What analysis technique evaluates customer purchases to recommend complementary products?

The analysis technique that evaluates customer purchases to recommend complementary products is market basket analysis. This method is primarily used in retail and e-commerce to understand the purchasing behavior of customers by identifying relationships between items that are frequently bought together.

Market basket analysis works by analyzing transaction data from sales and determining associations between different products. For instance, if a customer buys bread, the analysis may find that they are likely to also buy butter or jam. This insight can be utilized to create targeted marketing strategies and personalized recommendations for customers, enhancing cross-selling opportunities.

While other techniques like cluster analysis and classification analysis also provide valuable insights into data, they do not specifically focus on the transactional relationships between products that market basket analysis does. Estimation analysis is more related to predicting values based on data, rather than uncovering relationships between products in the context of customer purchases.