面向企业管理的动态客户关系马尔科夫预测模型设计  

Design of Markovian Prediction Models for Dynamic Customer Relationships for Enterprise Management

作　　者：郑姝敏 ZHENG Shumin(Department of Business Administration,Quanzhou Arts and Crafts Vocational College,Quanzhou,Fujian 362500)

机构地区：[1]泉州工艺美术职业学院工商管理系,福建泉州362500

出　　处：《武夷学院学报》2025年第3期60-66,共7页Journal of Wuyi University

基　　金：福建省中青年教师教育科研项目(社科类)一般项目(JAS21658)。

摘　　要：针对由于缺乏对客户状态转移概率的有效分析,导致模型的预测精度不佳的问题。提出面向企业管理的动态客户关系马尔科夫预测模型。首先,通过结合客户与企业的交易量数据,构建出客户在不同阶段下的状态识别标准,实现动态客户状态识别。然后结合多元线性函数,对客户状态的转换意愿进行表征,构建出客户状态转移矩阵。结合逻辑回归方程对客户的购买行为概率进行计算,并构建出动态客户关系马尔科夫预测模型。测试结果表明,采用提出的方法对动态客户关系进行预测时,客户状态预测曲线与实际发展曲线的拟合程度较高,具备较为理想的预测精度。Aiming at the problem of poor prediction accuracy of the model due to the lack of effective analysis of customer state transition probability,a dynamic customer relationship Markov prediction model for enterprise management is proposed.First,by combining the transaction volume data of the customer and the enterprise,the state identification criteria of the customer under different stages are constructed to realize dynamic customer state identification.Then the transfer tendency of customer state is characterized by combining the multivariate linear function,and the customer state transfer matrix is constructed.Combined with the logistic regression equation to calculate the probability of customer’s purchasing behavior,and construct a dynamic customer relationship Markov prediction model.The test results show that when the proposed method is used to predict the dynamic customer relationship,the customer state prediction curve fits well with the actual development curve,and has a more ideal prediction accuracy.

关 键 词：企业管理 客户关系 客户状态 马尔科夫预测 

分 类 号：F523.8[经济管理—产业经济]