Market Basket Analysis (MBA) is a data mining technique used to uncover relationships between items. While standard sales analysis might list top-selling products by volume, MBA groups them by association. It answers the question: "If a customer buys Product A, how likely are they to buy Product B?" By analyzing transaction sets, MBA transforms raw receipt data into actionable merchandising insights. It evaluates three key metrics: Support (how frequently items appear in the data), Confidence (the conditional probability that buying item X leads to buying item Y), and Lift (the strength of the association compared to random chance). Instead of viewing a shopping cart as a random collection of goods, MBA reveals hidden patterns, identifying "Complementary Goods," "Substitute Items," or "Anchor Products," allowing a business to optimize layouts and cross-selling strategies.