Research on Community Consumer Behavior Based on Association Rules Analysis

Abstract

In order to analyze the inner needs and purchase behavior of consumers and increase the sales of goods, a community consumer behavior analysis method based on association rules is proposed. First, to solve the problems of the traditional Apriori algorithm, this article optimizes the data set and improves the efficiency of pruning, then uses the optimized Apriori algorithm to mine the consumer purchase records of the community supermarket to find out the correlation between multiple products, which calculating the consumer’s preference for goods and getting the corresponding association rules and marketing strategies. Finally, this research uses the shopping data of community supermarket retail to conduct experimental tests to consumer preferences. The results show that the optimized Apriori algorithm is more efficient and the correlation analysis result is more accurate.