考虑客户风险修正的客户终生价值建模  

Risk-adjusted Customer Lifetime Value Measurement

作　　者：齐佳音[1] 马君[1] 肖丽妍[1] 钟永光[2] 

机构地区：[1]北京邮电大学经济管理学院,北京100876 [2]青岛大学管理科学与工程系,山东青岛266071

出　　处：《管理工程学报》2015年第2期149-159,共11页Journal of Industrial Engineering and Engineering Management

基　　金：国家自然科学基金资助项目(71171023);教育部新世纪优秀人才支持计划资助项目(NCET-10-0241)

摘　　要：客户终生价值(Customer Lifetime Value,CLV)建模中如何考虑客户风险是目前客户关系管理领域所关注而且有待解决的难题。本文旨在探讨如何通过客户风险修正CLV模型。首先将客户风险划分为包括波动风险、衰退风险、流失风险与信用风险,并提出前三者的度量方法;随后采用改良的贝叶斯网络方法,从条件概率的角度描述了风险之间的关系,同时计算客户风险值;最后,借鉴金融领域对资产进行风险修正的方式,通过贝叶斯网络输出的风险得分,计算客户的Beta风险,对传统的CLV模型中的折现率进行风险修正,得到RCLV模型。本文利用河北省某电信公司的中小企业客户的固定电话数据进行模型仿真和验证,说明所建立模型的合理性和应用价值。Ever since the mid-late 20th century, in the field of customer relationship management, customer lifetime value （CLV） has been focused and received much attention from scholars and the enterprise managers. Although the idea that customer risk should be considered into the CLV modeling is widely accepted, it is still a question to be further studied that how to reasonably add the customer risk into CLV modeling. In this paper, we aim to explore the method of using customer risk to adjust CLV modeling. Our contributions are as follows： Firstly, we provide several kinds of customer risks that affect CLV and formulate metrics. We develop two selection rules for risks which are the risk is able to actually influence the cash flow and be measured by the data of enterprises. According to the rules, four types of risks are picked up, including the wave risk, the fall risk, the chum risk and the credit risk. The computational methods are provided for first three risks.Today, evaluation index system of customer risk is wildly used and its subjectivitymakes the evaluation results difficult to convince people, so we develop three mathematical models to measure risks objectively. Particularly, we adopt the proportional hazard function which is combined with the objective probability model and the factors of reality for calculating individual probability of chum. Secondly, we research the relationships between four types of customer risks and merge them into one single risk score with an improved Bayes Network. Nowadays, the traditional Bayes Network method uses in customer relationship research used basic datadirectly, so it＇s incapable of showing the mechanism of data and dealing with time series data.We abandon the traditional Data Mining method and improve the existing Bayes Network method in order to overcome the two weaknesses above. The specific method is calculating the risk through the formulate metrics in part one, making it to be the nodes of Bayes Network and then building the Bayes network of the various

关 键 词：客户风险 客户终生价值 贝叶斯网络 Beta风险 

分 类 号：F272.1[经济管理—企业管理]