IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v35y2016i2p275-283.html
   My bibliography  Save this article

Satisfaction Spillovers Across Categories

Author

Listed:
  • Xiaojing Dong

    (Leavey School of Business, Santa Clara University, Santa Clara, California 95053)

  • Pradeep K. Chintagunta

    (Booth School of Business, University of Chicago, Chicago, Illinois 60637)

Abstract

We provide a descriptive study of the cross-category effects of satisfaction with financial services on retention behavior. Behavioral contrast and learning theories provide the bases for our understanding of these effects. Our empirical results reveal the following: (i) Across banking and investment categories, when customers have different providers, satisfaction with one lowers the retention probability in the other service. (ii) A customer who is dissatisfied with the investment service is more likely to stay with the current banking service. (iii) Significantly, we find that when the same firm is involved in both categories, dissatisfaction with the firm in the investment category spills over into the banking category thereby lowering its retention probability. We also find that: (a) among customers who are satisfied with banking (investment), more exposure to media increases retention probability; (b) although switching costs and order of acquisition affect retention, they do not show cross-category interactions with satisfaction. We then obtain implications for customer lifetime value (CLV) and show that it can increase satisfaction by leveraging both the within and across category effects. Bottom line: It is important for a company providing multiple services to measure satisfaction at the category level but to manage customers across categories.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mksc.2015.0941 .

Suggested Citation

  • Xiaojing Dong & Pradeep K. Chintagunta, 2016. "Satisfaction Spillovers Across Categories," Marketing Science, INFORMS, vol. 35(2), pages 275-283, March.
  • Handle: RePEc:inm:ormksc:v:35:y:2016:i:2:p:275-283
    DOI: 10.1287/mksc.2015.0941
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.2015.0941
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.2015.0941?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Xueming Luo, 2009. "Quantifying the Long-Term Impact of Negative Word of Mouth on Cash Flows and Stock Prices," Marketing Science, INFORMS, vol. 28(1), pages 148-165, 01-02.
    3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    4. Roland T. Rust & Tuck Siong Chung, 2006. "Marketing Models of Service and Relationships," Marketing Science, INFORMS, vol. 25(6), pages 560-580, 11-12.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lily (Xuehui) Gao & Evert Haan & Iguácel Melero-Polo & F. Javier Sese, 2023. "Winning your customers’ minds and hearts: Disentangling the effects of lock-in and affective customer experience on retention," Journal of the Academy of Marketing Science, Springer, vol. 51(2), pages 334-371, March.
    2. Kohsuke Matsuoka, 2020. "Exploring the interface between management accounting and marketing: a literature review of customer accounting," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(3), pages 157-208, September.
    3. Cho, Jihoon & Aribarg, Anocha & Manchanda, Puneet, 2023. "Can firms benefit from integrating high-frequency survey measures with objective service quality data?," International Journal of Research in Marketing, Elsevier, vol. 40(3), pages 513-533.

    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. 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.
    2. Philipp Afèche & Mojtaba Araghi & Opher Baron, 2017. "Customer Acquisition, Retention, and Service Access Quality: Optimal Advertising, Capacity Level, and Capacity Allocation," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 674-691, October.
    3. G. Tomas M. Hult & Forrest V. Morgeson III & Udit Sharma & Claes Fornell, 2022. "Customer satisfaction and international business: A multidisciplinary review and avenues for research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 53(8), pages 1695-1733, October.
    4. Tarek Ben Rhouma & Georges Zaccour, 2018. "Optimal Marketing Strategies for the Acquisition and Retention of Service Subscriber," Management Science, INFORMS, vol. 64(6), pages 2609-2627, June.
    5. Evgeni Stanimirov & Vladimir Jechev, 2013. "Consumer Orientation as a Factor for Satisfying the Clients," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 56-89.
    6. Nejad, Mohammad G. & Amini, Mehdi & Sherrell, Daniel L., 2016. "The profit impact of revenue heterogeneity and assortativity in the presence of negative word-of-mouth," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 656-673.
    7. Ming-Hui Huang & Roland T. Rust, 2017. "Technology-driven service strategy," Journal of the Academy of Marketing Science, Springer, vol. 45(6), pages 906-924, November.
    8. Andrés Musalem & Yogesh V. Joshi, 2009. "—How Much Should You Invest in Each Customer Relationship? A Competitive Strategic Approach," Marketing Science, INFORMS, vol. 28(3), pages 555-565, 05-06.
    9. Kunz, Werner H. & Hogreve, Jens, 2011. "Toward a deeper understanding of service marketing: The past, the present, and the future," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 231-247.
    10. Oded Netzer & James M. Lattin & V. Srinivasan, 2008. "A Hidden Markov Model of Customer Relationship Dynamics," Marketing Science, INFORMS, vol. 27(2), pages 185-204, 03-04.
    11. Netzer, Oded & Lattin, James M. & Srinivasan, V. Seenu, 2007. "A Hidden Markov Model of Customer Relationship Dynamics," Research Papers 1904r, Stanford University, Graduate School of Business.
    12. Peter J. Danaher, 2002. "Optimal Pricing of New Subscription Services: Analysis of a Market Experiment," Marketing Science, INFORMS, vol. 21(2), pages 119-138, February.
    13. Ahmed Khwaja & Nathan Yang, 2022. "Quantifying the link between employee engagement, and customer satisfaction and retention in the car rental industry," Quantitative Marketing and Economics (QME), Springer, vol. 20(3), pages 275-292, September.
    14. Wankhede ABHA & Bhilawadikar VIBHA SUHAS, 2019. "Analysing the contribution of the product offerings to the customer satisfaction of co-operative Bank. A case study," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 1, pages 111-119.
    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. Sander F. M. Beckers & Jenny Doorn & Peter C. Verhoef, 2018. "Good, better, engaged? The effect of company-initiated customer engagement behavior on shareholder value," Journal of the Academy of Marketing Science, Springer, vol. 46(3), pages 366-383, May.
    17. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    18. Robert B. Ekelund & John D. Jackson & Robert D. Tollison, 2013. "Are Art Auction Estimates Biased?," Southern Economic Journal, John Wiley & Sons, vol. 80(2), pages 454-465, October.
    19. Song, Wei-Ling & Uzmanoglu, Cihan, 2016. "TARP announcement, bank health, and borrowers’ credit risk," Journal of Financial Stability, Elsevier, vol. 22(C), pages 22-32.
    20. Xu, Shen & Yin, Bichao & Lou, Chunjie, 2022. "Minority shareholder activism and corporate social responsibility," Economic Modelling, Elsevier, vol. 116(C).

    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:inm:ormksc:v:35:y:2016:i:2:p:275-283. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.