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Customer Future Profitability Assessment: A Data-Driven Segmentation Function Approach

机译:客户未来的盈利评估:数据驱动的分割功能方法

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One of the important tasks in customer relationship management is to find out the future profitability of individual and/or groups of customers. Data mining-based approaches only provide coarse-grained customer segmentation. It is also hard to obtain a high-precision structure model purely by using regression methods. This paper proposes a data-driven segmentation function that provides a precise regression model on top of the segmentation from a data mining approach. For a new customer, a structure model constructed from profit contribution data of current customers is adopted to assess the profitability. For an existing customer, external information such as stock value performance is taken into the regression model as well as historical trend prediction on the profit contribution. In addition, this paper shows how the proposed approach works and how it improves the customer profitability analysis through experiments on the sample data.
机译:客户关系管理中的重要任务之一是找出个人和/或客户组的未来盈利能力。基于数据挖掘的方法仅提供粗粒度客户分割。通过使用回归方法纯粹是纯粹获得高精度结构模型。本文提出了一种数据驱动的分割功能,该函数在数据挖掘方法的顶部提供精确的回归模型。对于新客户来说,采用目前客户的利润贡献数据构建的结构模型来评估盈利能力。对于现有客户,诸如库存价绩效等外部信息被带入回归模型以及对利润贡献的历史趋势预测。此外,本文显示了所提出的方法如何运作以及通过样本数据的实验提高客户盈利能力分析。

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