This document discusses how data mining techniques like association rule mining and classification rules can be used to analyze customer purchase data and reduce the gap between consumers and retailers. It proposes applying association rule mining to identify relationships between frequently purchased products, and using classification rules to categorize consumers by attributes like age, income, and marital status. This combined approach could provide retailers with useful insights into purchasing trends and patterns to help them better understand customer needs and improve marketing decisions.