Mastering Data Mining: The Art and Science of Customer Relationship Management
Mastering Data Mining: The Art and Science of Customer Relationship Management
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Computer assisted customer churn management: State-of-the-art and future trends
Computers and Operations Research
Toward a hybrid data mining model for customer retention
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
On learning algorithm selection for classification
Applied Soft Computing
Review: Data mining techniques and applications - A decade review from 2000 to 2011
Expert Systems with Applications: An International Journal
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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.