基于RFM的电商数据客户价值细分实例研究

Case Study on Customer Value Segmentation of E-commerce Data Based on RFM

为了分析某遥控模型电商公司的客户给企业带来的收益,对现有的已注册客户进行客户价值细分,利用RFM模型结合K-means聚类算法对该公司2018年期间的28162条订单交易数据进行聚类,并对其评价、分析和研究。实验表明,基于RFM模型并结合K-means聚类算法能对客户进行有效的细分,因此可以通过适当的营销手段刺激消费,为企业带来更多的收益。

In order to analyze the revenue brought by the customers of a remote control model E-commerce company,the customer value of the existing registered customers is subdivided.The RFM model combined with K-means clustering algorithm is used to cluster the 28162 order transaction data of the company in 2018,and its evaluation,analysis and research are carried out.Experiments show that RFM model combined with K-means can effectively segment customers,so it can stimulate consumption through appropriate marketing means,and then bring more profits to company.