Mining Profitability of Telecommunication Customers Using K-Means Clustering

Hasitha Indika Arumawadu; R. M. Kapila Tharanga Rathnayaka; S. K. Illangarathne

doi:10.4236/jdaip.2015.33008

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Journal of Data Analysis and Information... > Vol.3 No.3, August 2015

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 PDF HTML XML 3,973 Downloads 5,087 Views Citations

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

Share and Cite:

Arumawadu, H. , Rathnayaka, R. and Illangarathne, S. (2015) Mining Profitability of Telecommunication Customers Using K-Means Clustering. Journal of Data Analysis and Information Processing, 3, 63-71. doi: 10.4236/jdaip.2015.33008.

Conflicts of Interest

The authors declare no conflicts of interest.

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