A/B testing is a controlled experiment that randomly splits traffic between variants to measure which version produces a statistically significant lift on a defined metric. Also called split testing, it works across webpages, emails, ads, or product flows, with metrics like signup, purchase, click, or retention. It is the core experimental method underneath conversion rate optimization and most modern growth marketing.
A valid A/B test requires three things: random assignment (users land in variant A or B by chance, not by characteristic), a pre-defined primary metric (decided before the test starts, not picked after), and adequate sample size (calculated before launch using the baseline conversion rate, the minimum detectable e...