Google Play Experiments vs. A/B Testing in SplitMetrics

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The question I get very often from fellow mobile marketers is what’s the difference between app store pages tests in Google Play Experiments and SplitMetrics experiments? Let’s dwell on distinctions between these mobile AB testing platforms.

It’s clear that Apple App Store doesn’t allow A/B testing of app pages, so marketers have to bypass the App Store with custom coded landings or software like SplitMetrics. Google Play in its turn provides experiments within the store itself and these tests are free, so why go elsewhere?

Short answer: indeed, Google Play allows mobile publishers to run experiments on their app pages in the store, but these tests have significant limitations.

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How Not to Do Mobile A/B Testing: 7 Fails of Mobile App Marketers

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Split tests have become so mainstream that people are now launch A/B experiments for everything from educational videos to dating profiles (yes, this is happening). Yet, commoditization of the tactic means people too often fall into a trap of overlooking some basic rules A/B tests and experiments. Let’s look at some of the experiments fails in the context of mobile app store optimization.

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ASO checklist

Improve your ASO with the World's Most Ultimatest App Store Optimization Guide!

10 Tips On Designing Screenshots That Convert (Backed by 500+ A/B Tests)

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Your app’s story starts with the first page…your app store page. One of the key things that make your story stand out in the overpopulated marketplace of apps is your screenshot design. After testing hundreds of screenshot sets for a variety of apps, we’ve observed that some design approaches tend to work better than others. This article will discuss common pitfalls and best practices in designing app store screenshots that convert.

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What’s a Good App Store Page Conversion Rate? We Asked 10M Users.

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When clients call to talk about experiments they can run with our AB testing app, one of the questions that keeps coming up is what’s a good conversion rate. It makes sense – doesn’t matter how pretty the icon looks unless it brings you more installs and makes your products the best apps to advertise on for publishers. But what’s good app store conversion? How do you measure your app store page performance? Aggregated conversion data from other apps will help you see where you stand so that you can set better, smarter, and more tangible goals.

This post summarizes the data we’ve gathered from hundreds of experiments with over 10 million users. It also breaks down the median app store page and app store ads conversion stats by category. You can use these benchmarks as a starting point to guide your ASO activities (or to break and set new records in conversion optimization). Game on!

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The importance of ASO metadata optimization

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Have you thought that your App Store landing page might be more converting? We all know that there’s always something that can be improved but rarely have time to test our ideas.

Mobile app market is getting more and fierce in terms of competition for a user. Each and every app developer wants to acquire a quality user at a reasonable price. Mobile advertising is booming and prices go up every month… They only way to optimize your advertising budget is to be smart, test everything you can and find out the most effective combinations.

Ok cool, but in any case a user gets to your app page in App Store or Google Play and makes the final decision right there. So it’s crucially important to have your page optimized towards conversion as it brings you more users, lower CPIs as a result of higher conversions.

Mobile CPI rates Mobile CPI rates

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What is A/B testing?

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In marketing and business intelligence, A/B testing is a term for a randomized experiment with two (or more) variants, A and B, which are the control and treatment in the controlled experiment. It is a form of statistical hypothesis testing with two variants leading to the technical term, Two-sample hypothesis testing, used in the field of statistics. Other terms used for this method include bucket tests and split testing but these terms have a wider applicability to more than two variants. In online settings, such as web design (especially user experience design), the goal is to identify changes to web pages that increase or maximize an outcome of interest (e.g., click-through rate for a banner advertisement). Formally the current web page is associated with the null hypothesis.

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