Imagine you’re in the store and there’s a special offer: Your favorite beer is currently selling 4 beers for the price of what you usually pay for 2 beers. Sounds pretty good, right?

Now, what if I tell you, that you can achieve the same offer for your store page conversion.

Let’s look at an example:

Users who land on your store page convert to installs at a 20% rate. After optimizing your store page, you are able to achieve a conversion rate of 40%. So, instead of getting 20 000 installs for 100 000 page views, you’ll get 40 000 installs for the same 100 000 page views with the same budget.

Pretty much the same deal as your store had!

Let’s take a look at how to utilize a/b testing to achieve this.

A/B testing allows you to test your store pages with multiple visuals without having to upload and approve them in app stores. Build store pages that appear and feel like real store pages but are actually look-alike pages that analyze user behavior while they are on the page.

You can optimize your store page to match the preferences of your target audience and help convert visitors into installs in the most effective way. You will conduct UA campaigns using look-alike pages as the ad’s landing page. Build different variations of the store page to use as the landing page with Geeklab and find the best fit for your audience.

The goal of the testing is to find the metadata that engages and converts into installs with the highest rate. This usually includes multiple tests of different hypotheses. Since markets and user preferences are ever-changing, it’s also important to keep your store pages up to date at all times.

Now let’s look into how to run valid ASO a/b tests with some concrete steps

Screenshots are the most visible visual element on the store page, so it’s preferable to begin your a/b testing there. There are numerous elements in screenshots that can be tested. It’s best to start by focusing on the biggest elements.

To start planning for you’re a/b test you can find it insightful to analyze your competitors. With, for example, Geeklabs GrowthLab you can create lists out of your competitors and compare their metadata next to each other. You can use Quantic Foundry game motivation model to map some common traits that your competitors have in their screenshots.

With the findings you can then build hypothesis for your store page to test.

With the motivation findings, you can begin to test smaller visual elements. You can, for example, test how different characters affect the conversion rate. The characters and even the expressions on the characters’ faces can have a significant impact on the store page’s conversion rate.

You might also want to see how the page performs without one.

If you are testing the order of the screenshots, keep in mind that when users land on the Google Play store page, they will see four portrait screenshots. So, if you test different orders of four portrait screenshots in Google Play, regardless of the order, they will all be visible to users from the very beginning.

Conclusion

Create hypotheses about what to test to get started with your ASO a/b testing. This will allow you to see clearly through the process and fully benefit from the findings. Your competitors can be an excellent starting point for planning. You can identify some recurring elements on your competitors’ store pages. 

To get help with testing you’ll find this article helpful.