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An Approach to CRM: Usage Behavior Analysis with K-Means Algorithm

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dc.contributor.author Kyaw, May Thu
dc.contributor.author Lwin, Mar Mar
dc.date.accessioned 2019-07-22T08:01:34Z
dc.date.available 2019-07-22T08:01:34Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1168
dc.description.abstract Nowadays, information and communication technologies are developing with great speed. In the advent of information era, information technology has developed rapidly and has become significant for every business, particularly the credit card business. The purpose of this paper is to classify the selected customers into clusters using k-Means Algorithms and then decide with the concept of customer relationship management (CRM) to identify high profit, gold customers. The result of this study will benefit the organization in exploiting it to bring about competitive advantage and being able to retain customers as well as attract potential ones. The objective of this paper is to help the managers to segment the customers and identify which customers to target for credit card business services by using behavior analysis. Consequently, the results show that there is a clear distinction between the segments in terms of customer behavior. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.subject Data Mining en_US
dc.subject Customer Relationship Management en_US
dc.subject k-means algorithm en_US
dc.subject Credit Card en_US
dc.title An Approach to CRM: Usage Behavior Analysis with K-Means Algorithm en_US
dc.type Article en_US


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