upload, you will be asked to choose which columns should be mapped to *user\_id*.
5. Then click **Continue to Upload**. If you want to add the user to a group, select **Add users to Group after uploading**. For more details on uploading a CSV file to a group click [here](/docs/shared-study-foundations/main-tasks/groups#add-from-csv).
When respondents' User IDs are the same as existing User IDs, new data will be added to that visitor's page in the users tab. Existing attribute values will be overwritten.
If the respondent's User ID is unique (it does not match an existing User ID), a new visitor will be created. Email is **not** classified as a unique identifier; multiple visitors can share the same email attribute.
6. When it has been completed, Click **Users** to confirm that the new users have been uploaded.
7. Click the Browser **Reload** button (this causes the attributes to be loaded into the Sprig UI).
# Sprig AI Agents Overview
Source: https://docs.sprig.com/docs/native-ai/ai-analysis
Sprig transforms manual survey workflows with a system powered by research agents, enabling enterprise teams to move from question to defensible insight without compromising rigor.
Traditional survey platforms rely on manual configuration, static forms, and post-hoc reporting. Sprig introduces a modern survey system where specialized agents support study design, deployment, fielding, and synthesis while preserving research standards.
### [Design Agent](/docs/native-ai/design-agent/index)
Move from research goal to launch-ready study in minutes. Sprig’s Design Agent helps teams draft, validate, and refine complex surveys while maintaining full methodological control.
* Build survey drafts from natural language prompts
* Upload survey drafts and let AI build, configure, and draft your study for you
### [Field Agent](/docs/native-ai/field-agent/index)
Sprig’s Field Agent helps you reach the right participants at the right moment and create a survey experience that feels thoughtful, relevant, and easy to complete. The result is higher response rates, higher respondent satisfaction, and higher quality answers.
* Use AI to ask strategic follow-up questions to increase response quality
* Use AI to ask dynamic questions of users to fill in any gaps in survey responses
### [Synthesize Agent](/docs/native-ai/synthesize-agent/index)
Synthesize Agent transforms structured and open-ended responses into clear, evidence-backed research narratives. Not dashboards or keyword clouds. Real analysis you can defend.
* Reduce manual analysis with automated open-text analysis
* Turn experience data into actionable insights with AI Insights and AI Explorer
* Accelerate insight sharing with custom AI Study Reports aligned with your research goals
### Sprig's Native AI is available across all Sprig products:
| Sprig AI | In-Product Surveys | Surveys | Feedback | Replays | Heatmaps |
| :- | :- | :- | :- | :- | :- |
| Agent Context | ✅ | ✅ | ✅ | | ✅ |
| AI Prompt Builder | ✅ | ✅ | ✅ | | |
| AI File Upload Builder | ✅ | ✅ | ✅ | | |
| AI Follow Ups | ✅ | ✅ | ✅ | | |
| AI Dynamic Questions | ✅ | ✅ | ✅ | | |
| AI Study Reports | ✅ | ✅ | ✅ | | |
| Open Text Analysis (OTA) | ✅ | ✅ | ✅ | | |
| AI Insights | ✅ | ✅ | ✅ | | |
| Study Summaries | | | | | ✅ |
| Replay Themes | | | | ✅ (Web only) | |
| AI Explorer | ✅ | ✅ | ✅ | ✅ | ✅ |
### AI Security
AI Analysis is powered by OpenAI’s GPT large language models. You can see OpenAI’s privacy policy [here](https://openai.com/policies/api-data-usage-policies).
Sprig sends replay clip data and survey responses to OpenAI’s GPT model to generate insights, themes, summaries and replay groupings.
Sprig does not train models using customer or user data.
Note that Sprig has established the Zero Data Retention (ZDR) agreement with OpenAI. This means that neither our data nor our customers’ data will be stored in OpenAI’s system or used to train OpenAI models.
# Conjoint
Source: https://docs.sprig.com/docs/native-ai/conjoint
*Fit a discrete-choice model from survey responses, rank what drives decisions, and convert results into dollar willingness-to-pay by feature and segment. This example has been tested and validated with Claude.*
You need a defensible dollar figure attached to a specific feature (not just a popularity ranking) or you're pricing a product with several moving parts. Conjoint analysis shows what people actually trade off when choosing between whole configurations, which a preference survey can't.
This guide covers **choice-based conjoint (CBC)**, the variant most survey platforms default to. Two other flavors exist — adaptive conjoint and menu-based conjoint — but are not covered here.
For the full walkthrough, including a side-by-side comparison of plain vs. engineered attempts, the exact bugs that replicated across two independent runs, and worked WTP numbers by segment, see the [full conjoint analysis guide](https://sprig.com/guides/conjoint-analysis-claude).
## Prompt
Replace the bracketed placeholders with your own attribute names, filename, and threshold. Every column name must match your file's literal header row, not a spreadsheet column letter.
```text expandable lines theme={null}
I have a choice-based conjoint (CBC) dataset. I want to fit a
discrete-choice model, rank what drives decisions, calculate dollar
willingness-to-pay by feature, and break results out by segment.
What this prompt does:
- Fits a proper conditional/multinomial logit model on your choice
tasks
- Converts utility differences into dollar willingness-to-pay for
each attribute level, with uncertainty on every figure
- Checks whether segment differences are real or within the noise
the sample size allows
What it returns:
- A ranked importance table (each attribute's utility range as a
share of total range)
- A willingness-to-pay table with confidence intervals, per attribute
and per segment
- Any segment flagged as too small to model separately
- A bar chart of dollar WTP by attribute and segment
- A 2-3 sentence summary distinguishing confirmed findings from
directional ones
Please:
1. Load the data defensively. Do not treat "None," "NA," "N/A," or
"NULL" as missing values — these are valid category labels. Verify
that every task has exactly one chosen alternative (or none_chosen
= 1), never both or neither. Report the row count before and after
loading.
2. Fit a conditional or multinomial logit model. Dummy-code every
attribute against explicit reference levels — state what each
reference level is before estimating — rather than relying on
alphabetical defaults. Model each task's concepts (plus any
"none of these" option) against each other as a choice set, not
as independent yes/no rows.
3. Calculate relative importance as each attribute's utility range
divided by the sum of all ranges, in code at full precision.
Do not rank attributes by raw coefficient size.
4. Before splitting by segment, check whether each segment has enough
respondents. Flag any segment below [N, e.g., 84] respondents as
too small to model separately; keep those respondents in the
pooled model only.
5. Confirm each price coefficient is negative and non-zero before
converting anything to willingness-to-pay. If a price coefficient
is positive or zero, stop and report it rather than proceeding.
Convert utility differences to dollars only for models that pass
this check, and attach standard errors to every figure.
6. Compare model-implied WTP to any stated-preference benchmark
using a formal significance test (gap ÷ combined standard error
≥ 1.96). Report gaps that don't clear that bar as directional,
not confirmed findings.
7. Recompute every number independently through a second, genuinely
different implementation before reporting anything final. Flag any
mismatch rather than silently correcting it.
8. Present an importance table and a WTP table with uncertainty on
every figure and any under-sized segment flagged explicitly.
9. Build a grouped bar chart of dollar WTP by attribute and segment.
10. Summarize in 2-3 sentences, explicit about which segment
differences the sample size and standard errors actually support.
```
## Setup
**Code execution must be enabled** for step 4's verification to run. It's on by default for Team and Enterprise accounts. Free, Pro, and Max users: enable it under **Settings > Capabilities**.
If your survey data lives in Sprig, skip the export, the [Sprig MCP](/docs/native-ai/sprig-mcp) connects live surveys and responses directly into Claude so the analysis runs on current data.
## How it works
Checks that "None," "NA," and similar strings aren't silently read as missing values, a default CSV behavior that dropped a third of a 600-respondent dataset in plain-prompt testing. Reports row count before and after to surface any loss.
Fits a conditional/multinomial logit model with explicit, stated reference levels rather than alphabetical defaults. Models each choice task's options against each other as a set ( not as independent yes/no rows) and includes any "none of these" option.
Calculates each attribute's importance as its utility range ÷ total range, in code at full precision. Raw coefficient size is never used for ranking. In plain-prompt testing, skipping this step ranked price (the biggest real driver of choice) dead last.
Calculates the minimum respondent floor for your design before running any segment model. Segments below the floor are flagged, excluded from their own estimate, and kept only in the pooled model.
Confirms the price coefficient is negative and non-zero before converting anything to dollars. A positive price coefficient means the model is misspecified; the prompt stops and reports it rather than continuing.
If your survey includes a stated-preference calibration question, the prompt compares model-implied WTP to what respondents said they'd pay and tests whether the gap is real. Results that don't clear the bar (gap ÷ combined SE ≥ 1.96) are reported as directional.
Every number is recomputed through a genuinely different implementation before it's reported. Any mismatch is flagged rather than silently corrected.
A verified importance table, a WTP table with confidence intervals, a grouped bar chart by attribute and segment, and a 2–3 sentence summary that separates confirmed findings from directional ones.
A verified importance table, a WTP table with confidence intervals, a grouped bar chart by attribute and segment, and a 2–3 sentence summary that separates confirmed findings from directional ones.
A verified importance table, a WTP table with confidence intervals, a grouped bar chart by attribute and segment, and a 2–3 sentence summary that separates confirmed findings from directional ones.
## Things to check before trusting any conjoint output
* **Assume alphabetical reference levels until proven otherwise.** Both `pandas.get_dummies` and `statsmodels`' formula interface default to alphabetical order with no warning. The same backwards reference levels appeared in two independently-written plain-prompt attempts.
* **Verify your row count after loading.** If it's lower than expected, a valid category label was probably read as missing. Check what the default CSV reader did with "None" or "NA" in your columns.
* **A negative price coefficient is a prerequisite, not an assumption.** If price came out positive or near zero, the model isn't usable for WTP conversion, the prompt requires this check before proceeding.
* **Check segment n before splitting.** More segments on a fixed sample means smaller cells and wider intervals. Flag and exclude any segment below your design floor rather than reporting a noisy estimate as a finding.
# Create Surveys with MCP
Source: https://docs.sprig.com/docs/native-ai/create-surveys-with-mcp
## Overview
Use Sprig MCP and Design Agent to draft studies directly from Claude, ChatGPT, or any connected AI client. Describe what you want to learn and let your AI client build the study for you. You can then ask the AI client to create it within Sprig.
## How it works
When Sprig MCP is connected, your AI client can call Sprig's study creation tools on your behalf. You describe your research goal in plain language. The AI drafts the study, configures the settings, and after you prompt it creates it in Sprig as a draft ready for your review.
You stay in control. No study is launched from the AI client. It is always done via the Sprig UI.
## Before you start
* Sprig MCP must be connected in your AI client. See [Connect Sprig via MCP](https://sprig.mintlify.app/docs/native-ai/sprig-mcp) for setup instructions.
* You need Editor or Admin access in your Sprig workspace to create studies.
* Studies created via MCP are saved as drafts. You review and launch from the Sprig UI.
You may need to disconnect and reconnect your Sprig MCP Connector to use new features such as the survey creation endpoint.
## Create a study
### Step 1: Describe your research goal
Open your connected AI client and tell it what you want to learn. You do not need to write questions yourself describe the goal and let the AI handle the structure.
**Example prompts:**
**Basic study**
> "Create a Sprig study to understand why users are dropping off during onboarding. Use a 5-question format with a mix of rating scales and open text."
**NPS study**
> "Create an NPS study in Sprig for users who completed their first purchase. Include the standard NPS question and two follow-up questions asking for the reason behind their score."
**Feature feedback**
> "Create a Sprig study to collect feedback on our new dashboard redesign. Target users who have logged in at least three times in the last 30 days."
**Post-cancellation**
> "Create a short exit survey in Sprig for users who just cancelled their subscription. Keep it under three questions and focus on the primary reason for leaving."
### Step 2: Review the draft in Sprig
Once the AI creates the study, it will appear as a draft in your Sprig workspace.
1. Go to **Sprig → Studies** and open the draft.
2. Review the questions, settings, audience targeting, and delivery channel.
3. Make any edits directly in the Sprig study editor.
4. When ready, click **Launch** to field the study.
> Studies created via MCP are always saved as drafts first. Your AI client cannot launch a study without your explicit action in the Sprig UI.
### Step 3: Iterate with your AI client
If the draft needs changes, you can ask your AI client to create another study and recreate it in Sprig. The current study cannot be modified at this time.
## Prompt tips
* **Be specific about your audience** The more context you give, the better the study. Include user segment, product area, and any behavioral context (e.g. "users who signed up in the last 7 days").
* **Name the study type** If you have a specific format in mind: NPS, CSAT, usability, feature feedback. The AI will apply the right structure automatically.
* **Set a question limit** Shorter studies get higher completion rates. Ask for a maximum number of questions upfront: "Keep it to five questions or fewer."
* **Ask for a bias check** Before reviewing the draft in Sprig, ask your AI client to audit the questions first:
## What gets created
When your AI client creates a study via MCP, the following are set automatically:
| Field | What the AI sets |
| :- | :- |
| Study title | Based on your research goal description |
| Questions | Generated from your prompt, following Sprig's question formats |
| Question types | Rating scales, open text, multiple choice as appropriate |
| Response options | Options as needed for each question |
| Status | Draft always requires manual launch from Sprig UI |
Audience targeting, delivery channel, and advanced settings are best configured in the Sprig study editor after the draft is created.
## Frequently asked questions
* **Can my AI client launch a study without me reviewing it?** No. All studies created via MCP are saved as drafts. Launching requires a manual action from you in the Sprig UI. This is by design.
* **Can I create studies in bulk?** No. It is one by one for now.
* **What question types are supported?** All standard Sprig question types are supported: rating scales, NPS, open text, multiple choice, and ranking.
* **Can I use a template?** No. This is only based on the prompt you entered in the AI client.
* **Who can see drafts created via MCP?** All workspace members with access to your Sprig workspace can see the drafts created via MCP.
* **Will I know a study was created with MCP?** Yes the Design Agent chain-of-thought will indicate if a study was generated using MCP.
## Troubleshooting
* **Study did not appear in Sprig** Check that Sprig MCP is connected and authorized in your AI client. Go to Settings → Agents → Sprig MCP to verify the connection status.
* **AI created the study but questions look off** Open the draft in Sprig and edit directly, or ask your AI client to revise before reviewing.
* **Permission denied when creating a study** You need Editor or Admin access in Sprig to create studies via MCP. Ask your workspace admin to update your role.
***
Need help? Contact [support@sprig.com](mailto:support@sprig.com) or visit our [developer docs](https://sprig.mintlify.app/docs/native-ai/sprig-mcp).
# Cross Tab Analysis Across Segments
Source: https://docs.sprig.com/docs/native-ai/cross-tab-analysis-across-segments
*Break a survey metric down by segment and verify the numbers before reporting them. This example has been tested and validated with Claude.*
* A stakeholder asks whether a result holds for a specific segment.
* A metric needs comparison across plan tiers or company sizes.
* A topline number feels like it's hiding something once you consider who's behind it.
This prompt handles rating-scale, yes/no, and other categorical outcomes. For open-ended responses that need to be themed first, see the [advanced cross-tab guide](/docs/native-ai/cross-tab-analysis-1).
For a detailed walkthrough of plain vs. engineered prompts on the same dataset, including a side-by-side comparison of where a plain prompt silently under-reports by 7–17 percentage points, see the [full cross-tab guide](https://sprig.com/guides/cross-tab-analysis-with-claude-simple).
## Prompt
Replace \[OUTCOME VARIABLE], \[SEGMENT VARIABLE(S)], and \[N] with your own column names and threshold.
```text expandable lines theme={null}
I have a survey dataset with a categorical or rating-scale outcome
question and one or more segment/attribute variables (for example,
plan tier, company size, department, or customer segment). I want to
run a cross-tab analysis.
What this prompt does:
- Compares [OUTCOME VARIABLE] across the segments you specify
- Checks whether any segment has enough respondents to draw a real
conclusion from
What it returns:
- A table of counts and percentages (or means, for rating-scale
questions), broken out by segment
- A list of any segment comparisons that don't have enough data to trust
- A plain-language summary of the differences worth paying attention to
- A saved image of the table you can download and reuse
Please:
1. Cross-tab [OUTCOME VARIABLE] against [SEGMENT VARIABLE(S)]. These are
column headers from your data file, exactly as they appear in the
header row, like `plan_tier` or `nps_score`. They are not spreadsheet
cell references or column letters, like "C" or "G2". For a
categorical outcome, show counts and row percentages. For a
rating-scale or numeric outcome, show the mean and the full
distribution across scale points.
2. Use code to calculate this, not estimation. Exclude any missing,
blank, or non-response values from the calculations rather than
treating them as zero.
3. Flag any cross-tab cell with fewer than [N, e.g., 10] respondents. A
cell with ZERO respondents also counts as under the threshold, not
just small nonzero counts. Report the total flagged as a single
number computed directly from the full table, not calculated in
parts and combined.
4. Before giving me the final answer, recompute every number you're
about to report directly from the underlying table one more time,
using a genuinely different method than you used the first time,
for example a manual count instead of a formula-based one. Simply
re-running the same calculation again doesn't count as a check.
Correct anything that doesn't match rather than keeping your
first-draft number.
5. Summarize 2-3 patterns, and be explicit about which differences look
meaningful versus likely noise given sample size. Don't overstate
findings from a small dataset.
6. Save the table itself as an image file I can download, formatted so
it's easy to read at a glance.
```
## Setup
**Code execution must be enabled** for step 4's verification to run. It's on by default for Team and Enterprise accounts. Free, Pro, and Max users: enable it under **Settings > Capabilities**.
If your survey data lives in Sprig, skip the export, the [Sprig MCP](/docs/native-ai/sprig-mcp) connects live surveys and responses directly into Claude so the analysis runs on current data.
## How it works
Compares your outcome variable across each segment. Rating-scale outcomes return a mean and full distribution. Categorical outcomes return counts and row percentages.
Missing, blank, and non-response values, including markers like "SKIPPED”, are dropped before any calculation runs. This is explicit in the prompt, not left to default handling.
Any segment cell below your threshold (e.g., 10 respondents) is flagged, including cells with zero respondents. The total flagged count is computed from the full table at once, not assembled from parts.
Every number is recomputed using a genuinely different method before it's reported. Re-running the same calculation doesn't qualify as a check.
2–3 patterns, with explicit notes on which differences are meaningful versus likely noise given the sample size.
The final table is saved as a downloadable image, formatted for quick reading.
## Verify your own results
The built-in checks catch a lot, but spot-check before you publish or present:
* **Do group sizes add up?** Sum the segment counts and compare to your full dataset.
* **Does at least one number match a manual check?** Run a filter or pivot table on one percentage or mean.
* **Are any segments very small?** Treat anything reported for them as unreliable, even if not explicitly flagged.
A calculation that runs without an error isn't the same as one that's correct. Ask explicitly what should and shouldn't be excluded, don't rely on an absence of errors as confirmation.
# Cross Tab Analysis Across Themes
Source: https://docs.sprig.com/docs/native-ai/cross-tab-analysis-across-themes
*Sort open-ended responses into themes, then break those themes down by segment. This example has been tested and validated with Claude.*
* Your question has no pre-built answer to compare- open text like "what's stopping you from doing X" or "what do you wish we'd build next" has to be read and sorted into categories before it can be cross-tabbed.
* If you already have a rating, tier, or other existing attribute, use the attribute-based cross-tab prompt instead, it's faster and involves fewer judgment calls.
For the full walkthrough, including a worked example on a 300-response synthetic dataset and a side-by-side comparison with the attribute-based version, see the [full themed cross-tab guide.](https://sprig.com/guides/cross-tab-analysis-with-claude-advanced)
## Prompt
Replace `[OPEN-ENDED QUESTION COLUMN]`, `[LIST YOUR SEGMENT VARIABLES]`, and `[N]` with your own column names and threshold.
```text expandable lines theme={null}
I have a survey dataset with open-ended text responses and demographic
or segment/attribute variables. I want to run a themed cross-tab
analysis on [OPEN-ENDED QUESTION COLUMN].
What this prompt does:
- Reads open-ended responses and sorts them into a manageable set of
recurring themes
- Cross-tabs those themes against the segments you specify, and checks
whether any segment has enough responses to draw a real conclusion
from
What it returns:
- A list of themes with example quotes, so you can check the coding
before trusting it
- A table of theme counts and percentages, broken out by segment
- A list of any segment comparisons that don't have enough data to trust
- A plain-language summary of the differences worth paying attention to
- A saved image of the table you can download and reuse
Please:
1. Read all non-blank responses in [OPEN-ENDED QUESTION COLUMN] and
identify the 5-8 recurring themes that best capture the range of
answers. This is a column header from your data file, exactly as it
appears in the header row, like `biggest_barrier` or
`open_feedback`, not a spreadsheet cell reference or column letter.
Use an "Other/unclear" bucket rather than forcing every response
into a theme.
2. For each theme, give me 2-3 example quotes or paraphrases so I can
sanity-check the coding, plus the exact count and percentage of
responses in that theme, excluding blanks.
3. Assign each response to its single best-fitting theme as a new
column. Use code, not estimation, to do the counting.
4. Cross-tab the theme variable against these segment variables:
[LIST YOUR SEGMENT VARIABLES, e.g., plan tier, company size, usage
frequency]. These are also column headers from your data file, not
spreadsheet cell references. Show counts and row percentages for
each.
5. Flag any cross-tab cell with fewer than [N, e.g., 10] respondents. A
cell with ZERO respondents also counts as under the threshold, not
just small nonzero counts. Report the total flagged as a single
number computed directly from the full table, not calculated in
parts and combined.
6. Before giving me the final answer, recompute every number you're
about to report directly from the underlying table one more time,
using a genuinely different method than you used the first time, for
example a manual count instead of a formula-based one. Simply
re-running the same calculation again doesn't count as a check.
Correct anything that doesn't match rather than keeping your
first-draft number.
7. Summarize 2-3 patterns, and be explicit about which differences look
meaningful versus likely noise given sample size. Don't overstate
findings from a small dataset.
8. Save the table itself as an image file I can download, formatted so
it's easy to read at a glance.
```
## Setup
**Code execution must be enabled** for step 4's verification to run. It's on by default for Team and Enterprise accounts. Free, Pro, and Max users: enable it under **Settings > Capabilities**.
If your survey data lives in Sprig, skip the export, the [Sprig MCP](/docs/native-ai/sprig-mcp) connects live surveys and responses directly into Claude so the analysis runs on current data.
## How it works
Reads all non-blank responses and identifies 5–8 recurring themes. Responses that don't clearly fit go into an "Other/unclear" bucket rather than being forced into a theme.
Returns 2–3 example quotes per theme so you can verify the coding before trusting the counts. If a theme groups things you'd keep separate, check the quotes, tell Claude the split you want, and ask it to recode.
Assigns each response to exactly one best-fitting theme as a new column. Uses code to count, not estimation.
Cross-tabs the theme variable against your segment variables. Returns counts and row percentages for each cell.
Any cell below your threshold (e.g., 10 respondents) is flagged, including cells with zero respondents. The total flagged is computed from the full table at once, not assembled from separate counts. *More themes × more segments = more flagged cells. That's your sample size talking, not a failure of the method.*
Every number is recomputed using a genuinely different method before it's reported. This step caught a specific error in testing: cells with exactly zero respondents were counted separately and then dropped from the flagged total. The prompt now requires a single count computed directly from the full table, and an independent recompute to catch this before it reaches you.
2–3 patterns, with explicit notes on which differences are meaningful versus likely noise given the sample size.
The final table is saved as a downloadable image, formatted for quick reading.
## Customize for your dataset
| **Setting** | **Default** | **When to adjust** |
| :- | :- | :- |
| Number of themes (step 1) | 5–8 | Fewer for small datasets; up to 10–12 for long, varied response sets |
| Thin-cell threshold (step 5) | 10 respondents | Drop to 5 for a pilot study; raise to 20–30 for large-scale surveys |
## Verify your own results
* **Do theme counts sum correctly?** Total coded responses should equal your non-blank count.
* **Spot-check at least one cell.** Manually filter one segment and compare its theme breakdown to what was reported.
* **Treat flagged cells as unreliable.** Even if a number looks clean, don't act on it if the cell was flagged.
The verification steps in the prompt (steps 5–6) catch a lot, but they're a safety net, not a guarantee. Spot-check before you publish or present.
# AI File Upload Builder
Source: https://docs.sprig.com/docs/native-ai/design-agent/ai-file-upload-builder
Create Surveys in Minutes, Not Hours. Upload any survey document and let Sprig's AI instantly build a polished survey complete with question logic, skip rules, and confidence scoring.
## **How it Works**
* The AI builder analyzes your research objectives, proposes study approaches, and assembles the full survey with skip logic, mandatory questions, and randomized responses while showing you its reasoning every step of the way.
* Upload your survey document: Drag and drop a PDF, Word doc (up to 25 MB). AI analyzes your content
* Watch in real time as Sprig extracts your research goals and suggests study types
* Review your survey draft: A fully structured survey appears in the builder, pre-loaded with questions, mandatory flags, skip logic, display logic and randomized response options.
* Add AI Follow-Ups or AI Dynamic Questions
* Refine and launch: Edit any question, update the study goal, add AI follow-ups, then launch: all in the same workflow.
## **Why it Matters?**
* Stop starting from scratch: upload any doc and get a complete survey in under 2 minutes
* Best practices, built in to bring over skip logic, and other setup options as specified in your file/document
Available on all enterprise plans.
### Using the AI File Upload Builder
1. Navigate to **+** **New Study**
2. Select **Upload Survey Draft**
3. A modal will open, allowing you to upload your .pdf or .docx file for upload. Simply drag+ drop your file into the modal or browse for your file, and select from there.
1. Here, you can download a sample file, which outlines the file requirements, boundaries, and more.
4. Sprig's AI will:
1. Process your file
2. Select your study type (Survey OR In-Product Survey, which can be changed)
3. Generate your study questions and response options
4. Set:
1. Required/ Optional questions
2. Randomization
3. Skip Logic
4. Display Logic
5. Validate the survey, present the final draft, and present a Design Agent audit log documenting each step
## How to Structure Your Questions for Perfect Import into Sprig
To ensure the design agent can properly build your survey draft, keep the following formatting rules in mind.
* **\[Multiple Choice - Single]** - Choose one answer
* List response options with bullet points or dashes.
* Specify response randomization inline
* **\[Multiple Choice - Multi]** - Choose all that apply, with answer limits respected during import.
* List response options with bullet points or dashes
* Specify response randomization inline
* Specify selection limits for multi-select questions (e.g., "select up to 3") inline
* **\[Rating Scale]** - Rate on a scale (1-5, 1-10, etc.)
* **\[NPS]** - Net Promoter Score (0-10)
* **\[Rank Order]** - Rank items by preference
* **\[Matrix]** - Rate multiple items on the same scale
* Specify accordion mode inline
* **\[Open Text]** - Free text response
* **\[Text/ URL]** - Add messaging for survey respondents, or redirect users to an external link directly within a question (such a webpage, Sprig link survey, etc.)
* **\[Voice & Voice]** - Respondents answer by speaking on camera
* **\[AI Dynamic Question]** - Sprig generates the question in real time based on prior responses
* **\[Consent / Legal]** - Capture respondent consent or legal acknowledgment
* Specify inline whether to collect name
* Specify custom button label inline
**Also Supported:** AI-Follow ups
**Not yet supported via AI File Upload:** MaxDiff questions and adding prototype links to questions. These must be added manually in the survey builder after import.
*More coming soon!*
**Struggling with formatting?** Download a sample file in Sprig to use as reference when editing.
* Navigate to **New Study - Download Sample File**
### File Header
* Enter your study **title, goals, or objectives** at the top of the document.
* Sprig will bring this in as a draft of the [Agent Context](https://docs.sprig.com/docs/native-ai/synthesize-agent/agent-context) for the study.
* **Study type detection.**
* Sprig respects the intent of your document. Specify "In-Product Survey" or "IPS" anywhere in the file to have Sprig build the study as an IPS by default.
* If no study type is specified, Sprig will generate both an In-Product Survey and a Survey (LFS) variant from a single upload so you can choose which to use.
### Questions
* Each question must end with a question mark (?).
* Number your questions clearly (1., 2., 3., etc.).
* Indicate **question type** in \[brackets] if you want to specify the [question type](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/questions) (e.g., \[Open Text], \[Rating Scale], etc.).
* Add **mandatory** notes using the `REQUIRED:` prefix to indicate required questions for respondents.
* Add **AI Follow-Ups** notes inline, for Sprig to ask an intelligent follow-up based on what the respondent says to a certain question
### Logic
* Add **skip logic** notes next to questions using the `SKIP LOGIC:` prefix.
* Add **display logic** notes using the `DISPLAY LOGIC:` prefix to show a question only when a condition is met.
* Add **randomization** notes using the `RANDOMIZE:` prefix.
### Pages
**Note:** using multiple questions on a single page is optional. If no page delegations are set, Sprig will simply show 1 question per page.
* To add **multiple questions to a single page (MQSP)**, clearly mark the **beginning** and **end** of the page with page numbers.
* Example: `[Page 1 Start — Onboarding Experience]` … `[Page 1 End]`
* You may also include an optional page name
* Sprig uses pages to denote sections within a survey
* **Note: the following question types cannot be placed inside MQSP pages:**
* Consent/Legal, Text/URL Prompt, and Video/Voice
* Prototype links
# AI Translations
Source: https://docs.sprig.com/docs/native-ai/design-agent/ai-translations
Add a language. Sprig Design Agent translates your entire survey instantly, every question, choice, and button label, ready to review and launch in seconds.
Teams running global research know which languages they need. The slow part is everything in between: exporting translation files, routing them to translators or localization teams, waiting days for the file to come back, then uploading and checking every field.
**How AI Translation Works**
AI Translations runs directly inside the Study Builder, and you stay in control at every step:
* Detects every translatable field in your study: questions, descriptions, choices, and button labels.
* Generates translations for each language you select, all at once.
* Displays translations inline so you can review them side by side with the original (e.g. English).
* Edit any translation directly, your changes are saved.
* Regenerate anytime if you update your survey questions.
* ***Note***\*: regenerating creates new AI translations for every question and field, so any edits you've made to existing translations will be **lost**.\*
**Using AI Translations**
1. Build your survey in your default language.
2. Select **Add language** in the Language card at the bottom of the Questions tab.
3. Choose your language(s) from the dropdown menu.
4. Press **Translate with AI**. Sprig generates translations for every translatable field across all selected languages.
5. Review the translations inline and edit any field as needed. Then set your language targeting, preview, and launch.
**Recommendation**
Always generate translations after your survey is finalized. This way all questions get translated and there are no leftover questions or responses.
# Design Agent
Source: https://docs.sprig.com/docs/native-ai/design-agent/index
Strong research starts with strong design. The Design Agent helps teams move quickly while preserving the standards that protect data quality and organizational credibility.
### Sprig's Design Agent allows you to:
* Translate a plain language into a structured study, with [Sprig's AI Prompt Builder](/docs/native-ai/design-agent/prompt-based-builder)
* Ingest a research brief or survey document and let Sprig AI build your survey draft for you, with Sprig's [AI powered File Upload Builder](/docs/native-ai/design-agent/ai-file-upload-builder)
* Generate AI translations so studies can run across multiple languages, seamlessly *(coming soon!)*
# Prompt Based Builder
Source: https://docs.sprig.com/docs/native-ai/design-agent/prompt-based-builder
Type one prompt. The Design Agent builds a complete, research-grade survey - right question types, right order, ready to launch in under two minutes.
Teams know what they want to learn. The slow part is everything in between: picking question types, phrasing them well, ordering them so people don't drop off, then iterating.
## **How it Works**
The Design Agent runs in four visible stages, and you can intervene at any point:
* Understands your prompt: audience, behavior, survey goal.
* Assigns the right format: survey, in-product survey
* Generates the full set of questions, mixing types for signal.
* Edit it directly within the Study Builder
* It is ready to review, and launch.
## Using the prompt based builder
1. Navigate to **+** **New Study**
2. Select **Create with AI**
3. The Design Agent will open, allowing you to input your prompt. Simply type in or copy+ paste your prompt and select **Generate Study Ideas.**
4. Sprig's AI will generate 3 sample studies for your review. Simply click through the examples, select your study starting point, and continue modifying the survey as needed! The survey created will be fully customizable, just like if you used a template or started from scratch.
Prompts are limited to 5000 characters at this time.
# AI Dynamic Questions
Source: https://docs.sprig.com/docs/native-ai/field-agent/ai-dynamic-questions
AI Dynamic Questions, powered by the Field Agent, automatically generate intelligent open-ended questions based on respondent input, so every survey adapts in real time without manual logic.
## How it works
* **For the study designer**: Insert an AI Dynamic Question anywhere in your study following an open text, rating, or multiple choice question.
* You can optionally provide a custom prompt to guide each question.
* The system always respects skip logic and quotas.
* There is no limit on AI dynamic questions that can be added to any study
* **For the user**: The AI generates a concise, neutral question in your study’s primary language. If it can’t generate safely or quickly, the question is skipped.
* Moderation filters are active to block PII, bias, and unsafe content.
* **For the analyzer**: AI-generated questions and their corresponding responses are available in the Reports tab. They appear alongside your standard results, ready to review individually or together.
#### Best Practice
Start with one or two AI Dynamic Questions per survey to gain depth without adding respondent fatigue.
## Why it matters
* **Dynamic probing**: Enables deep questioning based on all prior responses and context signals.
* **Reduced Setup Time**: Eliminates the need for complex branching logic needed, since the AI handles dynamic questioning automatically.
* **Faster analysis:** AI responses are grouped and displayed so researchers can quickly identify patterns & themes.
## How the questions are generated
The Field Agent utilizes a variety of signals to ensure questions remain relevant and aligned with research objectives.
