Comparing clustering techniques for telecom churn management

Authors:
Adem Karahoca;Ali Kara
Affiliations:
Bahcesehir University, Engineering Faculty, Computer Engineering Department, Istanbul, Turkey;Bahcesehir University, Engineering Faculty, Computer Engineering Department, Istanbul, Turkey
Venue:
TELE-INFO'06 Proceedings of the 5th WSEAS international conference on Telecommunications and informatics
Year:
2006

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Abstract

Mobile telecommunication sector has been accelerated with GSM 1800 licenses in the Turkey. Since then, churn management has won vital importance for the GSM operators. Customers should have segmented according to their profitability for the churn management. If we know the profitable customer segments, we have chance to keep in hand the most important customers via the suitable promotions and campaigns. In this study, we implemented clustering algorithms to 250 subscribers' 100MBs call detail records(CDRs), demographic data and billing information. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) compared with K-Means, Expectation Maximization and Farthest-First clustering techniques. As a result, DBSCAN has good distinct clusters for profiling customer segments.