A/B testing (also known as bucket testing) is a test that compares two variants of a webpage or an app against each other to see which of the variants performs better for a given conversion goal. For A/B testing, the target group is divided equally into an A and B group. One group is shown the initial version, while the other is shown the version to be tested, that is, with a change. Important remark: you need to check only one variation in A/B testing so that you are able to collect accurate data about the impact of that change. Then, statistical analysis is applied to find out which variant works better in relation to a certain conversion goal.
A/B testing is important since it allows making careful changes to user experience while still gathering data on the results. This, in turn, helps to understand why certain elements of the user experience impact their behavior. Hence, along with improving a single conversion goal, A/B testing can help continually enhance user experience.