* Team context (if available, *coming soon!*)
* Agent Context (if available) to stay aligned with your research objective
* All prior questions and responses in the survey
* Question prompt (if available)
* NLP signals such as:
* intent (e.g. pricing, bugs, feature requests, churn risk, compliments),
* sentiment,
* topics (e.g. onboarding, billing, performance, UX),
* and entities (e.g. product, competitor, plan tier)
* Clarification: Resolve ambiguity or vague answers
* Depth: Probe for reasons, mechanisms, or examples
* Context: Compare with past experiences or alternatives
* Impact: Explore effects, severity, or frequency
* Sentiment: Acknowledge tone and ask what influenced it
* Keyword: Drill into mentioned keywords or entities
AI Dynamic Questions are available on Enterprise plans only, and can be added to In-Product Surveys, Surveys, and Feedback Studies.
## Prompt Examples
There are endless ways to configure AI Dynamic Question prompts to ensure high quality questions are asked to your respondents. A few common prompts are listed below.
You can test the AI output at any time in preview mode prior to launching your study.
1. Based on everything the respondent has shared so far, ask one question that fills the biggest gap in understanding their \[workflow, feedback, experience].
2. If the respondent has mentioned a frustration or pain point earlier in the survey, probe deeper on that. **Do not** ask about pricing or budget.
3. If the respondent's answers seem to contradict each other, ask a clarifying question to reconcile the difference. **Do not** point out the contradiction directly or make them feel called out.
4. Ask about a use case or scenario the respondent has not yet covered, given what they have shared. **Do not** ask demographic questions or anything about their job title.
5. If the respondent mentioned a competitor or alternative product earlier, ask what would make them switch fully. **Do not** ask for negative feedback about the competitor by **name**.
6. Based on the goals or outcomes the respondent described earlier in the survey, ask what success would look like for them in the next 3 months. **Do not** ask about specific metrics or numbers.
# AI Follow Ups
Source: https://docs.sprig.com/docs/native-ai/field-agent/ai-follow-ups
AI Follow-Up Questions let you dig deeper automatically by generating a follow-up open text question to an existing question, based directly on each respondent’s answer. This helps you capture richer context and clearer detail without manually programming additional probes.
Ask a smart, automatic follow-up the moment a respondent answers, so vague feedback turns into specific, actionable insight without adding researcher workload.
## Key features
* Attaches to most question types (see Supported question types below), not just open text.
* Generates a short, neutral follow-up question in your study's primary language as soon as the respondent submits their answer.
* Skips automatically if a safe and relevant question cannot be generated quickly, protecting survey quality.
* Runs alongside skip logic on the same parent question (new in this release). You no longer have to choose one or the other.
## Supported question types
Enable AI follow-ups on:
* Open text
* Rating scale (number, smiley, and star)
* Multiple choice, single select
* Multiple choice, multi-select
* NPS
* Matrix
* Rank order
Not available for: Video/voice, Recorded task, Legal consent, Text/URL prompt, and MaxDiff.
## Why use AI follow-up questions?
* Probe for clarity, examples, and root causes so you capture the "why" behind a response, not just the rating or selection.
* Mimic a live interviewer at scale, improving response quality without adding researcher workload.
## How to use
1. In the study builder, open any supported question and turn on the AI Follow-Up toggle.
2. (Optional) Add a prompt to guide the AI output.
3. The AI generates a single follow-up focused on clarification, impact, sentiment, or depth.
To generate a relevant question, the AI draws on:
* Agent Context (if provided): keeps the follow-up aligned with your research objectives.
* The respondent's prior questions and answers: broadens contextual understanding.
* Signals from the response itself: intent, sentiment, topics, and entities.
* Your prompt inputs (if applied).
Test the AI output any time in preview mode before launching your study.
## Using skip logic with AI follow-up
You can now enable skip logic on a parent question that also has an AI follow-up turned on.
Skip logic runs after the parent question. If a response matches a rule, the AI follow-up is skipped and the respondent routes to the designated question (or the survey ends). For example: when the parent answer is "Not applicable," skip the follow-up entirely; when it is a specific value, route to a designated question or end the survey.
When AI follow-up is available for a question type, the skip logic tooltip calls out this behavior. The AI Follow-Up tooltip is unchanged.
## Results
View both the AI-generated probe and the respondent's answer in the Results tab.
### **Best Practice**
Use 1–2 AI Follow-Up questions per survey to balance deeper insights with respondent experience.
### Prompt Examples
There are endless ways to configure AI-Follow Up prompts to ensure high quality questions are asked to your respondents. A few common prompts are listed below.
Note that you can test the AI output at any time in preview mode prior to launching your study.
1. Ask the respondent to share a specific example that illustrates their previous answer.
2. If the previous answer was vague or short (for example, "it's fine" or "good"), ask what specifically makes them feel that way.
3. If the respondent expressed frustration or a negative sentiment, ask what would have made the experience better. **Do not** ask them to rate the severity on a scale.
4. Ask why the respondent chose that answer, but do not ask them to compare it to competitors or other products.
### **CSV File Export**
The AI Follow-ups feature stores follow-up prompts and responses that were generated by AI for a respondent’s original answers. The CSV format for bulk export/import of AI follow-ups
* Q1a\_Question\_Text
* Q1a\_Response
* Q1b\_AI\_Followup\_Question\_Text
* Q1b\_Response
The Q1a/b refers to the parent question and response. Q2 a/b refers to the child question and response.
### **API Endpoint Updates**
**/responses endpoint:**
The only difference is the addition of parentQuestionId
```text expandable lines theme={null}
{
"visitorId": 0,
"surveyId": 31064,
"questionId": 241190,
"updatedAt": "2026-01-29T18:14:18.167Z",
"createdAt": "2026-01-29T18:14:18.167Z",
"responseGroupUid": "d9bb8e7f-a0c5-4844-bf2f-01c6a14993fb",
"response": "payments was confusing",
"questionText": "can you clarify your response?",
"parentQuestionId": 241188,
"externalUserId": "",
"partnerAnonymousId": "",
"visitorUuid": "dfe1361a-0055-40f7-ab50-0e2bda8a6f06",
"questionType": "AIDYNAMICFOLLOWUP"
},
```
**/surveys endpoint:**
The only addition is parentId, and of course the type now can also include AIDYNAMICFOLLOWUP
```text expandable lines theme={null}
{
"id": 242496,
"type": "AIDYNAMICFOLLOWUP",
"order": 2,
"options": [],
"parentId": 242495,
"questionText": "Dynamic follow-up placeholder",
"routingOptions": [],
"optionsProperties": {
"required": false,
"conceptUrl": null
}
}
```
**/themes endpoint**
No change
# Field Agent
Source: https://docs.sprig.com/docs/native-ai/field-agent/index
Many surveys lose participants because they feel long, impersonal, or disconnected from context. The Field Agent is built to reduce friction and make participation feel more natural, all while ensuring high-quality experience data capture.
Sprig's Field Agent can:
* Generate [AI-powered follow-up](/docs/native-ai/field-agent/ai-follow-ups) questions aligned to your research goal, to assure high quality data collection- every time.
* Harness [AI-powered Dynamic questions](/docs/native-ai/field-agent/ai-dynamic-questions) to use AI as a moderator in surveys for richer data collection at scale
# Gabor Granger
Source: https://docs.sprig.com/docs/native-ai/gabor-granger
*Build a demand curve from survey responses, calculate a revenue-optimizing price, and verify it before calling it an answer. This example has been tested and validated with Claude.*
You have a short list of candidate prices and want to know how each one performs. Gabor-Granger answers "which of these specific numbers should we charge"- not "what would people pay for something like this in general." It's a single-product read that doesn't model competitor pricing, and it works best when respondents already understand what they're paying for.
**Note on survey design:**
This prompt handles both fixed-sequence surveys (every respondent sees every price) and branching surveys (respondents are routed up or down based on their answer). Steps 1–2 normalize either shape of data into the same clean table; everything from step 3 on is identical either way.
For the full walkthrough, including a side-by-side comparison of two plain-prompt attempts that each produced different wrong prices, the demand curve output, and notes on how Gabor-Granger compares to Van Westendorp, see the [full Gabor-Granger guide](https://sprig.com/guides/gabor-granger-analysis-claude).
## Prompt
Replace the bracketed placeholders with your own column names, price list, and threshold.
```text expandable lines theme={null}
I have a Gabor-Granger pricing survey dataset. I want to build a
demand curve, calculate a revenue index at each price point, and
identify the revenue-optimizing price with confidence intervals.
What this prompt does:
- Turns purchase-intent answers into a cumulative demand curve and
revenue index at each tested price
- Checks whether the top price is statistically distinguishable from
its closest rival before calling it a winner
What it returns:
- A verified table: price, n, % willing to pay, 95% CI, flagged/not,
revenue index, 95% CI on the index
- A demand curve and revenue index chart with error bars
- A plain-language summary distinguishing what the data supports from
what's simply the highest point estimate
Please:
1. If a pre-coded outcome column exists, verify it against the raw
answer columns before using it and show the check. For branching
surveys, reconstruct cumulative willingness-to-pay from the raw
columns rather than trusting the coded field alone.
2. For fixed-sequence surveys: check monotonicity (a respondent who
says yes to a higher price and no to a lower one). Report the
fraction of inconsistent respondents, then run steps 3-8 twice —
excluding and including them — and report whether the conclusion
changes. For branching surveys, skip this step.
3. For each tested price, calculate the percentage of respondents
willing to pay at least that price using cumulative logic: a
respondent whose price ceiling is $249 is also counted as willing
at $99. Use code, not estimation.
4. Flag any price point backed by fewer than [N, e.g., 30] respondents
as too few to trust. A zero base counts as too few, not just small
nonzero counts.
5. Add a 95% confidence interval around each percentage that clears
the minimum sample threshold.
6. Calculate a revenue index (price × full-precision % willing) at
each price, carrying the confidence interval through. Round only
at display time, not during calculation.
7. Identify the price with the highest revenue index. Check whether
its confidence interval overlaps the next-highest price's interval.
If it does, report a leading candidate, not a settled answer.
8. Recompute every number independently using a genuinely different
method or code path. Flag any mismatch rather than silently
correcting it.
9. Present the verified numbers as a table: price, n, % willing,
95% CI, flagged/not, revenue index, 95% CI on the index.
10. Plot the demand curve and revenue index with error bars, built
only from the table in step 9.
11. Summarize in 2-3 sentences. Distinguish what the data actually
supports from what is simply the highest point estimate.
```
## Setup
**Code execution must be enabled** for step 4's verification to run. It's on by default for Team and Enterprise accounts. Free, Pro, and Max users: enable it under **Settings > Capabilities**.
If your survey data lives in Sprig, skip the export, the [Sprig MCP](/docs/native-ai/sprig-mcp) connects live surveys and responses directly into Claude so the analysis runs on current data.
## How it works
If a pre-coded price column exists, the prompt checks it against the raw answer columns before using it. Branching surveys reconstruct cumulative willingness-to-pay from raw columns rather than trusting a derived field.
Fixed-sequence surveys can produce a contradiction branching ones can't: a respondent who says yes to a higher price and no to a lower one. The prompt reports how many do this, then runs the analysis both ways- with and without those respondents- and tells you whether the conclusion changes.
Calculates % willing to pay *at least* each price using cumulative logic. A respondent whose ceiling is \$249 is counted as willing at \$99, \$149, and \$199 too. Skipping this step is what caused two wrong prices (\$149 and \$249) in plain-prompt testing on identical data.
Any price backed by fewer than your threshold (e.g., 30 respondents) is flagged. Zero counts as too few, not just small nonzero counts.
Every percentage and revenue index (price × % willing) gets a 95% confidence interval. Rounding happens only at display time to avoid compounding errors.
Every percentage and revenue index (price × % willing) gets a 95% confidence interval. Rounding happens only at display time to avoid compounding errors.
Identifies the highest revenue index, then checks whether its confidence interval overlaps the next-highest price's. If it does, both are reported as viable, not a single winner. In testing on a 300-response synthetic dataset, \$99 was the leading candidate with \$149 flagged as statistically tied.
Every number is recomputed using a genuinely different method before it's reported.
A verified table and a demand curve + revenue index chart with error bars, both built from the same verified numbers.
A verified table and a demand curve + revenue index chart with error bars, both built from the same verified numbers.
2–3 sentences that separate what the data supports from what's simply the highest point estimate.
## Verify your own results
* **Demand should decline monotonically.** A curve that rises between two price points is a signal something went wrong in the cumulative calculation- check before acting on any individual number.
* **State each column's population.** Confirm whether a yes-rate was calculated against the full sample or a branching-created subset. A wrong denominator is a real error, not a rounding issue.
* **Check whether the top two prices are actually separate.** Overlapping confidence intervals mean the data can't pick between them. Don't force a single winner from a statistical tie.
# MaxDiff
Source: https://docs.sprig.com/docs/native-ai/maxdiff
*Rank a long list of features or messages from best-worst picks, with bootstrapped confidence intervals and an optional anchor check to separate what wins head-to-head from what's actually essential. This example has been tested and validated with Claude.*
You have more candidate items than a rating scale can responsibly compare, and you need a ranking built from real trade-offs rather than generous scores. MaxDiff is purely relative- it tells you what beat what, not whether anything matters much on its own. Add the anchor question (step 6) if that distinction matters for your decision.
**Versions of this Prompt**
* **Base MaxDiff**: steps 1, 2, 3, 5, 7, 8, 9, 10. Complete analysis on its own.
* **Anchored MaxDiff**: add step 6 to compare relative ranking against absolute importance ratings and flag hygiene factors and false differentiators.
* **Segmented**: add step 4 to either version.
For the full walkthrough, including a side-by-side comparison of two plain-prompt attempts that each caught only one of two anchor mismatches (for two unrelated reasons), the z-score false-positive problem in detail, and all 12-item results, see the [full MaxDiff guide](https://sprig.com/guides/maxdiff-analysis-claude).
## Prompt
Fill in the setup block with your study details, then send the full prompt as written. Every column name must match your file's literal header row.
```text expandable lines theme={null}
I have best-worst (MaxDiff) survey data on [PRODUCT/SERVICE/CATEGORY].
The items tested were: [LIST YOUR ITEMS]
Each respondent saw [K] items per screen, across [J] screens, with each
item appearing [approximately how many] times total. [DESCRIBE HOW THE
DESIGN WAS GENERATED.]
The data is in [DESCRIBE FORMAT]. Columns are: [LIST YOUR COLUMNS —
use actual header strings, not question labels like "Q7"].
[IF ANCHORED: I also asked respondents to independently classify each
item as "must-have," "nice-to-have," or "not important." Compare
relative MaxDiff importance against this absolute measure, separating
real differentiators (high on both) from hygiene factors (low relative
rank, high absolute rate) and false differentiators (high relative
rank, low absolute rate).]
[IF SEGMENTING: I also want to compare results across [SEGMENT VARIABLE].]
Please:
1. Load the data defensively. Do not treat "None," "NA," or "NULL" as
missing values — these may be valid category labels. Verify that
every task shows exactly [K] items with exactly one "best" and one
"worst," and that the two are never the same item. Confirm every
item appears the expected number of times. Stop and flag any
failures rather than modeling around them.
2. Fit a sequential best-worst logit: "best" as a conditional logit
over the items shown; "worst" as a conditional logit over the
remaining items with utilities negated, after removing the chosen
"best." State explicitly which item is the reference (utility fixed
at 0) — do not let a tool's alphabetical default pick it. Report
fitted utilities with standard errors, confirm none are degenerate,
check the gradient at the solution, and confirm a different starting
point lands in the same place.
3. Calculate each item's preference share as exp(utility) ÷ sum of
exp(utility) across all items, as a percentage summing to 100%.
Confirm this is unchanged if you refit with a different reference
item — if it changes, that is a coding error to fix before
continuing. Do this in code at full precision, rounding only for
final display.
4. [SEGMENTING ONLY] Before splitting, check the sample size in each
segment. Flag any segment under [N, e.g., 30] respondents —
including zero — as too small to model separately; keep those
respondents in the overall model from step 2. Refit steps 2-3 for
every segment that clears the threshold.
5. Resample respondents with replacement and recompute steps 2-3 (and
step 4 if segmenting) from scratch on each resample, at least
[N, e.g., 1,000] times. Report a bootstrapped confidence interval
for each item's preference share (and anchor rate, if anchored).
6. [ANCHORED ONLY] Using the same bootstrap replicates from step 5:
In each replicate, rank items by preference share and separately
by anchor (must-have) rate. Use rank position, not a z-score —
preference share is more right-skewed than a plain rate, so
z-scoring and subtracting compares magnitude of standing, not
order. Calculate each item's divergence score as preference-share
rank minus anchor-rate rank, averaged across all replicates.
Sort items by |mean divergence|. Find the largest gap between
consecutive values and set the threshold at its midpoint; divide
that gap by the median of the other gaps and require it to clear
3x. Flag an item only if both hold: its confidence interval
excludes zero AND its divergence magnitude clears the threshold.
State the direction: worse preference rank + better anchor rank =
hygiene factor; the reverse = false differentiator.
7. Before finalizing, recompute every number through a second,
genuinely different implementation — not the same code path run
twice. Use both absolute and relative tolerance together
(|a − b| ≤ atol + rtol × |b|) to judge matches. If a number
doesn't match, report both values, the likely cause, and which
you trust. For bootstrap distributions, verify a random subsample
of at least 10 resamples rather than the full set, and say plainly
it's a subsample check.
8. Present a results table: item, preference share (% with CI),
anchor rate (% with CI, if anchored), divergence score with CI
(if anchored), and any flag from step 6.
9. Build a horizontal bar chart sorted by preference share, with a
second bar for anchor rate if anchored, and flagged items labeled
directly. Build it only from the step 8 table — do not recompute
for the chart.
10. Summarize in 2-3 sentences. Be explicit about what the data
actually supports versus what is directional but not something
to act on with confidence.
```
## Setup
**Code execution must be enabled** for step 4's verification to run. It's on by default for Team and Enterprise accounts. Free, Pro, and Max users: enable it under **Settings > Capabilities**.
If your survey data lives in Sprig, skip the export, the [Sprig MCP](/docs/native-ai/sprig-mcp) connects live surveys and responses directly into Claude so the analysis runs on current data.
## How it works
Checks that category labels like "None" or "NA" aren't silently read as missing values. Verifies every task has exactly one best and one worst pick, and that they're never the same item.
Fits "best" and "worst" picks as a single choice model rather than counting picks independently, using all the information in each task. Reference levels are stated explicitly before estimation — not left to alphabetical default. Convergence is verified from a second starting point.
Converts fitted utilities to a preference share that sums to 100%, at full precision. Confirms the share is stable under a different reference item, if it shifts, that's a coding error to fix before continuing.
Checks respondent counts before splitting. Flags any segment below your threshold, keeps them in the pooled model, and only refits for segments that clear the bar.
Resamples at the respondent level and refits the full model on each resample. Returns a CI for every preference share (and anchor rate, if anchored). In plain-prompt testing, two independent attempts produced correct rankings but no uncertainty on any reported number.
Compares relative ranking against absolute must-have rates using rank position, not a z-score. (Preference share is more skewed than a plain rate; z-scoring both and subtracting compares how extreme a number looks, not how it ranks, an early pass on the test dataset flagged six of twelve items as mismatched before this fix was applied.) An item is flagged only if its CI excludes zero *and* its divergence clears the magnitude threshold. Direction is stated: hygiene factor vs. false differentiator.
Every number is recomputed through a genuinely different implementation. Bootstrap distributions are spot-checked across a random subsample of resamples rather than fully re-run, with that caveat stated explicitly in the output.
A verified results table, a bar chart built only from that table, and a 2–3 sentence summary that separates confirmed findings from directional ones.
A verified results table, a bar chart built only from that table, and a 2–3 sentence summary that separates confirmed findings from directional ones.
A verified results table, a bar chart built only from that table, and a 2–3 sentence summary that separates confirmed findings from directional ones.
## Things to check before trusting MaxDiff output
* **State your reference item.** If you don't, the tool will pick one alphabetically, and backwards reference levels will silently flip utility signs. Confirm the reference is what you intended.
* **Pair relative ranking with an anchor question when it matters.** A list of 12 mediocre features produces a confident ranking just as easily as 12 genuinely important ones. Relative rank alone can't tell the difference.
* **Don't use a z-score to compare two differently-shaped measures.** Preference share from a choice model is skewed; a must-have rate usually isn't. Rank position is the right unit of comparison.
* **A CI excluding zero is not the same as a gap worth reporting.** At a few hundred respondents, nearly any consistent difference clears that bar. Pair it with a magnitude check.
* **Check convergence yourself.** Verify gradient norm at the solution and confirm a second starting point lands in the same place. A solver can flag a correct answer as unresolved just as easily as it can wave through a bad one.
# MCP Prompt Examples
Source: https://docs.sprig.com/docs/native-ai/mcp-prompt-examples
What you can do with Sprig MCP
## Prompt Examples
Try these prompts in any connected AI client once Sprig MCP is set up.
1. **Summarize a study** *Summarize the key themes from my most recent Sprig study and highlight the top 3 issues users mentioned.*
2. **Extract NPS insights** *Pull all NPS studies from Sprig in the last 30 days. What are the most common reasons users gave for low scores?*
3. **Compare studies over time** *Compare the results from my Q1 and Q2 onboarding surveys in Sprig. What changed?*
4. **Segment analysis** *From my latest Sprig study, show me how responses differ between power users and new users.*
5. **Feature feedback digest** *Pull all Sprig responses that mention \[feature name] and summarize what users are asking for.*
6. **Draft a research summary doc** *Using my latest Sprig study results, write a one-page research summary I can share with my team.*
7. **Turn feedback into hypotheses** *Based on the open-text responses in my latest Sprig study, generate 5 product hypotheses I could test next.*
8. **Prioritize from feedback** *From my Sprig study on checkout experience, rank the top pain points by frequency and suggest which to fix first.*
9. **Prep for a research readout** *Using my Sprig study results, create a bullet-point readout I can present in a 10-minute team meeting*
10. **Look up by Study ID or Study Title**
## MCP to MCP: connecting Sprig with other tools
When both Sprig and another tool are connected to the same AI client, you can run workflows that span both, pulling data from Sprig and acting on it in another system automatically.
**Note:** MCP to MCP workflows require both Sprig and the destination tool to be connected in the same AI client. Check that both connections are active before running these prompts.
1. **Sprig + Linear** *Summarize the top 5 pain points from my latest Sprig study and create a Linear issue for each one, assigned to the product team.*
2. **Sprig + Jira** *Pull negative responses from my Sprig checkout study and create Jira tickets with the user quotes as description text.*
3. **Sprig + Notion** *Fetch my latest Sprig study results and write a research summary into my Notion research repository page.*
4. **Sprig + Figma** *Pull the top usability issues from my Sprig study on the onboarding flow and add them as comments on the relevant Figma frames.*
5. **Sprig + Slack** *Every time a Sprig study gets more than 50 responses, post a summary of the top themes to the #product-research Slack channel.*
6. **Sprig + HubSpot** *Find all Sprig respondents who gave an NPS score below 6 and update their HubSpot contact record with a 'detractor' tag.*
7. **Sprig + Salesforce** *Pull Sprig survey responses from enterprise-tier users and log the key feedback as activity notes on their Salesforce account records.*
8. **Sprig + Google Sheets** *Export all responses from my latest Sprig study into a new Google Sheet, with one row per response and columns for question, answer, and segment.*
9. **Sprig + Confluence** *Pull my last 3 Sprig studies and write a quarterly research digest page in Confluence summarizing key findings across all three.*
10. **Sprig + GitHub** *From my Sprig developer experience study, extract bug reports and usability issues and create GitHub issues with appropriate labels.*
# MCP Security
Source: https://docs.sprig.com/docs/native-ai/mcp-security
# **Sprig MCP: Answering All Your Questions about Data Security**
Sprig MCP is designed so an AI client sees only the survey data your Sprig role already permits, scoped by OAuth and enforced at every tool call. Agents can create studies in draft only, users approve before anything reaches respondents, and admins hold an org-wide kill switch. Unlike a CSV export, MCP leaves no permanent, unscoped copy of your data.
## **Data Handling and Retention**
### **1. What happens to Sprig data inside the LLM conversation? Is it retained or used for training?**
When your team prompts Sprig through MCP, the returned data becomes part of that conversation on the LLM provider's side. MCP introduces no new data exposure category beyond what your organization already accepted by adopting the LLM tool. Sprig does not store copies with the provider and does not control the provider's retention.
* In transit, tool calls run over TLS between the client and [mcp.sprig.com](http://mcp.sprig.com).
* In context, the data lives inside the conversation for its duration.
* After the conversation, retention, training treatment, and provider-side access are governed by your organization's agreement with the LLM provider, not by Sprig.
### **2. Does Sprig or the LLM provider train models on our response data?**
Sprig does not use your response data to train models. Data returned through MCP is subject to your LLM provider's own data handling terms, so enterprise customers should confirm their Claude, OpenAI, Gemini or Copilot agreement excludes training on API and connector traffic, which enterprise plans typically do.
### **3. How is MCP different from exporting a CSV and uploading it to an LLM?**
A CSV export is a permanent, unscoped copy; MCP is scoped, live access with no lasting copy. Once a CSV is downloaded, it sits outside Sprig's permission model: anyone with the file can share it, upload it anywhere, and retain it indefinitely, with no way for you to revoke it. MCP inverts that. Data is fetched at prompt time, scoped to what the authenticated user is allowed to see, and access ends the moment an admin revokes the token or disables the server. A CSV upload is a one-time transfer with zero ongoing control; MCP is live access with your controls intact.
## **Access and Permissions**
Sprig MCP lets AI clients, like Claude, ChatGPT, and Cursor, query your Sprig research data with no standing copy leaving Sprig. Access is scoped by OAuth to your existing Sprig role and enforced on every request. Agents draft studies but never launch them, admins can cut off all access instantly, and Sprig never trains on your responses.
* Permissions are checked at every tool call, not once at connection time.
* Agents create studies in draft state only.
* Admins can revoke all MCP connections org-wide, instantly, from one setting.
* Data returned into an LLM conversation follows your provider agreement, meaning enterprise plans from Anthropic, OpenAI, and Microsoft exclude it from model training.
### **4. What data can an LLM client access through Sprig MCP?**
An LLM client can access aggregated and derived research data through Sprig MCP: surveys, responses, open-text themes, and response counts. It reaches this data at prompt time and only within the scope the authenticated user is allowed to see. The client does not receive a bulk export or a standing copy of your workspace.
### **5. How is access authenticated and controlled?**
Every Sprig MCP connection runs through OAuth. Users authenticate with their own Sprig credentials, and the MCP server enforces the same role-based permissions as the Sprig app. A user cannot see data through Claude, ChatGPT, or Cursor that they could not see logged into Sprig directly. Because authorization is tied to the individual user's role, access reflects your existing Sprig permission model rather than a separate one.
### **6. How do LLM clients handle Sprig permissions on their side?**
The LLM client never holds standing access to your Sprig workspace. It holds an OAuth token tied to one user, and every tool call is authorized against that user's Sprig permissions at request time. If a change is made to a user's role or their token is revoked, then the client's access changes with it. Admins on enterprise LLM plans also control which connectors are available to their org at all, adding a second permission layer on top of Sprig's.
## **Agent Actions and Control**
### **7. Can an AI agent launch or modify live studies through MCP?**
No. Sprig MCP exposes study creation in draft state only. A human reviews and approves every study in the Sprig app before it reaches respondents. MCP-created drafts are indicated as such, so your team can identify their origin during review. An agent cannot push a study live, change a running study, or reach respondents on its own.
### **8. What happens if we need to shut off access immediately?**
Admins can turn the MCP server off from Integrations, AI & MCP in Sprig. This kill switch revokes all active connections org-wide, immediately, without waiting on individual users to disconnect their clients. It gives security and IT teams a single control to cut off all MCP access at once.
Connect your workspace to Sprig MCP- instructions [here](/docs/native-ai/sprig-mcp).
# Sprig MCP: How to Connect
Source: https://docs.sprig.com/docs/native-ai/sprig-mcp
## Connect Sprig via MCP
Use the Sprig MCP server to connect your survey data directly to AI tools- no manual exports needed. Your studies, responses, segments, and Agent Context become available as live context wherever you work.
**Before you start, ensure you have the following:**
1. A Sprig account with at least one study
2. Admin access to enable MCP
3. One of the supported AI clients below:
* Claude.ai
* Claude Code
* Claude Cowork
* ChatGPT
* OpenAI Codex
* Google Gemini CLI
* Microsoft GitHub CoPilot
* Cursor
* Figma
* Linear
* Notion
## Step 1: Sprig Admins - Enable MCP in Sprig
1. From the Integrations tab, navigate to **AI & MCP**
2. Toggle Sprig MCP Server **ON**
3. Copy your MCP server URL: `https://mcp.sprig.com/mcp`
Only administrators have permissions to turn Sprig MCP on
## Step 2: Connect your AI client
*Team and Enterprise plans. Owner role required.*
**Claude Admin setup**
1. From the sidebar in [claude.ai](http://claude.ai), select **Customize**, then **Connectors**.
2. Click the **+** icon, then **Add Custom Connector**.
3. Give it the name "Sprig" and paste in the Sprig MCP server URL: `https://mcp.sprig.com/mcp`
4. Click **Connect** and complete the OAuth authorization flow by logging in with your Sprig account.
Members can now find Sprig under **Customize → Connectors** and connect with one click.
**End user setup**
If your admin has already added Sprig:
1. From the sidebar in [claude.ai](http://claude.ai), select **Customize**, then **Connectors**.
2. Find "Sprig" in the list and click **Connect**.
3. Complete the OAuth authorization flow by logging in with your Sprig account.
4. Try: *"Summarize the results from my last NPS study in Sprig."*
If you are setting up Sprig yourself (Free, Pro, Max plans):
1. From the sidebar in [claude.ai](http://claude.ai), select **Customize**, then **Connectors**.
2. Click the **+** icon, then **Add Custom Connector**.
3. Give it the name "Sprig" and paste in the Sprig MCP server URL: `https://mcp.sprig.com/mcp`
4. Click **Connect** and complete the OAuth authorization flow by logging in with your Sprig account.
5. Try: *"Summarize the results from my last NPS study in Sprig."*
**Tip:** Claude can now read your Sprig studies, responses, and themes, no copy/paste needed.
*Individual setup, Developers*
1. In your terminal, run `claude mcp add sprig -t http https://mcp.sprig.com/mcp` and follow the prompts.
2. Run `claude mcp list` to verify the connection. Sprig should appear, but it likely will not be connected yet.
3. Start a session to confirm the integration is live. The first time you invoke a Sprig tool, a browser window may open to complete the authorization flow. Try: *"What is the name of my most recently created study?"*
4. Once connected, try asking: *"What are the top themes from our most recent Sprig study?"*
**Tip:** Pull user research context directly into your coding sessions. Ask what users said about the feature you're building.
*For Free, Pro, and Max users (or Team/Enterprise Owners adding for their org)*
**Claude Admin Setup**
1. In the Claude Cowork desktop app, go to **Settings → Connected tools**. From the sidebar, select "Customize," then "Connectors."
2. Select **Add custom connector**. Give it a name (e.g., "Sprig") and paste in the Sprig MCP server URL: `https://mcp.sprig.com/mcp`
3. Click **Connect** to authorize the connection in a new browser tab. Once you've granted permissions, return to Claude.
Once added, individual members can enable it themselves via **Customize > Connectors**, where they'll find and connect to the Sprig connector by name.
*For non-Owner Team/Enterprise members*
**End User Setup**
1. Go to **Customize > Connectors** and click the **+** button.
2. Search for "Sprig" (or whatever your Owner named the connector) and select it.
3. Click **Connect** to authorize your individual connection.
4. Ask Cowork to pull Sprig study results into a doc, spreadsheet, or slide as part of any automated task.
**Tip:** Great for non-developers who want to automate research reporting. Cowork can pull Sprig data and write it directly into files.
*Plus, Team, and Enterprise plans. Admin role required.*
**ChatGPT Admin setup** *Team and Enterprise plans. Admin role required.*
1. Go to [chatgpt.com](http://chatgpt.com) → **Settings → Admin controls → Connectors**.
2. Click **Add connector** and paste in the Sprig MCP server URL: `https://mcp.sprig.com/mcp`
3. Give it the name "Sprig" and complete the OAuth authorization flow by logging in with your Sprig account.
Members can now find Sprig under **Apps** and connect with one click.
**End user setup**
If your admin has already added Sprig:
1. Go to [chatgpt.com](http://chatgpt.com) → **Apps → Search for Sprig**
2. Click **Connect** and follow the prompts to authorize ChatGPT to access your Sprig account
3. **Sprig** will now be available in the "**+**" menu under "**More**"
**Tip:** Sprig survey data becomes available as context in any ChatGPT conversation or custom GPT you build.
Add Sprig to ChatGPT as described above under "ChatGPT". Sprig will then be available as an app in Codex.
*End users and developers*
1. Locate `~/.gemini/settings.json` and add the Sprig server to the `mcpServers` list:
```json theme={null}
{
"mcpServers": {
"sprig": {
"httpUrl": "https://mcp.sprig.com/mcp",
"oauth": {
"enabled": true
}
}
}
}
```
2. Restart the Gemini CLI and use the following command to authenticate with the Sprig MCP:
```text theme={null}
/mcp auth sprig
```
3. In the window that opens, allow all read access and click **Authorize Gemini CLI MCP Client**
4. When successful, you will see an **Authentication Successful** screen
5. Back in the Gemini CLI, you can verify that the Sprig MCP is connected properly by running the following command:
```text theme={null}
/mcp list
```
Gemini CLI is ideal for scripting research workflows. Combine Sprig data with Google Workspace outputs like Docs and Sheets.
**Github Copilot Admin Setup**
VS Code with the **GitHub Copilot Chat** extension is required (the older GitHub Copilot extension is deprecated, use `GitHub.copilot-chat` instead). VS Code version **1.99 or later** is required.
