基于数据挖掘的客户价值预测方法

提出了一种利用聚类和分类等数据挖掘技术预测客户价值的新方法.通过对客户历史交易数据的分析,获得能够综合反映老客户忠诚度和价值度的指标.基于该指标对老客户进行聚类,将老客户划分为若干个不同价值的客户群,即为每个老客户赋予一个价值等级标号.利用朴素贝叶斯分类方法来预测新客户(或潜在客户)的价值,并依据预测结果来制定相应的重点客户发展战略.实例验证了该方法的有效性和可行性.

Method Based on Data Mining to Forecast Customers' Value

A new method to forecast customers' value is put forward using such data mining techniques as clustering and classification.The indicators reflecting old customers' value and business integrity are gained through analyzing the historical transaction data.Then,these old customers are clustered and further classified into different groups in accordance to their value indicators,i.e.,each and every old customer is assigned with a mark equivalent to its value.The naive Bayesian classification method is used to forecast new or potential customers' value,and a relevant customer development strategy is thus available.A numerical example is given to verify the effectiveness and practicability of the method proposed.