The present study proposes a Customer Behavior Mining Framework on the basis of data mining techniques in a telecom company. This framework takes into account the customers’ behavior patterns and predicts the way they may act in the future. Firstly, clustering technique is used to implement portfolio analysis and previous customers are divided based on socio-demographic features using k</em...

Much has been written about word of mouth and customer behavior. Telephone call detail records provide a novel way to understand the strength of the relationship between individuals. In this paper, we predict using call detail records the impact that the behavior of one customer has on another customer’s decisions. We study this in the context of churn (a decision to leave a communication servi...

The key question of this study is: How long should the length of customer event history be for customer churn prediction? While most studies in predictive churn modeling aim to improve models by data augmentation or algorithm improvement, this study focuses on a another dimension: time window optimization with respect to predictive performance. This paper first presents a formalization of the t...

The Indian telecom sector has been met with competitive pressure after deregulation. Many key developments took place in the early 2000. The telecom service providers are expected to struggle with complex issues of new technologies, and value added services through continuous innovations. Though many service industries are affected by the churn phenomenon, the problem is extremely acute in the ...

Several studies have demonstrated the superior performance of ensemble classification algorithms, whereby multiple member classifiers are combined into one aggregated and powerful classification model, over single models. In this paper, two rotation-based ensemble classifiers are proposed as modeling techniques for customer churn prediction. In Rotation Forests, feature extraction is applied to...

Facing the issue of increasing customer churn, many service firms have begun recommending pricing plans to their customers. One reason behind this type of retention campaign is that customerswho subscribe to a plan suitable for themshould be less likely to churnbecause theyderivegreater benefits from the service. In this article, the authors examine the effectiveness of such retention campaigns...

Organizations always take part in competition and as the competition grows; they are more concern about their customers rather than products. Organization always focuses on customer’s behaviour to retain in market competition. Churn prediction models are developed to manage and control customer churn in order to retain existing customers. Churn prediction aims to predict profitable customers. T...