In web analytics, A/B testing is a randomized experiment with two variants, A and B. It includes the application of statistical hypothesis testing. In the field of statistics, hypothesis testing is also known as "two-sample hypothesis testing".
A/B testing is a way to compare two versions of a single variable, typically by testing the response to an A variant against a B variant. The objective is to determine which of the two variants is more effective.
In content marketing, the process of comparing the two versions can determine which version produces better results. Most A/B testing in marketing is directed toward improving conversion rates.
A/B testing is also known as bucket tests, split, or split-run testing.