Market Basket Analysis
Market Basket Analysis is a data mining technique used to discover associations between items in transactional datasets, commonly applied in retail and e-commerce. It identifies patterns such as which products are frequently purchased together, often using algorithms like Apriori or FP-Growth to generate association rules. This analysis helps businesses understand customer purchasing behavior for applications like product recommendations, store layout optimization, and cross-selling strategies.
Developers should learn Market Basket Analysis when building recommendation systems, analyzing sales data, or optimizing business operations in retail, online platforms, or any domain with transactional data. It's particularly useful for implementing features like 'customers who bought this also bought' suggestions, inventory management, and targeted marketing campaigns based on purchase patterns.