A/B testing

A/B testing (also called split testing) is a method of comparing two versions of a page, element or message to find out which one performs better. Real visitors are split into two groups: one sees version A, the other version B, and their behaviour — clicks, sign-ups, purchases — is measured. The version that produces better results wins, based on data rather than opinion.

How A/B testing works

A test isolates a single change, such as a different headline, button colour or layout, so that any difference in results can be attributed to that change. Traffic is divided randomly and both versions run at the same time to avoid the influence of external factors. Once enough data is collected to be statistically meaningful, the results reveal which variant drives more of the desired action. Testing one variable at a time keeps the conclusions clear.

Why A/B testing matters

A/B testing removes guesswork from optimisation. Instead of debating which UI or copy is better, teams let user behaviour decide, which steadily improves conversion and UX. It is widely used on landing pages, sign-up flows, checkout steps and email campaigns. Because changes are validated on real traffic, A/B testing reduces the risk of shipping a redesign that hurts results. It works best as a continuous habit: small, evidence-based improvements compound over time. It is worth remembering that performance matters too — a variant that looks better but loads slower can lose, since speed metrics like Core Web Vitals and even SEO influence how users respond. Disciplined testing, with a clear hypothesis and adequate sample size, turns optimisation into a measurable, repeatable process.