Implementation of data mining technique for customer relationship management (CRM) on online shop tokodiapers.com with fuzzy c-means clustering

L. Zahrotun
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引用次数: 8

Abstract

Online business competition is very tight. One strategy that can be done is to retain customers. By applying the concept of CRM (Customer Relationship Management), the online shop can identify customers, so customers can get special facilities in the appropriate marketing strategies according to their needs. This research discusses about how data mining process from customer data at shop online tokodiapers.com. The process of data mining begins with clustering process using Fuzzy C-Means (FCM) method which is then tested by clustering using purity test. The result of this research is a web-based data mining application that is able to segment customer data on tokodiapers.com using fuzzy C-Means clustering method. The test is done using purity test showed that the best grouping is found on the grouping with 4 clusters with the valueof purity test 0.79.
基于模糊c均值聚类的tokodiapers.com客户关系管理数据挖掘技术的实现
网上商业竞争非常激烈。一个可行的策略是留住客户。通过运用CRM (Customer Relationship Management,客户关系管理)的概念,网店可以识别客户,使客户能够根据自己的需求,在相应的营销策略中获得特殊的设施。本研究讨论了如何从tokodiapers.com网上商店的客户数据中进行数据挖掘。数据挖掘过程首先使用模糊c均值(FCM)方法进行聚类,然后使用纯度测试进行聚类测试。本研究的结果是一个基于web的数据挖掘应用程序,该应用程序能够使用模糊c均值聚类方法对tokodiapers.com上的客户数据进行分割。用纯度测试法进行测试,结果表明,4个簇的组为最佳组,纯度测试值为0.79。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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