A/B testing is a controlled experimental method based on statistical principles, which validates hypotheses by randomly assigning target users to version A and version B, and comparing behavioral data differences between the two groups. This method is widely applied in scenarios like product design optimization, marketing strategy adjustment, and user experience improvement, helping teams make data-driven decisions rather than relying on subjective judgment. A/B testing requires control of key elements like sample size, testing period, and statistical significance to draw reliable conclusions.
