Market basket analysis is a data analysis technique used in retail businesses to identify relationships between products that are frequently purchased together by customers. It involves analyzing the transaction data from point-of-sale systems to identify items that tend to be purchased together.

The goal of market basket analysis is to identify patterns of customer behavior, such as which items are frequently purchased together or which items are frequently purchased after a certain event, such as a promotion or a holiday. By identifying these patterns, retailers can optimize their inventory, product placement, and promotions to increase sales and customer satisfaction.

The output of market basket analysis is typically a set of association rules, which describe the relationships between items in terms of probability or confidence scores. For example, an association rule might state that "customers who purchase bread are 80% likely to purchase milk as well."

Market basket analysis is a powerful tool for retailers to understand customer behavior and optimize their business operations. It is also used in other industries, such as e-commerce and finance, to identify patterns in large datasets.