 CRBT customer churn prediction: can data mining techniques work?Qian Su, PeiJi Shao and Tao Zou International Journal of Networking and Virtual Organisations, 2010, vol. 7, issue 4, 353-365 Abstract: Coloring Ring Back Tone (CRBT) is one of the most successful Value-added (VAD) services in China telecommunication operators. Under fierce competition conditions, CRBT customer churn has significantly decreased the profits of operators. Thus churn management has become a major focus to retain subscribers via satisfying their needs under resource constraints. One of the challenges is that churn prediction specific to this business is not available in existing literature. Through empirical evaluation, this study analyse the features of CRBT, compare various data mining techniques that can assign a 'propensity to churn' to each CRBT subscriber. The results indicate that our models can achieve satisfactory prediction effectiveness by using customer demographics, billing and service usage information. At the same time, we find some new symptoms different from existing telecom churn literature, and try to explain them, and point out which predictors are needed to intensively monitor by telecom operators. Keywords: churn management; coloring ring back tone; CRBT; data mining; decision trees; neural networks; telecommunications; resource constraints; customer demographics; billing; service usage; customer churn prediction. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijnvor:v:7:y:2010:i:4:p:353-365 Access Statistics for this article More articles in International Journal of Networking and Virtual Organisations from Inderscience Enterprises Ltd |
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