If your organization uses a Copilot Business or Enterprise plan, an org admin must also **enable the "MCP servers in Copilot" policy** in GitHub organization settings; it is disabled by default. Admins register the Sprig MCP server once. Developers in the org get it automatically and only need to complete the OAuth flow on first use, with no JSON editing required on their end.
**Option A: Shared workspace config (recommended)** Create a `.vscode/mcp.json` file in your project root and commit it to your repo:
```text theme={null}
{
"servers": {
"sprig": {
"type": "http",
"url": "https://mcp.sprig.com/mcp"
}
}
}
```
All developers who open the project in VS Code will have Sprig available automatically.
**Option B: User-level global config**
For a personal setup that applies across all projects without modifying any repo, open the Command Palette (`Cmd/Ctrl+Shift+P`), run **"MCP: Open User Configuration"**, and add the following:
```text theme={null}
{
"servers": {
"sprig": {
"type": "http",
"url": "https://mcp.sprig.com/mcp"
}
}
}
```
**Note:** The key must be "servers", not "mcpServers" or "[github.copilot.chat](http://github.copilot.chat).mcp.servers". Using the wrong key will cause the server to silently fail to load.
Whether you use option A or Option B, each developer will see an OAuth prompt on first use and will need to login to Sprig to complete the connection.
**End User Setup**
If your admin has deployed Sprig via shared workspace config or you've set it up via user-level config, the server is registered in your VS Code. You need to start it and authorize it on first use.
1. Open your `mcp.json` file (either `.vscode/mcp.json` or your user config via the Command Palette → **"MCP: Open User Configuration"**). Look for the **Start** button that appears inline at the top of the `"servers"` block and click it. If you don't see it, try opening Copilot Chat in Agent mode first, or run **"MCP: List Servers"** from the Command Palette to start it from there.
2. Open **Copilot Chat** (`Cmd/Ctrl+Alt+I`).
3. Switch to **Agent mode** using the mode dropdown in the chat input.
Sprig tools are only accessible in Agent mode, and they will not appear in Ask or Edit mode.
4. Click the **tools icon** in the top-left of the chat box to confirm Sprig appears in the tool list.
5. Invoke a Sprig tool or ask a Sprig-related question. A browser window will open to complete the OAuth authorization flow.
6. Log in with your Sprig account and grant access.
7. Try: *"What were the general themes from my latest Sprig study?"*
**Tip:** Useful for bringing user research into your code editor. Ask Copilot to reference Sprig feedback while reviewing or writing features.
*Individual setup, Developers*
1. In Cursor, open a New Agent and run the following command to install `mcp-remote`:
```text theme={null}
install mcp-remote
```
2. Navigate to Settings → Tools & MCPs and click **Add Custom MCP**
3. In the `mcp.json` file, add the following:
```json theme={null}
{
"mcpServers": {
"sprig": {
"command": "mcp-remote",
"args": ["https://mcp.sprig.com/mcp"]
}
}
}
```
4. Open the menu in the top right and click Save File
5. In the window that opens, login to Sprig and click Authorize Gemini CLI MPC Client
6. When successful, you will see an **Authentication Successful** screen
7. Open a New Agent and try: *"List my Sprig studies"*
**Tip:** Pull user research context while writing product code. Ask Cursor what users said about a specific feature.
### Linear
**Linear Admin setup**
*Workspace admin role required.*
1. Go to **Linear → Settings → Integrations → MCP**.
2. Paste in the Sprig MCP server URL: `https://mcp.sprig.com/mcp`
3. Click **Connect** and complete the OAuth authorization flow by logging in with your Sprig account.
Members can now connect their individual accounts once the admin has enabled Sprig.
**End users**
1. Go to **Linear → Settings → Integrations → MCP**.
2. Find Sprig and click **Connect**
3. Complete the OAuth authorization flow by logging into Sprig
4. Ask Linear's AI assistant to pull feedback from Sprig when creating or triaging issues.
**Tip:** Close the loop between user feedback and product decisions. Create Linear issues directly from Sprig response themes.
**Notion Admin Setup**
1. Go to **Notion → Settings → AI → Connected tools**.
2. Click **Connect a tool** and enter your Sprig MCP server URL and API key.
3. Complete the OAuth authorization flow by logging into Sprig.
4. Member can now connect to individual accounts once the admin has enabled Sprig.
5. Use Notion AI to summarize Sprig study results directly into your research docs.
**Tip:** Ask Notion AI: *"Summarize the key themes from our latest Sprig study and add them to this page."*
*End user setup. No admin configuration required in Figma.*
Sprig is a listed MCP in the Figma Make marketplace.
1. Open **Figma Make** or **Design** and start or open a project.
2. Open a new chat (if using Design vs Make) and then click the **+ icon** in the toolbar
3. Select **Connectors**
4. Under **Featured,** find **Sprig** in the marketplace list and click **Connect**.
5. Complete the OAuth authorization flow by logging in with your Sprig account and granting app permissions
6. Sprig tools are now available in your Figma Make and Design sessions!
**Try:** *"Pull the top usability issues from my latest Sprig study and add them as annotations on the relevant frames."* or *"Find the top 3 navigation issues during onboarding and draft 3 different prototypes addressing those navigation issues"*
## What Sprig exposes via MCP
| Description | MCP Tool |
| :- | :- |
|
Retrieves study configurations. Up to 1000 at a time.
Studies were formerly surveys; survey is accepted anywhere study appears.
| `get_surveys` |
|
Retrieves responses from studies. Up to 1000 responses at a time.
| `get_responses` |
|
Retrieves themes with the responses associated with each theme.
| `get_response_themes` |
|
Creates a draft study. No study can be launched from the AI client. Launching studies can only be done via the Sprig UI.
| Works inside AI tools (no public API endpoint) |
## Troubleshooting
1. **Connection not working** Make sure you completed the OAuth authorization flow fully. Try disconnecting and reconnecting Sprig from your AI client's connector settings, then log in with your Sprig account again when prompted.
2. **No studies appearing** Make sure you have at least one published study in your workspace and that your account has access to it.
3. **OAuth window did not open** Check that your browser is not blocking pop-ups. Try opening the authorization URL manually if your client provides one.
4. **Permission denied errors** Your Sprig account may not have access to the studies you are querying. Check your workspace role with your Sprig admin.
5. **Config not recognized (Claude Code, Codex, Gemini CLI, GitHub Copilot)** Make sure the config file is saved in the correct location and the JSON is valid. Restart the client after making changes.
6. **End users not seeing the Sprig connector (Claude, Claude Cowork, ChatGPT, Linear, Notion)** The connector must be added by a workspace Owner or admin first. Ask your admin to follow the Admin setup steps for your tool above.
7. **Microsoft GitHub Copilot: Sprig not appearing after admin deployment** Make sure you are on VS Code 1.99 or later with the GitHub Copilot extension up to date. If using the workspace config option, confirm the .vscode/mcp.json file has been committed and pulled to your local repo.
**Need help?** Contact [support@sprig.com](mailto:support@sprig.com) or reach out to your dedicated customer success representatives.
# Agent Context
Source: https://docs.sprig.com/docs/native-ai/synthesize-agent/agent-context
Generate more tailored, relevant insights without data training with Agent Context.
### **Agent Context**
Note: **Agent Context** was previously called "Study Goal."
Adding an Agent Context significantly aids AI analysis by increasing priority of information that is most relevant to your current objective. Agent Context is used to inform our Field Agent and Synthesize Agent output.
* Agent Context can be added from within the study builder OR on study results pages
* Agent Context can be updated multiple times and can be updated across both in-progress and completed survey studies
* Agent Context is available on: In-Product Surveys, Surveys, Feedback, and Heatmaps
* The Agent Context has a limit of 5000 characters.
* Agent Context can be added to: align AI output toward study goals, provide terminology or feature definitions, give context on the study participant pool or respondent characteristics, and more.
**Find the AI analysis helpful or not?**
Each and every thumbs up / down you click is used to improve the model!
### **Where to find Agent Context**
1. From within the study builder, you can access, update, and modify Agent Context by navigating to the ribbon icon
2. From a study results page, you can access, update, and modify Agent Context from the Reports Tab
### **AI Study Summary**
**AI summaries are only generated for Heatmap studies**, AI summaries across In-Product Surveys, Surveys, and Feedback studies have been rolled into [AI Study Reports.](https://docs.sprig.com/docs/native-ai/synthesize-agent/ai-study-reports)
On Heatmap studies, Sprig will automatically generate study summaries:
* After a certain number of initial captures
* On an ongoing, periodic basis as the study receives more captures
* When Agent Context is added or updated
Sprig study summaries can be easily copy + pasted by clicking on the clipboard icon just above the generated study summary
# AI Product Insights & Feed
Source: https://docs.sprig.com/docs/native-ai/synthesize-agent/ai-generated-insights-feed
## Overview
The Sprig AI Product Insights Feed centralizes all of the most relevant and interesting insights from across all of your Sprig studies into a single, easy-to-navigate feed. This means that you can easily stay up-to-date on the latest user sentiment across your Sprig studies powered by AI, without having to manually review multiple reports and dashboards.
It’s super easy to get started. Just head over to your [Sprig Home Page](https://app.sprig.com/welcome) to see your insights.
There are four types of insights and artifacts that Sprig AI generates and surfaces on your home feed:
* **Opportunities**: Areas for improvement, making it easy to surface and solve your product’s pain points.
* **Strengths**: Positive product feedback to help your team tap into your strengths and build on your success.
* **Correlations**: Connections between responses within a survey.
* **Summaries**: Paragraph summary for in-progress and completed surveys highlighting key takeaways
## Using The Sprig Insights Feed
1. Create and launch a [Survey](/docs/sprig-studies/in-product-surveys/index)
2. Collect at least 30 responses
3. Check back the next day, if Sprig can generate an insight, it will show up on the insights feed and the corresponding study results page
4. Keep checking back, Sprig continues to generate insights throughout the lifespan of a survey based on new responses
5. Click into an insight to see contributing responses or the chain of thought reasoning behind an insight
Keep in mind that AI isn’t perfect and we’re actively working to improve the insights we generate for customers.
Have feedback? Submit it [here](https://a.sprig.com/U0pjVmZxLTdRUX5zaWQ6NWVhYWNlZGQtMDRjMy00OTM5LWIwZDgtZmUxMmEwMDYyNGIz)!
## FAQs
### Why am I not seeing insights generated for a particular study?
Sprig needs a certain amount of data in order to generate insights. Additionally certain studies might not be suitable for insights generation (e.g. single question surveys, complex skip logic, etc.)
* Opportunities & Strengths require at least 3 open-text responses before being insight eligible
* Correlations are dependent on survey structure, require a minimum of 50 responses, and require at least two of the following question types: Open-text, Multiple-Choice, Likert, NPS, and/or rating scale
### When are insights generated?
* Insights are computed nightly for insight-eligible studies. Insight eligible studies are those that have at least 30 responses or includes at least one of the following question types: Open Text, Multiple Choice, Rating Scale, Multiple Select, or NPS.
* Summaries are generated when new Agent Context is added or the Agent Context is changed, and periodically when a survey reaches a given number of responses (starting at 6 responses) when the survey includes at least one of the following question types: Open Text, Multiple Choice, Rating Scale, Multiple Select, or NPS.
### Are insights generated for completed studies?
* Any qualifying study should AI generated insights, as long as it was collecting responses prior to February 2024
### Why does the study card say based on many responses but the insight only has a handful of contributing responses?
* *Based on # responses* refers to the number of responses that a survey had at the time the insights were generated, not necessarily the number of contributing responses
* *# of contributing responses* refers to responses that contribute to an insight being generated. Insights are often generated with other contextual information that might not be reflected in the insights chain-of-thought-artifact
# AI Powered Open Text Analysis
Source: https://docs.sprig.com/docs/native-ai/synthesize-agent/ai-powered-open-text-analysis
## The Open-Text Analysis Problem
One of the richest sources of customer experience data is an open-text survey response. Historically this is also one of the most difficult data formats from which to extract meaningful insights, especially at scale.
When product teams run surveys with open-text questions, a common goal is to group the huge number of responses into a small number of bite-size and actionable takeaways. The identified themes are shared with product stakeholders and play a critical role in determining how to improve the product experience. An example with some responses and a summarizing theme could be:
* Response: "I'm lost, can't really find anything easily in the product."
* Response: "It'd be nice if there was a way to find users by name."
* Response: "Please add a search field."
#### Solution create a theme: “Add search functionality”
Performed manually, this analysis takes the form of:
* placing the responses into a large spreadsheet
* reading through them to locate patterns
* defining themes that represent actionable groups of responses
* assigning all responses to one or more of these themes (a.k.a. "coding").
This is a detailed process and can't scale easily beyond a few hundred responses. Automating this process is a powerful way to increase the leverage of a product team and reduce the survey life cycle from weeks to hours. The ability to do this accurately and at scale is one of the key differentiators between Sprig and other product experience insights platforms.
# Sprig Open-Text AI Analysis
Sprig Open-Text AI Analysis saves you from endless manual analysis by automatically transforming open-text survey responses into actionable product insights with the power of OpenAI's GPT large language model. AI Analysis synthesizes open-text survey feedback into product opportunities and issues with additional summary details, so you have a clear-cut picture of your users' feedback without having to review individual responses.
### How it works
1. Sprig sends responses to OpenAI’s GPT model to generate summary themes, which include a short label with description capturing the nuance of the responses.
Note that OpenAI API data is automatically deleted after 30 days and NOT used to train the Open AI models.
1. Each response is processed and categorized, making Sprig's Open-Text Analysis far more relevant and accurate than typical LLM summaries of Open-Text data
2. As new responses come in, themes are assigned in real time, and themes regenerate to account for shifts in response clusters.
1. Themes are also monitored by humans for quality assurance, and Sprig makes periodic updates to the AI, however, Sprig does not use customer or user data for any data training at any time.
3. Sprig will always cite the source of each theme, and users can click into each theme to review contributing survey responses.
1. Users can update the Agent Context to re-run the study AI analysis at any time.
2. Users can also elect to edit the theme names and descriptions by selecting "Edit" when reviewing responses, to match company language more closely.
4. Users can also elect to export the Open-Text AI Analysis in tandem with survey responses for deeper analysis, reporting, or charting outside of Sprig.
### To find the AI themes generated by the responses to your open-text questions:
In the Navigation pane, click Studies. Click on the study in question.
Click Summary, then scroll down to the open-text question response table.
All themes identified by Sprig will be shown in the table. Make sure to click on any themes of interest to review the individual open-text responses driving it.
# AI Replay Analysis (beta)
Source: https://docs.sprig.com/docs/native-ai/synthesize-agent/ai-replay-themes
# Overview
Sprig AI Replay Analysis helps you quickly understand user behavior without needing to watch every clip. Sprig AI will group clips into themes based on user behavior within the collected clips to help isolate friction points, navigational challenges, and more.
This section walks through [getting started with Sprig's Replay AI Analysis](/docs/native-ai/synthesize-agent/ai-replay-themes#getting-started) and [FAQ's](/docs/native-ai/synthesize-agent/ai-replay-themes#faqs-1).
* Sprig Replay AI requires Web SDK v2.26.2 and above in order to generate groups.
* Currently, this feature is only available for standalone Replay studies OR In-Product Survey Studies with Replay capture.
* Currently, this feature is only available for Web Replay studies.
* This feature is currently in Beta, so we welcome your [feedback](https://a.sprig.com/U0pjVmZxLTdRUX5zaWQ6NGM4ZmM4MzItMGE5Ni00NDcwLWI3ZGItZjY1YWQ3MDViYzk3) as we look to improve the feature
# Getting Started
Using Sprig AI Replay Themes is as easy as:
1. Launch a Replay Study or In-Product Survey Study with Replay Capture
2. Complete the Study
3. Check back in a few hours, and Voila!
**Sprig AI will automatically:**
* Generate Clip Groupings that you can click into to see the individual clips
* Re-generate Clip Groupings periodically as more clips are captured
* Post new AI Replay Themes to your Sprig AI Insights feed for proactive review
# FAQs
### How are Replay Themes generated?
* Sprig AI generates groups based on similar clip characteristics based on user behavior within a session
* Inputs include both code and no code Sprig events, as well as interactions with the DOM even if they aren't tracked as a Sprig event. This could be a CTA that folks interact with (e.g. the CSS styling on an HTML element) or even interacting (e.g. highlighting) certain text on the page.
* Example themes may include (but are not limited to):
* Navigational Confusion (users are flipping back and forth between two different pages)
* Pricing Page Dropoff (users are dropping off after viewing a certain page related to pricing)
* Empty Widgets (users are seeing empty widgets due to extended loading times or other issues)
### What Session Replays are eligible for AI Analysis?
* Sprig AI Replay Themes are only available for standalone Session Replays or Survey Studies with Replay Capture on Website or Web Applications.
* Sprig AI Replay Themes requires clips to have been recorded using Sprig Web SDK v2.26.2 or newer in order to generate groups
### When are Clip Groupings generated?
* Sprig AI generates groups at various milestones throughout a Replay's lifecycle. Groups are first generated after 5 clips are recorded, then at 15, 30, 50, 100, 200, 300 clips received.
# AI Study Reports
Source: https://docs.sprig.com/docs/native-ai/synthesize-agent/ai-study-reports
Go from raw responses to insights and opportunites in minutes with Sprig's Synthesize Agent.
# What is an AI Study Report?
An AI Study Report is a structured document that gives you a leg up on the time-consuming process of analyzing, summarizing, and extracting meaningful insights from raw study responses. Study Reports are created by Sprig's [Synthesize Agent](https://docs.sprig.com/update/docs/synthesize-agent) and they use the responses in the study, the [Agent Context](https://docs.sprig.com/update/docs/agent-context-summaries) provided for the study, and a consistent format based on best practices.
AI Study Reports make it easy to share insights and learnings from studies by including the following sections:
* **Executive Summary** - high-level summary of the study and what was learned
* **Research Objective** - the focus and purpose of the study (this is heavily influenced by input to the study's Agent Context)
* **Key Insights** - the main takeaways from the study
* **Opportunities** - areas to focus on in terms of next steps
AI Study Reports are available for Surveys, In-Product Surveys, and Feedback studies. **Note: report content will always be in English.**
# Generate an AI Study Report
To generate a report for a study, click the **Generate** button in the upper right corner of the "Report" tab. In order to be able to generate a report, a few criteria must be met first:
* A study must have collected at least 10 responses.
* The Agent Context for that study must be filled in.
Generation can take anywhere from a minute or two to over 10 minutes for studies with significant response volume (100,000 responses for instance). Only users with the Editor or Admin roles can generate reports. As the report generates you can review summarized responses on the Data tab (formerly called "Summary"), or the raw responses, you do not have to stay on the Report tab (or even that study) while the generation process runs.
AS long as a report was ***not*** manually generated while a study was in-progress, when the study completes a report will automatically be generated as long as the Agent Context has been filled in.
If a report had been created and edited while the study was in-progress, no automatic generation will occur.
# Edit, share, or download a report
Once a report has been generated, anyone with an Editor or Admin role can edit the report and save changes. All roles can download a report or use the share button to copy the link to the report. After saving edits the editor's name and a timestamp will be visible at the top of the report to help other people on the team understand who last worked on it.
Until a report is generated, the study will default to opening the Data tab with the question-by-question-summary of study responses.
If new responses have been collected since the report was last generated or edited, an indicator with the number of new responses since the last edit/generation will show at the top of the report.
Updating the **Agent Context** for a study or clicking the **Generate** button will cause any previous edits to an existing report to be overwritten.
# FAQs
**Which study types can I create a report for?**
AI Study Reports are available for Feedback studies, In-Product Surveys, and Surveys.
**How many responses are required before I can generate a report?**
10 responses must be collected before a report can be generated.
**What can I do with a report that was generated?**
You can edit the report directly in Sprig, download it in various formats, share the link to the report, and generally enjoy having spent less time creating shareable content!
**Do I have to stay on the page while the report generates**
No, you can work on other things in Sprig while the report generates. Once it's done the animation will be replaced by the report.
**What data is used to create a report?**
The Synthesize agent uses the Agent Context you provided before generating the report, responses to the study, AI Insights that were generated for the study, and details about the study like what platform it ran on, how many people submitted replies, and their attributes, to create the report's content. Sprig ensures that only the data from that study was used to generate the insights, opportunities, and strengths.
Any statistics created by the agent are linked back to the data for the relevant questions so you can quickly verify or dive in deeper. Hover over the link icon in the report to see what data was referenced for that insight.
**Where is all the information I used to see when opening an existing study?**
The question-by-question data visualizations are now available on the "Data" tab of a study. Nothing about these analyses has been changed.
The quick summary of the study's progress is now in the top right of the page header instead of in the Summary tab. Hover over it to see the same details that were previously available.
**Where is the Connect tab I used to set up a connection to Slack to send responses there in real-time?**
This same functionality is now available in the last icon on the right side of the study page, below the Preview and Study Details:
# Synthesize Agent
Source: https://docs.sprig.com/docs/native-ai/synthesize-agent/index
Synthesize Agent transforms structured and open-ended responses into clear, evidence-backed research narratives. Not dashboards or keyword clouds- just real analysis you can defend.
**The Synthesize Agent analyzes your full study and crafts a coherent story grounded in your data, goals, and context.**
* Interpret responses in the context of your research goals with [Sprig Agent Context and Study Summaries](/docs/native-ai/synthesize-agent/agent-context)
* Identify themes and patterns that shape the story of the study, with [Sprig AI Insights](/docs/native-ai/synthesize-agent/ai-generated-insights-feed)
* Save hours in analysis of open-text responses, with [Sprig Open-Text Analysis](/docs/native-ai/synthesize-agent/ai-powered-open-text-analysis)
* Connect qualitative feedback to quantitative signals and eases the lift to turn experience data into actionable insights, with [AI Study Reports](/docs/native-ai/synthesize-agent/ai-study-reports)
* Compare perspectives across segments and behaviors, with [Sprig AI Explorer](/docs/native-ai/synthesize-agent/ai-explorer)
* ...and ground every insight in underlying responses, with defensible, source-cited intel, every time.
# Send Sprig Data to AI Tools
Source: https://docs.sprig.com/docs/native-ai/synthesize-agent/sprig-data-to-ai-tools
# Send to AI Tools
Send your Sprig data, responses, and Study Reports straight into AI Tools (like ChatGPT, Cursor or Claude), without copying, pasting, or reformatting anything.
You already use AI tools to think through your research. Until now, getting Sprig data into them meant screenshotting charts, exporting CSVs, or pasting responses one block at a time. Send to AI Tools removes that step. Click once, pick your tool, and it opens with your Sprig content already loaded and ready to work with.
***
## What it does
Send to AI Tools packages the content you are looking at in Sprig and opens it in ChatGPT or Claude in a new tab. The content arrives as a pre-loaded prompt, so you can start asking questions immediately: "summarize the top themes," "compare this to what you'd expect for a checkout flow," "turn this into three slides for my team."
Nothing is sent automatically or in the background. Data only moves when you click the button, and only the content you are viewing at that moment.
## Where you'll find it
The **Send to AI Tools** button appears in three places:
**1. Study data** On any study's results view. Sends the aggregated results for the questions in view: response counts, breakdowns by option, scale distributions, and completion stats. If you have filters applied (by date range, audience, or attribute), only the filtered view is sent.
**2. Responses** On the responses view for open-text questions. Sends the individual responses currently in view, along with the question they answered. Filters apply here too: if you've narrowed to a segment or theme, only those responses are included.
**3. Study Reports** On any Study Report generated by the Synthesize Agent. Sends the full report: the TL;DR, findings, recommendations, and method notes. This is the fastest way to keep working with a report, whether that's pressure-testing a conclusion, drafting a stakeholder update, or combining it with data from outside Sprig.
## How to use it
1. Open the study data, responses, or Study Report you want to work with.
2. Click **Send to AI Tools**.
3. Choose **the AI tool**
4. A new tab opens in the tool you chose, with your Sprig content loaded as a prompt. Add your question and go.
## What actually gets sent, and where it goes
The content goes from your browser directly to the AI tool you chose, into your own ChatGPT or Claude account. Sprig does not send your data to OpenAI or Anthropic on your behalf, and does not store a copy of what you send. Once the content is in ChatGPT or Claude, it is governed by that tool's terms and your account settings there (for example, whether your workspace allows training on conversations).
A few things worth knowing:
* You can only send content you already have permission to see in Sprig. The button never exposes anything beyond your current view.
* If you're unsure what your organization allows, check with your admin before sending raw responses to an external tool.
## Powered by the Sprig MCP connector
Send to AI Tools runs on Sprig's MCP connector, the same secure connection that lets AI tools read Sprig data directly.
Here's what that means in practice:
* **One-time setup per tool.** The first time you send to a tool, you'll authorize the connection by signing in with your Sprig account. After that, every send is one click.
* **Read-only by design.** The connector can read your Sprig data; it cannot change or delete anything in your account.
* **Your admin holds the keys.** Admins choose which AI tools can connect to your workspace and can control access to individual responses separately from aggregated results.
For full setup instructions and the security model, see ......
## Ideas for what to ask once it's open
* "Summarize the top 3 themes in these responses and pull one representative quote for each."
* "What follow-up questions should I ask in my next study based on this data?"
* "Rewrite this Study Report as a 5-bullet Slack update for my product team."
* "Which of these findings would you challenge, and what evidence would change your mind?"
## FAQ
**Does this cost anything or require a specific plan?** No, it is included in all Enterprise plans
**Can admins turn this off?** Yes, admin can turn off the MCP connector for that specific AI tool which will remove this option.
**Is there a size limit?** Very large data sets or long response lists may exceed what the AI tool can accept in a single prompt. If that happens, send one question's data at a time.
# Attributes
Source: https://docs.sprig.com/docs/shared-study-foundations/attributes
An *Attribute* is a set of key-value pairs made up of strings, numerics, and booleans that help you get the most out of Sprig. Specifically *Attributes* provide more context about the user in order to gain a better understanding of who they are when they come to your application. Listed below are examples of attributes as a set of key-value pairs.
| **Attribute Key** | **Attribute Value** |
| :- | :- |
| Language | Spanish, English, Hindi, Arabic, Bengali, Portuguese, Russian, Chinese |
| Temperature | 23.3, 22.1, 19.0, 28.2, -9.1 |
| Day | Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday |
| Plan Type | Free, Professional, Standard, Advanced, Enterprise |
Sprig supports [categorical](https://en.wikipedia.org/wiki/Categorical_variable), [discrete](https://en.wikipedia.org/wiki/Continuous_or_discrete_variable#Discrete_variable), [continuous](https://en.wikipedia.org/wiki/Continuous_or_discrete_variable), and [ordinal](https://en.wikipedia.org/wiki/Ordinal_data) attributes. There is no limit to the number of discrete values for any given key.
Attributes cannot be deleted unless the entirety of the data for a given visitor is also deleted. This means that you must be careful when considering an update to the key-value pairs of a given Attribute. As an alternative to deleting, you may consider creating a new Attribute instead of trying to update the original Attribute.
## Purpose of Attributes
Attributes can be used to refine the target users and also filter the response data.
| | |
| :- | :- |
| [Filtering](c:study-triggers-user-filters) | Attributes, like Events, can be used in a study to target and help refine the cohort of users you wish to study. Unlike Events, Attributes cannot fire or trigger a Study; they can only Filter. |
| Study Response | Attributes can also be used as filters to drill into the study response data (once responses are collected and if at least one of the Respondents had (a) value(s) set for a given Attribute when the study was delivered the responses contain the Attribute’s values) |
## Managing Attributes
#### Installation and Setup
| | Filtering - further target a cohort of users on a given study. | Response "More Filters" - refine or view responses to the study. |
| :- | :- | :- |
| Sprig UI | Read Only | Read Only |
| Web SDK | ✅️ | ✅️ |
| Mobile SDK | ✅️ | ✅️ |
### Integrations and Connections
Sprig supports the following methods to import Attributes.
| | Filtering - further target a cohort of users on a given study. | Response "More Filters" - refine or view responses to the study. |
| :- | :- | :- |
| [Sprig SDK](/docs/Installation/introduction-web/web-javascript) | ✅️ | ✅️ |
| [CSV Import](/docs/Integrations/data-sources-introduction/uploading-a-csv) | ✅️ | ✅️ |
| [Google Tag Manager](/docs/Installation/introduction-web/web-google-tag-manager) | ✅️ | ✅️ |
| [Segment](/docs/installation/introduction-web/segment-web) | ✅️ | ✅️ |
| [Public API](/reference/sprig-api/v2/post-user-v2-1) | ✅️ | ✅️ |
### Viewing
To view the Attributes being sent to Sprig, click **Attributes** in the Navigation Pane.
The Name of the attribute is shown in the first column. This label may be generated by the attribute source; it is known as the Key. You can override the Key with a more descriptive Display Name. To change from a Key to a Display Name label:
1. Click the Attribute in question.
2. Click **Configure**.
3. Uncheck **Use Key as display name**.
4. Type in the Display Name.
5. Optionally, update the **Description** field.
6. Click **Save Changes**.
You can filter which Attributes from which Sources to display and whether to display Active or Archived Attributes. To filter Sources, click "All Sources" and check or uncheck the sources that you want to display. To filter the attribute operational state, toggle between **Active Attributes** and **Archived Attributes**.
### Inspecting and Diagnosing
1. In the Navigation Pane, click **Attributes**.
2. To learn more about how often the attribute is updating, in the Usage column, hold the pointer over the diagnostics icon in **Usage**.
3. If the diagnostics icon is grey, your attribute has not updated from your source in the last week.
4. If the diagnostics icon green, your attribute has been updated within the last week.
Attributes uploaded from a CSV file will not update the Usage column.
### Archiving and Unarchiving
Archiving an attribute stops the Attribute from updating or being tracked by Sprig.
1. In the Navigation Pane, click **Attributes**
2. Make sure the filter is **Active Attributes**.
3. Click the check box next to the Attribute and click **Archive**.
Similarly, you can **Unarchive** an archived attribute to start tracking an attribute again.
1. In the Navigation Pane, click **Attributes**
2. Make sure the filter is **Archived Attributes**.
3. Click the check box next to the Attribute and click **Unarchive**.
### Manually Uploading Attributes
1. In the Navigation Pane, click **Attributes**
2. Click **Upload CSV**. More details on the file format and steps can be found [here](/docs/Integrations/data-sources-introduction/uploading-a-csv).
3. Once the Attributes have been uploaded, you can view them under **Attributes**.
# Dashboards and Folders
Source: https://docs.sprig.com/docs/shared-study-foundations/dashboards-and-folders
## Dashboards and Folders
Sprig supports ways to help you organize your studies.
# Dashboards
Dashboards allow you to monitor and track the study results you care about. For example, you could group your studies by product owner, subject, timeframe, product line, or team.
#### Create a New Dashboard
1. In the **Navigation Pane**, click **Dashboards**.
2. Click **+ New Dashboard**.
3. Type in a Name.
4. Click **Create New Dashboard**.
#### Edit the Name of a Dashboard
1. Over the Dashboard you want to edit, click the ellipses icon and select **Edit Details**.
2. Edit the Name and click **Save**.
#### Delete a Dashboard
1. Over the Dashboard you want to delete, click the ellipses icon and select Delete.
#### Make a Dashboard a Favorite
1. Over the Dashboard you want to make a Favorite, click the star icon.
#### Add a Response Result Chart to an existing Dashboard
1. In the **Navigation Pane**, click **Studies**.
2. Click a Study.
3. In the Summary Tab, click **Pin to Dashboard** for the Response Result Chart you want to add.
4. Select the Dashboard you want to add to.
5. Click **Save Changes**.
#### Add a Response Result Chart to a new Dashboard
1. In the **Navigation Pane**, click **Studies**.
2. Click a study
3. In the Summary Tab, click **Pin to Dashboard** for the Response Result Chart you want to add.
4. Click **+ New Dashboard**.
5. Type in a Name.
6. Click **Create New Dashboard**.
#### To Remove a Response Result Chart from a Dashboard
1. Over the Response Result Chart you want to remove, click the ellipsis icon and select **Remove**.
# Folders
Folders allow you to organize your studies into categories. As with Dashboards, you could group your studies by product owner, subject, timeframe, product line, or team. When you create a study, you can choose which folder to put the study in, and, by default, the General folder is selected. Users with Admin permissions can create new folders.
#### Move a Study to an existing folder, or a New Folder:
1. Hold the pointer over the study; then click the 3-dot icon and select.
2. Choose which folder, or select to create a new folder, to move it to.
#### Delete or Rename a Folder:
1. Hold the pointer over the folder title, then click the ellipses icon and select **Delete Folder** or **Rename Folder**.
2. If you delete a Folder, all studies within that folder are moved to the General folder.
# Completing & Editing Studies
Source: https://docs.sprig.com/docs/shared-study-foundations/editing-an-active-study-completing-a-study
# Complete a Study
#### Completing a Study
1. In the Navigation Pane, click **Studies**.
2. Single-click on the study you want to complete.
3. Click **In-Progress** and select **Complete Survey**.
# Other Actions for a Completed Study
#### Re-Launching a Completed Study
1. In the Navigation Pane, click **Studies**.
2. Single-click on the completed study you want to relaunch.
3. Click **Completed** and select either **Launch Survey**.
#### Archive a Study
1. In the Navigation Pane, click **Studies**.
2. Single-click on the study you want to archive.
3. Click **In-Progress** or **Completed** (depending on the operation state of the Survey, Replay, or Feedback study).
4. Then, select **Archive Survey**.
#### Re-Launching an Archived Study
1. In the Navigation Pane, click **Studies**.
2. Use the search field to find the Study you are looking for, or click on the Folder where your study is located, making sure the Status is set to Archived.
