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Holdout testing: The key to validating product changes
Ever rolled out a new product feature and wondered if it's really making a difference?
Sure, A/B testing can tell you a lot about immediate user reactions, but what about the long-term effects? That's where holdout testing comes into play.
In this blog, we're diving into the world of holdout testing—a technique that helps you truly understand the lasting impact of your product changes. We'll explore how to set up effective holdout tests, analyze the results, and integrate them into your product development process. Let's get started!
Related reading: CUPED explained
Understanding holdout testing
Holdout testing is all about understanding the long-term effects of your product changes. It's a technique where you deliberately keep a small group of users from seeing your latest updates. By doing this, you can compare their behavior and metrics against those who got the new changes.
Now, while A/B testing is great for measuring instant reactions, it doesn't always show you the whole picture. Holdout testing looks at how changes affect users over time—days, weeks, or even months. This is key for spotting any negative side effects or user fatigue that might sneak up later on.
By keeping an eye on metrics like engagement, retention, and revenue over a longer period, holdout tests give you valuable insights into how your product changes really perform. They help make sure that your updates actually benefit users and don't come with hidden downsides. This builds confidence in your experimentation process and helps shape future improvements.
Setting up holdout testing isn't just a set-it-and-forget-it kind of thing. It takes careful planning and ongoing monitoring to keep the holdout group intact and to make sense of the results in light of your long-term goals. But when you weave holdout testing into your product development cycle, it promotes a data-driven culture and helps reduce risks when rolling out new features.
Setting up and implementing effective holdout tests
How to create a holdout test
So, how do you set up a holdout test? It starts by creating an experiment with three groups: control, test, and holdout. The control group doesn't see any changes, the test group gets the new updates, and the holdout group is kept completely away from these changes. Deciding how many users go into each group is important—you need to balance statistical power with user experience. A common approach is to split it into 45% control, 45% test, and 10% holdout.
Best practices for implementation
Feature flags are your friend when it comes to isolating the holdout group from any changes. They make sure the holdout users don't accidentally get exposed to your updates during the test. It's also crucial to keep your user segmentation consistent to preserve the test's integrity—you don't want any unintended changes messing with your results.
Keep an eye on how the holdout group is performing compared to the control and test groups. Over time, watch key metrics like engagement, retention, and revenue to spot any delayed or unexpected effects. Techniques like stratified sampling can help ensure your holdout group accurately represents your overall user base.
Make sure holdout testing is a part of your bigger experimentation strategy. Figure out how often and how long to run these tests based on your development cycle and business goals. And don't forget to explain the purpose and outcomes of holdout testing to your team and stakeholders—it helps build a data-driven culture and trust in the process.
Analyzing and interpreting holdout test results
Analyzing your holdout test results is where the magic happens. Monitoring key metrics over time helps you see the long-term effects of your product changes. By comparing behaviors between the holdout and exposed groups, you can uncover the real impact and spot any unintended consequences.
Make it a habit to regularly check metrics like engagement, retention, and revenue. If you notice differences between the holdout and exposed groups, dig into the root causes—it might mean you need to tweak or even roll back some changes.
Interpreting these results can be tricky because effects might be gradual or delayed. Using techniques like stratified sampling ensures your holdout group is representative, and Monte Carlo simulations can help you estimate impacts accurately, even when results aren't statistically significant.
Collaborating is key here. Data scientists, product managers, and engineers should work together, sharing insights and making data-driven decisions. At Statsig, we've found that cross-team collaboration is essential for optimizing your product based on what you learn from holdout testing.
Integrating holdout testing into product development
Bringing holdout testing into your product development process, especially if you're using agile methodologies, means running these tests alongside your other experiments. Treat the results as important inputs for your sprint planning. Insights from holdout tests can validate your product decisions and shape your roadmap, making sure your improvements really make a difference. Plus, this practice promotes a data-driven culture and reduces risks when launching new features.
Coordinating holdout tests across different teams can be a bit of a juggling act. Clear communication and shared goals are essential. Rotating users in your holdout groups regularly can help prevent user frustration while still keeping your data statistically significant. By leveraging insights from holdout tests, you can drive data-informed decisions that optimize for long-term success.
You'll need robust monitoring and analysis tools to track key metrics over time. Consider incorporating holdout tests into your continuous delivery pipeline as part of your release process, with clear success criteria. And don't forget—regular communication of holdout test results to stakeholders builds trust in your experimentation efforts.
Closing thoughts
Holdout testing is a powerful way to understand the long-term impact of your product changes. By carefully setting up tests, analyzing results, and integrating the insights into your development process, you can make sure your updates truly benefit your users. Tools like Statsig make it easier to implement and manage holdout tests, fostering a data-driven culture within your team.
If you're interested in learning more about holdout testing and how it can improve your product development, check out these resources:
Hope you found this helpful!