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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归率,需要分析大规模客户数据集,以通过最适当的渠道为客户提供最佳产品优惠。但是,这个问题非常具有挑战性,因为通常只针对整个数据集的非常小的部分,收到了一些正回报。本文研究了银行产品营销的类似问题。所提出的方法是两层系统,首先将客户组成,然后构建产品和通信渠道提供的分类模型。现实生活银行竞选数据集的实验分析显示了有希望的结果。

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