通过稳健的 M 值估算,提升业务智能,实现客户终身价值

M. Elveny, Rahmad B. Y. Syah, Mahyuddin K. M. Nasution
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引用次数: 0

摘要

当企业过于专注于获取新客户而不是留住老客户时,有时就会犯错误。每个客户都有不同的价值。客户终生价值(CLV)是用于评估客户长期价值的指标。在任何商业活动中,客户价值都是一个关键问题。当客户行为存在变化时,当数据分布不正常且存在异常值时,CLV 可以预测客户总收入的价值。本研究采用最大似然估计法 Robust M-estimation 来改进 CLV 数据。通过最小化残差值的回归参数,稳健 Mestimation 可以消除客户指标数据中的异常值。R-square 的准确率为 94.15%,用于衡量模型的性能。这项研究表明,CLV 优化可作为企业的营销和销售策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An boosting business intelligent to customer lifetime value with robust M-estimation
When a business concentrates too much on acquiring new clients rather than retaining old ones, mistakes are sometimes made. Each customer has a different value. Customer lifetime value (CLV) is a metric used to assess longterm customer value. Customer value is a key concern in any commercial endeavor. When there are variations in customer behavior, CLV forecasts the value of total customer income when the data distribution is not normal, and outliers are present. Robust M-estimation, a maximum likelihood type estimator, is used in this study to enhance CLV data. Through the minimization of the regression parameter from the residual value, robust Mestimation eliminates data outliers in customer metric data. With an accuracy of 94.15%, R-square is used to gauge model performance. This research shows that CLV optimization can be used as a marketing and sales strategy by companies.
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