3. Single-click on the Archived study you want to relaunch.
4. Click **Archived** and select either **Launch Survey**.
# Editing In Progress Studies
For in-product Surveys, you can edit In Progress Studies to:
1. Add questions to the Study or change the order of existing questions.
2. Edit/Add logic to existing or new questions.
3. Make edits to question/response wording.
4. Update Targeting or Response Settings
**Note:** For Feedback studies, you can additionally update the label on your feedback button.
You are not able to change a question type or delete existing options for multiple-choice type questions.
While you may change the question semantic of an In-Progress study, it is not advised as the change may impact response consistency and data cleanliness. Consider restricting edits to correct any mistakes.
# Code Events
Source: https://docs.sprig.com/docs/shared-study-foundations/events/code-events
# Code Events
Code events may only be used for Web and Mobile applications. There are two ways to add events to Sprig: create the Code Event in the Sprig app, or have your developer send an event from the SDK.
## Proactive
If you use the Sprig app to create a Code event, a code snippet is generated with the matching SDK parameter that you can give to your developer to incorporate into their code.
1. In the Navigation Pane, click **Events**.
2. Click **Add Event**.
3. Click **Create Code Event**.
4. In the **Key** field, enter the Event name. The Event name must match the same SDK parameter you are using to track the event.
5. Click **Use Key as display name** to use a different string to describe the event instead of the **Key** label.
6. In the **Description** field, enter the event description.
7. Click **Add Event**. You’ll be directed to the Events page.
8. Locate and select the Event you just created.
9. Click Configure to Toggle between **JavaScript**, **iOS**, or **Android** to see the snippet that your engineers will need, depending on which study delivery platform you’re planning to use the Event on, and share that snippet with engineering. Direct them to the [Integrations](https://app.sprig.com/integrations/installation) section of the docs for more information on that specific platform, as well as how to locate the **Environment ID**.
## Reactive
1. Once your engineering team has sent a new event to Sprig, you will need to approve the request. You should see a banner similar to the following:
1. In the Navigation Pane, click **Events**.
2. Click **Manage Requests**.
3. Click the check box next to the event(s) and click **Approve**.
4. Click **X** to close the window.
You must *Approve* of an Event Request before it can trigger a study.\
If you *Deny* an Event Request, it will be removed from the Event Request list. However, if Sprig subsequently detects that same Event Request, it will re-appear in the list.
If you do not see an Event Request for an event you expect, perform the user behavior to generate the event in your application, and then reload the **Events** page and return to **Manage Requests** to approve it.
Legacy [Events ](https://app.sprig.com/events) do not have to be *Approved*.
# Events
Source: https://docs.sprig.com/docs/shared-study-foundations/events/index
In Sprig, *Events* are used to [Trigger](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#study-triggers) a Study. They cause your Study to be displayed to the user. All Web and Mobile studies require an event as a Trigger. *Events* can also be employed as an audience [Filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy), allowing you to refine further who is eligible to respond to the Study.
An *Event* is an action or occurrence in your website or application that allows you to track your users' behavior. Examples of *Events* include:
* Visiting a page
* Clicking or interacting with a button
* Scrolling to a specific point on a page
#### How to determine what kind of event you need?
Sprig offers several different solutions on ways to deploy events in your environment. Deciding what kind of event to implement is dependent on study requirements and technological factors:
* What kind of action is it? Is it in a simple UI action like clicking a button or some higher-level concept like signing up for a new subscription? A [No-Code event](/docs/shared-study-foundations/events/no-code-events) might support simple UI action but might not support a more complex semantic.
* What platform do you intend to launch your Study? Web studies support No-Code events, but mobile studies do not. Sprig Surveys and Sharable Link Studies do not support events.
* How good are your coding skills, and do you have access to the code? You may have to rely on a developer to implement your [code event](/docs/shared-study-foundations/events/code-events), or you may have access to GTM or other integration and not depend on a developer.
* Is it an event or an attribute? For example, do you want the Study to be triggered when the visitor completes the new subscription action, or would you like it to occur at a different time and only study those customers who have recently enrolled in a new subscription?
You could use two example workflows to determine what event type you need for Web and Mobile studies.
## Where You Can Use Events
Configuring Trigger and Filtering events are supported in the Sprig Application (No-Code), the Web and Mobile SDKs, Google Tag Manager, and Segment. The API only supports events for filtering. CSV Import does not support events.
| Event Type | Trigger | Filter |
| :- | :- | :- |
| Sprig Application (No-Code) | ✅ | ✅ |
| Web SDK | ✅ | ✅ |
| Google Tag Manager | ✅ | ✅ |
| Mobile SDK | ✅ | ✅ |
| API | ❌️ | ✅ |
| Segment Actions | ✅ | ✅ |
| Segment Classic | ❌️ | ✅ |
## Adding Events
*Web* and *Mobile* studies require events to track user behavior to display studies at the appropriate moment. *Link* studies do not require events because they are delivered to respondents asynchronously. You can configure Sprig to listen for or receive events in two ways; either:
1. Using the Sprig app, or
2. Directly in the Website or App code where you launch your studies.
Events configured through the Sprig app are [No-Code](/docs/shared-study-foundations/events/no-code-events) events. Events configured in the Website or App where you want to launch your studies are [Code](/docs/shared-study-foundations/events/code-events) events.
## Editing and More Info
1. In the Navigation Pane, click **Events**.
2. Click on the Event that you want to view.
* The **Display Name** and **Description** may be changed.
* For [No-Code](https://docs.sprig.com/docs/shared-study-foundations/events/no-code-events) events, the trigger interaction can be toggled between **Page URL**, **InnerText,** and **CSS**. The **Page URL pattern** can also be edited.
* For [**Code**](/docs/shared-study-foundations/events/code-events) events, the **Key** cannot be modified as an external source generates it.
The **Display Name** updates the event label throughout Sprig; you can use it to provide a more readable label than **Key**.
## Archiving
Archiving an event stops the Event, triggering studies. Events cannot be archived when associated with an in-progress study. You will need to pause, archive, or complete the study related to that Event to archive the Event. You can unarchive a previously archived study.
Unlike pausing a Study, archiving an Event also halts the MTU count.
1. In the Navigation Pane, click **Events**
2. Make sure the filter is set to **Active Events**.
3. Click the check box next to the Event.
4. Click **Archive**.
5. Click **Archive** a second time when prompted.
## Unarchiving
Similarly, if you want to restart using an event, you can unarchive a previously archived event.
1. In the Navigation Pane, click **Events**
2. Make sure the filter is set to **Archived Events**.
3. Click the check box next to the Event.
4. Click **Unarchive**.
## Sorting
1. In the Navigation Pane, click **Events**
2. Click on the column header to sort the **Events**
3. Click on the column header a second time to reorganize the sorting order of the **Events**
## Filtering and Searching
1. In the Navigation Pane, click **Events**
2. Click **All Sources** and select the source to view.
3. Click **Active** or **Archived** to select which events to view.
If you select Web No Code Events as a source to view, if present, events from Segment Web and Google Tag Manager sources will also be included.
## Inspecting and Diagnosing
1. In the Navigation Pane, click **Events**
2. To learn more about how often the event is firing, hold the pointer over the diagnostics icon in **Usage**.
3. If the diagnostics icon is grey, your event is either not added correctly or has been turned off from your website, web application, or mobile application.
4. If the diagnostics icon is green, your event is being tracked and is available for triggering or filtering a study.
5. The following tooltip will be displayed:
If you are using other platforms, for example, [Segment](/docs/Installation/introduction-web/segment-web), they will also be displayed in the tooltip.
# No Code Event URLs
Source: https://docs.sprig.com/docs/shared-study-foundations/events/matching-page-urls
Fine control over how your studies are triggered.
A Page URL event fires when the browser views a page matching the URL that you have defined. However, you may need to refine further how an Event is triggered in your application. Sprig provides several different ways to specify how the string matches the URL that you are targeting. When you are adding or editing an event, if you click on the **URL** menu you will see:
The following table describes the functionality of each menu item:
| **Menu Item** | **Description** | **Example** |
| :- | :- | :- |
| Exactly matches | The URL must exactly match the string you entered in the **URL**field. Identical domains in URLs with different paths do not fire events. | You specify: [www.example.com.](http://www.example.com./) Only page views at [www.example.com](http://www.example.com/) trigger events. Page views at [www.example.com/signup](http://www.example.com/signup) and or example.com do not trigger events. |
| Contains | This fires an event when the user accesses a URL which includes a specific string. | You specify: example. Page views at [www.example.com](http://www.example.com/) and [www.example.com/signup](http://www.example.com/signup) trigger events. |
| Starts with | The URL must start with the string you entered in the **URL**field. | You specify: exa. Page views at example.com trigger events. Page views at [www.example.com](http://www.example.com/) do not trigger events. |
| Ends with | The URL must end with the string you entered in the **URL**field. | You specify: com. Page views at example.com trigger events. Page views at example.net do not trigger events. |
| Does not contain | This fires an event when the user accesses a URL which DOES NOT include a specific string. | You specify: net. Page views at example.com trigger events. Page views at example.net do not trigger events. |
| Does not exactly match | This fires an event when the user accesses a URL which DOES NOT exactly match the string you entered in the **URL**field. | You specify: [www.example.com.](http://www.example.com./) Page views at [www.example.net](http://www.example.net/) and example.com trigger events. Page views at [www.example.com](http://www.example.com/) do not trigger events. |
| Matches regular expression | A regular expression specifies a pattern to be matched on. The string must match the regular expression. The syntax of the regular expression is described [here](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions/Cheatsheet). Note: When using "Matches regular expression", there is a limit of 255 characters per expression. | You specify: example.com/(login\|signup) Page views at example.com/login and example.com/signup trigger events. Page views at example.com/help do not trigger events. You specify: example.com/(?!login\|signup) Page views at example.com/help trigger events. Page views at example.com/login and example.com/signup do not trigger events. |
| Matches legacy pattern | If you had been using the Page URL functionality before September 27, 2021 expressions were created with a regular expression pattern that is now referenced as **Matches legacy pattern**. While the legacy functionality will continue to be supported, we recommend you update to the latest, standardized option by editing your Page URL event and updating the event with the **Matches regular expression** option. | |
## Wildcards (\*)
Wildcards (\*) are supported for both No Code URL events created from the Events page in addition to inline URL events created from the Targeting card.
For example, exactly matching [www.example.com/\*/dashboard](http://www.example.com/*/dashboard) will include any URL that has zero or more characters in place of \*, but will not include [www.example.com](http://www.example.com)
Note: Note, if you'd like to use a literal asterisk instead of a wildcard, please select "Matches regular expression" and add a backslash before the asterisk like so: "\*"
## Testing your Matching Pattern
Once you have completed your matching pattern, enter the URL you are trying to match in the **Test Your Event** field and click **Test Match** to see if your event's URL pattern matches the URL that you want to be tracked.
## Page URL Priority
Sprig can only track a single No Code URL event per page. Sprig uses the following priority stack to determine which No Code URL event to track in the case of multiple candidate events for a particular page:
1. Exactly matches
2. Matches regular expression
3. Starts with
4. Ends with
5. Contains
6. Does not contain
7. Does not exactly match
8. Matches legacy pattern
Events used as triggers for *In Progress* studies will always trigger over events not used as a trigger in an *In Progress* study.
For overlapping events - meaning multiple events that could fire on a single page load - Sprig will record events in an equal distribution.
For more information about no-code events, [see here](/docs/shared-study-foundations/events/no-code-events).
# No Code Events
Source: https://docs.sprig.com/docs/shared-study-foundations/events/no-code-events
# No-Code Events
No-Code events provide a way to configure Sprig to trigger Web studies **without** having to edit the source code on the server. No-Code events only support deploying Web-based studies. Code Events may be used for web and Mobile studies using the appropriate SDK, API, or Integration.
**There are two main types of No-Code Events:**
* **URL Events:** Triggers when a user visits a page whose URL matches a defined pattern.
* **Interactive Events:** Triggers when a user clicks a specific element on the page, identified by a CSS selector or inner text.
**Note:** All No-Code Events require a URL match- regardless of whether the event is URL-based or interactive. This ensures Sprig knows which page the user will be on when or before the event triggers. This enables customers to create no-code events for common scenarios (for example, pressing a button that says “Finish”) while maintaining governance over exactly where on the website the no-code event should trigger (for example, if there are multiple pages on the website with buttons labeled “Finish”).
## URL Events
URL Events trigger studies such as In-Product Surveys, Feedback, Replays, and Heatmaps when a user visits a page that matches a defined URL pattern. Your Sprig SDK must be installed on the same page that you are targeting with the URL. For more information, [see here](/docs/shared-study-foundations/events/matching-page-urls).
**Note:** Some study types, like Heatmaps and Feedback, require a URL Event rather than an Interactive or Code event.
## Interactive Events
Interactive events require a user to click on a specific element on a webpage or web application. They are available for In-Product Survey and Replay web studies (alongside [Code events](/docs/shared-study-foundations/events/code-events) and URL events).
You can specify the target element using either inner text or a CSS selector.
For example, to trigger a survey when a user clicks this button:\
``
You could use either inner text or a CSS selector, depending on your use case and web architecture:
* CSS selector: `#fireButton`
* Inner text: Click Me
**Note:** the presence of the element in the DOM is not sufficient for the event to be triggered; the user must click on the element.
No-Code events are triggered when a specific condition is met (for example, when the current page URL matches a string you have defined). On page load, the system triggers the first event that matches that specific condition. If you have other No-code events with that same trigger condition, the system will not trigger those other events. For more information, [see here](https://docs.sprig.com/docs/shared-study-foundations/events/matching-page-urls).
# Adding No-Code Events:
Prerequisite: Choose a page or a button on your website or web application.
* Keep that page open as you navigate to the following steps; you will need to copy information from this page into the Sprig app. You may want to open the browser **Inspect** window if you intend to use the CSS selection method.
**There are two ways to create a No-Code Events from within the Sprig UI.** You can either:
* Configure a reusable event in the Sprig dashboard on the Events tab (Select Add Event)
* Create a reusable event during study creation in the Targeting module (Select Add Event or URL)
**For a URL Events:** you can configure the URL and matching pattern directly within the targeting module by selecting "URL".
* Note that URL events created here won’t begin tracking activity until the study is launched, and the event will appear as a “Draft URL Event” in the study details until launch.
* Once launched, a default naming convention, "URL Event 1 for Study XXXXXX" will be applied, and the event will appear in the Events tab. The event name can be renamed here and given a description as well.
**For Interactive Events:** you can configure the event from within the targeting module of the study builder by selecting "Add Event" and then "New Event" from within the event selection dropdown
When creating a new No-Code Event, a URL is crucial to ensure proper event instrumentation. Sprig supports several different ways to match URLs. For more information on page URL matching, click [here](/docs/shared-study-foundations/events/matching-page-urls).
After you have added the URL and/or Interactive element, you can add additional context to the event to help users understand how the event functions:
* **Display Name** field, to enter the Event name
* **Description** field, to enter the Event description
Finally, you can **test your no-code URL, Survey, and event activity** to ensure proper instrumentation.
1. Once you have entered the URL string in the event creation window, enter the URL you are trying to match in the **Test Your Event** field and click **Test Event** to test if the string you entered matches the URL. Then, save the event.
2. You can preview the survey behavior on your website (using the URL you just tested) by selecting ["Preview on your website"](/docs/sprig-studies/in-product-surveys/study-testing) when the study is in draft mode or launched and in progress.
#### Testing the Event Activity after Study Launch
1. In your browser, perform the user behavior to generate the event
2. Reload your browser to refresh the **Events** page contents.
3. In the **Events** page, hold the pointer over **Daily Usage**. You should see that an event has been received.
## Key Considerations
1. **Web-only:** No-Code Events support web studies only and cannot trigger mobile studies.
2. **One per page:** Sprig can track only one No-Code URL Event per page. If multiple could fire, Sprig uses priority ordering. For more information, [see here](/docs/shared-study-foundations/events/matching-page-urls).
3. **Active studies take precedence:** Events linked to active studies override events not currently used in an active study.
4. **No-code event limitations:** If there are multiple elements on the same page that cannot be distinguished from one another through either inner text or CSS, a [code event](/docs/shared-study-foundations/events/code-events) may be required.
5. **Dismiss on Page Change.** This is a product-wide setting that is important for understanding no-code event behavior:
* When enabled: The survey appears only if the user stays on the same URL that triggered the survey
* When disabled: The survey appears even if the user navigates to a different page after triggering the event
6. **Preview behavior:** No-Code Events can trigger surveys in preview mode by selecting "Preview on your website" but only if the study is a draft or actively running (ie, in-progress). Studies that are paused cannot generate live previews, even if the event is still tracking activity.
7. Inner text triggers may not work with elements inside a closed shadow DOM or dynamically rendered content.
8. URL events are treated separately from interactive element events, but event overlap may occur with multiple no-code events on a single page.
# Exporting Study Data (CSV)
Source: https://docs.sprig.com/docs/shared-study-foundations/export-survey-data
Export a CSV file with your Study data
# Overview
Draw further insights from your data by exporting a CSV file.
CSV exports will be delivered to the user who requested them through a link in an email.
**Note:** Exporting CSV files is available for Surveys, In-Product-Surveys, and Feedback studies.
# Download a CSV File
1. Open a Survey, In-Product Survey, or Feedback study
2. In the right sidebar, select Download CSV
3. Choose a Column Format:
* Response text (Recommended) - a string describing the selected choice or theme
* Numerical value (preferred by Data Scientists) - an integer describing the selected choice or theme
* Both
4. (Optional) Select a timeframe to export a specific set of responses
* CSV exports support up to 950,000 rows. The Download CSV button will be disabled when viewing surveys that have more than this number of responses. Date filters can be used to narrow the number of responses and continue with exporting the data.
5. (Optional) Include themes generated by Sprig AI for open-text question responses
6. (Optional) Include user attributes (that were used for survey targeting) alongside responses
7. (Optional) Include bot detection captcha scores for manual review
* [Bot Detection](https://docs.sprig.com/docs/sprig-studies/surveys/bot-detection#bot-detection) must be enabled for the Sprig account to see the "Include captcha scores (bot detection)" checkbox.
8. Select Download CSV - An email with a link to download the CSV will be delivered to your email inbox when the file is ready
* For surveys with a large number of responses, it could take time for the email to arrive.
* The link will expire after 1 week.
## Column Format Options
### Response Text
Below are examples of what responses to Multiple Choice Multi-Select, Multiple Choice Single-Select, and Open Text questions with Themes will look like when exporting a CSV using the Response text Column Format:
### Numerical Values
When selecting the Numerical value Column Format, Multiple Choice Multi-Select questions will have answers indicated by a 1 that corresponds to a selection or 0 if a choice was not selected. Multiple Choice Single-Select and Matrix questions will have a number corresponding to the choice selected. If the third choice is selected, for example, the cell will have a 3 in it.
Below are examples of what responses to Multiple Choice Multi-Select, Multiple Choice Single-Select, and Open Text questions with Themes will look like when exporting a CSV using the Numerical value Column Format:
**Note:** All other question types will have their data structure displayed the same, regardless of column format choice.
## File Columns
The following columns will be provided in the export:
* **surveyId**: Number
* **surveyName**: String
* **visitorId**: UUID
* **href**: String
* For Surveys: the URL used to access the study
* For In-Product Surveys and Feedback studies: the page URL on which the study appeared
* **createdAt**: Datetime
* The study response start time/date in UTC
* **completedAt**: Datetime | Nullable
* The study completion time/date, if available, in UTC
* **userId**: String | Nullable
* **partnerAnonymousId**: UUID
* **os**: String
* The client OS
* **browser**: String
* **userAgent** : String
* Information about the user's browser and client
* **captchaScore** : Number | Nullable
* When the "Include captcha scores (bot detection)" checkbox is toggled, Sprig will return a column for captcha scores
* **customMetadata**: Object
* This will be an empty Object `{}` if there is no available custom metadata
* **triggeringEvent**: String
* The event that triggered the study for In-Product Surveys and Feedback studies
* **responseGroupUid**: UUID
* **eventProperties**: Object
* This will be an empty Object `{}` if there are no available event properties
* **Q#\_Question\_Text**: Text Object
* This is the stringified output of the question text. Due to the variable nature of AI follow-up question text and piping in questions, the text shown to the user is presented in this column
* **Q#\_Response**: Response Object
* This is the stringified output of the response. The response data comes in number, string, and object data types
* **Themes**: String
* When the "Include themes" checkbox is toggled, Sprig will return columns with theme data after an Open Text question response
* **Attributes\_#**: String
* When the "Include user attributes" checkbox is toggled, Sprig will append columns for all attributes included in CSV export
# Interpreting Studies
Source: https://docs.sprig.com/docs/shared-study-foundations/interpreting-studies
Understanding your study's progress.
At the top of the results page for each In-Product Survey, Survey, Feedback, or Heatmap study you launch, Sprig provides statistics to help you understand the study's status and performance throughout its run. See the below examples:
## Study Performance Statistics
* Sprig will show you total responses, clips, and captures, and calculate the completion percentage for any studies that are not set to run continuously or until a specified date.
* The completion percentage (as applicable) shows how close you are to completing your study based on the target number of responses or captures you've set.
* Sprig will indicate the number of responses/clips/captures received in the past 24 hours.
* For In-Product Surveys, Sprig will calculate and show the response rate; which is calculated slightly differently depending on which platform you are using:
* **Web & mobile studies (In-Product Surveys)** - The response rate is calculated by dividing the number of responses received by the number of studies seen by a respondent.
* **Survey (link) studies** - Response rates are not displayed since Sprig does not track how many link studies are sent or seen.
## Key Terms
***Sent*:** The term 'sent' has different meanings depending on which platform you are using for your study:
* *Web and mobile studies* - A web or mobile study is considered 'sent' when it is scheduled to be displayed to a user who is currently active on your site or app.
***Seen*:** The term 'seen' has different meanings depending on which platform you are using for your study:
* *Web and mobile studies* - A study is considered 'seen' when displayed in a user's browser or app. Studies that are sent may not be seen if, for example, a user navigates away from a page before meeting time-on-page criteria set during study creation.
***Response/Answer*:** A 'response' is counted every time someone answers one or more questions in a study; as such, the total response count includes both users who complete the entire study and users who only complete a portion of it.
***Completed*:** A question is completed with a valid response or answer.
***Skipped by User*:** The respondent has navigated to another page but the question is not completed with a valid answer.
***Not Displayed*:** The question was not displayed to the user (usually, because of skip logic configurations)
# Add an Image to a Question
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/add-an-image-to-question
By adding an image to a question you can quickly and easily add visual context to a question, enabling you to test things like a new logo, name, visual indicator, button or other visual element without much effort.
This functionality is available for Surveys and In-Product Surveys.
## **Add an Image or Gif to a Question**
1. Navigate to a new or existing Survey or In-Product Survey.
2. Navigate to an existing question or add a new one.
1. Adding an image or gif works with all question types **except**:
1. Video & Voice
2. AI Dynamic
3. Multi-Question: Single Page
3. Click the “**Add Media**” button on the right side of the question header.
4. Follow the file type and size requirements and upload an image or gif. Add Alt Text for users who rely on screen readers.
1. Note: In files that are uploaded with spaces in their names, the spaces will be replaced with underscores.
5. Edit and preview as needed.
6. Launch the survey.
## **Disabling the Ability to Add an Image to a Question**
Since images can contain sensitive information, Admins can decide if including visuals with surveys is right for their team. To turn off the ability to add images to questions have an Admin navigate to **Settings > Surveys > Configure > Allow Images in Questions** and switch the toggle off. If images had already been added to surveys when this is done, they'll be hidden from both respondents and anyone building or reviewing surveys in the Study Builder.
## **FAQs**
* You can modify or remove images after launch.
* This functionality works with both the standard and conversation survey formats.
* To have an image or gif display in a mobile or web app survey, you will need to be on the most [current version of the SDK](https://docs.sprig.com/docs/developer-center/sprig-sdk/features-by-sdk-version).
* It is not yet possible to translate the alt text for images. Please let us know if you need this!
* Images that are rectangular or square-shaped work best. Images that are very skinny, either horizontally or vertically, can be awkward for respondents to view.
* This functionality is not compatible with the old link format In-Product Surveys.
# Backward Navigation
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/backward-navigation
Allow respondents to change their answers to prior questions in link surveys by enabling backward navigation, which results in a back button showing in the Survey.
# Overview
Backward navigation is a survey-level setting that lets respondents return to previous questions and change their answers while taking a Survey. It gives respondents a chance to correct mistakes or reconsider a response, which can improve the accuracy of the data collected.
Backward navigation is currently only supported in link Surveys. Support for In-Product Surveys will be available in October.
Backward navigation cannot be enabled for Surveys set to the Conversation format.
# Enable backward navigation
Backward navigation is off by default. To turn it on:
1. Create a new link Survey or locate an existing one
2. Switch to Edit mode
3. Go to the **Settings** tab and scroll to the **Survey Navigation** section
4. Toggle on the **Allow backward navigation** setting
The back button will appear in the preview once it refreshes.
You can enable and disable backward navigation at any time, including while a survey is live. For any respondents taking the survey while the setting is changed, unless they refresh the tab, they'll keep the experience they had in the Survey when they started it.
# How backward navigation works
## Supported question types
Backward navigation works with all question types except Voice & Video. For Conjoint and MaxDiff questions, going back takes the respondent through each task they saw for that question, one at a time. It's not possible to go back to the start of either of these question types in one click.
## What happens to answers when a respondent goes back
A respondent's previous answers are preserved as they go back to prior questions. This way they can review their responses and move forward again without re-entering everything.
If a respondent changes an answer that affects the survey's flow or question-generation, some later answers may be cleared. This happens when:
* A changed answer triggers different study logic, such as a skip or branch, such that later questions no longer apply.
* Later questions, such as AI Dynamic Questions or AI Follow-ups, depend on the changed answer, which are generated from a respondent's earlier input.
When this happens, the respondent needs to answer the affected or new questions.
## User experience changes caused by the back button
When backward navigation is enabled, some visual adjustments are made to certain questions:
* Centered forward buttons move to the right.
* Some question types normally display their forward button in the center of the content column. When the back button is present, the forward button moves to the right so the layout stays balanced.
* Questions without a forward button get one.
* Some question types, such as MaxDiff, normally don't have a forward button because selecting an answer moves the respondent forward automatically. With the back button enabled, these questions get both a back and a forward button to balance the user experience.
For questions that normally advance automatically, selecting an answer still moves the respondent forward. Because of this, the respondent may not see the forward button become active before the survey moves to the next question. This is expected behavior.
## Limitations
The back button uses the respondent's browser local storage, so respondents can only go back within a single session.
If a respondent leaves the survey and later opens the original link again, in a different tab, on different browser, or at a later time, the survey starts over. In that new session, they can only go back through answers they submitted during that session.
There will soon be a setting to allow respondents to resume a link survey. Once that's available it'll work with backward navigation such that someone can only take the survey once, using the original link they were sent, but can do so across devices or sessions.
# Frequently asked questions
**I enabled the back button, but it isn't showing in my survey.** You may need to click into the preview or to the next question before the back button appears. Please note that the back button never appears on the first question of the Survey.
**A respondent went back and some of their later answers disappeared or changed.** **Why?** If a respondent changes an answer that affects survey logic, or that later questions are based on (such as AI Dynamic Questions or AI Follow-ups), the answers that may no longer apply are cleared so the respondent can answer them again. If a respondent uses the back button to take different paths through a Survey only their last path with be recorded.
**A respondent closed the survey and came back later. Why can't they go back to their earlier answers?** For now, backward navigation only works within a single browser session. Reopening the Survey link in a new tab, a new browser, or a later session starts the survey over. Once the "resume" setting mentioned above is released, navigating back to answers given in prior sessions will be supported.
**Why does the forward button on a MaxDiff question not seem to do anything? Why is it even there?** Normally these questions advance automatically when an answer is selected so they do not have a forward button. However, when backward navigation is enabled, the forward button is shown so the user experience is consistent. To advance forward the respondent can either select their answer or the forward button if their answer is already populated.
# Carry Forward Functionality
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/carry-forward-functionality
Automatically populate a question's answer choices from a respondent's answers to an earlier question.
Carry Forward lets a question pull its answer choices directly from what a respondent selected earlier in the same survey, instead of asking them to choose from a static, author-written list. It's a quick way to build "narrow it down" flows.
For example, you can ask "Which of these amenities did you use during your stay?" followed by "Which of these would you recommend most to a future guest?" and have the selected options in the first question automatically populate as the list of available options in the second question.
Carry Forward is configured per question and works alongside your survey's other questions and logic. You can mix Carry Forward destinations with plain, self-authored questions anywhere else in the study.
# Configure Carry Forward
1. Add or open the question you want to use as the destination, or the one whose choices should be filled in automatically.
2. In the choices list, click **Add Choice**, then select **Carry forward responses**.
3. In the "Carry forward responses from..." picker, choose an earlier question to source choices from. Only eligible questions are listed (see Source requirements below).
4. If the destination already has its own choices, you'll be asked to confirm the replacement. Confirming Carry Forward replaces the destination's existing choice list. Canceling leaves the question untouched.
5. Save your changes, and the carried choices appear as read-only rows, in the same order as the source question, labeled with the question they came from.
To remove Carry Forward from a question, simply click the trash can icon next to the "Carry forward choices" in the destination question, and the question will revert to a normal, editable choice list (with at least two empty slots to fill in).
# Source Question Requirements
A question can be a Carry Forward source if it's a:
* [Multi-Select](#multiple-choice-multi-select), with a selection amount other than exactly 1. (A Multi-Select capped at 1 selection behaves like Single-Select and isn't offered as a source.)
* [Matrix](#matrix-/-accordion), you'll also need to choose at least one column value to define which respondent selections get carried (for example, "carry rows where the respondent chose Excellent").
[Multiple Choice Single-Select](#multiple-choice-single-select), [Open Text](#open-text), [NPS](#net-promoter-score), and [Rank Order](#rank-order) questions can't be used as sources.
A source question must also:
* Come **before** the destination in the survey.
* Not share a **page** with the destination. Carry Forward can't connect two questions on the same page.
* Not itself be a Carry Forward destination, **chaining isn't supported**.
* Be able to supply **at least 2 carriable choices**. "None of the above" doesn't count toward that minimum, and a selection-amount cap on the source lowers how many of its choices can ever be carried.
A display limit (randomized subset shown to respondents) on the source question isn't factored into the 2-choice minimum; only the source's total choice count and its selection-amount cap are.
# Destination Question Behavior
Multiple Choice Multi-Select, Multiple Choice Single-Select, Rank Order, and Matrix questions can all be Carry Forward destinations.
* Carried choices render read-only, in source order, each labeled with the question they came from. You can't edit a carried choice's label directly, but you can edit it on the source question, and the change propagates to every destination that carries from it.
* A destination can't also use a display limit ("show N options" / randomized subset). Carry Forward and display limit are mutually exclusive on the same question. Turning one on prompts you to replace the other.
* On a Matrix destination, carried content lands on rows; columns stay fully author-controlled.
# Guardrails
Because a destination depends on its source, the Survey builder blocks or warns on edits that would break the pairing:
* **Reordering** - dragging the destination above its source, the source below its destination, or either question onto the same page as the other, triggers a warning before the move goes through. Confirming cleans up the Carry Forward configuration rather than leaving it dangling.
* **Deleting the source** - you'll get a confirmation that names the consequence for the destination. After confirming, the destination is left valid, with no dangling Carry Forward config.
* **Changing the source's question type** - blocked or warned, since a type change (for example, Multi-Select → Multiple Choice) could leave the destination in an invalid state.
* **Launch blocking** - a study with a broken Carry Forward pairing can't launch. The launch blocking message will name the affected question and the specific reason, and the destination question shows a matching inline banner.
* **Skip Logic overlap** - if a question carries both Skip Logic and Carry Forward, moving or deleting it surfaces both concerns, not just one.
## Interaction with other logic
* [**Randomization**](#randomization) - a Carry Forward destination is never shown to a respondent before its source, whether you've randomized all pages, all questions, or a mix, and whether the source is pinned or itself inside a randomized block. Unlike Response Piping, turning on Randomization does not disable Carry Forward.
* [**Display Logic**](#display-logic) - works alongside Carry Forward the same way it does on any other question.
* **Duplicate & templates** - duplicating a study, or creating one from a template, re-points the destination to the copy's own source question; carried choices reflect the copy's source answers, not the original study's.
* **Translations** - carried choice labels are included in translation exports and auto-translate, and respondents see them in their assigned language rather than falling back to English.
## Respondent experience
When a respondent reaches a Carry Forward destination, they see only the choices they personally selected on the source question, in the order those choices appeared on the source.
## Data & reporting
* **Data tab** - destination questions show a Carry Forward indicator below the question title. Since not every respondent sees every choice, per-choice counts are shown to make it easy to understand how many people saw a particular response option vs the question as a whole.
* **Responses tab** - individual responses show the carried choice labels the respondent saw.
* **CSV export** - sources and destinations appear as normal.
# Conversational Surveys
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/conversational-surveys
# What is a Conversational Survey?
A Conversational Survey is a chat-style survey experience that presents questions one at a time in a natural, dialogue-like flow. Instead of seeing multiple questions on a single page, respondents interact as if they’re having a conversation. This design is more engaging, feels more human, and often encourages richer responses.
**Note:** The Conversation format is available for In-Product Surveys, Surveys, and Feedback studies.
# Why Use Conversational Surveys?
* **Higher Engagement**: Feels personal and lightweight, driving stronger response rates.
* **Better Data Quality**: Open-text answers come through richer, more authentic, and more detailed.
* **Improved Experience**: Respondents find it more enjoyable, intuitive, and natural.
# When to Choose Conversational vs. Standard
**Choose Conversational if:**
* You want deeper insights with richer qualitative feedback (e.g., checkout studies, feature feedback, usability research).
* You want to create a positive and engaging respondent experience.
**Choose Standard if:**
* You need a fast, efficient pulse check (e.g., quick NPS or CSAT).
* Speed and brevity are more important than open-text depth.
