本文把数据挖掘技术应用于基于客户价值矩阵的客户价值细分中，建立各类价值客户的分类模型。

This thesis applies data mining techniques to customer segmentation based on customer value matrix and builds the classification model of customer with different value.

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国外已有一些关于消费者行为应用于客户细分方面的研究，如RFM细分模型、客户价值矩阵模型等。

There has been some research abroad on consumer behavior applied in the field of consumer segmentation, like RFM model, Customer Value Matrix (CVM) model, etc.

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首先，通过使用基于价值矩阵的行为细分方法将老客户分成四类，并确定了其中的重要客户。

First, by using behavior segmentation method based on value matrix, customers who have consumed more than one time are segmented into four categories, and the valuable customers are identified.

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