Title :
A Hybrid Approach to Predict Churn
Author :
Basiri, Javad ; Taghiyareh, Fattaneh ; Moshiri, Behzad
Author_Institution :
Sch. of Electr. & Comput. Eng., Univ. of Tehran, Tehran, Iran
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.
Keywords :
customer relationship management; forecasting theory; market research; OWA algorithm; OWA technique; business; churn management system; churning customer; customer retention; marketing researcher; ordered weighted averaging; prediction accuracy; prediction algorithm; telecommunication company; Artificial neural networks; Bagging; Boosting; Classification algorithms; Classification tree analysis; Open wireless architecture; Prediction algorithms; Bagging and Boosting; LOLIMOT; OWA; churn management system; hybrid approach;
Conference_Titel :
Services Computing Conference (APSCC), 2010 IEEE Asia-Pacific
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-9396-8
DOI :
10.1109/APSCC.2010.87