A/B Testing is an empirical method that randomly assigns users to different versions (e.g., Version A and Version B) to compare their performance, enabling data-driven decision-making. It is widely used in product optimization, marketing strategies, and user experience improvements, helping teams reduce subjective speculation and validate hypotheses with quantifiable evidence.