* You’re collecting simple, quantitative metrics.
# How to Set Up a Conversational Survey
1. Navigate to a Feedback study, Survey or In-Product survey.
2. Click Edit.
3. Click the **Settings tab** near the top of the survey.
4. Select "Conversation" from the **Survey Appearance** options.
5. *\[Optional]* Enable the **Show Survey Provider Persona** setting if you'd like to provide additional context to respondents about where the questions they're seeing are coming from. This is helpful for ensuring respondents understand the survey isn't a chatbot and for building trust.
# Groups
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/groups
## Creating & Managing Groups
Groups help you segment visitors for multiple studies. Instead of setting up each study individually, you can create a group filter and use it across studies.
Groups can be created a variety of ways:
1. [Manually](#creating-a-manual-group) - With the users you have already tracked in Sprig
2. [via CSV Upload](#add-from-csv) - With additional attributes about users
3. via [Dynamic Groups](#creating-a-dynamic-group) - With existing and future users based on Attributes, Event History, or other Groups
# Creating a Manual Group
Manual groups are fixed collections of users.
1. Go to **Users > All Users**.
### Add to New Group
2. Select users by checking the boxes.
3. Click **Add to Manual Group**.
4. Click **Create Manual Group**.
5. Name and describe the group.
6. Click **Create Manual Group**.
7. Close the window.
8. Check your new group under the **Groups** tab.
### Add to Existing Group
2. Select users by checking the boxes.
3. Click **Add to Manual Group**.
4. Choose the group(s) to add users to.
5. Click **Add to Group**.
6. Check your updated group under the **Groups** tab.
# Add from CSV
2. Click **Upload CSV**.
3. Select and upload your file.
4. Map the column to **User ID**.
5. Check **Add users to Group after uploading**.
6. Click **Continue**.
7. Choose to add users to an existing group or create a new group.
8. Click **Add to`` Group**.
9. Refresh to check if validation is complete.
10. Close the window.
# Creating a Dynamic Group
Dynamic groups change based on filters.
1. Go to **Users**.
2. Click **Filter Users**.
3. Add filter conditions (e.g., `Language = French`).
4. Apply the filter to see results.
5. Click **Create Dynamic Group** if satisfied with the results.
6. Name and describe the group.
7. Click **Create Manual Group**.
8. Check your new group under the **Groups** tab.
# Study Creation Foundations
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/index
# Shared Creation Foundations Across Studies
There are shared Sprig foundations across the creation of Sprig studies, such as:
* [Question types](/docs/shared-study-foundations/main-tasks/questions)
* [Logic](/docs/shared-study-foundations/main-tasks/survey-logic) (skip logic, randomization, attribute and response piping)
* [Study triggers & user filters](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy), and [groups](/docs/shared-study-foundations/main-tasks/groups)
* [Multi-Language Surveys](/docs/shared-study-foundations/main-tasks/multi-language-support)
* [Conversational Surveys](/docs/shared-study-foundations/main-tasks/conversational-surveys)
* [Display an image in a question](/docs/shared-study-foundations/main-tasks/add-an-image-to-question)
# Multi Language Surveys
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/multi-language-support
Launch Surveys and target users in their native language
# Overview
Sprig allows you to translate a survey into multiple languages that can be configured to selectively display to users on a localization attribute, event, or user group of your choosing. All languages, including right to left languages like Hebrew or Arabic are supported.
Here's an overview of the process:
**Note:** Multi Language Surveys are available for Web or Mobile In Product Surveys and Surveys. Feedback is not supported at the time.
[FAQ's](/docs/shared-study-foundations/main-tasks/multi-language-support#faq)
## Translating a Survey
1. Create and configure a Survey in a default language - most users do so in English.
2. Select *Add language*.
3. In the Language card, add your language(s) from the dropdown menu.
4. Download the translation file - translatable fields will be in rows, with the target languages across the top as columns.
1. Translatable fields include questions, descriptions, choices, and button labels.
5. Populate your translation file CSV with your translations.
1. *Be sure not to add or delete any rows or columns!*
6. Upload your CSV file by selecting *Upload translations*.
7. Continue onto the Audience tab, where you can select your delivery platform and configure the study's targeting.
8. For each uploaded language, add a filter to ensure the right users receive a study in the right language.
9. Configure Response Settings and Recontact Options
10. Launch!
### Auto Translated Survey Fields
For web and mobile surveys that are *not* manually translated, there are a few UI elements that are automatically translated based on the survey respondent's browser locale language, in the case that a Sprig user *does not choose to override the placeholder text*:
* "Next" and "Finish" CTAs
* Thank you card text ("Thanks for your input!")
These fields are automatically translated into the following languages: German (DE), Spanish (ES), French (FR), Hindi (HI), Italian (IT), Japanese (JA), Korean (KO), Portuguese (PT), Russian (RU), and Chinese (ZH). For Surveys, the above elements will remain in English.
## Analyzing Responses
All responses will be captured, in aggregate, for all language versions of the survey in the Results tab.
To analyze results by language, we recommend using the same attribute filter used for language targeting.
#### Open Text Themes
Sprig AI automatically translates open-text responses and outputs themes in English, but the individual responses will be displayed in the native language.
**Note:** Filtering down results will not generate themes based on the subset of responses.
# FAQ
### What happens if there are no matching language filters?
A survey will *not* be displayed to a visitor if there are no matching language filters.
### How do I show the survey in the default language if there are no matching language filters?
Set the top-level filter to is set = Yes
### How do right-to-left language surveys work?
Sprig supports any right-to-left languages. Simply upload a translation as you would with any other language and observe the formatting in the Preview pane.\
If a survey taker matches your prescribed filtering criteria for a right-to-left language, our formatter will right-justify and flip the orientation of the UI elements for the best survey taker experience.
### Does Sprig support RTL Languages?
Yes! If you don't see a language listed in the dropdown, please reach out to [support@sprig.com](mailto:support@sprig.com).
### Can I translate Surveys with Consent/Legal or Voice and Video Question Types?
#### Consent/Legal
Certain fields can be translated, but we only support the upload of a single PDF
#### Voice and Video
Certain fields can be translated, but "Record Your Response", "Back to Question", and Recording controls are unable to be translated.
### I don't see my desired target language listed in the dropdown. What should I do?
Language labels are just that-- labels; They have no effect other than to name columns or dropdowns.
You can simply move forward with selecting a different language as an *alias*. For example, I can choose Dothraki from the dropdown, but upload a translation file in Pig Latin, and subsequently configure targeting such that Pig Latin (labeled in the system as Dothraki) is displayed to my Pig Latin-speaking visitors.
# Question Types
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/questions
Learn about the question types available in Sprig.
# Supported Question Types
By default, every question type is supported across all:
* Plans (Free, Starter, and Enterprise)
* Study Types (In-Product Surveys, Surveys, Feedback Studies, and Prototype Tests)
* Delivery Methods (Web, Mobile, and Link)
* Survey Formats (Conversational and Standard)
Exceptions are noted in the **Constraints** column below:
| **Question Type** | **Description** | **Constraints** |
| :- | :- | :- |
| [Rating Scale](https://docs.sprig.com/docs/questions#rating-scale) | Also known as a Likert scale. Used to measure respondents' attitudes toward a statement. | |
| [Open Text](https://docs.sprig.com/docs/questions#open-text) | Open text response to a text question. Our AI Analysis constructs themes based on these responses. We also support AI Follow-up Questions for this question type. | |
| [Validated Text](/docs/shared-study-foundations/main-tasks/questions#validated-text) | Validates that a respondent's text answer matches a required format, like an email address, phone number, URL, or a custom pattern. | Not available on Heatmap or Replay studies. |
| [Matrix / Accordion](https://docs.sprig.com/docs/questions#matrix--accordion) | Allows you to collect many responses for similar question sets. | |
| [Multiple Choice Single-Select](https://docs.sprig.com/docs/questions#multiple-choice-single-select) | Users may select only one option from a list. | |
| [Multiple Choice Multi-Select](https://docs.sprig.com/docs/questions#multiple-choice-multi-select) | Users may select multiple options from a list. | |
| [NPS](https://docs.sprig.com/docs/questions#net-promoter-score) | NPS measures customer loyalty on a scale from 0 to 10. Results are automatically categorized into Promoters, Passives, and Detractors. | |
| [Consent / Legal](https://docs.sprig.com/docs/questions#consent--legal) | Enable respondents to consent to disclaimers before conducting the study. | Only available on In-Product and Surveys. |
| [Text / URL prompt](https://docs.sprig.com/docs/questions#text--url-prompt) | Used to introduce or conclude a study, or permit the study respondent to navigate to a URL. | |
| [Video and Voice](https://docs.sprig.com/docs/questions#video-and-voice) | Enable respondents to provide video and audio-only questions and responses. | Not supported on Feedback Studies. |
| [Rank Order](https://docs.sprig.com/docs/questions#rank-order) | Enable respondents to prioritize a set of options so you can make data-driven decisions. | Only available on Enterprise Plans. Only available on In-Product and Surveys. |
| [Recorded Task](https://docs.sprig.com/docs/prototype-testing#recorded-task) | Allows you to watch a user attempt a specific goal in your prototype while capturing their screen, voice, and video. | Only available on Enterprise Plans. Only available on Prototype Tests. |
| [MaxDiff](https://docs.sprig.com/docs/questions#maxdiff) | Gather granular preference information on longer lists of items. | Only available on Enterprise Plans. Only available on Surveys in Standard Format. |
| [Conjoint](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/questions#conjoint) | Collect detailed preference data to make pricing and packaging decisions. | Only available on Enterprise Plans. Only available on Surveys in Standard Format. |
| Multi-Question: Single Page | Add a page that can contain multiple questions. | Only available on Surveys. |
**Note:** Video and Voice and Recorded Task questions are not supported in HIPAA-compliant environments.
# Supported Question Types
## Rating Scale
A Rating or Likert scale is a type of scale used in survey research that measures respondents’ attitudes towards a certain subject. You can change the range or number of points, the labels, icons, and the lowest and highest value labels.
There are eight options for configuring skip logic on numerical question types.
1. is equal to
2. is not equal to
3. is less than
4. is less than or equal to
5. is greater than
6. is greater than or equal to
7. is submitted (any value selected)
8. is skipped (no value selected)
## Net Promoter Score
Net promoter score (NPS) is a widely used market research metric that typically takes the form of a single survey question asking respondents to rate the likelihood that they would recommend a company, product, or service to a friend or colleague. NPS is a commonly requested sentiment score that investors and boards review across companies, segments and verticals. For more information on NPS, click [here](/docs/study-best-practices/measuring-cx/should-you-be-tracking-nps).
There are eight options for configuring skip logic on numerical question types.
1. is equal to
2. is not equal to
3. is less than
4. is less than or equal to
5. is greater than
6. is greater than or equal to
7. is submitted (any value selected)
8. is skipped (no value selected)
## Open Text
Open Text uses AI [Thematic Clustering](/docs/native-ai/synthesize-agent/ai-powered-open-text-analysis#how-it-works) to automatically group qualitative responses to text-based questions into themes.
#### AI Follow-up Questions
Open Text questions support AI-powered follow-up questions. When enabled, Sprig AI dynamically generates a contextual follow-up based on the respondent's open text response, surfacing deeper insights without requiring you to anticipate every answer path in advance. To enable AI follow-up questions on an Open Text question, toggle AI Follow-up Question on in the question settings. See [AI Follow-up Question](/docs/native-ai/field-agent/ai-follow-ups) for full configuration details and best practices.
There are four options for configuring skip logic on Open Text question types.
1. is submitted (any value selected)
2. is skipped (no value selected)
3. contains
4. does not contain
## Validated Text
Validated Text questions ensure a respondent's text answer matches a specific format, so the data you collect is usable right away instead of needing to be cleaned up after the fact.
#### Supported Formats
When adding a Validated Text question, choose one of the following formats to validate a respondent's answer against:
* **Email address**
* **Numeric** (numbers only)
* **URL**
* **Phone number**
* **Custom** (define your own format using a regular expression)
#### Error Messaging
If a respondent's answer doesn't match the selected format, they'll see an error message explaining what's wrong before they can continue. This message can be customized and translated like other study copy.
#### Required vs. Optional Behavior
* **Required questions:** If the response doesn't pass validation, the respondent cannot advance to the next question.
* **Optional questions:** Respondents can leave the question blank and proceed. However, if they enter any text, it must pass validation before they can proceed.
#### Feature Support
* Validated Text questions support the same logic options as Open Text questions.
* AI Follow-up Questions and Open Text theming/AI analysis are not supported for this question type.
* It's not possible to add a prototype link to a Validated Text question.
#### Configuration Notes
* Translations are supported, including custom error messages.
* The global Open Text footer setting (Settings > Surveys) does not apply to Validated Text questions.
| Platform | Minimum SDK Version |
| :- | :- |
| Web | 2.51.0 |
| iOS | Coming soon |
| Android | Coming soon |
| React Native | Coming soon |
There are four options for configuring skip logic on Validated Text question types.
1. is submitted (any value entered)
2. is skipped (no value entered)
3. contains
4. does not contain
## Matrix / Accordion
Matrix questions bundle multiple questions sharing the same rating scale or response options into one cohesive table. Rows represent different items being evaluated, while columns represent the scale.
| Platform | Minimum SDK Version |
| :- | :- |
| Web | 2.25.1 (Desktop), 2.32.0 (Accordion on Desktop), 2.31.2 (Accordion on Mobile Web) |
| iOS | 4.22.3 |
| Android | 2.16.4 |
| React Native | 2.17.0 |
#### Display Behavior
* Desktop Web: Defaults as a full-scale matrix, with an option to *always display as an accordion on desktop*
* Mobile Web & Mobile Apps: Always displayed as an accordion (full-scale matrix not supported)
#### Editing Post-Launch
Matrix rows and columns cannot be deleted or reordered after launching a survey, but new rows and columns can be added as needed.
There are three options for configuring skip logic on Matrix questions.
1. is completely submitted (an answer is provided for every row)
2. is partially submitted (an answer is provided for at least one, but not all rows)
3. is skipped
## Multiple Choice
Multiple choice questions allow respondents to select one or more options from a list, depending on whether they are allowed to select one, a range, or unlimited options. Both single- and multi-select options support the following two configurations:
#### Randomized Order Supported
The order of responses shown to the user can be randomized using the **Randomize Order** dropdown menu. Additionally, users can configure choices to be pinned to the bottom of the list of responses by adding a **Pinned Choice**, even alongside an **Other** choice.
#### Display as Dropdown
You can choose to display multiple choice questions as a dropdown instead of a list by toggling *Show choices in a dropdown* ON. Note: When using the "Other" choice option, displaying as a drop-down is not supported.
### Multiple Choice Single-Select
The multiple-choice single-select question type allows a respondent to choose only one option from a list of possible answers.
There are three options for configuring skip logic on Single-Select questions.
1. is
2. is not
3. is submitted (any value selected)
**Using Images in Response Options**
* Add an image to each answer choice in a multiple choice question, so respondents pick between designs, layouts, or products by seeing them, not by reading a description of them.
* Visual questions used to require a workaround: describing each option in text, linking out to external mocks, or running the study in another tool. Every workaround had the same problem. When you describe a design in words, respondents react to your description, not the design. Images in response options removes that gap. The thing you're testing is the thing they see.
## What it does
* Images in response options is a display mode for multiple choice questions.
* Turn it on, and each answer choice gets an image alongside its text label.
* Respondents see the choices as tappable image cards: image on top, label underneath, and a border when selected.
* Under the hood, it's still a multiple choice question. Skip logic, randomization, and reporting all work exactly as they do today, because they operate on the option, not the image. You're not learning a new question type; you're adding pictures to one you already use.
## Where it's available
* **Question types:** Multiple Choice Single Select and Multiple Choice Multi Select.
* **Study types:** Surveys only.
* **Plans:** All plans (Free, Starter, and Enterprise).
* **SDK:** An updated SDK version is required for respondents to see image cards.
## How to set it up
1. In the builder, add a Multiple Choice Single Select or Multi Select question.
2. Switch the choice list to **With Image** mode. Each choice row gets an image slot.
3. Click the image slot on a choice and upload a JPEG, PNG, or WebP file, up to 10MB.
4. Give each choice a text label. Labels are always required, because they power reporting, the Data tab, piping, and AI Follow-ups.
5. Optionally add alt text for each image. If you leave it empty, screen readers use the text label instead.
6. Launch. Sprig won't let you launch a survey if any image option is missing its image, so you'll never accidentally ship a blank card.
A few builder behaviors to know:
* **Randomize order** works as usual. Cards shuffle as units, so each image stays with its option.
* **Show choices in a dropdown** is disabled in With Image mode, since dropdowns can't render images.
* **Other (please specify)** and **None of the Above** stay as text rows. They never get an image slot, and that's by design.
## What respondents see
* Choices render as a grid of image cards.
* With fewer than 15 options, respondents see 2 columns; with 15 or more, 3 columns.
* Tapping a card selects it and highlights the border. Respondents can right-click an image to open it full size in a new tab.
* Images display without cropping. Sprig fits the whole image inside the card rather than zooming or trimming it, so the corner of your design that matters doesn't get cut off.
* **If an image ever fails to load**, the option falls back to a standard text row and the respondent can still answer normally. A broken image never blocks a response.
## How results show up
* **Responses page:** each selected option appears as a thumbnail chip with its label and an expand icon that opens the full-size image. No more mapping "Option B" back to a screenshot from memory.
* **Data tab:** the question card shows each option's thumbnail next to its aggregate counts, with the same expand affordance.
* **CSV exports:** rows carry the option text, as they do today.
* **Charts:** option breakdowns show images as above. Other chart types (pie, line) are unchanged.
## Works with, doesn't work with
**Works with:**
* Skip logic, randomization, and quotas. All unchanged.
* AI Follow-ups. They read the text label, so follow-up questions reference your options naturally.
**Not supported:**
* Carry forward. Questions with images can't be a carry forward source or destination.
* An image library. Uploads are per survey for now.
* Image editing (cropping, borders, aspect ratio adjustments). Upload the image the way you want it shown.
* Images-only mode. Text labels are always shown and always required.
## FAQ
**Do I have to add an image to every choice?**
Every choice except Other and None of the Above needs an image before you can launch. Mixing image cards and text rows in one question isn't a supported authoring setup, though a failed image load will gracefully render as text.
**What happens if I delete a choice?**
It's image and alt text are deleted with it. Duplicating a question copies the images and alt text along with everything else.
**Does this change my data or exports?**
No. Responses are still recorded against the option, exactly as before. The image is presentation only.
**What file types and sizes are supported?**
JPEG, PNG, and WebP, up to 10MB per image. Unsupported or oversized files show an error in the upload modal.
### Multiple Choice Multi-Select
The multiple choice multi-select question type allows a respondent to choose multiple options from a list of possible answers.
#### Response Validation Options (also known as "Max Selectable")
There are three options for constraining responses to **Multiple Choice Multi-Select** questions:
1. **Unlimited** (default) - Respondents can select as many choices as they'd like.
2. **Maximum** - Set a maximum for the number of choices respondents can select.
1. Once the maximum has been reached, remaining choices will become unselectable.
3. **Range** - Define a minimum and maximum number of choices that respondents can select.
1. The lowest a minimum can be is 1, and the maximum can be up to the total number of choices in the list.
2. If a question is optional, respondents can skip it entirely. However, if they select any option, they must meet the minimum requirement to proceed.
3. Respondents will see a numeric indicator to know how many options they need to select to meet the minimum. The indicator will disappear once it's been met.
Best practice: Describe the validation requirements in the question or description so respondents know what's expected.
#### None of the Above Choice
For Multiple Choice Multi-Select questions, a **None of the Above** choice can be added to the list of options. When selected by a respondent, other options are automatically deselected.
* If Range or Maximum is selected for the question, a "None of the above" option cannot be added to the question.
* Similarly, if "None of the above" is already one of the options, you cannot change the Selection Amount to Range or Maximum.
* Remove the "None of the above" option to change the validation type.
Skip logic for multi-select questions triggers based on how the respondent's collective choices match your defined criteria. There are four options for configuring skip logic on Multi-Select questions.
1. is exactly: evaluates to TRUE when respondent selects the EXACT options specified.
| **Rule** | **Options** | **Result** |
| :- | :- | :- |
| Exactly \[a, b] | \[a] | false |
| Exactly \[a, b] | \[a, b] | true |
| Exactly \[a, b] | \[a, b, c] | false |
2. includes all: evaluates to TRUE when respondents select ALL that are included within specified options.
| **Rule** | **Options** | **Result** |
| :- | :- | :- |
| Includes all \[a, b] | \[a] | false |
| Includes all \[a, b] | \[a, b] | true |
| Includes all \[a, b] | \[a, b, c] | true |
3. includes at least one: evaluates to TRUE when respondents select one or more options specified.
| **Rule** | **Options** | **Result** |
| :- | :- | :- |
| Includes at least one \[a, b] | \[a] | true |
| Includes at least one \[a, b] | \[a, b] | true |
| Includes at least one \[a, b] | \[a, c] | true |
| Includes at least one \[a, b] | \[c] | false |
4. does not include: evaluates to TRUE when respondents do not select ANY of the options specified.
| **Rule** | **Options** | **Result** |
| :- | :- | :- |
| Does not include \[a, b] | \[a] | false |
| Does not include \[a, b] | \[c] | true |
| Does not include \[a, b] | \[a, b] | false |
| Does not include \[a, b] | \[c, d] | true |
If multiple skip logic statements are true, visitors will be routed to a **randomly selected** true logic statement.
For example:
* includes at least one \[a or b] = skip to 2
* includes all \[a and b] = skip to 3
If the user selects **a and b**, they are routed to a randomly selected TRUE logic statement. In the example above, a visitor would have an equal chance of landing on question 2 or 3.
## Text / URL Prompt
The Text / URL prompt can be used to add messaging for respondents into a study or redirect respondents to an external site. It comprises two text fields and a button that can go to the next question or a URL.
The steps to create a study with a Text / URL prompt are:
1. Select **Text / URL Prompt** from the **Add Question** menu.
2. Type in your purpose, question, or statement in the **Title** and **Description** fields. Both fields allow rich text formatting. Rich text formatting is supported on Web SDK v2.14.9 and later.
3. Select when the respondent clicks the button whether you want the navigation to continue in the survey or link to an external URL.
4. Type in the text for the button
5. If you selected **Button to link to an external URL**, type in the URL you want the respondent to navigate to. To construct unique links for each participant, you can enrich each link with the visitor's User ID.
There are two options for configuring skip logic on Text/URL questions.
1. is submitted (user selects the button, whether it links to a URL or not)
2. is skipped
#### Link Behavior on Mobile
When a Text / URL Prompt question is set to **Button to link to an external URL** and the study's platform is **Mobile**, a new setting called **Link behavior on mobile** appears on the **Settings** tab of the In-Product Survey. It controls what happens when a respondent taps the button:
* **Open in-app**: the link opens inside your app as a full-page in-app browser, so the respondent never leaves the app.
* **Open in default browser**: the link opens in the phone's default browser, taking the respondent out of the app.
This setting only shows up when both are true: the study includes a Text / URL Prompt question configured with an external URL, and the platform is set to Mobile. Without either, there's nothing for the setting to apply to, so it stays hidden.
The in-app view follows whichever theme setup you already have, light or dark, whether that's Sprig's built-in light/dark themes or your own custom dark theme, so the buttons and UI around the webpage match the rest of the study.
In-Product Surveys that were live, paused, complete, or archived when this feature shipped keep their existing behavior (opening in the default browser). You can switch a live study to the in-app setting at any time. Draft studies, and any created after this release, default to **Open in-app**.
### Identifying the Visitor
If you use a **Button to link to an external URL**, you can pass respondents' email and/or User ID to the destination website. This can be useful for [recruiting participants](/docs/study-best-practices/recruiting-participants) or connecting responses across different platforms, or to a Sprig Survey. More about using an In-Product Survey to navigate to Surveys [here](/docs/sprig-studies/long-form-surveys/delivering-lfs#linking-from-an-in-product-survey).
#### How to Use
* Add `{{email}}` or `{{user_id}}` to your URL. Sprig will automatically swap these with the respondent's actual data when they click the button.
* For example, `https://website.com/schedule?id={{user_id}}&email={{email}}` might become `https://website.com/schedule?id=23481&email=sara@example.com`.
* The exact format for the user ID and email name-value pairs may vary by destination site.
* To make user ID and email available in button URLs in studies, ensure they're set on the user before the study is displayed. If there's no value found for a parameter, it is removed from the URL so the link doesn't break.
* For example, if a visitor accessed `https://website.com/schedule?id={{user_id}}&email={{email}}` but only had a User ID set (and no email), it would become `https://website.com/schedule?id=23481`.
| Platform | Minimum SDK Version |
| :- | :- |
| Web | 2.15.3 |
| iOS | 4.3.0 |
| Android | 2.6.0 |
| React Native | 2.6.0 |
#### Sending Identity vs. Capturing Identity
To use identity placeholders (like `{{email}}`) in a Text/URL prompt, Sprig must first "know" who the visitor is.
**Sending Identity through In-Product Surveys (Outgoing)**: Once Sprig has captured the data, you can "pass" it to an external URL using this button. Data must already be in Sprig (via the SDK or CSV upload). End goal: an outgoing Button URL set to`https://website.com/schedule?email={{email}}` might become `https://website.com/schedule?email=sara@example.com`.
**Capturing Identity into Surveys (Incoming)**: To store a Survey respondent's user identity, you must "inject" the identity by adding the `{{user_id}}` or`{{email}}` parameter to the study link you distribute. See [here](/docs/sprig-studies/long-form-surveys/delivering-lfs) for details on how to capture identity in Surveys when they're distributed through third-party software or marketing tools.
### Customizing URLs with User Attributes
Aside from passing respondents' email and/or User ID to the destination website when using a **Button to link to an external URL**, you can also pass other attributes to personalize the URL. Simply include a placeholder in the format `{{attribute_name}}` anywhere in the URL and Sprig will automatically populate it with the corresponding value when a user clicks the link from within an In-Product Survey. If a value isn't available for a given visitor, its placeholder is automatically removed so the URL still resolves correctly and the link does not break.
```text theme={null}
https://website.com/schedule?id={{user_id}}&email={{email}}&invite={{code}}
```
```text theme={null}
https://website.com/schedule/{{code}}
```
## Consent / Legal
You can incorporate a Non-Disclosure Agreement into your Study for your participant's review and obtain their consent before proceeding with the study. The copy can be in text format and/or a PDF file. You can also capture the respondent's name.
There are two options for configuring skip logic on Consent/Legal questions.
1. is submitted (user selects the checkbox and selects the button)
2. is skipped
## Video and Voice
As well as [Open Text](/docs/shared-study-foundations/main-tasks/questions#adding-a-question) questions and responses, Sprig also supports video and audio-only questions and responses. The video and voice responses are automatically transcribed and optionally translated. Contact Sprig [Support](/docs/support-privacy-and-technical/support) to enable the translation service. The transcription enables the same AI analysis used for text to be applied to video responses. However, video and audio responses provide an additional emotional dimension that is not always visible in text-only responses. Because recording video or audio requires more effort from respondents, expect lower response rates compared to standard text questions. Consider focusing voice and video questions on a specific area of interest and only share that study with recipients you think the topic would be particularly relevant.
The steps to create a study with video-enabled questions and responses are:
1. Select **Video & Voice** from the **+Add Question** menu.
2. Click **Request Permissions** to enable Sprig to request access to your camera and microphone.
3. Click Allow for the browser to permit Sprig access to your camera and microphone.
4. Click **Record** to begin the recording countdown, and it will automatically begin recording for you to record your question. Optionally, click the **Video Camera** icon to turn off video and record the audio only.
5. Click the stop icon to **Stop** recording, the play icon to **Play** back your recording, and the trash can icon to **Delete** if you'd like to start over.
6. Distribute the survey link to prospective respondents using your usual methods.
7. Note that respondents who engage with this question must give permission in their browser to enable camera and microphone access.
There are two options for configuring skip logic on Video/Voice questions.
1. is submitted (user uploads a video/voice response)
2. is skipped
Videos are only accessible within the Sprig dashboard and cannot be downloaded or exported.
### Content Security Policy
Supporting Video and Voice questions for Web studies may require you to update your web application's [Content Security Policy](https://en.wikipedia.org/wiki/Content_Security_Policy) (CSP). This is because Sprig uses third-party libraries to support Video & Voice questions, including fetching an external stream of the question and uploading the response.
The following list of sources is required to use Video & Voice questions:
* Base64 SVGs and fonts.
* Connecting to Mux (for streaming and short video uploads).
* Connecting to Google APIs (for long video uploads).
* A worker source required by our third-party library (videos).
Examples are shown in the following CSP source list:
```html theme={null}
```
**Warning:** As every company has different security policies, the example may not reflect the complete configuration. You may need to add additional keys and values in order to comply with your own organization’s policies. *Note: Video and Voice questions are not supported in HIPAA compliant environments.*
#### Troubleshooting Errors
After creating your first study with Video and Voice questions, test its display on your website using these [instructions](/docs/Installation/introduction-web/web-javascript#browser-console). Check your browser console for any CSP-related errors if the questions are not rendering correctly or responses aren't uploaded. You may have to work with your engineering and security teams to update your website's or app's CSP settings to resolve the errors.
## Rank Order
Rank Order questions are only available on the Enterprise plan.
Capture relative preferences by having respondents prioritize a set of options. Supported in Long-Form and In-Product Surveys. This question type only supports the "is submitted" conditional for skip logic.
### Configure
* Add 2 - 10 options and optionally set them to display in a random order
* Set the labels for the top and bottom of the list to help respondents understand the criteria they should be using to rank the options
There are two options for configuring skip logic on Rank Order questions.
1. is submitted (user ranks items)
2. is skipped (user does not interact with any items)
### Respondent Experience
Items are unranked until the respondent ranks their first item. Respondents can drag and drop items or set a specific ranking for an item. If they set a ranking, the items in the list will move to reflect the new order. Note that drag and drop is not yet supported when surveys are taken on Android devices.
### Review results
Once you've collected results, view details about how each item was ranked in a histogram. Hover over the histogram to get a tool tip containing a breakdown with percentages.
## MaxDiff
MaxDiff questions are only available on the Enterprise plan and for Surveys.
MaxDiff questions, also known as Best-Worst Scaling or Maximum Difference Scaling, allow you to gather detailed preference information from respondents. They're often used when the goal is to deeply understand the importance of the items, like product improvements or brand messages, being rated.
**Benefits**
For researchers: mitigate position and order bias by showing items in different groupings and orders; gather deeper insights and detailed preference data.
For respondents: reduced cognitive load due to only needing to select the best and worst items from a small set of items. Once a user selects both a Best and Worst, the survey automatically advances to the next set; there's no "Next" button between sets.
### Build
1. **Create items:** MaxDiff questions require a minimum of 4 and a maximum of 24 items in the list to be rated.
2. **Create labels:**
* The **left** label must be a **positive** descriptor for Sprig's Best-Worst calculation to be accurate. By default, this is "Best."
* The **right** label must be a **negative** descriptor for Sprig's Best-Worst calculation to be accurate. By default, this is "Worst."
3. **Required or Optional?**
* If a MaxDiff question is required, respondents must finish all sets to proceed.
* If it's Optional, respondents can skip the whole experiment. However, if they start a set, they must finish that specific set.
4. **Construct the experiment:** determines the number of items per set and the number of sets that a user sees. There are two options:
* **Recommended**: Sprig will use half the total possible items as the number of items per set (up to a maximum of 8), and it will use the following formula to determine the total number of sets: (total # items/items per set) \* 3.
* For example, in a question that has 24 items: Items per set = half of 24, max 8 = 8 Number of sets = (24/8) \* 3 = 3 \* 3 = 9 So, users will see 9 sets of 8 items.
* In a question that has an odd number of items, the items per set is the number below the halved value. However, Sprig always rounds up to the nearest whole *set* to ensure coverage. For example, in a question that has 11 items: Items per set = half of 11 = 5.5, which is rounded down to 5 Number of sets = (11/5) \* 3 = 2.2 \* 3 = 6.6, which is rounded up to 7 So, the user will see 7 sets of 5 items.
* **Custom**: Configure the number of items per set and the number of times each item should be shown to each respondent, within the ranges noted below the fields. Based on those values, Sprig will calculate the number of sets to show each respondent.
There are two options for configuring skip logic on Maxdiff questions.
1. is submitted (user picks a "best" and "worst" for each set shown)
2. is skipped (user immediately clicks forward button, or does not pick a "best" and/or "worst" for all sets shown)
### Results
Sprig records the "best" and "worst" selection for each set, and the order of items shown in each set.
* The "best" percentage is the percentage of times that item was chosen as the best across all sets. The "worst" is the percentage of times the item was chosen as worst.
* The score is based on the following formula and ranges from 100 to -100: (# Best - # Worst) \* 100 / total number of appearances.
Results on the survey summary page are based on "completed" questions, where respondents filled in all of the sets they were shown. To view partial responses, download the CSV.
After a survey is launched, you can only edit the existing items in a MaxDiff question. You cannot add or remove items. Likewise, you cannot change the configuration of MaxDiff item sets once the survey has been launched.
#### How are sets configured?
Sprig's MaxDiff sets will:
* Show items in different pairs evenly, such that all pair comparisons are shown to each respondent or can be inferred
* ensure each item is shown an equal number of times with other items (so strawberries aren't always shown with kiwi and durian)
* Show each item the same (minimum) number of times across all sets (some rounding occurs, especially when there are an odd number of items or sets)
* Show items in different positions within sets (top, bottom, middle)
* Show items evenly across sets so they aren't shown only up front and not later
#### Do all respondents see the same sets?
* All sets a respondent will see are generated as the survey initially loads; the order of the items displayed will be randomly determined and will differ between respondents.
