Customer churn analysis - a case study

Teemu Mutanen

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Customer churn and segmentation Customer Service Quality and Loyalty Consumer Market Behavior and Pricing

Abstract

Customer value analysis is critical for a good marketing and a customer relationship management strategy. An important component of this strategy is the customer retention rate. Customer retention rate has a strong impact on the customer lifetime value, and understanding the true value of a possible customer churn will help the company in its customer relationship management. Conventional statistical methods are very successful in predicting a customer churn. The goal of this study is to apply logistic regression techniques to predict a customer churn and analyze the churning and no-churning customers by using data from a personal retail banking company. * The use of the name of the Technical Research Centre of Finland (VTT) in advertising or publication in part of this report is only permissible by written authorisation from the Technical Research Centre of Finland. RESEARCH REPORT VTT-R-01184-06 3 (19)

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2004Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting 2003An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry 2003A novel evolutionary data mining algorithm with applications to churn prediction 2000Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry 1999The Lifetime Value Concept in Customer-Based Marketing 2005Predicting customer loyalty using the internal transactional database 2002Customer lifetime value modeling and its use for customer retention planning 2004Data Mining Techniques on the Evaluation of Wireless Churn

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2013Data Mining as a tool to Predict the Churn Behaviour among Indian bank customers 2016Determining the Customer Lifetime Value based on the Benefit Clustering in the Insurance Industry 2014Churn analysis: Predicting churners 2024Enhancing e-commerce customer churn management with a profit- and AUC-focused prescriptive analytics approach 2011

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