The enhancement of existing relationships is of pivotal importance to companies, since attracting new customers is known to be more expensive. Therefore, as part of their customer relationship management (CRM) strategy, many researchers have been analyzing “why” customers decide to switch. However, despite its practical relevance, few studies have investigated how companies can react to defecti...

Modeling Churn and Usage Behavior in Contractual Settings The ability to retain existing customers is a major concern for many businesses. However retention is not the only dimension of interest; the revenue stream associated with each customer is another key factor influencing customer profitability. In most contractual situations the exact revenue that will be generated per customer is uncert...

For winning in global competition, companies need to recognition and monitoring of customer's behavior to forecast their behavior and desires earlier than competitors. This research tries to recognize the attributes which lead to customer churn. For this, behavior of 3150 subscribers of an Iranian mobile operator, has observed during one year and trends of them has analyzed by a customized LLNF...

Companies’ interest in customer relationship modelling and key issues such as customer lifetime value and churn has substantially increased over the years. However, the complexity of building, interpreting and applying these models creates obstacles for their implementation. The main contribution of this paper is to show how domain knowledge can be incorporated in the data mining process for ch...

Abstract The definition and modeling of customer loyalty have been central issues in customer relationship management since many years. Recent papers propose solutions to detect customers that are becoming less loyal, also called churners. The churner status is then defined as a function of the volume of commercial transactions. In the context of a Belgian retail financial service company, our ...

The success of prediction models for business purposes should not be measured by their accuracy only. Their evaluation should also take into account the higher importance of precise prediction for “valuable” customers. We illustrate this idea through the example of churn modeling in telecommunications, where it is obviously much more important to identify potential churn among valuable customer...

Churn prediction is a useful tool to predict customer at churn risk. By accurate prediction of churners and non-churners, a company can use the limited marketing resource efficiently to target the churner customers in a retention marketing campaign. Accuracy is not the only important aspect in evaluating a churn prediction models. Churn prediction models should be both accurate and comprehensib...