Benchmarking the Data Mining Algorithms with Adaptive Neuro-Fuzzy Inference System in GSM Churn Management

Turkey has started to distribute Global Services of Mobile (GSM) 900 licences in 1998. Turkcell and Telsim have been the first players in the GSM market and they bought licenses respectively. In 2000, GSM 1800 licenses were bought by ARIA and AYCELL respectively. After then, GSM market has saturated and customers started to switch to other operators to obtain cheap services, number mobility between GSM operators, and availability of 3G services. One of the major problems of GSM operators has been churning customers. Churning means that subscribers may move from one operator to another operator for some reasons such as the cost of services, corporate capability, credibility, customer communication, customer services, roaming and coverage, call quality, billing and cost of roaming (Mozer et al., 2000). Therefore churn management becomes an important issue for the GSM operators to deal with. Churn management includes monitoring the aim of the subscribers, behaviours of subscribers, and offering new alternative campaigns to improve expectations and satisfactions of subscribers. Quality metrics can be used to determine indicators to identify inefficiency problems. Metrics of churn management are related to network services, operations, and customer services. When subscribers are clustered or predicted for the arrangement of the campaigns, telecom operators should have focused on demographic data, billing data, contract situations, number of calls, locations, tariffs, and credit ratings of the subscribers (Yu et al., 2005). Predictions of customer behaviour, customer value, customer satisfaction, and customer loyalty are examples of some of the information that can be extracted from the data stored in a company’s data warehouses (Hadden et al., 2005). It is well known that the cost of retaining a subscriber is much cheaper than gaining a new subscriber from another GSM operator (Mozer et al., 2000). When the unhappy subscribers are predicted before the churn, operators may retain subscribers by new offerings. In this situation in order to implement efficient campaigns, subscribers have to be segmented into classes such as loyal, hopeless, and lost. This segmentation has advantages to define the customer intentions. Many segmentation methods have been applied in the literature. Thus, O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg