Applying Bayesian Belief Network approach to customer churn analysis: A case study on the telecom industry of Turkey

Bundling of telecom offerings: An Empirical Investigation in the Turkish market

“…Annual churn rate of European mobile operators is between 20% and 38%, which is very destructive to operators as cost of churn is measured billions of dollars in the sector (Lemmens & Gupta, 2013). Naturally, telecom operators aim to reduce churn rate and keep their subscribers from other telecom operators' attacks (Kisioglu & Topcu, 2011). High level of competition in the telecommunications sector induces telecom operators from acquiring customers to retaining customers (Ahn, Han, & Lee, 2006).…”

Detecting GSM churners by using Euclidean Indexing HDMR

“…Churner behaviors have been analyzed to obtain predictive models for campaign and churn management. Bayesian Belief Network is used to determine the casual relations between the factors that affect customer churn [2]. Later, alternative promotions were offered to the customers in order to retain them.…”

Survey of Data Mining Techniques Used for Real Time Churn Prediction

“…Anuj Sharma et al [22] focused artificial neural network approach to predict churn and suggested that neural network can be combined with other techniques like support vector machines, genetic algorithm to develop a new hybrid model to improve the performance and accuracy for churn prediction. Michael C.Mozer et al [23] used neural network, logistic regression to obtain higher prediction accuracy in churn.…”