App store test hypotheses

App Store Test Hypotheses are solid intentions that will be either proven or disproven at the end of an A/B testing period.
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What are App Store Test Hypotheses

App Store Test Hypotheses are solid intentions that will be either proven or disproven at the end of an A/B testing period which will introduce scope for further investigation. Hypotheses can be based around any element on a product page. 

Hypotheses should be close-ended and require a resolution. A few examples of strong hypotheses for a travel app may be:

  • Visitors will respond more to vacation rentals that feature award winning icons more than award winning text.
  • Visitors looking to book a summer vacation prefer to see images of sunny relaxing locations more than images of busy, crowded cities.

It’s worth avoiding the testing of nuanced, subtle changes, such as changing the background colour on imagery from green to blue, which may not lead to valuable insights.

Why App Store Test Hypotheses are Important

It’s important to keep hypothesizing, testing, re-hypothesizing and re-testing in order to be in a constant state of learning. Over time the results from tested hypotheses come together to form a solid framework in which a successful app product page can be built upon, resulting in the methodical improvement of conversion rates (CVR).

Hypotheses should be researched well and formed smartly. Over time the process of building hypotheses can be based on knowledge gained from seeing how users behave in the store. Take this hypothesis as an example:

  • Changing an app’s description will result in higher CVR.

For people in the industry who know that only 1-2% of users tap to read more on the description, this means it can’t be conclusively proven or disproven as the engagement numbers are so low, to begin with, any impact is negligible. Any change to an app’s description will likely go unnoticed by the vast majority of visitors to the page; exposing changes to a low minority of users wouldn’t make the best use of the testing opportunity. 

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