Sequential A/B Testing: Workflow and Advantages over Classic Experiments

Comparing classic and sequential A/B testing

When it comes to A/B tests, anyone has a natural desire to get trustworthy results without spending a heap of money on traffic. Alas, it’s not always possible with classic A/B testing which requires enormous sample sizes at times. 

Is there a better way? Sure, there is!

Sequential A/B testing might become a robust alternative. Such experiments don’t only optimize necessary traffic volumes but also reduce the likelihood of mistakes. Let’s take a closer look at this method and how it differs from the classic A/B testing flow.
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ASO checklist

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

10 Ways to Use Mobile A/B Testing in Pre-Launch: from Ideas Validation to Product Page Refinement

mobile A/B testing in pre-launch

Nowadays, winning users hearts is not an easy task it used to be at the dawn of major app stores. The industry matured and the competition is enormous. Judge for yourself, there are approximately  2.1 million Android apps in the Play Market and almost 1.8 iOS apps available in the App Store.

There’s no use developing a random app in the hope of overnight success. You have to play it smart and validate every single idea before bringing it to life. The best possible way of doing it is mobile A/B testing in pre-launch.
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ASO Starter Pack: App Store Optimization, Mobile A/B Testing and Apple Search Ads

App Store optimization with SplitMetrics

If you’re new to the SplitMetrics blog, check out this post to equip yourself with insights into App Store Optimization (ASO), deep understanding of mobile A/B testing and the most efficient hacks to empowering your Apple Search Ads.
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Guide to Mobile A/B Testing: Proven Strategies, Professional Tips, and App Store Optimization Best Practices

mobile A/B testing guide by SplitMetrics

Mobile A/B testing has been around for quite a while and for a good reason. It can be widely used for marketing purposes: from getting data on the behavior of the target audience to user acquisition on major app stores.

If you understand the value of data-driven decisions, mobile A/B testing might become your go-to solution as it lets you get beyond the guesswork. Splitmetrics teamed up with Apptimize and created a comprehensive guide to App Store and in-app A/B testing which will help you grow your mobile business.

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Google Play App Description: Tips and Tricks for the Best Conversions

SplitMetrics Google Play description tips

Are you looking to create a description for your new Android app that will help you to achieve maximum conversions? Searching for the best practices of Google Play app description is a good idea.

The truth is even the best app in the world won’t be successful if it’s not marketed properly. Besides, with 3.8 million apps in Google Play Store, competition is fierce in every category, so standing out from the crowd is simply essential.

Since the description of your Google Play app is one of the most important aspects of app store optimization (ASO), we’re going to take a smart approach and give you all the tips you need to capture a potential user’s attention.
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Google Play Store Redesign: What’s New

Google Play store redesign

After months of testing different iterations, Google finally launches new design of their Play Store. In general, Android users are accustomed to constant minor changes of the store, but the latest redesign seems to be one of the most substantial ones over the last few years.

Let’s study out all of the changes in the updated Google Store and explain how you can adjust your app store optimization efforts to the changing tides of Google Play.
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All You Need to Know about A/A Testing – from Goal Setting to Results Interpretation

A/A testing is the tactic of using a testing tool to test two identical variations against each other. Whether it is worth to conduct A/A testing and, if so, for what purposes are the questions that invite conflicting opinions.

In this post, we explore why some users of testing tools like SplitMetrics practice A/A tests and dwell on the things they need to keep in mind while performing this sort of tests.
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Category and Search A/B Tests: How to Improve App Store Search Ranking

category and search A/B test

Ever thought how category and search ranking affects your app’s conversion rate? Taking into consideration that about 65% of downloads are the result of a search in the App Store, the most successful mobile marketers never disregard the optimization of their apps for competitive surrounding.

If you aim to improve App Store search ranking, a consistent mobile A/B testing strategy is a must. Search and category split tests should become an integral part of such strategy and today we’ll discuss how to run this kind of A/B experiments to guarantee the best possible results.
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App Store Icon Requirements, Best Practices and Tips

SplitMetrics guide to mobile icons

Imagine that you are opening App Store seeking out new apps you may like – some keywords in a search bar, quick scanning – and the choice is made – you are on the selected app page deciding whether to download it or not. What caught your eye and determined your choice?

Considering the fact that human brain processes visual information much faster than text, the way mobile icons look must be a governing factor for ASO. In this article, we will give you a brief overview of what requirements a “good” mobile icon must meet. We’ll also share best practices, discuss variations of styles and offer a couple of handy icon optimization tips to start with.
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Advancing Mobile A/B Testing with Bayesian Multi-Armed Bandit

A/B Testing with Multi-Armed Bandit

In the course of an A/B experiment, the correct calculation of a sample size is one of the key success ingredients. Yet, sometimes the amounts of traffic necessary for statistical significance of tests put app publishers off. Indeed, a required sample size can be large that means a test lasts longer than you’d like.

However, this obstruction is not that dramatic if you run your A/B tests with help of SplitMetrics. The thing is the platform can apply an alternative approach called Bayesian Multi-armed Bandit (MAB), which can solve the above-mentioned drawback without even bothering you.

A Bayesian Multi-armed Bandit test allows choosing an optimal variation of the two or more. Unlike a classic A/B test, which is based on statistical hypotheses testing, a Bayesian MAB test proceeds from Bayesian statistics. In this post, we’ll learn more about the principles behind it.
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