IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v31y2012i2p216-235.html
   My bibliography  Save this article

The Joint Sales Impact of Frequency Reward and Customer Tier Components of Loyalty Programs

Author

Listed:
  • Praveen K. Kopalle

    (Tuck School of Business at Dartmouth, Dartmouth College, Hanover, New Hampshire 03755)

  • Yacheng Sun

    (Leeds School of Business, University of Colorado, Boulder, Colorado 80309)

  • Scott A. Neslin

    (Tuck School of Business at Dartmouth, Dartmouth College, Hanover, New Hampshire 03755)

  • Baohong Sun

    (Cheung Kong Graduate School of Business, New York, New York 10019)

  • Vanitha Swaminathan

    (Katz School of Business, University of Pittsburgh, Pittsburgh, Pennsylvania 15260)

Abstract

We estimate the joint impact of the frequency reward and customer tier components of a loyalty program on customer behavior and resultant sales. We provide an integrated analysis of a loyalty program incorporating customers' purchase and cash-in decisions, points pressure and rewarded behavior effects, heterogeneity, and forward-looking behavior. We focus on four key research questions: (1) How important is it to combine both components in one model? (2) Does points pressure exist in the context of a two-component loyalty program? (3) How is the market segmented in its response to the combined program? (4) Do the programs complement each other in terms of the incremental sales they produce? Our most basic message is that the frequency reward and customer tier components of loyalty programs should be modeled jointly rather than in separate models. We find strong evidence for points pressure for both the customer tier and frequency reward components using both model-based and model-free evidence. We find a two-segment solution revealing a "service-oriented" segment that highly values cash-ins for room upgrades and staying in "luxury" hotels, and a "price-oriented" segment that is more price sensitive and highly values the frequency reward aspects of the loyalty program. Furthermore, we find that both components generate incremental sales. Also, there was slight synergy between the programs but not a huge amount. Overall, each component contributes to increased revenues and does not interfere with the other.

