A/B testing

Experiment methodology / From Wikipedia, the free encyclopedia

Dear Wikiwand AI, let's keep it short by simply answering these key questions:

Can you list the top facts and stats about A/B testing?

Summarize this article for a 10 years old


A/B testing (also known as bucket testing, split-run testing, or split testing) is a user experience research methodology.[1] A/B tests consist of a randomized experiment that usually involves two variants (A and B),[2][3][4] although the concept can be also extended to multiple variants of the same variable. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare multiple versions of a single variable, for example by testing a subject's response to variant A against variant B, and determining which of the variants is more effective.[5]

Example of A/B testing on a website. By randomly serving visitors two versions of a website that differ only in the design of a single button element, the relative efficacy of the two designs can be measured.