A/B testing involves comparing two versions of a web page (Version A and Version B) to determine which performs better. It directly compares a variation against the current experience to collect data on the impact of changes. A/B testing takes the guesswork out of optimization by enabling data-driven decisions. The process involves modifying a page to create a second version, then showing each version to half the traffic to measure which has a better conversion rate.