A/B testing, also known as split testing, compares two versions (A and B) of something, e.g. a webpage, email, or ad, to see which performs better in terms of predefined metrics. Users are randomly shown one of the versions, and their interactions are measured. Statistical analysis determines if there's a significant difference. The version with better results is then implemented. It's a powerful method for optimising marketing strategies and user experiences.