Mining Profitability of Telecommunication Customers Using K-Means Clustering

Hasitha Indika Arumawadu¹, R. M. Kapila Tharanga Rathnayaka^2,3, S. K. Illangarathne⁴

¹School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China.
²School of Economics, Wuhan University of Technology, Wuhan, China.
³Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka, Balangoda, Sri Lanka.
⁴School of Management, Wuhan University of Technology, Wuhan, China.

DOI: 10.4236/jdaip.2015.33008                

Abstract

Data mining is the powerful technique, which can be widely used for discovering the customers’ behaviors as well as customer’s preferences. As a result, it has been widely used in top level companies for evaluating their Customer Relationship Management (CRM) system today. In this study, a new K-means clustering method proposed to evaluate the cluster customers’ profitability in telecommunication industry in Sri Lanka. Furthermore, RFM model mainly used as an input variable for K-means clustering and distortion curve used to identify optimal number of initial clusters. Based on the results, telecommunication customers’ profitability in Sri Lanka mainly categorized into three levels.

Keywords

K-Means Clustering, Data Mining, RFM Model, Customer Relationship Management

Conflicts of Interest

The authors declare no conflicts of interest.

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