What is Google Play Experiments?
Google Play Experiments(GEx) is Widely known as Google Play Store listing experiments, it’s the A/B testing functionality tool provided by Google for app marketers to find the best app icon, images, video, and descriptions for your app on Google Play.
The internal tool enables the testing of these elements on live Google Play Store traffic in order to compare two or more variants with different creatives / messaging to see which versions bring higher conversions.
With Google Play Experiments, Apps and games developers and marketers can easily decide how many users would get to each variation and divert a portion of traffic to test.
Why Google Play Experiments are Important?
A/B testing is vital because conversion rates (CVR) especially for first time installs, is one of the factors that influences mobile app growth and specifically organic growth the most, as it signals to the platform to surface the app through charts and search results.
The insights received from each experiment give a general sense to whether certain creatives work better than others, which is an important aspect of optimization.
A/B testing increases growth by getting Google Play Store pages to be more efficient in capturing installs from every X number of impressions an app developer / marketer is able to drive through difference channels and sources.
Google Play Experiments and ASO
Google permits a number of forms of experiments to run, together with one international experiment of the primary default graphics and as many as 5 localized experiments by language, along with all the weather highlighted within the prime paragraph. By conducting experiments efficiently, it’s attainable to construct a robust ASO technique that provides an app/sport an aggressive benefit over a sport in the same class.
For ASO, the A/B testing within the Google Play Console is likely one of the instruments obtainable that assist in improving CVR, CVR being a pillar of the ASO trade. Unfortunately, a major disadvantage to GEx is that on-page behavioral analytics are lacking, comparable to video watch rates, screenshot gallery rates.
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