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Investigating the post-complaint period by means of survival analysis

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  • B. LARIVIÈRE
  • D. VAN DEN POEL

Abstract

Firms increasingly view each contact with their customers as an opportunity that needs to be managed. The primary purpose of this article is to gain a better understanding of the customers’ post-complaint period. Specific focus is placed on the impact of effective complaint handling on actual customer behavior throughout the time, whereas previous research has mainly focused on time-invariant or intentional measures. Survival analysis techniques are used to investigate the longitudinal behavior of complainants after their problem recovery. The proportionality assumption is tested for each explanatory variable under investigation. In addition, the impact for each variable is estimated by means of survival forests. Survival forests enable us to explore the evolution over time of the effects of the covariates under investigation. As such, the impact of each explanatory variable is allowed to change when the experiment evolves over time, in contrast to “proportional” models that restrict these estimates to be stationary. Our research is performed in the context of a financial services provider and analyzes the post-complaint periods of 2,326 customers. Our findings indicate that (i) it is interesting to consider complainants since they represent a typical and rather active customer segment, (ii) furthermore, it is beneficiary to invest in complaint handling, since these investments are likely to influence customers’ future behavior and (iii) survival forests are a helpful tool to investigate the impact of complaint handling on future customer behavior, since its components provide evidence of changing effects over time.

Suggested Citation

  • 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.
    • Handle: RePEc:rug:rugwps:05/299
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    File URL: http://wps-feb.ugent.be/Papers/wp_05_299.pdf
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    References listed on IDEAS

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    1. Bougie, J.R.G. & Pieters, R. & Zeelenberg, M., 2003. "Angry customers don't come back, they get back : The experience and behavioral implications of anger and dissatisfaction in services," Other publications TiSEM 1708fb71-fd68-41d9-b870-e, Tilburg University, School of Economics and Management.
    2. 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.
    3. B. Larivière & D. Van Den Poel, 2004. "Investigating the role of product features in preventing customer churn, by using survival analysis and choice modeling: The case of financial services," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/223, Ghent University, Faculty of Economics and Business Administration.
    4. 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.
    5. Martin R. Young & Wayne S. DeSarbo & Vicki G. Morwitz, 1998. "The Stochastic Modeling of Purchase Intentions and Behavior," Management Science, INFORMS, vol. 44(2), pages 188-202, February.
    6. 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.
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    Cited by:

    1. Vivek Astvansh & Anshu Suri & Hoorsana Damavandi, 2024. "Brand warmth elicits feedback, not complaints," Journal of the Academy of Marketing Science, Springer, vol. 52(4), pages 1107-1129, July.
    2. Mathieu Béal & William Sabadie & Yany Grégoire, 2019. "The effects of relationship length on customer profitability after a service recovery," Marketing Letters, Springer, vol. 30(3), pages 293-305, December.
    3. Jens Hogreve & Nicola Bilstein & Leonhard Mandl, 2017. "Unveiling the recovery time zone of tolerance: when time matters in service recovery," Journal of the Academy of Marketing Science, Springer, vol. 45(6), pages 866-883, November.

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    Keywords

    Data mining; customer relationship management; consumer complaint behavior; actual customer behavior; proportionality; survival forests.;
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