* Not all items will be shown to each respondent, and each respondent may not see each item the exact number of times the formula calls for, usually when there's an odd number of items and rounding occurs.
## Conjoint
Conjoint questions are a structured research method that simulates real-world decision making. Rather than asking respondents to rate features in isolation, a conjoint question presents them with realistic combinations of features and asks them to choose between options, just as they would in an actual purchase or usage scenario.
Choice-Based Conjoints are particularly well-suited for:
* Pricing and packaging research
* Understanding willingness to pay
* Estimating relative feature importance
* Simulating market share across product configurations
Note: Conjoint questions are available to **Enterprise teams** on **link surveys only**.
1. Navigate to a new or existing Survey (link survey, previously known as Long-Form Surveys)
2. Click **Add Question** and select **Conjoint** from the menu.
3. Define your features and levels (see below).
4. Configure display and behavior settings.
5. Optionally: add exclusion groups to prevent unrealistic combinations and/or a “None of these” option.
**Note:** The features and levels cannot be added, removed, or reordered after the survey is launched. Task configuration also cannot be changed. Plan your question structure before going live.
A Conjoint question requires at least **3 features**, each with at least **3 levels**. There are maximums for both — Sprig will indicate these constraints in the builder.
**To add a feature (also commonly known as an attribute):**
* Enter the feature name (e.g., "Price", "Delivery Speed", "Support Type")
**To add levels (specific values) to a feature:**
* Enter each value you want to test for that feature (e.g., "\$10", "\$25", "\$50")
Levels should represent realistic, meaningfully different values. Avoid overly similar levels or values that would never coexist in a real product.
Once features and levels are defined, configure how the experiment will run:
* **Randomize feature order:** Toggle this on to randomize the order in which features are displayed across respondents which mitigates position bias. Each respondent will always see features in the same order.
* **Options per task:** Set how many options (product combinations) are shown side-by-side in each task. Maximum: **4 options**.
* **Tasks per respondent** Set how many tasks each respondent will complete. More tasks yield richer preference data but increase survey length. Maximum: **15 tasks**.
* **"None of these" option:** Optionally add a "None of these" choice to each task. This allows respondents to indicate that none of the presented options would satisfy them and is useful for pricing research and realistic purchase simulation. The text can be customized and translated.
Exclusion Groups prevent logically inconsistent or unrealistic combinations from appearing in an option. For example, if your highest price point should never appear alongside your lowest feature tier, you can define this as an exclusion.
**To create an Exclusion Group:**
1. Select a feature and the level(s) that should not appear together.
2. Add additional feature/level pairs that shouldn’t be shown together.
3. Save the group.
Note: If your exclusion rules eliminate too many possible combinations, Sprig will display a warning. You'll need to adjust the rules to ensure enough valid combinations can be generated for the experiment.
When a respondent reaches a Conjoint question, they will see multiple options side by side, several times in a row. Each option shows the same set of features with different level values.
* Respondents click anywhere on an option to select it.
* Unlike some other question formats, respondents control when they advance to the next task using the button below the options. This allows time for deliberation.
* On **mobile**, options are displayed vertically and respondents tap to select, then use the button at the bottom of the list to advance.
**Skip behavior for Conjoint questions that are optional:**
* If a respondent has not started responding to the first task, they can skip the question entirely using the button below the options.
* If a respondent starts a task (selects an option from a task) and then skips, no data is recorded for that task.
**From the Data Tab**
Conjoint results in the Data tab are organized by feature. For each level within a feature, you can see:
* **Times Shown**: how many times that level appeared across all tasks and respondents
* **Times Selected**: how many times an option containing that level was chosen
* **Selection Rate**: the percentage of the time it was selected when shown
Note: For deeper analysis in external tools or statistical software, download the raw data as a CSV. The export includes task-level detail for every respondent:
* Which option they selected in each task
* All options they were shown in that task
* The full feature and level breakdown for each option
# Study Triggers & User Filters
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy
This document explains how to add Study Triggers and User Filters to a study in Sprig
Sprig SDK Installation & Event/Attribute Instrumentation Required for Targeting
In-product Studies like Surveys, Feedback, Replays and Heatmaps require SDK installation and events to be instrumented to properly capture your user's experience. Learn more about [Installation](/docs/Installation/introduction-web/index), [Events](/docs/shared-study-foundations/events/index) and [Attributes](/docs/shared-study-foundations/attributes)
This section walks through available study triggers and user filters during study creation, and also applies to user filtering when reviewing study results.
**Table of Contents:**
* [Study Triggers](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#study-triggers)
* [User Filters](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#user-filters---attributes-group-or-event-history-optional) (attributes, events, groups)
# Overview
Targeting unlocks the full potential of Sprig by enabling you to reach the right users at the right time across Surveys, Feedback, Replays, and Heatmaps, using study trigger events and/or URLs, user filters, and other advanced filters.
## Study Triggers
Study triggers consist of [events](/docs/shared-study-foundations/events/index) and/or URLs that initiate Surveys, Feedback, Replays, and Heatmaps, and are required for all in-product studies.
Events coming from server-side integrations (such as [Rudderstack](/docs/Integrations/data-sources-introduction/rudderstack) or [Segment](/docs/Integrations/data-sources-introduction/segment-classic) as a source rather than a destination) are **not** able to trigger studies. However, they *can* be used in your target users' [event history](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy#event-history).
### Steps to add a Study Trigger:
1. **Configure your Survey (for Surveys & Feedback)**
2. **Select a Platform**
3. **Select Trigger Type:**
* Click *Add event or URL*
* Heatmaps and Feedback are restricted to inline URL events only
* (optional) Add additional triggers - Sprig supports up to 10 triggers per in-product study.
4. **Configure Trigger: Event Properties** (optional)
* Event properties allow you to more specifically target users, limited to [Code](/docs/shared-study-foundations/events/index#code-event) events
* Note: You are limited to 10 event properties across all triggers in a study. For example, if your study has 2 triggers, you can have 5 event property filters per trigger.
**Note:** You can use the same event to trigger more than one Study, but if the same study type, your visitors will be evenly sampled to contribute to a study
#### Wait Time Filter - Surveys Only (Optional)
Wait times allow you to ensure that you are not interrupting key user flows. Adding a wait time will delay the survey from displaying for some number of seconds.
#### Inline URL Event Triggers
Inline URL Event Triggers work the same under the hood as [No Code Events](/docs/shared-study-foundations/events/matching-page-urls), just with the ability to create a No Code Event directly inline from the Targeting card.
As with all No Code Events, your SDK must first be installed on the same page that you are targeting with a URL.
#### Advanced Session Filters
1. Session History - # of visits before triggering
1. Measured as 12-hour windows in which a visitor has one or more events tracked
2. Page View History - # of web pages seen in a single session (Web studies only)
## User Filters - Attributes, Group or Event History (Optional)
User filters allow you to target specific user segments based on their attributes or behaviors. This helps in personalizing the study to relevant user groups.
There are several types of filters available:
1. [Attributes](/docs/shared-study-foundations/attributes): Enables filtering by properties of your users (e.g. `Plan = Enterprise`)
2. [Groups:](/docs/shared-study-foundations/main-tasks/groups) Enables filtering by groups of users
3. [Event History](/docs/shared-study-foundations/events/index): Enables filtering by previous interactions (e.g. `Dashboard - Sign Up Complete Last Occurred > 60 Days Ago`)
4. Question Types & Logic Statements( e.g. `How would you rate your satisfaction with the following is 4`)
5. [No Code Event URLs](/docs/shared-study-foundations/events/matching-page-urls)
6. [Frustration Signals - Public Beta](/docs/sprig-studies/replays/session-replay-clip-playback/frustration-signals)(e.g. `Rage Clicks = to 5`)
#### Steps to Add a User Filter:
1. Click the Filter button
2. Select one of the available categories, depending on Survey Type, categories and options will vary - see options variables below:
### Survey Filters
| Questions | Operators | Value |
| :- | :- | :- |
| Questions created in the survey. *Use to narrow down questions you want to highlight or dig deeper on.* | `Is`, `Is not` , `is submitted` , `is skipped` | Options specific to the question selected |
| Trigger Events | Operators |
| :- | :- |
| Events that have been triggered in a survey. *Used to filter specific events that triggered the survey.* | `Triggered study`, `Did not trigger study` |
| Trigger Page | Operators | Value |
| :- | :- | :- |
| Page on which a user was on when the survey was displayed. *Use to target specific survey results when a page was viewed.* | `Exactly matches`, `Contains` , `Starts with` , `is skipped`, `Does not exactly match`, `Does not contain`, `Matches regular expression`, `Matches regular express (case sensitive)` | Name, path, or a URL of desired page |
### Replay Filters
| Pages | Operators | Value |
| :- | :- | :- |
| Page on which a user was on when the survey was recording. *Use to target specific replay results when a page was viewed.* | `Exactly matches`, `Contains` , `Starts with` , `is skipped`, `Does not exactly match`, `Does not contain`, `Matches regular expression`, `Matches regular express (case sensitive)` | Name, path, or a URL of desired page |
| Events | Operators | Value |
| :- | :- | :- |
| Replay Events that are contained within the Replay clips of the study. If an event was never triggered and captured in the Replay study, then it should **not** show on this list. | `= (equal to)`, `≠ (not equal to)` , `< (less than)` , `≤ (less than or equal to)`, `> (greater than)`, `≥ (greater than or equal to)`, `Not tracked in clip` | Numerical value |
| Signals | Operators | Value |
| :- | :- | :- |
| Replay Signals are tracked by interactions and frustrations. Clicks, Rage Cicks, and Dead Clicks are three signals we use in Replays today. | `= (equal to)`, `≠ (not equal to)` , `< (less than)` , `≤ (less than or equal to)`, `> (greater than)`, `≥ (greater than or equal to)`, `Not tracked in clip` | Numerical value |
| Devices | Operators |
| :- | :- |
| Filter the recordings by device that was used. | `is device)`, `is not device` |
### User Filters
| Attributes | Operators | Property |
| :- | :- | :- |
| Ideally only showing Attributes of users captured in the study. | `= (equal to)`, `≠ (not equal to)` , `< (less than)` , `≤ (less than or equal to)`, `> (greater than)`, `≥ (greater than or equal to)`, `Contains`, `Does not contain`, `Starts with`, `Ends with`, `Is set`, `Is not set` | Available properties are specific to Attribute selected |
#### Event History
Event History has sub-filters after selecting an Event specific to your use-case. Use these filters to set parameters around a specific event in your survey.
| Filter | Operator | Value | Use |
| :- | :- | :- | :- |
| Tracked | `= (equal to)`, `≠ (not equal to)`,`\< (less than)`,`≤ (less than or equal to)`, `> (greater than)`, \`\`≥ (greater than or equal to)\` | Numeric value | The `Tracked` operator compares the total number of times an event has been triggered by a visitor, since first being tracked, to the specified value provided by the user |
| First tracked | `Is greater than`, `Is less than` , `is greater than or equal to` , `is less than or equal to` , `is equal to` | | The `First tracked` operator compares the first recorded event trigger and compares to the value specified by the user |
| Last tracked | `Is greater than`, `Is less than` , `is greater than or equal to` , `is less than or equal to` , `is equal to` | | The `Last tracked` operator compares the last recorded event trigger and compares to the value specified by the user |
| Is Set | `Yes` | | The `Is Set` operator checks whether or not there is a value stored for the intended event |
# Study Logic
Source: https://docs.sprig.com/docs/shared-study-foundations/main-tasks/survey-logic
Control survey flow and personalize surveys with powerful configuration tools.
Sprig offers several ways of personalizing and routing respondents through surveys, including [Skip Logic](#skip-logic), [Display Logic](#display-logic), [Randomization](#randomization) for questions, pages, and response options, [Response Piping](#response-piping), and [Attribute Piping](/docs/shared-study-foundations/main-tasks/survey-logic#attribute-piping). These options ensure respondents see only the questions they need to see, which results in higher engagement rates and richer data.
# Skip Logic
Skip Logic is a great way to ensure that respondents see the question you want them to see. At the bottom of each question, click **Add skip logic** to configure.
For example, imagine a study question "How easy is it to use the cut & paste feature in Google Docs?" with a response rating scale from 1 to 5.
If the user answers with a **2**, it won't make sense to follow up with: "What do you like most about the cut & paste feature in Google Docs?"
Instead, you might consider some routing logic only to show a "What can we do to make the feature easier?" question based on the response/response group.
There are minimum SDK version requirements to support Skip Logic in In-Product Surveys and Feedback Studies. See [Features by SDK Versions](/docs/developer-center/sprig-sdk/features-by-sdk-version) for details.
| Platform | min SDK Version |
| :- | :- |
| Web | 2.24.0 |
| iOS | 4.17.0 |
| Android | 2.14.0 |
| React Native | 2.15.0 |
If the SDK version(s) are insufficient, you will still be able to launch a survey, but respondents without the minimum SDK version on the target platform may not be presented with the survey, or they will receive a backwards compatible version of the study.
The logic statements that require the minimum SDK versions noted above are:
* Use of logic conditions with AND grouping
* Logic conditions *contains* and *does not contain* for Open Text Questions
* Logic conditions that depends on the answer from a previous question
See the [SDK Versions by Feature](/docs/developer-center/sprig-sdk/features-by-sdk-version#sdk-versions-by-feature) table to determine other limitations based on your SDK version.
### Skip Logic in Surveys
Skip Logic in Surveys functions similarly to how it works in other survey types; however, there are some unique considerations when multiple questions are displayed on the same page. Here are the key points to keep in mind:
* **Single Skip Logic button per page:** When multiple questions appear on the same page, only one Skip Logic button is available, below the last question. You can still use the responses from any question on that page in your logic.
* **Skipping to any question or page:** You can skip a respondent ahead to any page or specific question in the survey, even from a page containing multiple questions.
* **Skipping to a question within a page:** If a respondent is directed to any question other than the first on a page with multiple questions, the questions on that page before the one they're directed to will be hidden from the respondent.
* **Removing Questions:** If you move the second-to-last question off a page that contains Skip Logic, the page will be removed from the survey, including the Skip Logic rules associated with it.
* **Limitations of Skip Logic for Multiple Questions:** Skip Logic cannot be used to redirect respondents from one question to another on the same page.
# Display Logic
There are minimum SDK version requirements to support Display Logic for In-Product Surveys and Feedback Studies. See [Features by SDK Versions](/docs/developer-center/sprig-sdk/features-by-sdk-version) for details.
* Display Logic is available in Surveys, In-Product Surveys, and Feedback studies.
* Display Logic is only available on the Enterprise plan.
Display Logic allows you to show questions in a survey based on a respondent's prior answers in the survey or their specific user attributes.
## Configure Display Logic
1. Navigate to a survey and locate the question you want to conditionally show. Click the **Add Display Logic** button at the top of the question builder.
2. Set criteria based on prior responses in the survey or user attributes stored in Sprig.
* If adding Display Logic to the first question in a survey, only attributes can be used, as there are no prior responses to refer to.
All surveys must have at least one question **without** Display Logic to ensure that blank surveys aren't delivered. Sprig will prevent you from launching a survey that doesn't meet these criteria.
## Ensure Display Logic based on attributes will run
The attribute values specified in Display Logic criteria need to be added to Sprig before the survey is deployed or loaded for the user. If they are not, the respondent may not meet the criteria for the question, and thus the question may not display properly.
If using attributes for Display Logic criteria, you must:
* Track users for In-Product Surveys so that Sprig can look up each person's attribute values when loading the survey for them. Learn more about tracking users.
* Distribute unique Survey links with user identifiers in them so that Sprig can identify who is taking the survey and look up each person's attribute values when loading the survey for them. Learn more about including [user identifiers in survey links](/docs/sprig-studies/surveys/delivering-surveys#enrich-with-identity).
# Randomization
Randomization allows you to randomize the order of response options in certain types of questions, questions within a page, and pages within a survey. Randomization helps prevent bias in results and provides a way for questions that come later in a survey to be seen by some respondents instead of being significantly affected by respondent drop-off.
## Randomize questions or pages within a survey
1. Add a question to your survey
2. Click the **Randomize** button in the Action Bar at the top of the Study Editor. This button won't appear until there's at least one question in the study.
1. If you're doing this in a Survey, you'll have two options:
1. **Randomize all** - randomize all of the pages within your survey and questions that appear together on the same page (questions on page 6 will be shuffled within page 6 but not moved to another page).
2. **Randomize pages only** - randomize pages only; questions that are shown together on a page will stay in the order shown in the Study Editor.
2. If you're working on a Feedback or In-Product study, you won't see any options. Randomization in these study types only randomizes all of the pages in the survey since questions in these surveys don't appear together on the same page.
3. Once randomization is applied, a new button will appear to the right of each question or page title indicating that it has been randomized.
4. To exclude a question or page from randomization, click the randomization button next to the page or question title. The button will change to a "pin" option.
1. Pinning ensures that the question or page stays in the position you've placed it in, for example, if you pin question 3, it will always be the third question for respondents (unless Skip Logic impacts when it's shown).
To remove randomization from a survey, click the button in the Action Bar. All the buttons next to question/page titles will be removed, indicating that randomization is off.
### Things to keep in mind about survey-level Randomization
* If Skip Logic and Randomization are both applied to a question or page, Sprig will ensure that the destinations of Skip Logic don't come before the questions that route to them. For example, if you randomize a 10-question survey, and question 1 has Skip Logic that points to question 5, question 5 won't come before question 1 even if all the questions in the survey are set to randomize.
* Additionally, if Skip Logic uses a response from a question that came earlier in the survey as criteria, Sprig will ensure that the question comes before the Skip Logic that refers to it so that the response is available.
* Survey and page-level randomization will not affect the small preview panel that displays to the right of survey questions/responses when viewing a survey while signed into Sprig. To test randomization in a preview, use the full-screen preview.
## Randomize the order of response options in questions
Randomizing the display of response options is available in [Multiple Choice: Single-Select](/docs/shared-study-foundations/main-tasks/questions#multiple-choice-single-select), [Multiple Choice: Multi-Select](/docs/shared-study-foundations/main-tasks/questions#multiple-choice-multi-select), [Rank Order](#rank-order), and [Matrix](/docs/shared-study-foundations/main-tasks/questions#matrix--accordion) questions.
### Displayed choices limit (Enterprise plan only)
When randomizing the choices in a Matrix or Multiple Choice: Multi-Select question, you'll have the option to limit the number of choices displayed to each respondent. This can be useful when you have a long list of options and don't want to overwhelm respondents with too many choices. Pinned options will always display. The question requires there to be at least 3 choices before this setting becomes available.
When viewing survey data, in the CSV export and the Responses tab, you'll be able to view which options were shown to each respondent, although not the order they were displayed.
# Response Piping
There are minimum SDK version requirements to support Response Piping in In-Product Surveys and Feedback Studies. See [Features by SDK Versions](/docs/developer-center/sprig-sdk/features-by-sdk-version) for details.
By allowing you to pull in a respondent's previous answers to questions and descriptions, Response Piping makes it easy to personalize surveys and provide a more engaging experience.
* Response Piping is available in Surveys, In-Product Surveys, and Feedback studies.
* Response Piping is only available on the Enterprise plan.
To refer to a respondent's previous answer in a question or description, click the Response Piping button in the editing toolbar. This will open a modal that shows all of the previous answers that can be piped into the current question or description. There must be at least one prior question in the survey for the response piping button to appear. When selecting the responses to be piped into a question or description, you'll also set fallback text that will be used if the content that should come from response piping is unavailable for some reason. Once the fallback text is complete you'll see a placeholder in the question text that represents the content that will be filled in as the respondent takes the survey.
If you no longer want to use response piping, you can delete the reference using the **x** that appears when you hover over the placeholder, or by deleting it using your keyboard.
In Surveys, you can pipe from one question on a page to another question on the same page.
Responses to the following question types **can** be piped into questions or descriptions that come later in the survey:
* Open Text
* Rating Scale
* Multiple Choice Single-Select
* Multiple Choice Multi-Select
* The entire list of selections will be piped.
* NPS
* Matrix
* The entire list of selections across rows and columns will be piped.
* Rank Order
Responses to the following question types **cannot** be piped into later questions or descriptions:
* Legal/Consent
* Video/Voice
* Text/URL Prompt
* Recorded tasks
**Note:** Randomization and Response Piping can't be used at the same time. If one has been added to the survey, the other will be disabled.
# Attribute Piping
There are minimum SDK version requirements to use Attribute Piping in In-Product Surveys and Feedback studies. See [Features by SDK Versions](/docs/developer-center/sprig-sdk/features-by-sdk-version) for details.
Use Attribute Piping to create a personalized survey-taking experience for respondents by having Sprig dynamically display a respondent's unique attribute values as they are presented with questions. For example, if you store the names of the companies your respondents belong to in Sprig, you could ask a question like "How has your experience using the Barista Pro coffee maker at ACME Corp been?" instead of "How has your experience using the Barista Pro coffee maker at work been?"
* Attribute Piping is available for Surveys, In-Product Surveys, and Feedback studies.
* Attribute Piping is only available on the Enterprise plan.
### **Important**
In order for unique attribute values to be displayed for respondents:
* The value of the attribute must be stored in Sprig ahead of the survey being displayed to respondents
* For In-Product Surveys, **you must track users**. [Learn more](/docs/Installation/introduction-web/web-javascript).
* For Surveys, **links with user identifiers** need to be distributed (meaning there is one survey link per respondent). [Learn more](/docs/sprig-studies/long-form-surveys/delivering-lfs#enrich-with-identity).
## Add attributes to questions
Adding [attributes](/docs/shared-study-foundations/attributes) to questions follows the same process as Response Piping: above the text field for the question or description, locate the piping button, click to open a menu to select the attribute you want to add, fill in a fallback value in case the data is missing for a respondent, and that's it! Other things to know:
* Attributes can be added to questions and descriptions.
* Attributes can be piped into the first question in a survey (unlike responses).
* The survey preview will show fallback text.
* In Slack notifications, individual responses on the Responses tab, and CSV exports, the exact text displayed to a respondent will be shown; in the Summary tab of a survey, the placeholder text, for example, `city`, will be shown.
* Attribute Piping can be used alongside Randomization.
* If both Attribute Piping and Response Piping are used in a survey, Randomization won't be available because it can't be used alongside Response Piping.
## Launch surveys that include Attribute Piping
No matter which type of survey or study you're adding attributes to, the unique data for each respondent that you want displayed needs to be in Sprig before the survey is rendered/loaded for that user. You can add this data manually through CSV imports or on an ongoing basis with the SDK. If the attribute data is unavailable for any reason or doesn't exist, the fallback text will be displayed.
**In-Product Surveys:** In order to ensure surveys display attribute data, make sure values for those attributes are set for all respondents who will receive the survey, or use Targeting to specify the values/respondents who should receive the survey.
**Surveys:** Since Surveys are delivered through links, in order for Sprig to know what values to show, it needs to know who is taking the survey. This can be accomplished by including a user identifier, such as the user's ID, in the link to the survey. [Learn more](/docs/sprig-studies/surveys/delivering-surveys#enrich-with-identity).
**Note:** Attributes included in Attribute Piping are not available in CSV exports unless they were included in the Targeting criteria for the survey/study.
# Reviewing Responses & Insights
Source: https://docs.sprig.com/docs/shared-study-foundations/responses-and-insights
The real power of Sprig studies is when you start receiving Survey responses, Replay clips, and Test results from your users.
At the top of the results page for each study you launch, Sprig provides statistics to help you understand the study's status and performance throughout its run.
## 1. Locate Your Study
1. Navigate to [your Studies](https://app.sprig.com/studylist/all).
2. Browse, sort by, or search for the study you wish to view. Simply click into the study to review results and AI insights.
## 2. Review Responses, Results, and Recordings
1. Scroll down, scan, and hover on elements on the **Summary**, "Clips", and "Responses" tabs.
* Sprig will automatically generate charts for each question in In-Product Surveys, Surveys, and Feedback studies on the "Summary" tab. Individual responses can be read and segmented on the "Responses" tab.
* Sprig will provide multiple visualizations automatically for Heatmap studies on the "Summary" tab (heatmaps, scroll maps, and click maps)
* Sprig will provide a filterable table view of all replay clips on the "Clips" tab, and automatically generate replay themes using AI on the "Summary" tab
2. Use the filters on the **Summary**, Clips, and Responses tabs to refine the dataset if desired.
* Filter by attributes, question responses, date range, events, etc., depending on the study type
* For more information on filtering study results, [see here ](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy)
## 3. Exclude a Response from Analysis
If a response is skewing your results (a test submission, spam, or an answer that doesn't reflect a real user), you can exclude it from analysis without deleting it.
1. Go to the **Responses** tab of a study.
2. Find the response you want to hide and click the ellipsis (...) on the right side of it.
3. Select **Exclude from analysis**.
The response gets a new status so you can spot it at a glance, and you can reverse this at any time by selecting the same option to un-exclude it.
Excluding a response removes its data from:
* The Data tab
* The AI Study Report (and Study Summary)
* Theme counts
It's still included in:
* The Responses tab
* Total Responses (the count in the study header)
* Open text analysis (theme generation)
* AI Insights
* CSV exports
* The public API and MCP
That same menu also has a **Delete Response** option. Use exclude when you still want the response around (for CSV exports, the API, or later reference) but don't want it factored into analysis. Use delete when the response shouldn't exist at all, for example a test submission created while building the study. Deletion is permanent and can't be undone.
## 4. Share Results
1. Toggle over to the **Responses** or "Clips" tab at the top
2. Scroll and scan the individual responses and Replay recordings.
3. Share results:
1. Export survey and feedback responses by choosing **Download CSV** from the right-hand toolbar
2. Share replay clips by selecting "Share clip" from the playback window
3. Share individual survey and feedback responses by clicking the ellipsis (...) on any response and selecting "Share Response."
4. Use any of Sprig's APIs, Webhooks, or pre-built integrations to export survey response data to other platforms or internal tools
## What's next?
* [Interpret studies](/docs/shared-study-foundations/interpreting-studies)
* Review [AI analysis and insights](/docs/native-ai/ai-analysis)
# Overview of Shared Foundations
Source: https://docs.sprig.com/docs/shared-study-foundations/shared-foundations
### Sprig supports 5 study types:
* [Surveys](/docs/sprig-studies/surveys/index) - create complex surveys with advanced logic options and additional settings. Deliver a modern respondent experience with links that can be embedded in a variety of channels.
* [In-Product Surveys](/docs/sprig-studies/in-product-surveys/index) - a set of questions that can be delivered to respondents via Web and Mobile.
* [Feedback](/docs/sprig-studies/feedback/index) - collect continuous user-initiated feedback via an easily customizable button.
* [Replays](/docs/sprig-studies/replays/index) - capture clips of your users’ experience alongside their in-product feedback.
* *Replays can be added to the other study types to further contextualize the data you collect.*
* [Heatmaps ](/docs/sprig-studies/heatmaps/index)- capture user interactions (scrolls and clicks) with your app in an easy-to-digest visual.
# Shared Foundations Across Studies
There are shared Sprig foundations across these study types in terms of:
## **Study Creation & Management**
* [Events](/docs/shared-study-foundations/events/index) and [Attributes](/docs/shared-study-foundations/attributes) tracking and management
* [**Question types**](/docs/shared-study-foundations/main-tasks/questions)
* [Logic](/docs/shared-study-foundations/main-tasks/survey-logic) (skip logic, randomization, attribute, and response piping)
* [Study triggers and user filters](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy)
* User management with [groups](/docs/shared-study-foundations/main-tasks/groups)
## **Study Review, Analysis, and Export**
* [Completing and Editing Studies](/docs/shared-study-foundations/editing-an-active-study-completing-a-study)
* [Exporting study data](/docs/shared-study-foundations/export-survey-data)
* Organizing studies and responses through [dashboards and folders](/docs/shared-study-foundations/dashboards-and-folders)
* Reviewing [Responses, AI Analysis, and Insights](/docs/shared-study-foundations/responses-and-insights)
# Installing & Getting Started with Sprig
# Feedback Creation
Source: https://docs.sprig.com/docs/sprig-studies/feedback/feedback-creation
Reminders:
* Feedback is supported on web-based delivery methods, such as your web application or website.
* Feedback studies specifically will require a No Code Event URL to deploy
* The minimum SDK version required for Feedback studies is [v2.27.0](https://docs.sprig.com/docs/developer-center/sprig-sdk/features-by-sdk-version)
# 1. Create Feedback
### Option A: Create from Scratch
1. Click on **+ New Study** and select **Feedback** from the **Start from Scratch** widget.
### Option B: Duplicate a Study
1. In the Navigate Pane, click **Studies**.
2. Hold the pointer over the Feedback study you want to copy, then click the ellipses (...) and select **Duplicate**.
3. Edit the study as desired.
### **Option C: Use a Template**
1. Click on **+ New Study** and select **Create from a Template** to harness a company-owned custom template OR a pre-built, expert-made template from Sprig's template library.
# 2. Add or Modify Questions and add Skip Logic
Next, you'll see the **Sprig Study Editor**. Here, you can further customize your Feedback study to match your goal by editing the copy, deleting or adding questions, etc. There are a ton of question types to choose from, plus additional customization options like Skip Logic and Display customization.
1. Optional: In the top field, rename your Feedback study
2. Add or edit your Feedback questions. For more information on question types, see HERE.
3. Optional: Add or edit Skip Logic, randomization, and more.
* [Study Logic guide](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/survey-logic)
* [Study Questions](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/questions)
#### Marking a Question as *Required*
Toggle *Required* on or off at the top of each question card. *Required* questions disallow your users to skip ahead in the study.
#### Drag to Change the Order of Questions
Click on the question number to the left of each question module and drag and drop it to the desired position in your study.
# 3. Audience & Targeting
Once you like what you see, head over to the **Audience** tab, where you can add the part of the website that you wish to deploy your study. You'll also have the options to set filters and to create a hyper-targeted study audience.
### Audience
1. Click on the Audience tab in your Feedback study Website / Web App will already be selected as the Delivery Platform
### Targeting
**Prerequisite:** Sprig installation is completed.
1. Under **Targeting**, select an existing no-code or URL based [Event](/docs/shared-study-foundations/events/index) or click and create a **New Event** to trigger the Feedback study.
2. Optional: Click **+Add [Filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy)** in the "If user..." section of targeting to determine which users are eligible for your study.
### Response Configuration
1. Configure the **Response Settings** for your Feedback study to either run continuously or until a specific number of responses.
1. Continuously: Sprig will allow unlimited responses until the study is marked complete or paused
2. Until a specific number: Sprig will cap the responses at a certain threshold, and mark the study as complete automatically once that number is met
### Optional: Replays
You can choose to add [Replays ](/docs/sprig-studies/replays/index)to your Feedback to gather even more user insights.
* Set the Replay clip recording window (time of clip capture, and whether the replay is captured "Before", "After", or "Before and After" the event trigger.
For more information on replays, please see [here.](/docs/sprig-studies/replays/index)
# 4. Survey & Button Design
Choose the Design tab and you can choose from many style choices for your Feedback button - including color, placement, and label. (See [Feedback look and feel](/docs/sprig-studies/feedback/feedback-look-and-feel) for more information on styling options!)
1. Label - Add name for your label
2. Color - Select light or dark
Once you’ve finished customizing all of your Audience and designs settings, you can preview your study to make sure it looks exactly how you’d like.
# 5. Launch Feedback
Click **Launch Feedback** to launch and start watching your product insights roll in.
# Feedback FAQ's
Source: https://docs.sprig.com/docs/sprig-studies/feedback/feedback-faqs
# FAQ
### Why isn't my Feedback button showing on the page I expect it to?
There are a few reasons why the Feedback study might not be showing up on a particular webpage:
* Your URL No Code event might not be configured correctly. Head over to the [Events](https://app.sprig.com/events) page to verify that your event is recording Activity.
* Your URL No Code event might be clashing with another No Code URL event due to our URL No Code priority system
* To ensure your Feedback study displays properly, it is recommended that you use the highest priority parameters or archive conflict URL events that may no longer be in use
### How do Feedback studies impact MTUs?
Feedback requires a no code URL event trigger to display on your website or application. Events could increase the number of MTUs if you begin to send events from new anonymous visitors or visitors that are not previously tracked in a given month.\
Learn more about MTUs [here](/docs/account-and-settings/usage-muu/usage).
### Does Feedback work with both single-page and multi-page applications?
Yes! Feedback works with applications and websites of all shapes and sizes including both single and multi-page websites and applications.\
With some multi-page applications, the feedback tab might need to be reloaded on every page. This is especially obvious if the Sprig SDK is set to load on delay!
# Feedback Look and Feel
Source: https://docs.sprig.com/docs/sprig-studies/feedback/feedback-look-and-feel
Apply custom Look & Feel styling to match your product or website branding!
## Feedback Study Customization
Adding custom CSS allows you to tailor Feedback buttons and surveys to match your company branding. Common updates customers make include, *but not limited to*:
* Customize Feedback tab styling
* Precise Feedback button positioning
* Change the font and font colors
* Move location of the close button
* Change the shape of the survey container
> **Warning:** Feedback CSS Styling requires Web SDK v2.29.0+. Learn more [here](/docs/developer-center/sprig-sdk/sdk-traffic).
For a deeper dive into how the CSS editor works and how to safely override Sprig's default rules, see [Styling Studies with Custom CSS](/docs/developer-center/styling/styling-your-studies-with-custom-css). If you style colors, also see [Dark Mode](/docs/developer-center/styling/dark-mode).
