Sprig

Today, we're proud to launch Sprig AI Recommendations, the final step in our Sprig 2.0 vision. With Sprig AI as your product partner, you can now generate specific, actionable recommendations to achieve your goals. Sprig AI Recommendations empowers you to: ???Get instant, data-backed solutions to optimize your product. ???Make informed roadmap decisions with confidence. ???Boost key metrics with actionable, real-time insights. Whether you're trying to improve onboarding, increase conversion, or enhance usability, AI Recommendations provides a powerful way to know exactly what to do next in your mission to build products your users love. Start generating tailored solutions at scale—create a free Sprig account today! ?? Try it out here: https://lnkd.in/gpRixWcT

Invoice2go increased onboarding completion by 25% with Sprig. Here’s how: Invoice2go is an all-in-one app for small businesses to get paid fast by customers and manage cash flow. They prioritized user research early on—the company had several UXRs on staff before they reached 100 team members! While expanding from an invoicing platform to a full-service solution, the company launched Invoice2go Money—a banking solution enabled by an integration with Plaid. Early on, though, the team saw a problem: Customers were dropping off after signing up for Invoice2go Money. Here’s how they solved their user drop-off issue: 1. Determined there was an issue in the first place Customers had to go through a new set of flows to use the payment and banking capabilities. However, the team quickly noticed a stark drop-off between users applying for the card payment offering, getting approved, and actually using it. They needed to find the obstacle. 2. Launched an in?product Sprig survey to understand where the obstacle was The team had a hunch: Using Plaid to link a bank account presented an issue to users, causing the drop-off. To collect data on this, they launched an in-product survey with Sprig, targeting users who applied for the new card payment system, were approved, but didn’t actually start using the app. This was the best plan of action to isolate the customers they wanted to reach. 3. Used the survey results to validate their hypothesis The survey included an open-text question to get feedback on areas for improvement and friction. As expected, 30% of users cited Plaid and uncertainty with the platform as reasons they didn’t provide bank details. Additional issues with usability and awareness also presented themselves here. The Results: Feature update decreased drop?off and increased completion by 25%. With answers from the in-product Sprig surveys, Invoice2Go quickly introduced a new flow to mitigate these issues by increasing awareness of Plaid and improving usability. If you want to replicate their success: 1. Target the right users with in-product surveys triggered at critical points in their journey. Invoice2go targeted users who had begun but not completed the process of implementing card payments. By asking only those users, they could understand the exact concerns standing in the way. 2. Use a quantitative approach to qualitative research. Invoice2go surfaced qualitative insights at a quantitative scale by asking open-ended questions to validate hypotheses. Sprig AI can analyze these responses to extract the top themes. 3. Use research to prioritize the roadmap and make iterative improvements to existing products. Hunches—even strong ones—aren’t enough to invest time, energy, and resources into a project. Validating that hypothesis with data lets you prioritize the roadmap with conviction. We hope you found this helpful! Let us know if you have any questions.

You can’t improve your product without understanding users’ wants and needs. Here’s the easiest way to understand them: The key for UXRs and product teams is to seamlessly gather this valuable feedback without disrupting the product experience or burdening their team with excessive effort. The best way to do this is to launch a Sprig Feedback study. This will allow you to capture continuous feedback directly within your product or website, keeping you constantly informed of user needs. The template shown below is free and can be easily installed wherever you want on your site. For the questions themselves, we encourage you to keep them at a higher level because you’re addressing a larger audience. Some example questions: - How satisfied are you with our products/services? - On a scale of 1 to 10, how would you rate your overall experience with our brand? - On a scale of 1 to 10, how would you rate the product experience? Collection is really only the first step, though. Analysis is the second. Here are some tips for analyzing product feedback results that will yield the most actionable insights: 1. Uncover trends and patterns: Examine your data to identify patterns and trends that reflect areas of opportunity across your product (Sprig AI helps with this). 2. Put results in context: Think about how things have changed since the last time you researched similar questions. Also, consider whether your findings are related to market changes or other research within your company. 3. Visualize results: Use dashboards to help your team understand complex information and effectively communicate results and next steps. These insights can help you make informed product decisions, improve the user experience, and optimize key metrics like conversion and adoptions. If you have any questions, feel free to leave a comment below!

We spent years developing our AI Analysis for Surveys to empower research, design, and product teams. The result? The easiest way to analyze survey answers and generate relevant insights. Below, you’ll see a demo of Sprig AI Analysis with a sample survey. Key highlights: (1) Open-text analysis Sprig AI groups open-text answers into the top themes, making it easy for your team to understand the survey takeaways without manually reading through endless responses. Plus, you can click on each theme to view the specific responses that contribute to it. But Sprig AI’s power doesn’t end there. (2) Sprig AI Insights Sprig AI generates custom summaries of your survey results tailored to your specific study goal. Based on that survey data, it also extracts actionable opportunities, trends, correlations, and strengths for your product. In short, it’s easier and faster than ever for UXRs and product teams to get relevant, timely survey insights. If you want to see more on this, book a free demo from our bio.

