NDLI: A Hybrid Approach to Predict Churn

Content Provider	IEEE Xplore Digital Library
Author	Basiri, J. Taghiyareh, F. Moshiri, B.
Copyright Year	2010
Abstract	Acquiring new customers in any business is much more expensive than trying to keep the existing ones. As a result, many prediction algorithms have been proposed to detect churning customers. In this paper, the ordered weighted averaging (OWA) technique is brought to the attention of marketing researchers. We have applied OWA technique to improve the prediction accuracy of existing churn management systems. The decision lists of underlying prediction algorithms have been fused using OWA algorithm. Applied to the database of a telecommunication company, this method is found to significantly improve accuracy in predicting churn compared to the best existing result in the literature of the churn management. Our findings lead us to believe that using OWA technique could cause to increase profit for the companies.
Starting Page	485
Ending Page	491
File Size	419836
Page Count	7
File Format	PDF
ISBN	9781424493968
DOI	10.1109/APSCC.2010.87
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	hybrid approach Bagging and Boosting Artificial neural networks OWA Prediction algorithms Boosting Open wireless architecture Classification algorithms churn management system LOLIMOT Bagging Classification tree analysis
Content Type	Text
Resource Type	Article

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