A method for researching and measuring user interactions using two different versions of a digital product.

What is A/B Testing?

A/B testing, also known as group testing or split testing, is conducted to measure the performance of changes made to various digital products such as websites, email content, digital advertisements, and mobile applications.

For example, A/B testing allows you to analyze how users respond to any interface change on your website. There might be different reasons prompting you to make changes to your website. You can use A/B testing to identify how changes made to solve a detected problem or a newly added feature are received by users.

A/B tests can be adapted to measure user behavior across different digital products and marketing content, ranging from websites and email newsletters to sent SMS messages and notifications, mobile applications, and advertisements. You can learn which of the two different notifications sent to users engages them more or the acceptance rate of an interface change made in a mobile application.

The Importance of A/B Testing

A/B testing systematically measures user behavior in areas where it can be applied, such as websites or mobile applications. It is a highly effective method for solving encountered problems. For instance, the presence of a button intended for users to click but not interacting with is a problem. To find out how to make the button more visible and engaging, A/B tests are used. This way, instead of wasting time with random trials, changes made to the button are presented to a user group, and the changes are observed. If necessary, it is revised and re-tested.

How to Conduct A/B Testing?

A/B testing processes can vary depending on the product, your goals, and the current number of visitors. For example, a website with a low number of visitors should run the test for a longer period to include enough participants. Despite these differences, the fundamental steps to follow in the A/B testing process are:

Research and Data Collection

You need to gather information that answers questions such as why the change is needed in your product, the source of the problem, and what users are demanding. Insufficient traffic on certain pages or a feature you offer being used less than expected could be valid reasons for making changes.

Setting Goals

The purpose of the A/B test and what is targeted with the changes should be determined. This way, you can decide whether the changes were successful after the test.

Developing Hypotheses

You should make assumptions about how users will behave in different scenarios. For example, these hypotheses could assume that changing the location of an interface element will increase user interaction.

Creating Variations

Based on the assumptions, you need two versions of your product: the current one and the modified one for A/B testing. This stage may include processes like design and coding.

Implementing the Test

You need to present the created variations by dividing your user base into groups. The duration of the test should be set to allow enough data collection for accurate results. It is crucial to launch both variations simultaneously and present them to an equal number of users. Presenting version A first and then version B at different times will lead to erroneous results. Similarly, presenting one version to fewer users than the other will also result in misleading conclusions.

Evaluating Results

As a result of the A/B test, you will have data to evaluate how successful the changes were in achieving your goals. If the changes yield the desired outcome, you can present them to all users. If the test fails, you can go back to the beginning and seek a new solution.