We’ve made improvements to Sprig's newest product Replays, so it's easier to analyze your users’ product experience. You can now watch session clips at your own pace with custom speed controls. Plus, you can review a user's replay clip and in-product survey response side-by-side, linking their session to their sentiment. If you’re in the Replays beta, launch one today to test out the updates!

Dig deeper into your study results with Sprig's new study response filters. Now, you can filter your study responses to only users who respond to a specific question in a particular way. Wondering if respondents in a certain age group are more likely to be satisfied with a feature? Or if customers who prefer a certain competitor have common feedback on why? Now, you can analyze your results to find these answers directly in Sprig.

This feature is an addition to Sprig’s existing date range and attribute filters for study response analysis. To analyze with response filters, just go to your study Summary page and under Received within, click More Filters and then Add Filter.

Want more control over the studies your team launches? With the Editor Lite role, you can give certain team members permission to create and edit studies, but to launch them, they need to share the study link with a Developer, Editor, or Admin. To add new team members with the Editor Lite role or update existing team members’ roles, go to Settings and in the Team section, click Members.

Want more insight into your Sprig account’s MTU usage and where they’re coming from? We’ve added a new feature that allows you to break down your team’s MTU usage by user identity (anonymous vs identified) or platform (Web, Android, iOS, Segment, API, CSV Upload). You can find MTU filter views by just going to Settings and clicking Usage in the Team section.

Want to make sure your study design and triggers are working as expected before launch? You can now use Sprig's new study preview feature to test your study directly in your web product. Once you finalize your study’s Audience settings, select Preview on your website on the right hand sidebar and generate your study test in just a few clicks!

With our new and improved Skip Logic beta feature, you have even more control over which questions you display to your users based on how they respond to both current and previous questions. Improvements to this feature also include the ability to add multiple logic conditions to a single question and new “does not include” operator for multiple choice multi-select questions. Create a new study to try out advanced Skip Logic (just make sure your Sprig web SDK is up to date!)

Now, you can get all of your burning Sprig questions answered easily and quickly, thanks to our new support chat! Wondering what’s the best installation method for your team? Or need tips on creating the right study targeting to reach the right audience? Our support team is here to help via chat! Just click on the purple chat icon at the bottom right of the Sprig app and ask away.

With Sprig's new integrations with Mixpanel and Launchdarkly, product teams can now quickly identify areas for improvement, measure the impact of changes, and confidently iterate to create better product experiences. Already using Mixpanel or Launchdarkly? Start using them with Sprig today by heading over to the Sprig Integrations Gallery to install in just a few clicks.

The Sprig Data Hub and People page have been replaced by the new Users, Events, and Attributes pages. This flattened navigation makes it easier to review the user data that you send into Sprig and leverage for precise study targeting. Explore these new pages by adding a new Event or attribute, creating a Group to regularly reach certain cohorts, and more.

Sprig AI Analysis, now powered by Open AI’s GPT, has officially launched and is available to all Sprig Enterprise customers. Sprig AI Analysis now offers much faster and more detailed feedback summaries of your open-ended survey responses. Check out your recently-launched studies to see the new AI in action, turning loads of raw response data into clear-cut product recommendations.