IDEAS home Printed from https://ideas.repec.org/p/rug/rugwps/03-164.html
   My bibliography  Save this paper

Customer Attrition Analysis For Financial Services Using Proportional Hazard Models

Author

Listed:
  • D. VAN DEN POEL
  • B. LARIVIÈRE

Abstract

This paper studies the topic of customer attrition in the context of a European financial services company. More specifically, we investigate predictors of churn incidence as part of customer relationship management (CRM). We contribute to the existing literature: (1) by combining several different types of predictors into one comprehensive retention model including several ‘new’ types of time-varying covariates related to actual customer behaviour; (2) by analysing churn behaviour based on a truly random sample of the total population using longitudinal data from a data warehouse. Our findings suggest that: (1) demographic characteristics, environmental changes and stimulating ‘interactive and continuous’ relationships with customers are of major concern when considering retention; (2) customer behaviour predictors only have a limited impact on attrition in terms of total products owned as well as the interpurchase time.

Suggested Citation

  • 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.
  • Handle: RePEc:rug:rugwps:03/164
    as

    Download full text from publisher

    File URL: http://wps-feb.ugent.be/Papers/wp_03_164.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dekimpe, Marnik G. & Degraeve, Zeger, 1997. "The attrition of volunteers," European Journal of Operational Research, Elsevier, vol. 98(1), pages 37-51, April.
    2. Rust, Roland T. & Metters, Richard, 1996. "Mathematical models of service," European Journal of Operational Research, Elsevier, vol. 91(3), pages 427-439, June.
    3. Ruth N. Bolton, 1998. "A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction," Marketing Science, INFORMS, vol. 17(1), pages 45-65.
    4. S. Baranzoni & P. Bianchi & L. Lambertini, 2000. "Multiproduct Firms, Product Differentiation, and Market Structure," Working Papers 368, Dipartimento Scienze Economiche, Universita' di Bologna.
    5. Lorin M. Hitt & Frances X. Frei, 1999. "Do Better Customers Utilize Electronic Distribution Channels: The Case of PC Banking," Center for Financial Institutions Working Papers 99-21, Wharton School Center for Financial Institutions, University of Pennsylvania.
    6. Lorin M. Hitt & Frances X. Frei, 2002. "Do Better Customers Utilize Electronic Distribution Channels? The Case of PC Banking," Management Science, INFORMS, vol. 48(6), pages 732-748, June.
    7. Athanassopoulos, Antreas D., 2000. "Customer Satisfaction Cues To Support Market Segmentation and Explain Switching Behavior," Journal of Business Research, Elsevier, vol. 47(3), pages 191-207, March.
    8. Maxham, James III, 2001. "Service recovery's influence on consumer satisfaction, positive word-of-mouth, and purchase intentions," Journal of Business Research, Elsevier, vol. 54(1), pages 11-24, October.
    9. Jones, Michael A. & Mothersbaugh, David L. & Beatty, Sharon E., 2002. "Why customers stay: measuring the underlying dimensions of services switching costs and managing their differential strategic outcomes," Journal of Business Research, Elsevier, vol. 55(6), pages 441-450, June.
    10. 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.
    11. Golany, B. & Phillips, F. Y. & Rousseau, J. J., 1995. "Optimal design of syndicated panels: A mathematical programming approach," European Journal of Operational Research, Elsevier, vol. 87(1), pages 148-165, November.
    12. Baesens, Bart & Viaene, Stijn & Van den Poel, Dirk & Vanthienen, Jan & Dedene, Guido, 2002. "Bayesian neural network learning for repeat purchase modelling in direct marketing," European Journal of Operational Research, Elsevier, vol. 138(1), pages 191-211, April.
    13. Kumar, Dhananjay & Westberg, Ulf, 1997. "Maintenance scheduling under age replacement policy using proportional hazards model and TTT-plotting," European Journal of Operational Research, Elsevier, vol. 99(3), pages 507-515, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Boehm, Martin, 2008. "Determining the impact of internet channel use on a customer's lifetime," Journal of Interactive Marketing, Elsevier, vol. 22(3), pages 2-22.
    2. Buckinx, Wouter & Van den Poel, Dirk, 2005. "Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting," European Journal of Operational Research, Elsevier, vol. 164(1), pages 252-268, July.
