Classification Method of Internet Catering Customer Based on Improved RFM Model and Cluster Analysis

作者：Xin Hu, Ziyan Shi, Yanfei Yang, Lanhua Chen · 年份：2020 · DOI：10.1109/icccbda49378.2020.9095607 · 被引用次数：16 · 研究领域：Complex Network Analysis Techniques、Customer Service Quality and Loyalty、Customer churn and segmentation

According to the characteristics of customer data of Internet catering takeaway orders, this paper proposes an RFMT customer classification model based on customer behavior. The principal component analysis method is used to determine the weight of each indicator, and the K-means++ clustering algorithm is used to classify customers into five types of customer groups: high-quality customers, stable customers, potential customers, general customers and low-quality customers. Simulation results show that the customer classification method based on the improved RFM model can make Internet catering merchants adopt targeted strategies for customers with different values.