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Data Mining Based Product Marketing Technique for Banking Products

机译:基于数据挖掘的银行产品产品营销技术

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In direct marketing, in order to increase the return rate of a marketing campaign, the massive customer dataset is needed to be analyzed, to make best product offers to the customers through the most proper channels. However, this problem is very challenging, since, usually only for very small portions of the whole dataset, some positive returns are received. This paper studies the similar problem for bank product marketing. The proposed approach is a two layer system, which first clusters the customers and then, constructs a classification model for product and communication channel offers. Experimental analysis on real life banking campaign dataset shows promising results.
机译:在直接营销中,为了提高营销活动的回报率,需要分析庞大的客户数据集,以便通过最适当的渠道向客户提供最佳产品。但是,此问题非常具有挑战性,因为通常仅对整个数据集的很小一部分而言,会收到一些正回报。本文研究了银行产品营销中的类似问题。所提出的方法是一个两层系统,该系统首先将客户聚类,然后为产品和通信渠道产品构建分类模型。对现实生活中的银行活动数据集的实验分析显示出可喜的结果。

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