Customer Value Prediction Model Based on Markov Chain in B2C

Ma Hui-min, Chen Jian-ling, Zhu Kai
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引用次数: 3

Abstract

According to the flexibility and predictive features of Markov chain model and the analysis of customers' historical behavior of RFM (recency, frequency, monetary), this paper employs these two models into the customer value prediction in B2C context. By refining the conventional RFM model, the prediction of the customer's value becomes more precise. Such method helps to make effective customer marketing and relationship management polices. The article also describes a case study that demonstrates its accuracy
基于马尔可夫链的B2C客户价值预测模型
本文根据马尔可夫链模型的灵活性和预测性特点,分析了客户RFM的历史行为(最近、频率、金钱),将这两种模型应用到B2C环境下的客户价值预测中。通过改进传统的RFM模型,对客户价值的预测变得更加精确。这种方法有助于制定有效的客户营销和关系管理政策。本文还描述了一个案例研究来证明其准确性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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