Studies can now be duplicated between environments, so you can set up a study in Development, test it out, and then duplicate it to Production to launch it!

When studies are duplicated, all of the questions, as well as the platform setting, will be carried over to the duplicated study. You will still need to configure the Audience settings to select Triggers and Filters in your Production environment.

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The latest Sprig solution Concept & Usability Testing enables you to test ideas, designs, and prototypes before building a product.

That means you can now use Sprig to:

  • Embed multiple interactive Figma prototypes into a single Sprig test with just one click
  • Ask users to complete recorded usability tasks and provide feedback via audio or video without downloading plugins or extensions
  • Add an NDA for review and obtain consent from users before they start a test

Combined with the In-Product Surveys you know and love, your team can now research across the product development lifecycle. Take a stab at creating your own concept and usability tests or use one of our 14 new templates to explore what’s possible when testing with Sprig.

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Use Sprig to source participants in‑product or import from a panel

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We're excited to announce a major revamp of our Template Gallery, which makes it quick and easy to see what’s possible within the Sprig platform. The new experience organizes templates by use case, enables searching for specific templates using keywords, and allows you to preview templates at the question-level prior to selecting it.

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New Templates Gallery

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Template Gallery search

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Question-level previews

We've made two improvements to Attributes that give you more options and control when determining who receives a study (or who belongs in a Group!) based on user attributes.

New filter operators

In addition to the existing comparison operators (equal, greater than, etc), there are a new set of string (text) operators: contains, does not contain, starts with, and ends with. These are case-insensitive and can be used on any Attribute. For example, you can now easily create a Group of all internal employees:

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This Group can be used to exclude studies from being shown to internal users, or as a way to test your studies on Production with fellow teammates before launching.

Removal of 100-value limit

Previously, Attributes were restricted to 100 discrete values, and any Attributes that had more than 100 values were automatically removed. We've been hard at work to remove this limitation and now proudly support any number of values for an Attribute!

With our new visually-redesigned filter dropdowns, it's easier than ever to find the right trigger or filter for your study!

You can easily view and search through your Events, Attributes, and Groups — and a beautiful new popover shows relevant information like description and usage for each item to help you decide which targeting criteria you want to use.

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Studies can now be previewed in full screen, accurately showing how your users will see and experience the study.

To open a fullscreen preview, open any study and click the Preview Study button.

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You'll see a study that reflects your Look & Feel settings, and can toggle between different device sizes. You can also use Share Preview to copy a unique preview link to share with anyone!

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We've also updated previews for email studies to be more realistic, and showcase the user experience from receiving the email through the end of the study.

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Groups are a brand-new way to manage cohorts of people. When setting up a study, Groups can be used to determine who sees your study, helping your team manage frequently-studied sets of users and reducing errors in targeting set-up.

There are two types of groups: Manual Groups and Dynamic Groups:

Manual Groups

Manual Groups are a defined list of users that can be uploaded from CSV or created by selecting people from the People table. Manual Groups can be used to target (or avoid targeting) specific people, manage panels or email lists, or import group information from other data sources.

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Dynamic Groups

Dynamic Groups are a set of saved filters (filtering people based on events, attributes, or other groups). The people included in a Dynamic Group dynamically change over time based on the eligibility criteria saved in the filters. As your user base grows and changes, the population of a Dynamic Group will change accordingly.

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We've redesigned the Events management experience in Sprig to provide more customization and controls for your team.

Display names

Your team can now add display names to events, which will be shown across Sprig in place of the key (the event name sent from the SDK). This allows your team to set more descriptive or relevant names for all of your Code Events – and because display names can be changed at any time (unlike the event key), it will be easier to keep event names in sync with the product as changes are made.

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Archive & Unarchive

Events can now be archived and unarchived, and you can select multiple events at once to modify in bulk. Events that are archived will not be tracked, but can be restored at any time by unarchiving.

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Event requests

The new Events experience allows you to manage Code Events that have not been imported into Sprig yet. When a new event request is sent to Sprig from the SDK, it can be approved or denied before it begins tracking.

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New look & feel

We've made a variety of other quality-of-life improvements, including more source filters for Code Events, a redesigned modal for event details, and a new event creation/editing experience.

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We’re making it easier than ever to create Studies. Your task flow is more optimized as you can now create Events during the study creation process for Web. To directly create the event you need to display your in-product study, when you add a new event trigger to a Web study, click + New Event.

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We've recently introduced the ability to add logic based on skipped responses for Video & Voice, Open Text, and Multiple Choice Multi-Select questions.

This change enables study creators to customize their study based on submitted and skipped responses, powering use cases like screening out users that don't respond to a specific question, or directing users that skip questions to a different part of the study.

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