Which process can best identify patterns in consumer behavior to predict future purchases?

Market basket analysis is a process that specifically looks at consumer behavior by analyzing the co-occurrence of purchases made by customers. It aims to identify patterns or relationships between different products in transactions. For example, if customers often purchase bread and butter together, market basket analysis can reveal this association, allowing businesses to predict that customers will likely buy these items concurrently in the future. This insight helps retailers with product placement, promotions, and inventory management to maximize sales based on typical purchasing patterns.

While estimation analysis, cluster analysis, and classification analysis also pertain to understanding data, they serve different purposes. Estimation analysis typically deals with predicting numeric values and trends based on existing data rather than directly identifying patterns in consumer purchasing. Cluster analysis groups similar items or customers but does not necessarily focus on predicting future behaviors based on purchasing patterns. Classification analysis categorizes data into predefined groups but may not reveal the association rules between products that lead to the actionable insights drawn from market basket analysis. Overall, market basket analysis is uniquely suited for predicting future purchases by evaluating historical transaction data to uncover shopping patterns.