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Hajiha, A., Radfar, R. and Malayeri, S.S. (2011) Data Mining Application for Customer Segmentation Based on Loyalty: An Iranian Food Industry Case Study. IEEE International Conference on Industrial Engineering and Engineering Management, Singapore, 6-9 December 2011, 504-508.

has been cited by the following article:

• TITLE: Mining Profitability of Telecommunication Customers Using K-Means Clustering

  AUTHORS: Hasitha Indika Arumawadu, R. M. Kapila Tharanga Rathnayaka, S. K. Illangarathne

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

  JOURNAL NAME: Journal of Data Analysis and Information Processing, Vol.3 No.3, August 21, 2015

  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.