Why You Need A/B Testing For Your Mobile App? 

With the app industry becoming more competitive than ever, knowing how to optimist your app – and your marketing strategies – is critical. It’s critical to test what works because even minor changes to your app’s user experience can have a huge influence on conversion rates.

For example, utilizing A/B testing tools, e-commerce startup Wall Monkeys raised its conversion rate by 550 per cent. This form of testing is vital for all app marketers since it reveals how your app can be improved. We’ll show you all you need to know about A/B testing in this article, including why you need A/B testing for your mobile app?

What is Mobile App A/B Testing

A/B testing for mobile apps involves dividing a user base into two (or more) groups and seeing how a variable influences their behaviour. It’s utilized to figure out how to give the best user experience and produce the best results.

Let’s imagine you want to increase the number of people who download your mobile game. You decide to employ video advertisements to target young boys in the country as part of your user acquisition plan.

It’s smarter to expose your commercials to a small section of that audience – and even smarter to A/B test your video ad – than throwing money at ads that haven’t been proved to work.

You can figure out which video ad produces the best outcomes in this circumstance. If video A featured smaller text than video B but the latter had a 20% better conversion rate, it makes sense to show the video with larger text to a larger audience.

Why You Need A/B Testing For Your Mobile App? 

The advantages of A/B testing on mobile apps are comparable to those of A/B testing on the web.

  • A/B testing enables you to test multiple hypotheses for app experiences and make adjustments to your app experience based on evidence rather than gut instinct.
  • A/B testing tools help to evaluate the effects of changes you make to your app with statistical confidence, as well as to measure how significant that impact will be.
  • You will be able to continuously improve the experience of your mobile app and bring out new features that you know will increase your conversion metrics if you conduct tests on it regularly.

It’s why leading companies like Amazon, Facebook, and Google undertake A/B tests in their mobile apps on a regular basis.

  • On mobile devices, A/B testing is critical for experience optimization, conversion rate optimization, and customization.
  • Another advantage of using a mobile A/B testing tool like Optimize is that you may make modifications to an app that has already been published on Apple’s app store without having to go through the review process. This enables you to iterate on changes more quickly, as well as make corrections and upgrades to live apps.

How to Correctly Do A/B Testing?

A/B testing is a cyclical process that you may use to improve your app and ads over time. With this in mind, here’s how you properly conduct A/B testing:

Make a hypothesis.

To begin, you must conduct research, assess the data, and formulate your hypothesis. You won’t be able to define which variable to test unless you have this.

For example, you might believe that having fewer products on display when you first open your e-commerce app will lengthen your experience. This hypothesis can then be used to define your variable, which should be based on previous research (the number of products on your homepage.)

Before implementing A/B testing, make sure to cross the following items off your list:

  • What do you wish to put to the test?
  • Who do you want to reach out to?
  • What will you do if your hypothesis is confirmed or refuted?

If you’re having trouble deciding what to test, start by defining an issue you’d like to solve. This will provide you with a solid starting point for determining what should be monitored in order to resolve the problem.

Segment Your Target Market.

You’re ready to test these versions on audience samples now that you’ve established your hypothesis and variable. Keep in mind that having several variables will result in a reduced level of confidence in your research.

Simply said, it will be considerably more difficult to determine what factors have influenced the success of your campaign.

You should now split your audience groups and expose them to versions A and B using an A/B testing tool like our Audience Builder. You’ll need a large enough audience to get credible data to evaluate. If your target audience is too tiny, you risk misidentifying app optimizations that will not have the desired impact on wider groups of people.

Analysis

You can now figure out which option produces the best results. Remember to look at every significant measure that could have been affected, as this will allow you to get a lot more information from a single test. Even if your goal is to increase conversions, there may have been an unintended consequence in terms of engagement or session time.

Make the necessary adjustments.

You can confidently expose a bigger audience to effective adjustments if you have found a positive result. Even if your test was ambiguous, the information is still valuable and should be used to revise your hypothesis.

Adapt your hypothesis and test it again.

A/B testing allows you to keep refining your hypothesis over time. Because there will always be methods to improve, you should continually be testing new approaches to increase conversions. To stay ahead of the competition, keep building your hypothesis on new data and implementing new tests.

5 A/B Testing Recommended Practices

Make a list of the things you want to test.

It’s vital to understand why you’re testing a certain variable in the early stages. Do not begin testing until you have a clear hypothesis and a plan for dealing with different outcomes. This may appear to be a straightforward task, but knowing why you’re running these tests ensures you’re not spending time and money on something that won’t give you useful information.

In your research, be prepared for unexpected outcomes.

User behavior will always be complex, which means your A/B tests will occasionally produce unexpected results. In this situation, it’s critical to keep an open mind and apply what you’ve learned. Otherwise, you run the danger of losing money if you don’t learn from your own data.

Even if you aren’t seeing results, don’t cut your tests short.

Even if your hypothesis proves to be incorrect or the outcome looks to be definitive early in the testing phase, A/B tests are useful. It’s critical to persist with your tests long enough to have a high level of confidence in the outcome.

Don’t make any extra charges to your tests.

Because the goal of A/B testing for mobile apps is to determine which variables would increase performance, it’s critical not to make any changes in the middle of the test. This reduces your trust in your findings because you will no longer know which changes resulted in the desired outcome.

Remember, you’re looking for a cause and effect relationship based on conclusive evidence.

Seasonal testing

Your results will be influenced by the time period in which you tested, regardless of vertical. As a result, you can test the same variables at different times of the year and get different findings.

It’s possible, for example, that creative that didn’t work well in the summer will perform well in the winter. This is especially essential in industries like e-commerce, where customers would be prompted to act differently depending on the season.

Types of A/B testing for mobile apps

App marketers and developers should be aware of two forms of A/B testing. Both work on the same idea (finding a positive variable by comparing audience groups), but they serve distinct purposes.

A/B testing within the app

Developers can use this to see how changes to their app’s UX and UI affect KPIs like session length, engagements, retention rate, stickiness, and lifetime value (LTV). There will be more metrics that are particular to the purpose of your app.

For marketing campaigns, A/B testing is used.

A/B testing is a method for app marketers to improve conversion rates, drive installs, and successfully re target consumers. For example, determining which ad creative is more effective for new user acquisition campaigns or determining which creative encourages churned users to return.

Bottom Line 

Mobile App A/B Testing is an excellent tool for all developers since it helps them to identify areas for development in their app’s landing pages, make substantial modifications depending on the results, and, most importantly, understand their users’ behavior. The data is at your fingertips, making deciding what’s best for your app a breeze.

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