    3. K. Coussement & D. Van Den Poel, 2006. "Churn Prediction in Subscription Services: an Application of Support Vector Machines While Comparing Two Parameter-Selection Techniques," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/412, Ghent University, Faculty of Economics and Business Administration.
    4. Risselada, Hans & Verhoef, Peter C. & Bijmolt, Tammo H.A., 2010. "Staying Power of Churn Prediction Models," Journal of Interactive Marketing, Elsevier, vol. 24(3), pages 198-208.
    5. Gómez Fernández, Juan F. & Márquez, Adolfo Crespo & López-Campos, Mónica A., 2016. "Customer-oriented risk assessment in network utilities," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 72-83.
    6. Wang, Yi-Shun & Wu, Shun-Cheng & Lin, Hsin-Hui & Wang, Yu-Yin, 2011. "The relationship of service failure severity, service recovery justice and perceived switching costs with customer loyalty in the context of e-tailing," International Journal of Information Management, Elsevier, vol. 31(4), pages 350-359.
    7. K. Coussement & D. Van Den Poel, 2008. "Improving Customer Attrition Prediction by Integrating Emotions from Client/Company Interaction Emails and Evaluating Multiple Classifiers," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 08/527, Ghent University, Faculty of Economics and Business Administration.
    8. Basiony, Abd Elazim & abd alla, Ghada & shaker El Sayed, Alaa, 2014. "Evaluating Tourism Service Quality Provided to the European Tourist “Applied on the British tourist"," MPRA Paper 57164, University Library of Munich, Germany, revised 2014.
    9. Rocío G. Martínez & Ramon A. Carrasco & Cristina Sanchez-Figueroa & Diana Gavilan, 2021. "An RFM Model Customizable to Product Catalogues and Marketing Criteria Using Fuzzy Linguistic Models: Case Study of a Retail Business," Mathematics, MDPI, vol. 9(16), pages 1-31, August.
    10. Conor M. Henderson & Lena Steinhoff & Colleen M. Harmeling & Robert W. Palmatier, 2021. "Customer inertia marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(2), pages 350-373, March.
    11. M. Ballings & D. Van Den Poel, 2012. "The Relevant Length of Customer Event History for Churn Prediction: How long is long enough?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/804, Ghent University, Faculty of Economics and Business Administration.
    12. Bilgicer, Tolga & Jedidi, Kamel & Lehmann, Donald R. & Neslin, Scott A., 2015. "Social Contagion and Customer Adoption of New Sales Channels," Journal of Retailing, Elsevier, vol. 91(2), pages 254-271.
    13. M. Ballings & D. Van Den Poel & E. Verhagen, 2013. "Evaluating the Added Value of Pictorial Data for Customer Churn Prediction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/869, Ghent University, Faculty of Economics and Business Administration.
    14. Nagengast, Liane & Evanschitzky, Heiner & Blut, Markus & Rudolph, Thomas, 2014. "New Insights in the Moderating Effect of Switching Costs on the Satisfaction–Repurchase Behavior Link," Journal of Retailing, Elsevier, vol. 90(3), pages 408-427.
    15. Roland T. Rust & Ming-Hui Huang, 2014. "The Service Revolution and the Transformation of Marketing Science," Marketing Science, INFORMS, vol. 33(2), pages 206-221, March.
    16. B. Larivière & D. Van Den Poel, 2005. "Investigating the post-complaint period by means of survival analysis," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/299, Ghent University, Faculty of Economics and Business Administration.
    17. B. Larivière & D. Van Den Poel, 2004. "Predicting Customer Retention and Profitability by Using Random Forests and Regression Forests Techniques," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/282, Ghent University, Faculty of Economics and Business Administration.
    18. Liao, Shuling & Cheng, Colin C.J., 2014. "Brand equity and the exacerbating factors of product innovation failure evaluations: A communication effect perspective," Journal of Business Research, Elsevier, vol. 67(1), pages 2919-2925.
    19. Christian Pfeil & Thorsten Posselt & Nils Maschke, 2008. "Incentives for sales agents after the advent of the internet," Marketing Letters, Springer, vol. 19(1), pages 51-63, March.
    20. Yao Zhang & Eric T. Bradlow & Dylan S. Small, 2015. "Predicting Customer Value Using Clumpiness: From RFM to RFMC," Marketing Science, INFORMS, vol. 34(2), pages 195-208, March.

    More about this item

    Keywords

    Banking; marketing; retention modelling; proportional hazard model; Cox regression;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rug:rugwps:03/164. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nathalie Verhaeghe (email available below). General contact details of provider: https://edirc.repec.org/data/ferugbe.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.