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A new application of clustering for segmentation of banks’ e-payment services based on profitability

机译:集群技术在基于盈利能力的银行电子支付服务细分中的新应用

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In today' s extremely competitive environment, customers are the most important asset of any business and success of any organization depends on loyal customer retention. Therefore, it is important to learn more about different groups of customers and propose appropriate plans to take care of them. Customer segmentation is one of the most common methods to analyze customer’s behavior. The market can be divided into several smaller homogeneous groups, which helps organizations deliver targeted marketing techniques and provides optimized techniques for resource allocation. This paper uses the information gathered from Point of Sales (POS) in one of Iranian private banks and using two methods of K-Means and Kohonen, customers are clustered into four segments to detect the most profitable customers.
机译:在当今竞争异常激烈的环境中,客户是所有业务中最重要的资产,任何组织的成功都取决于忠诚的客户保留率。因此,重要的是要更多地了解不同的客户群体并提出适当的计划来照顾他们。客户细分是分析客户行为的最常用方法之一。市场可以分为几个较小的同类组,这有助于组织提供有针对性的营销技术并提供优化的资源分配技术。本文使用从一家伊朗私人银行的销售点(POS)收集的信息,并使用K-Means和Kohonen的两种方法,将客户分为四个部分,以检测最有利可图的客户。

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