Developing a mobile app without A/B testing is basically like navigating an ocean without a map. Guesswork will only bring shoddy results and performance issues.
Meanwhile, your competitors are leveraging data-driven insights to optimize their apps. This leaves you at risk of falling behind and losing valuable time, money, and users.
Mobile app A/B testing eliminates this guesswork. If you test your app’s variables, you can then tailor user experiences, improve engagement, and boost retention. Let’s explore why you must start putting your app to the test.
Here are some noteworthy statistics that demonstrate the impact of A/B testing on today’s mobile landscape (and beyond):
These figures show that A/B testing is highly valued for impacting user experience and conversion. Moreover, it’s becoming more in demand and accessible than ever.
Mobile app A/B testing involves testing multiple versions of an app-based variable. This could be a feature, content, or UX copy. A/B testing for mobile apps is typically server-side. It enables more sophisticated, detailed tests on user behavior, engagement, activity, and conversions.
There are many upsides to conducting A/B tests in your app. Through this process, you can:
For every benefit, there’s a feature you can A/B test to optimize your app’s performance.
Virtually every aspect of an app can be A/B tested. Here are some features often tested on mobile (including apps that typically run each one).
Through user flows, users can navigate an app more simply. A/B testing helps to highlight the most straightforward paths to keep users engaged.
In mobile games, developers want users to progress through challenges, levels, and rewards. Finding a healthy balance between challenging and addictive gameplay improves these flows.
Developers can A/B test:
You need to get new users up to speed as smoothly as possible. For onboarding flows, you can A/B test:
Combining these steps can impact onboarding completion rates.
Apps with smooth onboarding flow: Slack, TikTok, and Duolingo.
A/B testing subscription flows can heavily influence revenue. You want to make the signup, choice of plan, and payment processes all painless for users. Split testing lets you experiment with variables such as:
A/B testing shows developers the smoothest flow for users to make an easy decision.
Apps with smooth subscription flow: Spotify, Netflix.
Mobile devices notoriously have high cart abandonment rates (75.5%). So it’s imperative for apps to A/B test their checkout processes to remove potential friction. Consider testing:
Apps with smooth checkout flow: Amazon, Etsy, Shopify.
In-app experiences should make user journeys seamless and enjoyable. Three examples of in-app A/B tests include:
Push notifications can effectively re-engage churned users. However, they can have the opposite effect if overused or poorly designed. Key variables to test include:
Example: Food delivery app Uber Eats tests which notification generates the highest click-through rate (CTR).
This experimentation allows apps to validate ideas, eliminate bugs, and segment users. Functionalities like paywall access and recommendations can be A/B tested pre-implementation.
Through mobile game-based examples, we’ve shortlisted five key practices for A/B testing in mobile apps.
Firstly, what do you want to learn about your app that contributes towards business goals? Write a hypothesis to predict what you expect from the A/B test. Reviewing your current data will inform your approach, and which variables to test.
Example: “Based on the analysis of user behavior, we expect a daily login reward system to increase user retention by 15% over a week.”
Testing different variables can make your findings pretty muddy. By testing one variable at a time, you can focus on one single root cause of user behavior.
Example: Test two placements of a purchase button to determine the higher click-through rate. Version A goes in the bottom center. Then Version B is placed at the top-right-hand corner.
Segmenting A/B tests reveals how different users react to different app changes. It also makes app optimization more accurate, helping you tailor features for different user needs.
Example: Segment players when testing the impact of daily rewards. Test A’s for casual players (1-2 daily logins) and Test B’s for hardcore players (5+ daily logins). This makes reward systems more personalized.
Running an A/B test once is not going to yield any meaningful, accurate results. Each test is potentially going to provide different insights. Previous tests impact how you conduct future ones, making them vital assets for optimization efforts.
Test different features, flows, and functionalities repetitively. These findings will teach you much more about how users interact with your app.
Example: Iteratively test level difficulties. In the first test, adjust the difficulty for two different player segments (A: Difficult B: Easy). In the follow-up test, introduce more dynamic difficulties for players, to optimize engagement.
It’s essential to keep track of all A/B test findings. By documenting these results, you can keep your optimization efforts organized. This makes it easier to inform future decisions.
By reviewing those findings, you can recalibrate your product roadmap. Then, you can prioritize new features and optimizations more accurately.
We have picked five of the best A/B testing solutions for mobile apps. Each one has unique features and special purposes.
| A/B Testing Tool | Key Features | Best For |
| AB Tasty | – Feature experimentation – Advanced segmentation – Personalization | Boosting user experience |
| Adobe Target | – A/B and multivariate testing – AI-driven automation – Omnichannel personalization | Automated user personalization |
| Apptimize | – Cross-platform optimization – User segmentation – A/B testing – Feature flags | Cross-platform testing/optimization |
| Firebase A/B Testing | – User group segmentation – Remote config to adjust app behavior/appearance – Wording/messaging optimization | Feature release management |
| VWO | – Behavior analytics – Mobile split and multivariate testing – Advanced targeting | Increasing conversions and understanding user engagement |
The results are in! Without mobile app A/B testing, you miss a golden opportunity to fully understand how users are interacting with your app. This data-driven approach is a surefire way to eliminate guesswork and address user frustration.
It’s not just about improving your app. It’s about creating personalized experiences for each user, which will undoubtedly lead to long-term success.
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