Data Mining and Marketing Strategy Analysis of E-commerce Enterprises Based on RFM Model

In the era of big data, in order to improve the core competitiveness of e-commerce enterprises, it is necessary to accurately segment enterprise customers, and then adopt personalized marketing strategies to improve customer satisfaction and loyalty. Based on the RFM model and combined with K-means clustering, this paper scientifically establishes a feedback model through five steps of business system raw data collection, effective data extraction, data exploration and preprocessing, modeling and application, and results and feedback. It analyzes customer consumption behavior data, and finally classifies customers, helps companies identify potential customers, evaluates, categorizes and effectively manages customers, and provides an important reference for formulating reasonable marketing strategies. This paper advocates "differentiated" marketing for e-commerce customers based on the results of scientific analysis of "big data", so as to achieve the effect that input is proportional to output.