It’s no secret that marketing overall rests largely on data. The same applies to mobile marketing and user acquisition. In this domain, choosing the right product page elements for the App Store and Google Play can make a crucial difference to the success of an app or mobile game. Mobile A/B testing is a tool that helps to make that choice based on data. 

However, how many times have we heard the argument that A/B testing doesn’t bring the desired results, or that someone is not sure they run mobile experiments right? This often happens due to some common mistakes and misinterpretation of data. In this post, I will cover the biggest mistakes and misleading conclusions in mobile app A/B testing, knowledge of which will help you achieve success. 

1.  Finishing an experiment before you get the right amount of traffic

This is one of the most common mistakes in mobile A/B testing. In case you are an adherent of classic A/B testing, finishing an experiment before you get the necessary amount of traffic  – sample size – presents a risk that you will get statistically unreliable results

To get reliable evidence, you need to wait until the required amount of traffic is reached for both A and B variations.

If you are looking for an alternative to the classic option, resort to sequential A/B Testing. You will need to start with specifying the baseline conversion rate (conversion rate of your current variation), statistical power (80% by…

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