### Adding Custom CSS to a Feedback study
1. Head over to the [Look & Feel](https://app.sprig.com/settings/feedback-look-and-feel) section in Settings.
2. Select **Add Custom Styles** to open the custom CSS modal
1. At least one draft Feedback study first must exist for your product before you are able to modify Feedback styling
3. Select a study from dropdown for which to apply custom CSS styling
4. Select **Update Preview** to observe how your applied styles impact that particular survey
5. Accept the disclaimer and select **Apply Styles** to make your changes to the studies for which you modified CSS styling
To revert any changes made back to the default style, click **Restore contents to default style**, then select **Apply Styles.**
> 👍 Feedback styling applies on per study basis
>
> If you wish to create a new Feedback study and apply previously used CSS styling to the study, you must copy, paste and apply the styling to the new study under [Look & Feel](https://app.sprig.com/settings/feedback-look-and-feel)
### Supported CSS Classes
#### Button Styles
```css theme={null}
#sprig-feedback-button {
}
.sprig-feedback-button-label {
}
.sprig-feedback-button-right {
}
.sprig-feedback-button-bottom {
}
.sprig-feedback-button-light {
}
.sprig-feedback-button-dark {
}
#sprig-feedback-container {
}
.sprig-feedback-container-left {
}
.sprig-feedback-container-center {
}
.sprig-feedback-container-bottom {
}
```
#### Study Styles
```css theme={null}
/*
Base Typography
Applied generally to every view
*/
html,
body {
/* font-family: -apple-system, BlinkMacSystemFont,
'Segoe UI', Roboto, Helvetica, Arial, sans-serif,
'Apple Color Emoji','Segoe UI Emoji', 'Segoe UI Symbol'; */
}
b {
/* font-weight: 600; */
}
/*
Universal Elements
Footer, dots, and close button
*/
.ul-footer {
/* margin-top: 10px; */
}
.ul-footer-bubble {
/* width: 7px; */
/* height: 7px; */
/* border-radius: 3px; */
}
.close-container {
/* display: flex; */
/* justify-content: flex-end; */
/* width: 100%; */
}
.close-btn {
/* cursor: pointer; */
/* height: 18px; */
/* margin-inline-end: -10px; */
/* position: relative; */
/* top: -10px; */
/* width: 18px; */
/* z-index: 1; */
}
/*
Card Component
Used as the containing element in every question
*/
.ul-card {
/* border-radius: 2px; */
/* font-size: 17px; */
/* line-height: 19px; */
}
.ul-card__container--desktop {
/* padding: 20px 20px 5px 20px; */
/* margin: 15px; */
/* border: 2px solid #fff; */
/* box-shadow: 0px 0px 15px rgba(0, 0, 0, 0.15); */
}
.ul-card__container--mobile {
/* padding: 20px 20px 5px 20px; */
/* border-width: 0; */
/* box-shadow: 0px 0px 5px rgba(0, 0, 0, 0.25); */
/* margin-top: 5px; */
}
.ul-card__container {
/* background: #ffffff; */
/* font-size: 17px; */
/* line-height: 23px; */
/* border-radius: 6px; */
}
.ul-card-main-content {
/* padding: 0 20px 0 20px; */
}
.ul-question {
/* color: #343442; */
/* font-size: 20px; */
/* line-height: 125%; */
/* font-weight: 600; */
}
.ul-caption {
/* margin-top: 8px; */
/* margin-bottom: 15px; */
/* font-size: 15px; */
/* line-height: 130.35%; */
/* letter-spacing: 0.02em; */
/* color: #6c6c6e; */
}
.ul-card-text__button {
/* border-radius: 3px; */
/* color: white; */
/* font-size: 15px; */
/* line-height: 18px; */
/* padding: 10.5px 21px; */
/* font-weight: 600; */
/* border: none; */
/* cursor: pointer; */
}
.ul-card-text__button:disabled {
/* background-color: rgba(100, 100, 100, 0.5); */
/* color: #ffffff; */
}
.ul-card__button-wrapper {
/* margin-top: 4px; */
/* margin-bottom: 3px; */
/* display: flex; */
/* justify-content: center; */
}
.ul-card-skip__button {
/* background-color: rgba(100, 100, 100, 0.5); */
}
/* Rich text */
.ul-rich-text-body {
/* min-height: 2em; */
}
.ul-rich-text-body,
.ul-rich-text-body p {
/* margin-top: 10px; */
/* margin-bottom: 10px; */
}
.ul-rich-text-body p,
.ul-rich-text-body li {
/* font-size: 15px; */
/* line-height: 130.35%; */
/* letter-spacing: 0.02em; */
/* color: #343442; */
/* text-align: left; */
/* white-space: pre-line; */
}
.ul-rich-text-body:last-child,
.ul-rich-text-body li:last-child {
/* margin-bottom: 15px; */
}
/*
Choice Elements
Used in Multiple Choice,
Multiple Choice Multi-Select,
and Matrix Questions
*/
.ul-card--multiple {
}
.ul-card__choices--desktop,
.ul-card__choices--mobile {
/* margin: 5px 0 0 0; */
}
.ul-card__choices {
/* height: 100%; */
}
.choice--mobile {
/* border: 2px solid #e6e6e6; */
}
.choice--desktop {
/* border: 1px solid #e6e6e6; */
}
.choice--desktop,
.choice--mobile {
/* margin-bottom: 7px; */
/* font-size: 15px; */
/* line-height: 20px; */
/* padding: 10px 20px 10px 15px; */
/* background-color: rgba(0, 0, 0, 0.01); */
}
.choice {
/* color: #262136; */
/* box-sizing: border-box; */
/* border-radius: 3px; */
}
.choice--desktop:hover {
/* background-color: rgba(0, 0, 0, 0.05); */
}
.choice--desktop:active,
.choice--mobile:active {
/* background-color: rgba(0, 0, 0, 0.05); */
}
.select-label {
/* margin-left: 10px; */
}
.select-radio {
/* border: 1px solid rgb(225, 225, 225); */
}
/* For active radios */
.ul-select-active-dynamic-style .select-radio {
/* border: 1px solid #FFFFFF !important; */
}
/*
Matrix Question
Applies only to matrix question type
*/
.ul-card--matrix_grid {
/* row-gap: 4px */
}
.ul-card--matrix_container {
/* margin-bottom: 16px; */
}
.ul-matrix-column-label {
/* font-size: 15px; */
/* max-width: 150px; */
}
.ul-matrix-option-wrapper {
/* background: #f9f9f8; */
}
.ul-matrix-last-option {
/* border-start-end-radius: 4px; */
/* border-end-end-radius: 4px; */
}
.ul-matrix-row-label {
/* background: #f9f9f8; */
/* border-end-start-radius: 4px; */
/* border-start-start-radius: 4px; */
/* font-size: 15px; */
/* max-width: 200px; */
}
/*
One to Five Scale (Likert) Question
Applies only to one to five scale (likert) question type
*/
.ul-card--likert {
}
.ul-card--likert__numbers {
/* border-radius: 5px; */
}
.likert-number--mobile {
/* border: 2px solid #e6e6e6; */
/* margin-left: -2px; */
}
.likert-number--desktop {
/* border: 1px solid #e6e6e6; */
/* margin-left: -1px; */
}
.likert-number--desktop,
.likert-number--mobile {
/* background-color: rgba(0, 0, 0, 0.01); */
/* font-size: 18px; */
/* line-height: 24px; */
/* height: 67px; */
}
.likert-number {
}
.likert-number--desktop:hover {
/* background-color: rgba(0, 0, 0, 0.05); */
/* font-weight: 600; */
}
.likert-number--desktop:active,
.likert-number--mobile:active {
/* z-index: 2; */
/* background-color: rgba(0, 0, 0, 0.05); */
/* font-weight: 600; */
}
.ul-card--likert__labels {
/* color: #262136; */
/* font-weight: 600; */
/* font-size: 13px; */
/* line-height: 15px; */
/* margin: 7px 0 10px 0; */
}
/*
NPS Question
Applies only to NPS question type
*/
.ul-card--nps {
}
.ul-card--nps__numbers {
/* border-radius: 5px; */
}
.nps-number--mobile {
/* border: 2px solid #e6e6e6; */
/* margin-left: -2px; */
}
.nps-number--desktop {
/* border: 1px solid #e6e6e6; */
/* margin-left: -1px; */
}
.nps-number--desktop,
.nps-number--mobile {
/* background-color: rgba(0, 0, 0, 0.01); */
/* font-size: 18px; */
/* line-height: 24px; */
/* height: 67px; */
}
.nps-number {
}
.nps-number--desktop:hover {
/* background-color: rgba(0, 0, 0, 0.05); */
/* font-weight: 600; */
}
.nps-number--desktop:active,
.nps-number--mobile:active {
/* z-index: 2; */
/* background-color: rgba(0, 0, 0, 0.05); */
/* font-weight: 600; */
}
.ul-card--nps__labels {
/* color: #262136; */
/* font-weight: 600; */
/* font-size: 13px; */
/* line-height: 15px; */
/* margin: 7px 0 10px 0; */
}
/*
Open Text Card
Applies only to open text card question type
*/
.ul-card--text {
}
.ul-card-text {
/* margin-top: 2px; */
/* margin-bottom: 3px; */
/* padding: 0; */
}
.ul-card-text__container {
/* border-radius: 3px; */
/* margin-bottom: 12px; */
}
.ul-card-text__input--mobile {
/* border-radius: 3px; */
/* border: 2px solid #e6e6e6; */
/* max-height: 63px; */
}
.ul-card-text__input--desktop {
/* border-radius: 3px; */
/* border: 1px solid #e6e6e6; */
/* max-height: 150px; */
}
.ul-card-text__input--desktop,
.ul-card-text__input--mobile {
/* font-size: 15px; */
/* line-height: 20px; */
}
.ul-card-text__input {
/* background: rgba(0, 0, 0, 0.01); */
/* color: #343442; */
/* font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji',
'Segoe UI Emoji', 'Segoe UI Symbol'; */
/* min-height: 63px; */
/* padding: 12px; */
/* resize: none; */
/* width: 100%; */
}
.ul-card-text__input::placeholder {
/* color: rgba(108, 108, 110, 0.5); */
}
.ul-card-text__input:focus {
/* outline: none; */
/* background: white; */
}
.ul-card-text__input--desktop:hover:not(:focus) {
/* background-color: rgba(0, 0, 0, 0.05); */
}
/*
Text / URL Prompt
Applies only to Text / URL Prompt question type
*/
.ul-card__text-url-prompt {
}
.ul-card__text-url-prompt-button {
/* margin-right: auto; */
/* text-overflow: ellipsis; */
/* overflow: hidden; */
/* white-space: nowrap; */
/* max-width: 100%; */
}
/*
Consent / Legal card
Applies only to consent / legal question type
*/
.ul-consent-legal__name-input--mobile {
/* border: 2px solid #e6e6e6; */
}
.ul-consent-legal__name-input--desktop {
/* border: 1px solid #e6e6e6; */
}
.ul-consent-legal__name-input {
/* background: rgba(0, 0, 0, 0.01); */
/* box-sizing: border-box; */
/* color: #343442; */
/* font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji',
'Segoe UI Emoji', 'Segoe UI Symbol'; */
/* padding: 10px 20px 10px 15px; */
/* border-radius: 3px; */
/* font-size: 15px; */
/* line-height: 20px; */
/* margin-bottom: 7px; */
}
.ul-consent-legal__name-input::placeholder {
/* color: rgba(108, 108, 110, 0.5); */
}
.ul-consent-legal__name-input:focus {
/* outline: none; */
/* background: white; */
}
.ul-consent-legal__name-input--desktop:hover:not(:focus) {
/* background-color: rgba(0, 0, 0, 0.05); */
}
.ul-card__consent-legal .choice {
/* font-size: 15px; */
/* padding: 10px 15px 10px 15px; */
/* background-color: rgba(0, 0, 0, 0.01); */
}
.ul-card__consent-legal .choice--desktop:hover {
/* background-color: rgba(0, 0, 0, 0.05); */
}
.ul-card__consent-legal .choice--desktop:active,
.ul-card__consent-legal .choice--mobile:active {
/* background-color: rgba(0, 0, 0, 0.05); */
}
/*
Thank You Card
Applies only to the thank you card
*/
.ul-card--thanks {
}
.ul-thanks-check {
/* text-align: center; */
/* margin-bottom: 20px; */
}
.ul-card--thanks-content {
/* padding: 20px 0 10px 0; */
}
.ul-card--thanks .ul-question {
/* padding-top: 0; */
/* text-align: center; */
}
.ul-card--thanks .ul-caption {
/* padding-top: 0; */
/* text-align: center; */
}
```
> **Warning:** Styling may be limited if using unsupported SDK CSS selectors
>
> While you are able to customize your study layout with any SDK CSS selectors, we highly recommend sticking to the CSS classes listed above for the best support.
>
> Please reach out to [Customer Success](mailto:success@sprig.com) if there are additional CSS selectors we should support.
# Feedback
Source: https://docs.sprig.com/docs/sprig-studies/feedback/index
# What is Sprig Feedback?
Sprig Feedback enables you to always know what your users think by capturing continuous feedback right in your product or website.
Feedback helps teams:
* Easily uncover issues and opportunities across your product before they turn into customer support tickets.
* Measure customer satisfaction and loyalty on autopilot by capturing “always-on” feedback right in your product.
* Hear directly from users throughout their journey and get their ongoing input on how your product can better meet their needs.
Feedback can be launched in-product through your web application and require SDK installation into your product.
## Installation
We have a variety of install methods for [Web](/docs/Installation/introduction-web/index) apps and websites. Installing Sprig and deploying a Feedback study can be done in a few minutes.
# How can I get started?
1. Once installed, [build your Feedback study](/docs/sprig-studies/feedback/feedback-creation), and start collecting insights - instantly.
1. [Question Types](/docs/shared-study-foundations/main-tasks/questions) and [Study Logic](/docs/shared-study-foundations/main-tasks/survey-logic)
2. Targeting: [Study Triggers & User Filters](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy), and [Groups](/docs/shared-study-foundations/main-tasks/groups)
2. Configure [Conversational Surveys](/docs/shared-study-foundations/main-tasks/conversational-surveys) and [Feedback look and feel](/docs/sprig-studies/feedback/feedback-look-and-feel) through CSS styling (available in your Admin Settings).
3. [Reviewing Responses and Insights](/docs/shared-study-foundations/responses-and-insights)
1. [Interpreting Studies](/docs/shared-study-foundations/interpreting-studies)
2. [Sprig AI analysis](/docs/native-ai/ai-analysis)
4. [Feedback FAQs](/docs/sprig-studies/feedback/feedback-faqs)
# Heatmap Creation
Source: https://docs.sprig.com/docs/sprig-studies/heatmaps/heatmap-creation
Heatmaps allow you to visualize interactions and identify painpoints with a specific webpage
Heatmaps can be captured on web and mobile web.
# Creating Heatmaps
## Prerequisite
Before launching a Heatmap study, a Sprig Admin must customize the Heatmap privacy settings.
### Set Privacy Settings
To set Heatmap privacy settings:
1. Navigate to [*Settings > Replays > Configure*](https://app.sprig.com/settings/replays-configure).
1. **Note**: Masking settings apply to Replays and Heatmaps.
2. For web studies:
1. Select the Web tab.
2. Under Web Replay Privacy, choose the appropriate masking setting: Basic, Moderate, or Strict.
1. See [Masking Settings](https://docs.sprig.com/docs/replay-privacy#masking-settings) for more information about the various masking settings for web.
3. Customize Heatmap privacy by masking additional elements:
1. Under Advanced Privacy, add elements by CSS selectors to mask their content.
1. **Note**: Be sure to check your quotation mark formatting. Straight quotes ("") are supported for class masking, but typographic quotes (“”) may cause masking issues.
3. For iOS studies:
1. Select the iOS tab.
2. Under iOS Replay Privacy, choose the appropriate masking setting: Basic, Moderate, or Strict.
1. See [Masking Settings](https://docs.sprig.com/docs/mobile-replay-privacy-performance#masking-settings) for more information about the various masking settings for iOS.
3. Customize Heatmap privacy by masking or unmasking specific elements:
1. Under Advanced Privacy, add elements by class name and choose whether to mask or unmask their content.
1. **Note**: Be sure to check your quotation mark formatting. Straight quotes ("") are supported for class masking, but typographic quotes (“”) may cause masking issues.
For **Android**, all secure form content, including password fields, are not recorded or stored by default. Input fields configured with the `TYPE_NUMBER_VARIATION_PASSWORD` attribute are automatically masked, ensuring that sensitive numeric input is obscured to enhance privacy and security.
## Create a Heatmap
1. Click **+ New Study** and select ***Heatmap***
2. Name the Heatmap and add it to a specific study folder if desired.
### Targeting
1. Under **Targeting** > "Triggers when...", add an [Event](/docs/shared-study-foundations/events/index) or a [URL trigger](/docs/shared-study-foundations/events/no-code-events#adding-no-code-events).
1. The event will determine when users trigger the Heatmap.
2. (Optional) Add additional filters to the "If user..." section.
1. This can be done with user attributes, groups, or event history to ensure you are capturing the right users at the right time in their product experience.
### Attaching a Replay (Optional)
1. Add a **Replay** to collect Replay clips alongside page interaction data.
1. Adding a Replay to a Heatmap will allow you to capture aggregate view data from the Heatmap with individual user sessions from Replays.
Replay clips associated with Heatmaps are not visible in development environments.
### Configure Capture Settings and Options
1. **Capture Settings**: Choose to capture data continuously, until a certain number of page visits, or until a specific date.
2. **Capture Options**: Determine whether to capture data for users once, or unlimited times.
### Launch
1. Click **Launch Heatmap** to start collecting data.
### Add Study Goal (Optional)
1. Adding a study goal for a Heatmap improves the Sprig AI summary results by focusing your specific product question.
# Heatmap Visualizations
After capturing data for at least one user, a Heatmap will display data visualizations. The visualizations will be constructed from the 5000 most recent captures that match any filtering criteria.
The visualizations are categorizes into three forms:
* Heatmaps aggregating clicks into color-coded engagement zones
* Clickmaps showing individual clicks
* Scrollmaps displaying max scroll depth for user sessions
Hover over or click on elements in one of the visualizations to see the total number of clicks on that element and relevant Replay clips, if enabled. For example, if you want to know why users click the Help button, clicking on that area within the Heatmap and observing the attached Replays will help you uncover why users are seeking help.
### Visualization Overview
1. Time filter
2. Visualization controls: Heatmap, Scrollmap & Clickmap
3. (Report metadata) Page name that matches the backdrop image in the report
4. (Report metadata) Captures & clicks contained in the report based on applied filter criteria
5. Device toggles: Switch between Desktop & Mobile Web
6. Change backdrop image
1. The view variations modal will render a few different representations of webpages that are captured in the Heatmap report suggested by Sprig's algorithm.
2. *Note:* Changing a backdrop will save the backdrop for all Sprig team members
7. Heat Card: See additional data and Replay clips (if applicable) of users that interacted with a particular element on the page
1. Percentage of clicks & captures are calculated as a percent of the data represented in the report
# FAQs
### Why do I see a different number of clicks and captures from one background to another?
Heatmaps are built based on interactions with HTML elements that are represented in the selected background.
For example, if the same button spans across two different backgrounds, then the same number of clicks for that particular button will display on both versions of the Heatmap. Conversely, if a particular button appears on one background but not the other, those clicks will not count towards the total.
# Heatmaps
Source: https://docs.sprig.com/docs/sprig-studies/heatmaps/index
Heatmaps allow you to visualize interactions and identify painpoints with a specific webpage
# What are Sprig Heatmaps?
Sprig Heatmaps enable you to see an aggregated visual representation of user behavior within your product such as on landing pages and in-product dashboards. When coupled with [Replays](/docs/sprig-studies/replays/index), you can really see the whole picture and can playback clips of users that interacted with particular elements on a page.
Once the Heatmap collects data from at least one capture, it will fill in with visualization, and you'll be able to toggle between three visualizations:
* Heatmaps aggregate clicks into color-coded engagement zones.
* Clickmaps show individual clicks.
* Scrollmaps show max scroll depth for a user session
Launching Heatmaps will first require installing Sprig SDK into your website.
## Installation
We have a variety of install methods for [Web](/docs/Installation/introduction-web/index) products, so you can easily track behavior and send surveys to users as they experience your website or web app.
# How can I get started?
Review how to create Heatmaps, review results, and more [here](/docs/sprig-studies/heatmaps/heatmap-creation).
Watch a demo video [here](/docs/sprig-studies/heatmaps/index#demo-video)!
## Demo Video
# In-Product Surveys
Source: https://docs.sprig.com/docs/sprig-studies/in-product-surveys/index
Survey specific groups of users in-product to capture their real-time feedback.
## What are Sprig In-Product Surveys?
Sprig In-Product Surveys enable you to target specific users in your product and capture their product experience insights at scale.
Surveys help teams:
* Capture bite-sized user insights to answer the “why” behind product analytics.
* Learn exactly how users feel about new features.
* Measure core flows and ensure they’re meeting customer needs.
* Quickly discover pain points and prioritize what to work on next.
[**Watch a demo video.**](/docs/sprig-studies/in-product-surveys/index#video-tutorial)
### Installation
We have a variety of install methods for [Web](/docs/Installation/introduction-web/index) and [Mobile](/docs/Installation/introduction-mobile/index) products, so you can easily track behavior and send surveys to users as they experience your website, web app, or mobile app.
In-product surveys will require SDK Installation into your product.
# How can I get started?
1. [Creating a Sprig In-Product Survey](/docs/sprig-studies/in-product-surveys/survey-creation/index)
1. [Question Types](/docs/shared-study-foundations/main-tasks/questions) and [Survey Logic](/docs/shared-study-foundations/main-tasks/survey-logic)
2. Targeting: [Study Triggers & User Filters](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy), and [Groups](/docs/shared-study-foundations/main-tasks/groups)
3. [Multi-Language](/docs/shared-study-foundations/main-tasks/multi-language-support) and [Conversational Surveys](/docs/shared-study-foundations/main-tasks/conversational-surveys)
4. [Response Options](/docs/sprig-studies/in-product-surveys/survey-creation/custom-audience-sampling), [Recontact Periods](/docs/sprig-studies/in-product-surveys/survey-creation/resurvey-waiting-period), and [Survey Look and Feel](/docs/sprig-studies/in-product-surveys/microsurvey-look-and-feel)
2. [Testing In-Product Surveys](/docs/sprig-studies/in-product-surveys/study-testing)
3. [Reviewing Responses and Insights](/docs/shared-study-foundations/responses-and-insights)
1. [Interpreting Studies](/docs/shared-study-foundations/interpreting-studies)
2. [Sprig AI analysis](/docs/native-ai/ai-analysis)
3. [Survey diagnostics](/docs/sprig-studies/in-product-surveys/survey-diagnostics-funnel)
# Video Tutorial
# Survey Look and Feel
Source: https://docs.sprig.com/docs/sprig-studies/in-product-surveys/microsurvey-look-and-feel
Apply custom Look & Feel to match your product or website branding!
## Survey Customization
Adding custom CSS, logos and positioning allows you to tailor **In-product and link surveys** to match your company branding. Common styling changes include, *but are not limited to*:
* Add a company logo (link surveys only)
* Change the font and font colors
* Move location of the close button
* Change the shape of the survey container
* Enable/Disable the Sprig signature - Enterprise only
## Logo
Use this option to upload a logo that will be displayed in Shareable Link or Survey studies. File types supported include GIF, JPEG, and PNG.
## Survey Appearance
Positioning is only available for in-product Website Surveys and applies to all relevant Surveys at a Product level.
### Desktop
By default, on desktop/tablet screens, Sprig in-product Surveys will appear in the bottom right corner of your web application, but you can change that to also support:
* Bottom left
* Top left
* Top right
* Centered Modal
In-product Surveys that are Centered Modal have the option of a light or dark overlay and the option to allow or disallow exiting the survey by clicking outside the modal.
With the exception of center-positioned survey, your users may still interact with your website while the survey is visible.
### Mobile
On mobile devices, Sprig Surveys always appear at the bottom of your web application. By default, your website will still be visible as normal on the remainder of the screen and users will be able to interact with it.
In addition, you may choose either a light or dark overlay to focus attention on the survey. In this case, you have the option to allow/disallow the survey to be exited by clicking outside the study.
## Study Style
The color setting adjusts the primary color of the feedback prompt: the survey border, button background, and radio fills all pick it up.
Enter any valid hexadecimal (e.g. `#18B8DF`) or RGB (e.g. `rgb(24, 184, 223)`) color code. The default brand color is a warm charcoal, `#2f2e2c`.
If you enable [Default Dark Mode CSS](/docs/developer-center/styling/dark-mode#turning-it-on), a second **Brand Color** field appears for dark mode, so light and dark studies can use different colors instead of sharing one. The default brand color on dark mode is `#faf9f8`. In this example, the survey's brand color is `#18B8DF` for light mode and `#00008B` for dark.
## In-Product Website Survey Customization
By adding custom CSS, this feature enables you to tailor website surveys to reflect your brand accurately. Common use cases to update your CSS stylesheet are, *but not limited to*:
* Change the font
* Move location of the close button
* Change the shape of the survey container
* Update font color for question titles
* Custom button styling
### Adding Custom CSS to a Survey study
1. Head over to the Surveys > Look & Feel section in Settings.
2. Select **Add Custom Styles** to open the custom CSS modal
3. Select a question type and **Update Preview** to observe how your applied styles impact that particular question
4. Accept the disclaimer and select **Apply Styles** to make your changes to the studies for which you modified CSS styling
To revert any changes made back to the default style, click **Restore contents to default style**, then select **Apply Styles.**
> 👍 Survey CSS styling applies on per product basis
>
> Any new study created will be styled as configured under [Surveys > Look & Feel](https://app.sprig.com/settings/look-and-feel)
>
> Updating CSS styling will apply to all surveys, including active ones.
### Supported CSS Classes
#### Survey Styles:
```css theme={null}
/*
Base Typography
Applied generally to every view
*/
html,
body {
/* font-family: -apple-system, BlinkMacSystemFont,
'Segoe UI', Roboto, Helvetica, Arial, sans-serif,
'Apple Color Emoji','Segoe UI Emoji', 'Segoe UI Symbol'; */
}
b {
/* font-weight: 600; */
}
/*
Universal Elements
Footer, dots, and close button
*/
.ul-footer {
/* margin-top: 10px; */
}
.ul-footer-bubble {
/* width: 7px; */
/* height: 7px; */
/* border-radius: 3px; */
}
.close-container {
/* display: flex; */
/* justify-content: flex-end; */
/* width: 100%; */
}
.close-btn {
/* cursor: pointer; */
/* height: 18px; */
/* margin-inline-end: -10px; */
/* position: relative; */
/* top: -10px; */
/* width: 18px; */
/* z-index: 1; */
}
/*
Card Component
Used as the containing element in every question
*/
.ul-card {
/* border-radius: 2px; */
/* font-size: 17px; */
/* line-height: 19px; */
}
.ul-card__container--desktop {
/* padding: 20px 20px 5px 20px; */
/* margin: 15px; */
/* border: 2px solid #fff; */
/* box-shadow: 0px 0px 15px rgba(0, 0, 0, 0.15); */
}
.ul-card__container--mobile {
/* padding: 20px 20px 5px 20px; */
/* border-width: 0; */
/* box-shadow: 0px 0px 5px rgba(0, 0, 0, 0.25); */
/* margin-top: 5px; */
}
.ul-card__container {
/* background: #ffffff; */
/* font-size: 17px; */
/* line-height: 23px; */
/* border-radius: 6px; */
}
.ul-card-main-content {
/* padding: 0 20px 0 20px; */
}
.ul-question {
/* color: #343442; */
/* font-size: 20px; */
/* line-height: 125%; */
/* font-weight: 600; */
}
.ul-caption {
/* margin-top: 8px; */
/* margin-bottom: 15px; */
/* font-size: 15px; */
/* line-height: 130.35%; */
/* letter-spacing: 0.02em; */
/* color: #6c6c6e; */
}
.ul-card-text__button {
/* border-radius: 3px; */
/* color: white; */
/* font-size: 15px; */
/* line-height: 18px; */
/* padding: 10.5px 21px; */
/* font-weight: 600; */
/* border: none; */
/* cursor: pointer; */
}
.ul-card-text__button:disabled {
/* background-color: rgba(100, 100, 100, 0.5); */
/* color: #ffffff; */
}
.ul-card__button-wrapper {
/* margin-top: 4px; */
/* margin-bottom: 3px; */
/* display: flex; */
/* justify-content: center; */
}
.ul-card-skip__button {
/* background-color: rgba(100, 100, 100, 0.5); */
}
/* Rich text */
.ul-rich-text-body {
/* min-height: 2em; */
}
.ul-rich-text-body,
.ul-rich-text-body p {
/* margin-top: 10px; */
/* margin-bottom: 10px; */
}
.ul-rich-text-body p,
.ul-rich-text-body li {
/* font-size: 15px; */
/* line-height: 130.35%; */
/* letter-spacing: 0.02em; */
/* color: #343442; */
/* text-align: left; */
/* white-space: pre-line; */
}
.ul-rich-text-body:last-child,
.ul-rich-text-body li:last-child {
/* margin-bottom: 15px; */
}
/*
Choice Elements
Used in Multiple Choice,
Multiple Choice Multi-Select,
and Matrix Questions
*/
.ul-card--multiple {
}
.ul-card__choices--desktop,
.ul-card__choices--mobile {
/* margin: 5px 0 0 0; */
}
.ul-card__choices {
/* height: 100%; */
}
.choice--mobile {
/* border: 2px solid #e6e6e6; */
}
.choice--desktop {
/* border: 1px solid #e6e6e6; */
}
.choice--desktop,
.choice--mobile {
/* margin-bottom: 7px; */
/* font-size: 15px; */
/* line-height: 20px; */
/* padding: 10px 20px 10px 15px; */
/* background-color: rgba(0, 0, 0, 0.01); */
}
.choice {
/* color: #262136; */
/* box-sizing: border-box; */
/* border-radius: 3px; */
}
.choice--desktop:hover {
/* background-color: rgba(0, 0, 0, 0.05); */
}
.choice--desktop:active,
.choice--mobile:active {
/* background-color: rgba(0, 0, 0, 0.05); */
}
.select-label {
/* margin-left: 10px; */
}
.select-radio {
/* border: 1px solid rgb(225, 225, 225); */
}
/* For active radios */
.ul-select-active-dynamic-style .select-radio {
/* border: 1px solid #FFFFFF !important; */
}
/*
Matrix Question
Applies only to matrix question type
*/
.ul-card--matrix_grid {
/* row-gap: 4px */
}
.ul-card--matrix_container {
/* margin-bottom: 16px; */
}
.ul-matrix-column-label {
/* font-size: 15px; */
/* max-width: 150px; */
}
.ul-matrix-option-wrapper {
/* background: #f9f9f8; */
}
.ul-matrix-last-option {
/* border-start-end-radius: 4px; */
/* border-end-end-radius: 4px; */
}
.ul-matrix-row-label {
/* background: #f9f9f8; */
/* border-end-start-radius: 4px; */
/* border-start-start-radius: 4px; */
/* font-size: 15px; */
/* max-width: 200px; */
}
/*
One to Five Scale (Likert) Question
Applies only to one to five scale (likert) question type
*/
.ul-card--likert {
}
.ul-card--likert__numbers {
/* border-radius: 5px; */
}
.likert-number--mobile {
/* border: 2px solid #e6e6e6; */
/* margin-left: -2px; */
}
.likert-number--desktop {
/* border: 1px solid #e6e6e6; */
/* margin-left: -1px; */
}
.likert-number--desktop,
.likert-number--mobile {
/* background-color: rgba(0, 0, 0, 0.01); */
/* font-size: 18px; */
/* line-height: 24px; */
/* height: 67px; */
}
.likert-number {
}
.likert-number--desktop:hover {
/* background-color: rgba(0, 0, 0, 0.05); */
/* font-weight: 600; */
}
.likert-number--desktop:active,
.likert-number--mobile:active {
/* z-index: 2; */
/* background-color: rgba(0, 0, 0, 0.05); */
/* font-weight: 600; */
}
.ul-card--likert__labels {
/* color: #262136; */
/* font-weight: 600; */
/* font-size: 13px; */
/* line-height: 15px; */
/* margin: 7px 0 10px 0; */
}
/*
NPS Question
Applies only to NPS question type
*/
.ul-card--nps {
}
.ul-card--nps__numbers {
/* border-radius: 5px; */
}
.nps-number--mobile {
/* border: 2px solid #e6e6e6; */
/* margin-left: -2px; */
}
.nps-number--desktop {
/* border: 1px solid #e6e6e6; */
/* margin-left: -1px; */
}
.nps-number--desktop,
.nps-number--mobile {
/* background-color: rgba(0, 0, 0, 0.01); */
/* font-size: 18px; */
/* line-height: 24px; */
/* height: 67px; */
}
.nps-number {
}
.nps-number--desktop:hover {
/* background-color: rgba(0, 0, 0, 0.05); */
/* font-weight: 600; */
}
.nps-number--desktop:active,
.nps-number--mobile:active {
/* z-index: 2; */
/* background-color: rgba(0, 0, 0, 0.05); */
/* font-weight: 600; */
}
.ul-card--nps__labels {
/* color: #262136; */
/* font-weight: 600; */
/* font-size: 13px; */
/* line-height: 15px; */
/* margin: 7px 0 10px 0; */
}
/*
Open Text Card
Applies only to open text card question type
*/
.ul-card--text {
}
.ul-card-text {
/* margin-top: 2px; */
/* margin-bottom: 3px; */
/* padding: 0; */
}
.ul-card-text__container {
/* border-radius: 3px; */
/* margin-bottom: 12px; */
}
.ul-card-text__input--mobile {
/* border-radius: 3px; */
/* border: 2px solid #e6e6e6; */
/* max-height: 63px; */
}
.ul-card-text__input--desktop {
/* border-radius: 3px; */
/* border: 1px solid #e6e6e6; */
/* max-height: 150px; */
}
.ul-card-text__input--desktop,
.ul-card-text__input--mobile {
/* font-size: 15px; */
/* line-height: 20px; */
}
.ul-card-text__input {
/* background: rgba(0, 0, 0, 0.01); */
/* color: #343442; */
/* font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji',
'Segoe UI Emoji', 'Segoe UI Symbol'; */
/* min-height: 63px; */
/* padding: 12px; */
/* resize: none; */
/* width: 100%; */
}
.ul-card-text__input::placeholder {
/* color: rgba(108, 108, 110, 0.5); */
}
.ul-card-text__input:focus {
/* outline: none; */
/* background: white; */
}
.ul-card-text__input--desktop:hover:not(:focus) {
/* background-color: rgba(0, 0, 0, 0.05); */
}
/*
Text / URL Prompt
Applies only to Text / URL Prompt question type
*/
.ul-card__text-url-prompt {
}
.ul-card__text-url-prompt-button {
/* margin-right: auto; */
/* text-overflow: ellipsis; */
/* overflow: hidden; */
/* white-space: nowrap; */
/* max-width: 100%; */
}
/*
Consent / Legal card
Applies only to consent / legal question type
*/
.ul-consent-legal__name-input--mobile {
/* border: 2px solid #e6e6e6; */
}
.ul-consent-legal__name-input--desktop {
/* border: 1px solid #e6e6e6; */
}
.ul-consent-legal__name-input {
/* background: rgba(0, 0, 0, 0.01); */
/* box-sizing: border-box; */
/* color: #343442; */
/* font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji',
'Segoe UI Emoji', 'Segoe UI Symbol'; */
/* padding: 10px 20px 10px 15px; */
/* border-radius: 3px; */
/* font-size: 15px; */
/* line-height: 20px; */
/* margin-bottom: 7px; */
}
.ul-consent-legal__name-input::placeholder {
/* color: rgba(108, 108, 110, 0.5); */
}
.ul-consent-legal__name-input:focus {
/* outline: none; */
/* background: white; */
}
.ul-consent-legal__name-input--desktop:hover:not(:focus) {
/* background-color: rgba(0, 0, 0, 0.05); */
}
.ul-card__consent-legal .choice {
/* font-size: 15px; */
/* padding: 10px 15px 10px 15px; */
/* background-color: rgba(0, 0, 0, 0.01); */
}
.ul-card__consent-legal .choice--desktop:hover {
/* background-color: rgba(0, 0, 0, 0.05); */
}
.ul-card__consent-legal .choice--desktop:active,
.ul-card__consent-legal .choice--mobile:active {
/* background-color: rgba(0, 0, 0, 0.05); */
}
/*
Rank Order
Applies only to Rank Order question type
*/
.ul-card-rank__labels {
/* font-size: 14px; */
/* font-style: normal; */
/* font-weight: 600; */
/* line-height: 150%; */
}
.ul-card--rank__question-inner-container {
/* padding: 0 16px; */
}
.ul-card-rank__list {
/* list-style-type: none; */
/* padding-inline-start: 0; */
/* margin: 4px 0; */
}
.ul-card-rank__option {
/* display: flex; */
/* align-items: center; */
/* padding: 8px; */
/* gap: 8px; */
/* align-self: stretch; */
/* border: 1px solid #e2e3e1; */
/* border-radius: 8px; */
/* margin-bottom: 4px; */
}
.ul-card-rank__option:last-child {
/* margin-bottom: 0; */
}
.ul-card-rank__drag-btn {
/* display: inline-flex; */
/* align-items: center; */
/* justify-content: center; */
/* line-height: 0; */
/* padding: 0; */
/* width: 25px; */
/* height: 25px; */
/* margin-left: auto; */
/* color: #0B2330; */
/* cursor: grab; */
/* background: transparent; */
/* border: 0; */
}
.ul-card-rank__drag-btn:active {
/* cursor: grabbing; */
}
.ul-card-rank__option:active {
/* cursor: grabbing; */
}
.ul-card-rank__option svg {
/* display: block; */
}
.ul-card-rank__option.is-dragging {
/* opacity: 1; */
/* box-shadow: 0 8px 25px rgba(0, 0, 0, 0.15), 0 3px 10px rgba(0, 0, 0, 0.1); */
/* z-index: 1000; */
/* background: white; */
/* border-color: #0B2330; */
}
.ul-card-rank__option.is-drop-target {
/* background: rgba(11, 35, 48, 0.10); */
/* border-radius: 8px; */
/* border-color: rgba(11, 35, 48, 0.10); */
}
.ul-card-rank__option.is-drop-target select,
.ul-card-rank__option.is-drop-target span,
.ul-card-rank__option.is-drop-target button {
/* visibility: hidden; */
}
.ul-card-rank__option span {
/* font-size: 14px; */
/* font-weight: 400; */
}
.ul-card-rank__select {
/* appearance: none; */
/* -webkit-appearance: none; */
/* -moz-appearance: none; */
/* box-sizing: border-box; */
/* height: 25px; */
/* min-height: 25px; */
/* border: 1px solid #E2E3E1; */
/* border-radius: 4px; */
/* font-size: 14px; */
/* line-height: 1.4; */
/* padding: 2px 28px 2px 8px; */
/* background-image: url("data:image/svg+xml;utf8,"); */
/* background-repeat: no-repeat; */
/* background-position: right 8px center; */
/* background-size: 12px 12px; */
/* background-color: #FFF; */
/* cursor: pointer; */
}
.ul-card-rank__select.ul-card-rank__select--placeholder {
/* color: #B0B5B7; */
}
/*
Thank You Card
Applies only to the thank you card
*/
.ul-card--thanks {
}
.ul-thanks-check {
/* text-align: center; */
/* margin-bottom: 20px; */
}
.ul-card--thanks-content {
/* padding: 20px 0 10px 0; */
}
.ul-card--thanks .ul-question {
/* padding-top: 0; */
/* text-align: center; */
}
.ul-card--thanks .ul-caption {
/* padding-top: 0; */
/* text-align: center; */
}
```
> **Warning:** Styling may be limited if using unsupported SDK CSS selectors
>
> While you are able to customize your study layout with any SDK CSS selectors, we highly recommend sticking to the CSS classes listed above for the best support.
