Investigating the role of product features in preventing customer churn, by using survival analysis and choice modeling: The case of financial services
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 defection prone customers by offering the right set of products. Additionally, within the current customer attention “hype”, one tends to overlook the nature of different products when investigating customer defection. In this research, we study the defection of the savings and investment (SI) customers of a large Belgian financial service provider. We created different SI churn behavior categories by introducing two dimensions: (i) duration of the products (fixed term versus infinity) and (ii) capital/revenue risks involved. Considering these product features, we first gain explorative insight in the timing of the churn event by means of Kaplan-Meier estimates. Secondly, we elaborate on the most alarming group of customers that emerged from the former explorative analysis. A hazard model is built to detect the most convenient product categories to cross-sell in order to reduce their churn likelihood. Complementary, a multinomial probit model is estimated to explore the customers’ preferences with respect to the product features involved and to test whether these correspond with the findings of the survival analysis. The results of our study indicate that customer retention cannot be understood by solely relying on customer characteristics. In sum, it might be true that “not all customers are created equal”, but neither are all products.
|Date of creation:||Feb 2004|
|Contact details of provider:|| Postal: Hoveniersberg 4, B-9000 Gent|
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- Baesens, Bart & Verstraeten, Geert & Van den Poel, Dirk & Egmont-Petersen, Michael & Van Kenhove, Patrick & Vanthienen, Jan, 2004.
"Bayesian network classifiers for identifying the slope of the customer lifecycle of long-life customers,"
European Journal of Operational Research,
Elsevier, vol. 156(2), pages 508-523, July.
- B. Baesens & G. Verstraeten & D. Van Den Poel & M. Egmont-Petersen & P. Van Kenhove & J. Vanthienen, 2002. "Bayesian Network Classifiers for Identifying the Slope of the Customer - Lifecycle of Long-Life Customers," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 02/154, Ghent University, Faculty of Economics and Business Administration.
- Geweke, John & Keane, Michael P & Runkle, David, 1994. "Alternative Computational Approaches to Inference in the Multinomial Probit Model," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 609-632, November.
- John F. Geweke & Michael P. Keane & David E. Runkle, 1994. "Alternative computational approaches to inference in the multinomial probit model," Staff Report 170, Federal Reserve Bank of Minneapolis.
- Jon A. Breslaw, 2002. "Multinomial probit estimation without nuisance parameters," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 417-434, June.
- Rinus Haaijer & Michel Wedel & Marco Vriens & Tom Wansbeek, 1998. "Utility Covariances and Context Effects in Conjoint MNP Models," Marketing Science, INFORMS, vol. 17(3), pages 236-252.
- Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
- Vassilis A. Hajivassiliou & Daniel L. McFadden & Paul Ruud, 1993. "Simulation of Multivariate Normal Rectangle Probabilities and their Derivatives: Theoretical and Computational Results," Working Papers _024, Yale University.
- Keane, Michael P, 1992. "A Note on Identification in the Multinomial Probit Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 193-200, April.
- Van den Poel, Dirk & Lariviere, Bart, 2004. "Customer attrition analysis for financial services using proportional hazard models," European Journal of Operational Research, Elsevier, vol. 157(1), pages 196-217, August.
- D. Van Den Poel & B. Larivière, 2003. "Customer Attrition Analysis For Financial Services Using Proportional Hazard Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/164, Ghent University, Faculty of Economics and Business Administration.
- Pastor, JoseManuel & Perez, Francisco & Quesada, Javier, 1997. "Efficiency analysis in banking firms: An international comparison," European Journal of Operational Research, Elsevier, vol. 98(2), pages 395-407, April.
- Francisco Pérez García & Javier Quesada Ibañez & José Manuel Pastor Monsálvez, 1995. "Efficiency Analysis In Banking Firms: An International Comparison," Working Papers. Serie EC 1995-18, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).