基于RFMD模型和聚类分析的健身休闲行业客户分类

Customer Segmentation of Fitness and Leisure Industry Based on RFMD Model and Cluster Analysis

摘要: 本研究改进了原始RFM模型，构建了新的客户价值识别模型RFMD，用于对健身休闲行业客户进行分类，并根据所提出的模型识别出该行业的不同价值客户群体。研究使用了上海一家民营体育场馆的真实数据，在RFM模型中新增客户平均消费持续时长指标D，并采用两步聚类与K-means聚类相结合的两阶段聚类算法对客户进行聚类。研究结果表明，基于RFMD模型可将健身休闲行业客户分为“重要价值客户”、“一般价值客户”和“低价值客户”。

Abstract: This paper improves the original RFM model and builds a new customer value recognition model RFMD, which is used to classify customers in the fitness and leisure industry and identify different value customer groups in the industry based on the proposed model. The study used real data from a private sports stadium in Shanghai, added a customer average consumption duration indicator D in the RFM model, and used a two-stage clustering algorithm combining two-step clustering and K-means clustering to gather customers kind. The research results show that based on the RFMD model, customers in the fitness and leisure industry can be divided into “important value customers”, “general value customers” and “low value customers”.