Analysis of supermarket member classification based on K-means algorithm

Abstract:
The loss of members and the decline of consumption are the problems that department stores are facing in recent years. How to improve customer loyalty with lower investment and improve the consumption amount and profit margin of each order is the problem that the company needs to solve. Based on the retail data of XX supermarket in recent one year, this paper constructs an RFM model, applies k-means clustering algorithm to identify and segment members, and divides members into key customers Focus on developing customers and general customers, and give corresponding service strategies.