Beginner’s Guide to Pre-Launch Mobile A/B Testing

Pre-launch A/B testing for mobile apps is a method of validating an app idea and optimizing its potential performance before it’s released to the public, thereby increasing the probability of a successful launch and better performance.

Pre-launch A/B testing provides real data on what resonates with the target audience, helping developers make informed decisions about product features, marketing messages, and creative assets essential for app store optimization (ASO).

Typically, pre-launch A/B testing for mobile apps involves creating a simulated product page on the App Store or store listing on Google Play for a prospective app and driving traffic to it to see how a real audience reacts to various ideas introduced there.

How these tests are designed exactly, what metrics matter, depends significantly on the stage of app development.

1. The pretotyping phase (or planning and discovery) tests big ideas to find the right direction. It answers the question “Should we do this app”?
2. The prototyping phase (development and beta testing) can be used to optimize selected ideas, find the best audience for them, and validate user acquisition channels
3. Launch and the period directly preceding it are used to fine-tune all the details for the most successful and impactful launch.

In principle, pre-launch A/B testing follows the same framework as post-launch A/B testing for ASO, but there are enough unique aspects of it that a separate guide is needed to clarify it.

How to use A/B testing before an app’s release?

Pre-launch A/B testing scenarios vary depending on the stage of app development. These primarily impact how we approach designing our tests.

Pretotyping: validating ideas and audience probing

Pre-launch A/B testing can begin before development starts, allowing you to find the right creative direction or sample the market. The sequential A/B/n testing methodology is frequently utilized during this stage, as it allows to create a logical progression of experiments that build on each other.

At this stage, pre-launch A/B tests can be referred to as pretotyping.

Pretotyping answers the question “Should we build this app?” It focuses on testing market demand and user interest. To understand pre-launch A/B tests at this stage better, let’s examine the case of MSQRD, a virtual augmented reality app acquired by Facebook.

MSQRD team chose to focus on these features because of positive audience reaction to them during a round of A/B tests run with SplitMetrics, which turned out to be a tremendous success, ultimately going viral.

Pre-launch A/B testing may shed light on your further moves regarding app development, allowing you to identify specific features that should be highlighted on the App Store.

For example, from the initial pretotyping tests that pointed the MSQRD team in the right direction of augmented reality, continuous testing revealed more relevant audience preferences, like the fact that users were 55% more interested in live masks than in the face swap feature.

[tonestro screenshot with CPP and the default page]

Choosing the right feature to highlight is critical on any app store, whether on the default product page or store listing, or a custom one. Here’s the example of tonestro, which showcases music lessons as its default and primary feature, but selects to promote instrument tuning through custom product pages.

Prototyping: positioning and messaging

During the prototyping phase of pre-launch A/B testing, the focus can shift to refining the prototype based on audience feedback. Having already validated the app’s core idea during pretotyping, the goal now is to determine which features or themes to highlight and for which specific audience segments they are best suited.

To better understand the role of pre-launch A/B tests at this stage, let’s examine experiments run by Etermax, an international technology company with a gaming division whose offering exceeded 800 million downloads.

The company was already actively developing a new trivia game, but wanted to probe their audiences to verify which style of play is the most appealing, a decision with significant impact on the further visual design process and product page and store listing optimization (ASO).

Ready to launch: fine-tuning, localization, and ad channel validation

Pre-launch A/B testing, conducted right up to the release day, is crucial for securing a strong launch. An app’s debut significantly impacts its future performance, with high download velocity and conversion rates acting as key organic ranking factors on the App Store and Google Play, according to App Radar. A successful launch, marked by numerous downloads, ratings, and reviews, can establish a solid foundation for future user acquisition.

Fine-tuning app icon, screenshots, and videos

Now is the time formore granular tests, concerned with fine-tuning a product page or a store listing, equipping it with the best app icon, screenshots, or preview video. Here are some examples of the types of tests designed during the final stages of app development:

• Icon for a match-three game: the variation featuring one big object was 49% better than icon with lots of fine details.

• Icon for a Hidden Object Game: the close-up icon lost to the icon which depicted a character a bit further.

• Icon for a Puzzle Game: the icon which depicted an object beat the icon with a character with 27% conversion improvement.

App localization

The pre-launch period is an ideal time to prepare your app for launch in various regions. The level of nuance required for a successful, effective and well performing localization makes pre-launch A/B testing a great tool for finding the right way of adjusting our default product page or store listing for the target market.

Ad channel validation

Mobile A/B testing in pre-launch may also aid in the decision-making process when determining the most effective app advertising channels.

It’s possible to qualify different ad channels like news, Facebook, cross promo, and various ad networks. Thus, you can allocate your marketing budget more effectively once your app is live.

