@inproceedings{963174c018bc46999fa50f57fccc0905,
title = "Customer churn prediction - a case study in retail banking",
abstract = "This work focuses on one of the central topics in customer relationship management (CRM): transfer of valuable customers to a competitor. Customer retention rate has a strong impact on customer lifetime value, and understanding the true value of a possible customer churn will help the company in its customer relationship management. Customer value analysis along with customer churn predictions will help marketing programs target more specific groups of customers. We predict customer churn with logistic regression techniques and analyze the churning and nonchurning customers by using data from a consumer retail banking company. The result of the case study show that using conventional statistical methods to identify possible churners can be successful.",
author = "Teemu Mutanen and Jussi Ahola and Sami Nousiainen",
year = "2006",
doi = "10.3233/978-1-60750-633-1-77",
language = "English",
isbn = "978-1-60750-632-4",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "77--83",
editor = "Carlos Soares and Rayid Ghani",
booktitle = "Data Mining for Business Applications",
address = "Netherlands",
note = "ECML PKDD 2006 Workshop on Practical Data Mining : Applications, Experiences and Challenges ; Conference date: 18-09-2006 Through 22-09-2006",
}