Split testing, also known as A/B testing or multivariate testing, is a user experience research methodology that allows marketers to compare two or more versions of a web page, email, ad, or other digital marketing content to determine which performs better with the goal of boosting conversions. In a split test, users are randomly assigned to one of two or more versions of the content, and their activity is tracked to see how the different experiences affect the outcome. Split testing can be used to test nearly every element of a webpage, including visual elements like pictures and colors, as well as back-end heavy tests like different checkout processes.

Split testing is an effective way to learn what connects with your audience to improve their experience and increase conversions. However, it is important to properly design the test at the outset to be evenly distributed across key customer attributes, such as gender, to avoid experiment bias and inaccurate conclusions. Additionally, split testing is only one part of the conversion equation, and sometimes other optimization methods may bring a bigger lift.

Overall, split testing is a powerful and relatively pain-free method of optimization that can help marketers improve their digital marketing content and boost conversions.