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A quantile regression approach to gaining insights for reacquition of defected customers

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  • Yoo, Changsok
  • Cha, Kyoung Cheon
  • Kim, Sang-Hoon

Abstract

As customer loyalty keeps declining, the importance of customer relationship management is paramount especially for online-service marketers. Reacquisition of defected customers is better than acquiring new customers in terms of marketing efficiency as well as effectiveness. However, the issue of winning back defected customers has been largely neglected among scholars. In this paper, we present empirical analyses based on real transactional data from 4000 users of one of the most successful online games in Korea to investigate the relationship between demographic, RFM, behavioral, and social network variables and the users’ response to reacquisition campaigns. Since the dependent variable is skewed, a quantile regression method was utilized for model estimation. To figure out what kind of characteristics would influence the likelihood of “staying alive” after the campaigns, the results from Period 1(win-back) were compared against those from Period 2(retention). The findings shed many useful insights in targeting and designing win-back campaigns.

Suggested Citation

  • Yoo, Changsok & Cha, Kyoung Cheon & Kim, Sang-Hoon, 2020. "A quantile regression approach to gaining insights for reacquition of defected customers," Journal of Business Research, Elsevier, vol. 120(C), pages 443-452.
  • Handle: RePEc:eee:jbrese:v:120:y:2020:i:c:p:443-452
    DOI: 10.1016/j.jbusres.2019.10.068
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    References listed on IDEAS

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    1. Anita Elberse & Jehoshua Eliashberg, 2003. "Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures," Marketing Science, INFORMS, vol. 22(3), pages 329-354.
    2. Juran Kim & Seungmook Kang & Charles R. Taylor, 2018. "Technology driven experiences from mobile direct to virtual reality," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 28(1), pages 96-102, January.
    3. repec:dgr:rugsom:10008 is not listed on IDEAS
    4. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, vol. 58(3), pages 345-350, March.
    5. Heeju Chae & Eunju Ko & Jinghe Han, 2015. "How do customers' SNS participation activities impact on customer equity drivers and customer loyalty? Focus on the SNS services of a global SPA brand," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 25(2), pages 122-141, March.
    6. Yongjae Kim & Soojin Kim, 2013. "Segmenting sport video gamers by motivation: a cluster analysis," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 23(1), pages 92-108, January.
    7. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    8. Doreén Pick & Jacquelyn S. Thomas & Sebastian Tillmanns & Manfred Krafft, 2016. "Customer win-back: the role of attributions and perceptions in customers’ willingness to return," Journal of the Academy of Marketing Science, Springer, vol. 44(2), pages 218-240, March.
    9. Eric J. Johnson & John W. Payne, 1985. "Effort and Accuracy in Choice," Management Science, INFORMS, vol. 31(4), pages 395-414, April.
    10. Bijmolt, T.H.A. & Bl, 2010. "Should they stay or should they go? Reactivation and termination of low-tier customers," Research Report 10008, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    11. Joonheui Bae & Dong-Mo Koo & Pekka Mattila, 2016. "Affective motives to play online games," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 26(2), pages 174-184, March.
    12. Hoffman, Donna L. & Novak, Thomas P., 2009. "Flow Online: Lessons Learned and Future Prospects," Journal of Interactive Marketing, Elsevier, vol. 23(1), pages 23-34.
    13. Sang Jin Kim & Kyung Hoon Kim & Chang Han Lee, 2016. "Role of user-created programs in online game consumer behavior," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 26(3), pages 217-226, June.
    14. Mohanbir S. Sawhney & Jehoshua Eliashberg, 1996. "A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures," Marketing Science, INFORMS, vol. 15(2), pages 113-131.
    15. Paramaporn Thaichon & Thu Nguyen Quach, 2015. "The relationship between service quality, satisfaction, trust, value, commitment and loyalty of Internet service providers' customers," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 25(4), pages 295-313, September.
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