A/B testing is a method of comparing two versions of a webpage, app, email, or ad against each other to determine which performs better. Version A is the control, and version B is the variation with one changed element.

Traffic is split randomly between the two versions, and a predefined metric such as conversion rate or click-through rate is measured. Statistical significance is used to determine whether the difference is real. A/B testing is widely used in marketing, product development, and UX design to make data-driven decisions.

Key points

• Comparing two versions
• Randomised traffic split
• Measures a predefined metric
• Uses statistical significance