A/B Testing: Understanding and Implementing it for Continuous Improvement

Kacper Bąk
3 min readMar 23, 2023
Photo by Kadyn Pierce on Unsplash

A/B testing, also known as split testing, is a technique used in web development to compare one or more versions of variables such as websites, page elements, and applications to see which version performs better than the other. The purpose of A/B testing is to extract value from the comparison, not to see if something works as expected. In this article, I will discuss A/B testing, why it is important, and how to conduct it.

To start with, A/B testing involves creating two versions, A and B, where A is the original version or the control, while B is the variant, a new version of the original. A hypothesis is then raised, and the two versions are compared to see which performs better in relation to the other.

One of the primary reasons to use A/B testing is to achieve a certain goal, typically to increase sales. For instance, a grocery store may use A/B testing to experiment with different product placements and see which layout generates more sales. A/B testing is a powerful tool for businesses as it provides direction for continuous improvement of the product and helps gain more knowledge about clients and different target audiences.

From a software engineering standpoint, A/B testing may seem superfluous. Still, it is an essential tool to avoid costly mistakes and delays in software development. Instead of spending all the time on redesigning a website or application, A/B testing allows developers to test small or significant changes and understand if it’s worth the effort.

So, how do you do A/B testing? There are many ways to do it, but the first step is to have a hypothesis to test. This hypothesis can be anything, but there is a template phrase that can help you assemble a better hypothesis: “If the proposed change here would the expected result here because why the test would work.” This template helps to form a better hypothesis and provides a clear understanding of the purpose of the test.

After creating a hypothesis, the next step is to have options to perform the test of the given hypothesis. You must have two versions of the variable that you want to test. For instance, you can have two versions of a web page, A and B, with different layouts, colors, or font sizes, to see which version…

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