What is A/B Testing?

A/B testing compares two or more variants under controlled conditions to validate a product or marketing hypothesis with real user behavior. A signup page might test button copy, pricing layout, or form order while users are randomly assigned to different versions.

A reliable test starts with a clear hypothesis, such as “a shorter form will increase completion.” The team then defines the primary metric, sample size, and duration before launching. Calling a winner too early can produce false confidence, especially when traffic is low or weekly behavior patterns are strong.

Types of Tests

Classic A/B: Two versions of one change are compared.
A/B/n: Several variants run at the same time.
Multivariate testing: Combinations of elements such as headline, image, and button are measured together.
Server-side testing: Backend decisions such as pricing logic, recommendations, or onboarding steps are tested.

Business Use

A/B testing helps product teams make decisions from evidence instead of opinion. With a feature flag, a new experience can be exposed to a small segment and disabled quickly if metrics degrade. E-commerce teams often track add-to-cart rate, SaaS teams track activation, and publishers track subscription conversion rate.

Not every change needs a formal experiment. For low-traffic pages, user interviews or usability testing may produce clearer answers faster.