>
> Please reach out to [Customer Success](mailto:success@sprig.com) if there are additional CSS selectors you'd like to have supported.
## Want help customizing your CSS?
[See here](/docs/developer-center/styling/styling-your-studies-with-custom-css) for more information.
# Study Testing
Source: https://docs.sprig.com/docs/sprig-studies/in-product-surveys/study-testing
Test a draft study directly on your website or mobile application - no staging/development environment needed!
## Study Testing
Sprig's study preview feature can help ensure your study event triggers are working as expected by enabling you to test your study directly on your website or mobile application.
While studies can be tested in staging or development environments, we recommend utilizing this study preview feature to verify your study is configured correctly. Note that SDK install is required.
Before you get started:
* Ensure that your SDK is updated to a supported [version](/docs/developer-center/sprig-sdk/features-by-sdk-version)
* Note that for mobile study testing specifically, there are additional update requirements if your SDK install was completed before September 2023.
* To test directly in your mobile app, ensure that you have your deep link URL accessible - if you do not have access, a mobile developer will be able to provide it to you
In order to test your study within your Website or Mobile App, your event must be **active**. An inline URL Event configured on a draft study is not yet active. If you'd like to preview a draft study using a No-Code URL Event, [create it from the Events menu](/docs/shared-study-foundations/events/no-code-events#adding-no-code-events) first, then use that new event in your draft study.
### Testing a Study on your Website or Mobile App
1. Create a new study, customize the survey content, and select your platform and targeting criteria.
2. After selecting your platform and targeting criteria, you will have the ability to select **Preview on your website** or **Preview on your mobile app** from the study preview sidebar.
3. Enter the website URL or your mobile app’s deep link URL and click **Generate preview**.
1. Make sure to use the correct website domain if you have installed Sprig across different domains and/or with different installation methods.
4. Click **Open preview**, scan the QR code to view on a mobile device, or copy the the link directly
1. Anyone with the generated link will be able to view the preview until you launch the study or stop the preview
5. If you are required to sign into your product after clicking the preview link, you will need to come back to your study in Sprig and repeat steps 2 - 3 before revisiting the preview link
6. Replicate the event trigger(s) that should surface your study.
1. Attribute filters, response settings or recontact periods you have configured for this study are not considered for the survey preview
7. End the preview by launching the study or click **Stop preview** in the preview modal.
## FAQs
### Why am I unable to trigger my study in the generated preview?
There are a few reasons this may be happening:
* Web Studies
* Current SDK is not a supported [version](/docs/developer-center/sprig-sdk/features-by-sdk-version)
* SDK update was not made in all places where the Sprig SDK is installed
* Study Event Trigger is an inline URL Event that hasn't been published yet
* Study Event Triggers may not be configured correctly
* Study is not in one of the following statuses: New, In-Progress, or Draft
* Mobile studies:
* Current SDK is not a supported [version](/docs/developer-center/sprig-sdk/features-by-sdk-version)
* Note: SDK version must be both updated and pushed out to the device and application that you are using to test a study
* For initial installs before September 2023, an additional code snippet is required: see appropriate install guide ([iOS](/docs/Installation/introduction-mobile/ios-sdk-installation#study-previews), [Android](/docs/Installation/introduction-mobile/android-sdk-installation/index#study-previews), [React Native](/docs/Installation/introduction-mobile/react-native-module#study-previews))
* Incorrect deep link URL was pasted into your the Preview on your website/app modal
# Response Options
Source: https://docs.sprig.com/docs/sprig-studies/in-product-surveys/survey-creation/custom-audience-sampling
## Configuring Sampling Parameters
Sprig offers the ability to customize the response options for the Web and Mobile platforms.
Sprig, by default, will determine the total number of responses that need to be collected in order to meet [statistical significance](https://www.greenbook.org/marketing-research/statistical-significance-03377#:~:text=What%20is%20statistical%20significance%3F\&text=To%20say%20that%20the%20observed,drawn%20would%20yield%20similar%20results.) (yes, we do all the math, so you don't have to!).
When adjusting response sampling, there are two things you have to consider:
1. Response Options
2. Results Confidence (Adjust Confidence)
There are two response options to choose from, **Until a specified number** or **Ongoing**.
#### Until a specified number
Sprig will collect a fixed number of responses, after which the study will be set to *complete*.
#### Ongoing
Sprig will deliver a fixed number of responses per day and will continue doing so until paused (or marked as completed).
#### Results Confidence (Adjust Confidence)
By default, we recommend that all studies run at the 95% confidence interval (High confidence, slower results). However, you do have the option to adjust to accommodate your own user insights needs.
* Lower confidence, fastest results (80% confidence interval)
* Medium confidence, faster results (90% confidence interval)
* High confidence, slower results (95% confidence interval) - Default
* Highest confidence, slowest results (98% confidence interval)
* Custom
**How does Sprig calculate these numbers?** We use the sample size calculation for a binary outcome. This calculation is applicable to all of the question types offered by Sprig. [Click here](https://docs.google.com/document/d/1tpzyAYNZ6qJDRwb5SSIKSaRuXwF7r4s5ApE3y8GcpuY/edit?usp=sharing) to read more.
#### Custom Response Sampling
Sprig incorporates best-in-class practices to limit [sampling bias](https://www.scribbr.com/methodology/sampling-bias/#:~:text=Sampling%20bias%20occurs%20when%20some,external%20validity%2C%20specifically%20population%20validity.). How does this sampling work? We use what's known as the [leaky bucket](https://en.wikipedia.org/wiki/Leaky_bucket).
What you should know is that under standard guidelines, not everyone that qualifies for a study will receive one. Instead, we throttle sends to ensure a study runs over a period of time (days, or in some cases, a week, depending on response rate)
#### How to Override Sampling in Sprig
Want to have more control over your study delivery? By setting a Sprig study to **Deliver Continuously** AND selecting **Custom** from the dropdown, you can effectively nullify our pre-sets for sampling
Please enter a value between 1 - 100% for custom sampling. Setting this value to 100% will ensure that all qualifying users will receive a study.
Another option is to tell Sprig exactly how many responses to collect before the study should be set to complete.
# In-Product Survey Creation
Source: https://docs.sprig.com/docs/sprig-studies/in-product-surveys/survey-creation/index
This section covers in-product survey creation, from building, [adding or changing questions](#2-add-or-modify-questions-and-skip-logic), [configuring targeting](#3-audience--targeting), and controlling data flow through response settings and recontact options.
See FAQ's [here](/docs/sprig-studies/in-product-surveys/survey-creation/index#faqs).
# 1. Create a Survey
### Option A: [Use AI File Upload](/docs/native-ai/design-agent/ai-file-upload-builder)
* Click on **+ New Study** and then **Upload Survey Draft.** Then, upload your file and let AI generate and program your survey for you based on your draft.
### **Option B: [Use an AI Prompt](/docs/native-ai/design-agent/prompt-based-builder)**
* Click on **+ New Study** and then **Create with AI**. Then, simply input your Agent Context and let AI generate a few first-pass template ideas for you based on your use case.
### Option C: Create from Scratch
* Click on **+ New Study** and select "In-Product Survey" from the **Start from Scratch** widget
### Option D: Duplicate a Study
1. In the Navigate Pane, click **Studies**.
2. Hold the pointer over the In-Product Survey study you want to copy, then click the ellipses (...) and select **Duplicate**.
3. Edit the study as desired.
### **Option E: Use a Template**
* Click on **+ New Study** and select **Create from a Templates** to harness a company-owned custom template OR use a pre-built, expert-made template from Sprig's template library.
Next, you'll see the **Sprig Study Editor.** Here, you can further customize your survey to match your goal by editing the copy, deleting or adding questions, etc.
# 2. Add or Modify Questions and Skip Logic
There are a ton of question types to choose from, plus additional customization options like consent/legal modules, response piping, randomization, skip logic, and more. See HERE for more information.
1. In the top field of the builder, **rename your study** to something recognizable.
2. Select **Add Questions+** to add additional questions to your study, or click into individual questions to made modifications. You can also duplicate questions and select to "Insert new below" by clicking on the ellipses (**...**) in the upper right corner of any question box.
You can compress the survey using the arrow in the upper right corner of the builder for easy review of all questions and logic.
3. **Customize your survey logic** using skip logic, randomization of questions or response options, piping of responses and/or attributes, and more.
For more information about our survey questions, logic, etc. please see the below:
* [Study Logic guide](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/survey-logic)
* [Study Questions](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/questions)
#### Marking a Question as *Required*
Toggle *Required* on or off at the top of each question card. *Required* questions disallow your users to skip ahead in the study.
#### Drag to Change the Order of Questions
Click on the question number to the left of each question module and drag and drop it to the desired position in your study.
Once you like what you see, head over to the **Audience** tab, where you can choose your delivery method. Surveys can be sent via your **Website** or **Mobile App**. You'll also set your filters and triggers to create a hyper-targeted survey audience. Note that installation of Sprig is required to complete this step.
# 3. Audience & Targeting
### Audience
1. Click on the **Audience** tab in your study.
2. Select a compatible delivery option based on the study type shown above.
### Targeting
Prerequisite: Sprig installation is complete.
1. Under **Targeting**, select an existing [Event](/docs/shared-study-foundations/events/index), or click **New Event** to create a new event trigger (such as a no-code event, compatible with web studies).
2. Optional: Click **+ Add [Filter](/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy)** in the "If User..." section of targeting to narrow down which users are eligible for your study using events and [attributes](/docs/shared-study-foundations/attributes) For more information, please see [here](https://docs.sprig.com/docs/shared-study-foundations/main-tasks/study-triggers-user-filters-and-groups-copy).
### Response Configuration
1. Next, configure [**Response Options**](/docs/sprig-studies/in-product-surveys/survey-creation/custom-audience-sampling) for your survey. Response options can be set to:
1. Until a Specific Number
* Sprig will collect this specific number of responses and then automatically mark the study as complete
2. Ongoing
* Sprig will collect either a certain number of responses per day OR a certain sampling rate per day, depending on what is configured by the user
Both options can be customized, allowing you to change the number of responses you're collecting by clicking the `Adjust Confidence` dropdown and selecting your desired option.
1. Optional: Configure the [**Recontact Options**](/docs/sprig-studies/in-product-surveys/survey-creation/resurvey-waiting-period).
* Sprig offers an account wide recontact option that applies to all surveys in the account. Here, you can elect to override the recontact period as needed on a per-survey basis.
### Optional: Add a Replay
1. You can add a [Replay](/docs/sprig-studies/replays/index) to your Study to gather even more user insights. The replay will follow the same targeting criteria as the In-Product survey it is attached to.
2. Set the Replay clip recording window (time of clip capture, and whether the replay is captured "Before", "After", or "Before and After" the event trigger.
For more information on replays, please see [here](/docs/sprig-studies/replays/index).
Once you’ve finished customizing all of your Audience settings, you can [preview your survey](/docs/sprig-studies/in-product-surveys/study-testing) to make sure it looks exactly how you’d like.
# 4. Survey Design
Sprig offers two different experiences when it comes to survey design:
1. Sprig Standard Design
2. Conversational UI
You can configure the design on a per-study basis.
For more information, see [Conversational Surveys](/docs/shared-study-foundations/main-tasks/conversational-surveys).
# 5. Launch your Study
1. Click **Launch Survey** and start watching the insights roll in!
# FAQ's
### How does Sprig automatically distribute response collection?
To reduce bias and ensure a greater distribution of visitor responses, Sprig uses a leaky bucket algorithm to prevent a survey from collecting all of its responses immediately and completing. When more responses come in over a shorter period of time, Sprig will automatically reduce the rate at which a survey is sent out. As time increases, this rate will go back up and continue to adjust based on the survey's response rate.
### How can I send a survey to all eligible visitors?
In some cases, you might want to send a survey to all of your eligible visitors who trigger an event. This can be done by:
* Setting your survey to collect responses on an `Ongoing` basis.
* From the `Adjust Confidence` dropdown, select `Custom`
* Set the text input to send to `100` percent of your users.
* Save changes.
Note that this will prioritize this survey over others, and can reduce the rate of responses for other surveys using the same trigger event.
### What happens if I am running multiple surveys using the same event trigger?
When multiple surveys rely on the same event trigger, Sprig will automatically rotate through each survey to ensure that each survey is seen and is collecting responses at an appropriate rate. Surveys might still collect responses at different rates, due to different filter criteria (e.g. visitor attributes qualifying them) and recontact waiting periods.
# Link Studies
Source: https://docs.sprig.com/docs/sprig-studies/in-product-surveys/survey-creation/link-survey
Sprig Link Survey Basics
Link Studies are In-Product Surveys delivered via a shareable link rather than as an in-app intercept. This study type is no longer supported for new creation. Existing Shareable Link In-Product Surveys will continue to collect responses. They can still be embedded, enriched, and delivered in the same way as Surveys. See our documentation on [Delivering Link-Based Studies](/docs/sprig-studies/surveys/delivering-surveys). To share new surveys using a link, use [Surveys](/docs/sprig-studies/surveys/index) instead. If you use Shareable Links frequently, talk to our [Sales team](https://sprig.com/sales-demos) about adding Surveys to your contract.
# Recontact Waiting Period
Source: https://docs.sprig.com/docs/sprig-studies/in-product-surveys/survey-creation/resurvey-waiting-period
Sprig offers customers the ability to choose how often individual users can receive Sprig studies. This is done by adjusting the **Recontact Waiting Period** on the **Settings** page.
The Recontact Waiting Period is the minimum number of days Sprig waits after a user receives a study before sending them another study, and applies to all visitors who have seen a survey, even if they have not responded or completed it.
For Sprig Surveys, this feature ensures that you avoid over-surveying your users. For Sprig Replays, this feature ensures you avoid capturing multiple clips from the same users in a given period.
Seeing multiple studies? By design, the recontact window is only enforced in production Sprig environments. For testing purposes, a Sprig visitor record will always see a study in development Sprig environments, as long as they meet the qualifying event and attribute filters, regardless of when they last saw a prior study.
Choosing a recontact waiting period of 30 days, for example, means that a given user will not see any new studies for at least 30 days after the last time they were shown a study. (The one exception to this is link studies, as these studies are anonymous and delivery to users is not managed by Sprig.)
This is a default setting and will apply to all studies. Note also that, by default, the same user will never see the same study. This is to ensure data quality for your studies in addition to preventing study fatigue. However, for web and mobile studies, you may override this behavior on a per-study basis through the Recontact Options in the study creation process:
Choosing the **Allow users to retake the study** option allows the same user to retake the study. Additionally, specifying the recontact window here will override the default value specified in the settings.
Learn about Best Practices for choosing your recontact waiting period [here](/docs/study-best-practices/how-often-to-survey).
# Survey Diagnostics Funnel
Source: https://docs.sprig.com/docs/sprig-studies/in-product-surveys/survey-diagnostics-funnel
Understand the estimated population of end users at particular steps in Sprig’s survey selection and contact engine
# Survey Diagnostics Funnel Overview
The Survey Diagnostics Funnel allows you to understand the estimated population of end users at particular steps in Sprig’s survey selection and contact engine. The funnel will enable study owners to self diagnose why they may not be getting as many responses as expected and troubleshoot survey design.
Sprig uses an event-driven model. Each time a user sends an event to our backend, we check to see if there is a potential survey or set of surveys to present to the user. This process is documented in a surveys engagement funnel located in the Responses widget. Here’s an example of what a survey engagement funnel may look like:
It’s important to note that not all of these steps will be present in each funnel.
In particular, the following steps may not always be shown, as these will be dependent on the configuration of the study in question as well as other studies on the account:
* Matched Filters
* Included in Sampling
* Selected for this Study
## Survey selection works in the following steps:
1. A single event from a single visitor is received by the Sprig backend
2. We select the entire universe of in-progress surveys for that environment
3. The survey selector code begins to filter this universe down by filtering out surveys that:
1. Have the wrong SDK version\
Step: “Had required SDK”
2. Do not match resurvey criteria\
Step: “Met resurvey criteria”
3. Have a different event trigger than the one the user triggered\
Step: “Triggered event”
4. That the user has already seen (based on resurvey criteria)\
Step: “Hadn’t seen this study yet”
5. That the user doesn’t match filters and attributes for\
Step: “Matched Filters”
6. Need to be sampled or throttled\
Step: “Included in sampling”\
Step: “Selected for this study”
4. The result may be:
1. A single survey that is then served to the user
2. A randomized array of surveys, from which the first will be served to the user
The last four steps in the engagement funnel are:
1. Received Study
2. Viewed Study
3. Started Responding
4. Completed Study
These steps happen after the universe of surveys has been filtered down to the one particular survey this user should see, and that survey has been sent to their SDK instance.
## Using the Diagnostics Funnel
1. For any active or completed Web or Mobile Survey, navigate to the Survey Results page.
2. Select ***Inspect*** to launch the **Inspect Response Rate** modal.
1) The debugger will show you a list of checkpoints and the estimated population of end users at each checkpoint.
#### Note on Limitations:
* Survey Diagnostics Funnel will be unavailable for surveys completed before October 2023.
* Audience population estimations are limited to the last 30 days of an active survey.
* If any edit is made to an active study, including copy updates or targeting criteria, the diagnostics funnel will **reset** and begin collecting data from time last updated.
## Checkpoint Steps
Checkpoint steps and corrective measures are detailed below:
| Checkpoint | Step Details | Possible Corrective Measure |
| - | - | - |
| Has required SDK\* | Users that are sent to Sprig and have the correct SDK installed | Update SDK version |
| Met resurvey criteria | Users that are qualified based on global or survey level recontact period settings | Override global contact period, or adjust survey level recontact period |
| Triggered event | Users that triggered the survey contact event | Add additional events to trigger this survey |
| Hadn't seen this study yet | Users that have not seen this survey before (Shown only when “Show once per user” is on) | Adjust “Show once per user” setting |
| Matched filters | Users that meet Audience, Event, or Group targeting filter criteria (Shown only when at least one filter set) | Adjust filter settings to be more inclusive, or verify that filters are configured correctly |
| Included in send limit | Study send limit (#of times per day or sampling) settings are captured under Audience > Response settings (Shown only when this count is different than the previous stage) | Adjust sampling or send limit criteria to be more expansive |
| Selected for this study | Step is relevant only when multiple studies have the same targeting criteria (Shown only when # selected for this study differs from previous step) | Modify this study, or a conflicting study to have different triggering events |
| Received study | Users that have received the study | N/A |
| Viewed study | Users that have viewed the study | Modify the "waiting period" delay to be shorter |
| Started responding | Users that have started responding | N/A |
| Completed study | Users that have completed the entire survey | Update study design (shorter, question types, etc) to increase completion rates |
\*For mobile studies, if SDK update is bundled with an app update, end users will need to update your native app in order to qualify for a study with a minimum SDK requirement.
# FAQs
### How is overall response rate calculated?
The response rate graph is calculated by dividing the number of responded surveys by the number of seen surveys within a day based in Universal Time Coordinated (UTC).
### How do event properties get applied?
When targeting select users based on event properties, these event properties are applied during step 5, "Matched filters". The "Triggered Event" step will evaluate the event, and then "Matched filters" will evaluate the event property filters applied.
# Prototype Testing
Source: https://docs.sprig.com/docs/sprig-studies/prototype-studies/index
Prototype Tests let you collect feedback on early designs, wireframes, messaging, interactive prototypes, AI-generated prototypes, and more.
#### Prototype Testing can be accomplished with Sprig in two distinct ways:
1. Embedding prototype links within [Sprig Surveys](/docs/sprig-studies/surveys/index)
2. Integrating [Sprig In-Product Surveys](/docs/sprig-studies/in-product-surveys/index) into AI Prototypes
## Embedding Prototype Links within Sprig Surveys
You can embed prototypes from popular design tools and gather insights on usability, comprehension, and visual design, all without setting up any code. With support for prototype tools like Figma, Miro, Lovable, and even Google Drive, Sprig Surveys can easily accommodate a wide gamut of use cases, such as:
* Message Testing
* Monadic Concept Testing
* Usability Testing
* Design Testing
* Mobile Concept Testing
* ...and more!
#### Getting Started
Sprig Surveys are the foundation of prototype testing. Simply add a prototype URL to questions of interest in the Sprig survey builder, and Sprig will host the prototype side-by-side with corresponding survey questions. See the [prototype testing section ](/docs/sprig-studies/prototype-studies/prototype-testing/index) to learn more.
## Embed Sprig In-Product Surveys within AI-Generated Prototypes
You can easily embed Sprig In-Product Surveys within AI-generated prototypes made with tools like Lovable and Figma Make to capture feedback from your respondents as they engage with new concepts.
#### Getting Started
Installation is simple, and follows the same process as installing Sprig In-Product Surveys on your [website](/docs/Installation/introduction-web/index) or [mobile](/docs/Installation/introduction-mobile/index) app. That said, some AI-generated prototypes work better with certain installation methods than others. We've verified the following methods and tools work well together:
| Prototype Tool | Verified Installation Method |
| :- | :- |
| Lovable | HTML snippet |
| Claude (Artifacts) | HTML snippet |
| Builder.io | HTML snippet or npm |
| Figma Make | HTML snippet or npm |
| Replit | HTML snippet or npm; note that `pnpm` is used instead of `npm` in the terminal |
| Vercel v0 | HTML snippet or npm |
| AI Studio | HTML snippet |
Other AI-powered prototype tools may support embedding Sprig surveys, you'll just need to test to see which installation method works with your preferred tool. If you find a method that works for another tool, we'd love to know! Please let us know what you find by emailing [support@sprig.com](mailto:support@sprig.com).
Never written code before? See our [step-by-step, no-code guide to installing Sprig in AI prototyping tools](/docs/sprig-studies/prototype-studies/install-with-ai-prototypes/index), including tool-specific notes for each tool.
**Note:** in order for the survey to show up in the prototype you'll need to publish the prototype first.
Once the Sprig SDK is installed, navigate to your Sprig instance, create a new In-Product survey or feedback study, build the questions, and set up Targeting criteria (you can use Events or URLs).
**It's as easy as that!** You'll be able to see the survey in your prototype once it's published. As users explore the prototype and fill out the survey, response data will flow to Sprig as normal.
### Demo Video
# Installing Sprig in AI-Generated Prototypes
Source: https://docs.sprig.com/docs/sprig-studies/prototype-studies/install-with-ai-prototypes/index
Tools like Lovable, Figma Make, Replit, Vercel v0, Builder.io, Claude, and AI Studio let you build a working prototype just by describing what you want, no coding experience required. You can use the same approach to add Sprig to a prototype: paste the Sprig install snippet into the chat and ask the AI to add it for you. Once it's installed, you can start running In-Product Surveys, Heatmaps, Replays, and Feedback Studies!
**You don't need to write or read any code.** Everywhere this page says "give this to the AI," it means literally paste it into the chat box of the tool you're using, the same way you'd ask it to change a button color.
This page is for anybody with **no coding background**. Find your tool in the table below, then expand its section for the exact prompt to use and anything specific to that tool.
No-code events cover most cases, but Next Steps with Your AI Prototype has the prompt for code events and attributes. Works the same way on every tool on this page.
## Find your tool
Which install method to ask for (HTML snippet vs. npm/pnpm package) depends on how the tool bundles your prototype's code under the hood, not on anything you're doing wrong. The table below summarizes what we've verified for each tool.
| Prototype Tool | Ask the AI for... | Why |
| :- | :- | :- |
| [Lovable](#lovable) | HTML snippet | Easiest to use + does not support npm |
| [AI Studio](#ai-studio) | HTML snippet | Same structure as Lovable |
| [Claude (Artifacts)](#claude-artifacts) | HTML snippet | Artifacts are self-contained HTML documents by default, there's no bundler to install an npm package into. |
| [Figma Make](#figma-make) | npm or pnpm | Supports the standard SDK install. |
| [Builder.io](#builder-io) | npm or pnpm | Supports the standard SDK install; how you trigger surveys depends on whether you've deployed yet. |
| [Replit](#replit) | HTML snippet or npm | Both work; Replit's terminal uses `pnpm` instead of `npm` if you ever need to run a command yourself. |
| [Vercel v0](#vercel-v0) | HTML snippet | Works fine even though v0 can use npm; architecture more suited for HTML snippet |
Using a tool that's not listed here, or a general-purpose AI coding assistant like Cursor? Those tend to work more like adding Sprig to a website you already host yourself, rather than a one-click prototype flow. Email [support@sprig.com](mailto:support@sprig.com) and we can help, or try the general steps below.
## The General Pattern
Whichever tool you're using, the underlying steps are the same. Build your prototype first and get it working the way you want, don't worry about Sprig until then:
1. Go to your Sprig instance and open [Integrations > Javascript SDK](https://app.sprig.com/integrations/installation/javascript-sdk) to get your Environment ID. (Ask your Sprig admin for access if you don't have it.)
2. Copy the right prompt for your tool from [Prompts](#prompts) below, swap in your real Environment ID, and paste it into the AI's chat the same way you'd paste in any other request.
3. Ask the AI to publish or deploy the prototype (the exact wording depends on the tool, e.g. "publish this" or "deploy to production").
4. Open the **published** link (not the in-editor preview) and confirm Sprig loaded by checking for a network request to `api.sprig.com` in your browser's developer tools, or by asking a teammate with engineering access to check for you.
5. From the [Sprig dashboard](https://app.sprig.com/events), create no-code events based on your published URL, then create your study and set the trigger. More on [creating your audience](/docs/sprig-studies/in-product-surveys/survey-creation/index#3-audience-&-targeting) and [testing FAQs](/docs/sprig-studies/in-product-surveys/study-testing#faqs).
A prototype that's still open in the tool's own editor/preview window is not the same as a published prototype. Several tool-specific caveats below only show up in the editor preview and disappear once the prototype is actually deployed.
## Prompts
There are two prompts below: one for the HTML snippet, one for the npm/pnpm package. All you need to do is copy & paste one of these prompts into your AI assistant! Which one applies to your tool is called out in the table above and again in [Tool-specific notes](#tool-specific-notes), so check there before you paste either one in.
Swap in your real Environment ID before sending either prompt. You'll find it in your Sprig instance under **Integrations > Javascript SDK**.
### HTML snippet prompt
Lovable, AI Studio, Claude Artifacts, Replit, and v0 all use this one. It tells the AI to add the snippet right before the closing `` tag, not the ``. The script loads asynchronously, so placement doesn't affect load time, but `` is Sprig's own recommendation since it guarantees the snippet can never be what's blocking the rest of the page from rendering.
```text theme={null}
Add this script tag right before the closing tag of my site, exactly as written, don't change anything in it:
```
### npm or pnpm prompt
Figma Make and Builder.io use this one, since both support installing the SDK as a package directly.
```text theme={null}
Install the Sprig SDK using npm or pnpm.
Once it is in package.json, add this import to App.tsx:
import { sprig } from '@sprig-technologies/sprig-browser';
Then add this at the top level of App.tsx, outside of any component or function:
export const Sprig = sprig.configure({ environmentId: 'YOUR_ENVIRONMENT_ID' }).
Do not add any components. Do not create any new functions. Do not make any other calls to the Sprig SDK.
```
## Tool-specific notes
Always ask for the **HTML snippet**, not the npm package.
Paste the [HTML snippet prompt](#html-snippet-prompt) into Lovable's chat, then ask Lovable to publish, and verify on the published link.
Always ask for the **HTML snippet**, not the npm package.
Paste the [HTML snippet prompt](#html-snippet-prompt) into AI Studio's chat, then ask AI Studio to publish, and verify on the published link.
Claude builds Artifacts as a single self-contained HTML file, not a project with a package manager. Use the [HTML snippet prompt](#html-snippet-prompt) and have Claude add it right before the closing `
` tag of the Artifact's HTML.
The bigger catch: Artifacts run in a sandbox that blocks most outgoing calls to third-party services, including the calls Sprig's SDK makes to `api.sprig.com`. Sprig won't work in the live Artifact preview inside Claude, even with a correctly installed snippet, and there's no way around this from within Claude itself. Take the code Claude wrote and deploy it somewhere outside the sandbox, for example Vercel, Netlify, or GitHub Pages. Once it's on a real URL, the restriction disappears.