User acquisition channels have varying strengths and weaknesses, with TikTok being a great choice to reach young audiences or Apple Ads to acquire high-value customers, more likely to spend their money on subscriptions or in-app purchases.

Consequently, aligning you user acquisition channel mix with your app’s value proposition and messaging is critical. Investing in that research can secure a strong launch, ultimately resulting in bigger visibility.

How to analyze the results of pre-launch A/B tests?

The primary focus of A/B testing product pages or store listings for ASO on the App Store and Google Play is the conversion rate, as the goal is to find the best pefroming variant of creatives that will drive the most downloads. The full range of metrics available depends significantly on the way you choose to run pre-launch A/B tests. For example, SplitMetrics Optimize allows a full analysis of on-page user behavior, including potential sign-ups or other interactions signifying engagement. In general, the data points to look at while pre-release A/B testing should include:

1. Conversion rate (CR) remains a critical metric for any pre-launch A/B tests. Still, the scope of analysis should be and typically is much broader to gain a better understanding of the audience and its choices.
2. Performance across audience segments, as deep segmentation is what can help you identify your primary target audience (the more granular, the better). Later, you can evaluate which group was the most interested and evaluate its monetization prospects.
3. Performance across ad channels, with deep segmentation, helps out here once again, making it possible to identify the most efficient traffic sources.
4. Product page/store listing engagement metrics: including bounce rate, scroll depth for screenshots, video display length, and so on.

The more data about your audience you aggregate, the better you’ll be able to optimize specific product page elements (icons, screenshots, names, etc) and localize your app.

Remember, your goal is to not only verify which direction is right for your app in terms of features or themes. Pre-launch A/B testing can serve as a reliable market probe, allowing you to confidently estimate whether there’s real demand for what you’re about to develop.

Best practices for pre-launch A/B testing

Pre-launch A/B testing follows the same framework as post-launch A/B tests, and the principles remain:

1. Define a clear hypothesis and goals: Start each test with a specific question and a testable hypothesis.
2. Create high-quality and distinct variations: Variations should be noticeably different and professionally designed to yield statistically significant results.
3. Segment your audience: Drive traffic from a representative sample of your target audience, mindful of external factors that could skew results.
4. Prioritize statistical significance: Let tests run long enough to gather statistically significant data (aim for 95% confidence) to avoid false conclusions.
5. Use a “control” version: Include a baseline control group in every test to accurately measure the performance improvement of new variations.
6. Test the most important elements first: Prioritize elements with the most significant potential impact on conversion, such as the app icon and initial screenshots.
7. Look beyond conversion rate: Analyze other metrics like bounce rate, scroll depth, and click patterns for deeper insights into user behavior.
8. Analyze and iterate: Base decisions on data, not opinions. Document all experiments to build a knowledge base for continuous improvement.
9. Don’t overlook localization: Beyond translation, test different creative assets and messaging for various regions to ensure cultural resonance.

However, pre-launch A/B testing is different from testing a live app. Here’s advice critical to that type of testing in particular:

1. Focus on the core value proposition: validate the fundamental app concept and market demand. Pre-launch A/B tests are mostly about confronting ideas, not small, iterative changes first, with more granular experiments coming later.
2. Measure interest and engagement, not just installs or sign-ups: since users can’t install an app that hasn’t been released, define success metrics like click-through rate (CTR), email sign-ups, or survey responses to gauge genuine interest. The more you know about your audience pre-launch, the more room you’ll have for performance optimization you’ll have later on.

How to run pre-launch A/B tests

Pre-launch A/B tests and experiments are most frequently run with specialized platforms like SplitMetrics Optimize, to create tested product pages or store listing variations and provide comprehensive analytics necessary to interpret the results correctly.

While it’s possible to run pre-launch A/B tests independently, there are several considerations before committing to doing so. In general, when a specialized solution is used:

• Tests will be run under scientific rigor and consequently, offer the best, statistically sound results with high confidence.
• Difficult calculations will be handled automatically: for the minimum sample size, the statistical significance of results, and their confidence level.
• Different testing methodologies enable multiple approaches to testing, keeping costs under control, and allowing for the optimal method in a particular scenario.
• The creation of a testing product page or store listing is also automated, leaving testers with designing the creative assets that need to be tested.
• Extensive analytics enable the measurement of engagement, not only conversion rates (taps on the main call-to-action), but also numerous other performance indicators to properly understand the audience.

Final words

To maximize your app’s potential, especially during the crucial pre-launch phase, leveraging an advanced A/B testing platform is key. SplitMetrics Optimize offers comprehensive testing methodologies, powerful features, and expansive analytics designed for all types of A/B tests, proving especially beneficial for validating ideas and refining strategies before your app hits the market.