Suggested Citation

  • Praveen K. Kopalle & Yacheng Sun & Scott A. Neslin & Baohong Sun & Vanitha Swaminathan, 2012. "The Joint Sales Impact of Frequency Reward and Customer Tier Components of Loyalty Programs," Marketing Science, INFORMS, vol. 31(2), pages 216-235, March.
    • Handle: RePEc:inm:ormksc:v:31:y:2012:i:2:p:216-235
    DOI: 10.1287/mksc.1110.0687
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1110.0687
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.1110.0687?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. Doug J. Chung & Thomas Steenburgh & K. Sudhir, 2014. "Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans," Marketing Science, INFORMS, vol. 33(2), pages 165-187, March.
    2. Byung-Do Kim & Mengze Shi & Kannan Srinivasan, 2001. "Reward Programs and Tacit Collusion," Marketing Science, INFORMS, vol. 20(2), pages 99-120, June.
    3. Nanda Kumar & Ram Rao, 2006. "Research Note—Using Basket Composition Data for Intelligent Supermarket Pricing," Marketing Science, INFORMS, vol. 25(2), pages 188-199, 03-04.
    4. Sanjog Misra & Harikesh Nair, 2011. "A structural model of sales-force compensation dynamics: Estimation and field implementation," Quantitative Marketing and Economics (QME), Springer, vol. 9(3), pages 211-257, September.
    5. Keane, Michael P & Wolpin, Kenneth I, 1994. "The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 648-672, November.
    6. Matthew Osborne, 2007. "Consumer Learning, Switching Costs, and Heterogeneity: A Structural Examination," EAG Discussions Papers 200710, Department of Justice, Antitrust Division.
    7. Richard H. Thaler, 2008. "Mental Accounting and Consumer Choice," Marketing Science, INFORMS, vol. 27(1), pages 15-25, 01-02.
    8. Swait, Joffre, 2001. "A non-compensatory choice model incorporating attribute cutoffs," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 903-928, November.
    9. Joseph C. Nunes & Xavier Drze, 2006. "The Endowed Progress Effect: How Artificial Advancement Increases Effort," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(4), pages 504-512, March.
    10. Rajiv Lal & David Bell, 2003. "The Impact of Frequent Shopper Programs in Grocery Retailing," Quantitative Marketing and Economics (QME), Springer, vol. 1(2), pages 179-202, June.
    11. Ran Kivetz & Oleg Urminsky & Yuhuang Zheng, 2006. "The Goal-Gradient Hypothesis Resurrected: Purchase Acceleration, Illusionary Goal Progress, and Customer Retention," Natural Field Experiments 00658, The Field Experiments Website.
    12. Steven M. Shugan, 2005. "Brand Loyalty Programs: Are They Shams?," Marketing Science, INFORMS, vol. 24(2), pages 185-193.
    13. Baohong Sun, 2005. "Promotion Effect on Endogenous Consumption," Marketing Science, INFORMS, vol. 24(3), pages 430-443, July.
    14. Tülin Erdem & Susumu Imai & Michael Keane, 2003. "Brand and Quantity Choice Dynamics Under Price Uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 5-64, March.
    15. Tülin Erdem & Michael P. Keane & Baohong Sun, 2008. "A Dynamic Model of Brand Choice When Price and Advertising Signal Product Quality," Marketing Science, INFORMS, vol. 27(6), pages 1111-1125, 11-12.
    16. Paul Klemperer, 1987. "Markets with Consumer Switching Costs," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(2), pages 375-394.
    17. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    18. Wesley R. Hartmann, 2010. "Demand Estimation with Social Interactions and the Implications for Targeted Marketing," Marketing Science, INFORMS, vol. 29(4), pages 585-601, 07-08.
    19. Tülin Erdem & Michael Keane & T. Öncü & Judi Strebel, 2005. "Learning About Computers: An Analysis of Information Search and Technology Choice," Quantitative Marketing and Economics (QME), Springer, vol. 3(3), pages 207-247, September.
    20. Klemperer, Paul D, 1987. "Entry Deterrence in Markets with Consumer Switching Costs," Economic Journal, Royal Economic Society, vol. 97(388a), pages 99-117, Supplemen.
    21. Vincent R. Nijs & Shuba Srinivasan & Koen Pauwels, 2007. "Retail-Price Drivers and Retailer Profits," Marketing Science, INFORMS, vol. 26(4), pages 473-487, 07-08.
    22. Kivetz, Ran & Simonson, Itamar, 2003. "The Role of Effort Advantage in Consumer Response to Loyalty Programs: The Idiosyncratic Fit Heuristic," Research Papers 1738r, Stanford University, Graduate School of Business.
    23. Füsun Gönül & Kannan Srinivasan, 1996. "Estimating the Impact of Consumer Expectations of Coupons on Purchase Behavior: A Dynamic Structural Model," Marketing Science, INFORMS, vol. 15(3), pages 262-279.
    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. A. Yeşim Orhun & Tong Guo & Andreas Hagemann, 2022. "Reaching for Gold: Frequent-Flyer Status Incentives and Moral Hazard," Marketing Science, INFORMS, vol. 41(3), pages 548-574, May.
    2. Tao Chen & Baohong Sun & Vishal Singh, 2009. "An Empirical Investigation of the Dynamic Effect of Marlboro's Permanent Pricing Shift," Marketing Science, INFORMS, vol. 28(4), pages 740-758, 07-08.
    3. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    4. Hai Che & Tülin Erdem & T. Sabri Öncü, 2015. "Consumer learning and evolution of consumer brand preferences," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 173-202, September.
    5. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    6. Alina Nastasoiu & Neil T. Bendle & Charan K. Bagga & Mark Vandenbosch & Salvador Navarro, 2021. "Separating customer heterogeneity, points pressure and rewarded behavior to assess a retail loyalty program," Journal of the Academy of Marketing Science, Springer, vol. 49(6), pages 1132-1150, November.
    7. Hai Che & Tülin Erdem & T. Öncü, 2015. "Consumer learning and evolution of consumer brand preferences," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 173-202, September.
    8. Gonca P. Soysal & Lakshman Krishnamurthi, 2012. "Demand Dynamics in the Seasonal Goods Industry: An Empirical Analysis," Marketing Science, INFORMS, vol. 31(2), pages 293-316, March.
    9. Brett R. Gordon, 2009. "A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry," Marketing Science, INFORMS, vol. 28(5), pages 846-867, 09-10.
    10. Kopalle Praveen K & Neslin Scott A, 2003. "The Economic Viability of Frequency Reward Programs in a Strategic Competitive Environment," Review of Marketing Science, De Gruyter, vol. 1(1), pages 1-41, August.
    11. Pradeep Chintagunta & Tülin Erdem & Peter E. Rossi & Michel Wedel, 2006. "Structural Modeling in Marketing: Review and Assessment," Marketing Science, INFORMS, vol. 25(6), pages 604-616, 11-12.
    12. Pradeep K. Chintagunta & Harikesh S. Nair, 2011. "Structural Workshop Paper --Discrete-Choice Models of Consumer Demand in Marketing," Marketing Science, INFORMS, vol. 30(6), pages 977-996, November.
    13. Amirhossein Bazargan & Salma Karray & Saeed Zolfaghari, 2021. "Can restrictions on redemption timing boost profitability of loyalty programs in competitive environments?," Computational Management Science, Springer, vol. 18(1), pages 99-124, January.
    14. Dorotic, Matilda & Verhoef, Peter C. & Fok, Dennis & Bijmolt, Tammo H.A., 2014. "Reward redemption effects in a loyalty program when customers choose how much and when to redeem," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 339-355.
    15. Christiaan Behrens & Nathalie McCaughey, 2015. "Loyalty Programs and Consumer Behaviour: The Impact of FFPs on Consumer Surplus," Tinbergen Institute Discussion Papers 15-048/VIII, Tinbergen Institute.
    16. Andrew Ching & Susumu Imai & Masakazu Ishihara & Neelam Jain, 2012. "A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 151-196, June.
    17. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2017. "Empirical Models of Learning Dynamics: A Survey of Recent Developments," International Series in Operations Research & Management Science, in: Berend Wierenga & Ralf van der Lans (ed.), Handbook of Marketing Decision Models, edition 2, chapter 0, pages 223-257, Springer.
    18. Song Lin & Juanjuan Zhang & John R. Hauser, 2015. "Learning from Experience, Simply," Marketing Science, INFORMS, vol. 34(1), pages 1-19, January.
    19. Amir Gandomi & Amirhossein Bazargan & Saeed Zolfaghari, 2019. "Designing competitive loyalty programs: a stochastic game-theoretic model to guide the choice of reward structure," Annals of Operations Research, Springer, vol. 280(1), pages 267-298, September.
    20. Nastasoiu, Alina & Vandenbosch, Mark, 2019. "Competing with loyalty: How to design successful customer loyalty reward programs," Business Horizons, Elsevier, vol. 62(2), pages 207-214.

    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:31:y:2012:i:2:p:216-235. 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.