A/B Testing
A/B testing compares two versions of a page or element by splitting live traffic between them and measuring which produces more conversions. Version A is the control and version B is the variant. Statistical significance confirms whether the observed difference is real or the result of random chance.
Why It Matters
It replaces opinion and guesswork with evidence from real user behavior. Instead of debating which headline or button works, you let visitors decide, which protects revenue and compounds small wins into meaningful conversion gains over time.
Common Mistake
Calling a winner too early. Ending a test before it reaches an adequate sample size and significance means you act on noise, not signal, and often ship a variant that performs no better than the original.