?? Companies like Ramp use Sprig AI to analyze product feedback data and provide insights to product teams based off them. If you’re looking to make informed and impactful product decisions, improve your customer journey, and optimize key product metrics, you should use it too. Solving product challenges is easy with Sprig AI Insights. The process couldn’t be more simple: 1. Instantly launch a Sprig study Sprig AI will generate targeted Replay, Heatmap, Survey, and Feedback studies across your product to capture user behavior and feedback data. From there… 2. Sprig AI will surface product challenges. You can automatically see your study's most valuable product takeaways, including product opportunities, correlations, trends, and strengths. 3. You can take action with Sprig’s guidance. Review Sprig AI’s custom insights for each opportunity to see exactly what product changes to make to improve usability, conversion, and more. Importantly, the insights automatically update as new feedback comes in—ensuring the insights?you see are always up to date. After that, act on it as you see fit! We hope you find this helpful! Head to our site to read more about Sprig AI.

?? Introducing Always-On Replays! We’re excited to announce Always-On Replays, bringing continuous, AI-powered session insights to your product experience! With Always-On Replays, you can: ?? Automatically recreate user sessions across your entire product ?? Leverage AI-powered insights to surface friction points instantly ?? Organize replays effortlessly by product area, user segment, or interaction type No matter which part of your product you're optimizing—onboarding, checkout, or beyond—Always-On Replays gives you the full picture so you can make product decisions with confidence. ?? Now in beta! Be among the first to try it—link in the comments below!

We’ve rounded up the modern UXR tool stack for 2025! See if your favorites made the list: Research Repositories → Dovetail, Notion ?? Dovetail makes a team’s research insights easily accessible in a searchable hub. Plus, their active Slack community is a great resource for research-related and Dovetail-specific questions. ?? Notion feels like a bullet journal reimagined as a powerful, wildly successful tech product. Researchers can leverage its intuitive, easy-to-organize workspace for data management, including research reports and insights. It’s also a great option for user research libraries that need a structured hierarchy of folders and documents. Participant Management → User Interviews ?? User Interviews enables researchers and UX designers to seamlessly recruit quality participants for studies, with advanced targeting options based on job titles, skills, and consumer behavior. (Check out our integration!) Unmoderated Research → Sprig ?? Sprig powers targeted in-product surveys, session replays, and heatmaps, helping research teams quickly capture in-context user sentiment and behavior directly within their product. With Sprig AI, teams can instantly analyze responses and session clips to uncover patterns and extract key insights—turning raw feedback into real-time, actionable intelligence. It’s the fastest way to get deep, in-the-moment user insights while engaging participants directly within the product experience. Moderated Research → Grain ?? Grain makes it easy for researchers to record, transcribe, and clip key moments from research interviews, sales calls, and customer meetings—transforming conversations into actionable insights. We hope this roundup is helpful! What’s in your UXR tool stack? Let us know in the comments! ??

?? Did you know you can instantly analyze user feedback and behavior across your entire product experience to get holistic insights that drive smarter, faster product decisions? …only if you use Sprig AI Explorer, to be fair. The process is simple. All you have to do is: 1. Launch Sprig in-product studies in just a few clicks 2. Generate your Sprig AI Explorer report 3. Watch Sprig AI reveal actionable insights across your product 4. Explore the experience data behind each insight From there, you can make product decisions based on what your users want—because they told you they did. Check out this brief demo of how it works below!

Sprig helps companies like Coinbase, Notion, and Figma improve features, optimize usability, and elevate their user experience through in-the-moment product surveys. Here are 5 high-impact product survey questions to borrow from their playbook: (1) Did you find what you were looking for? Coinbase used this question while trying to figure out what users actually wanted to see in their tax center. They knew that users were visiting the interface, but they didn’t know why, what information they were looking for, or what they were downloading. Sprig’s in-product surveys helped them ask the question to targeted users + capture follow-up details to better understand their users’ needs. (2) How did you feel while exploring the product? Lenny Rachitsky—a product expert who interviews world-class product leaders—notes that top product people/teams have strong “product sense”. He developed a suite of questions like the one above to help leaders develop this skill. (3) What is holding you back from trying (product)? After the Sprig team noticed a dip in our conversion flow in product analytics, we used this survey question to dive deeper and better understand this new trend. Sprig's automated AI Analysis clearly told us that unclear pricing was a main reason why visitors were hesitant to sign up for Sprig. (4) How disappointed would you be if you could not use our product? This survey question helps determine how connected your users are to your product and if it truly meets their needs. It’s also a good indicator of product-market fit. (5) What current features do you find the most valuable? Our own product team uses this question to understand what features our customers find valuable and then determine what features we will invest in. If you loved these and want more, visit the Template Gallery on our site. There, you can choose from 70+ expert-made templates to uncover product opportunities and improve user experience ??

Novo increased customer feedback by 40% with Sprig. Here’s how: Novo is a platform for small businesses that couples a checking account with an ecosystem of financial and business applications. The Novo team’s biggest focus was making the product as easy to use as possible. As a result, they needed a way to collect customer feedback in an easy, scalable manner. Here’s how Sprig made it possible: 1. Novo ran in-product surveys directly in their platform to get feedback and answer key questions about their product, like the platform’s ease of use and what features would improve it. 2. They used Sprig’s Rudderstack integration to trigger these in-product surveys based on specific user events, enabling them to target and hear from their key audience. 3. With Sprig AI Analysis, the Novo team quickly turned thousands of responses into actionable product recommendations and insights—all without manually reviewing open-text survey responses. As Roger Liu, Director of Product at Novo puts it: “It’s really important that our platform is exceptionally easy to use - and Sprig enables us to build just that by helping us get feedback from customers on what works and what doesn’t.” If you want to do the same, book a free demo using the link in our bio!