The term "A/B testing" or "split testing" essentially refers to a marketing and product development methodology through which a comparison is made between two versions of a web page, app, or any other digital asset to find out which actually serves its intended purpose more effectively. In an A/B test, both versions A and B are shown to the two different user segments at the same time, later on using statistical analysis to find out which version holds a higher conversion rate, engagement, or other favored metric.
A/B testing is a way to optimize digital experiences and improve key performance indicators (KPIs). A/B testing gives you the opportunity to compare two versions of the tested webpage or its functionalities, so that based on the results obtained during the testing of design, copy, or functionality, a data-driven decision can be made. "A/B testing can test everything from the color of a call-to-action button to the layout of a landing page to the wording of an email subject line."
Running an effective A/B test requires coming in with a clear hypothesis for which change will lead to improved performance. The two versions should otherwise be identical, apart from that one element being tested, and the test should run long enough so that the results are statistically significant. After allowing the test to run its course, the winning version may be implemented, and the process iterated with new hypotheses in order to continually optimize performance.
A/B testing has become popular nowadays not only in digital marketing but also in e-commerce and software development. This is, therefore, an essential tool in business helping optimize user experience, increase conversions, and rapidly grow. As such, marketing automation and personalization tools rose, making testing through A/B testing more sophisticated and easier than ever before for even small businesses to be able to optimize their digital presence and be in a position to compete with the big players in their industry.