IDEAS home Printed from https://ideas.repec.org/p/feb/natura/00658.html
   My bibliography  Save this paper

The Goal-Gradient Hypothesis Resurrected: Purchase Acceleration, Illusionary Goal Progress, and Customer Retention

Author

Listed:
  • Ran Kivetz
  • Oleg Urminsky
  • Yuhuang Zheng

Abstract

The goal-gradient hypothesis denotes the classic finding from behaviorism that animals expend more effort as they approach a reward. Building on this hypothesis, the authors generate new propositions for the human psychology of rewards. They test these propositions using a field experiment, secondary customer data, paper-and-pencil problems, and Tobit and logit models. The key finding indicate that (1) participants in a real cafe reward program purchase coffee more frequently the closer they are to earning a free coffee; (2) Internet users who rate songs in return for reward certificates visit the rating Web site more often, rate more songs per visit, and persist longer in the rating effort as they approach the reward goal; (3) the illusion of progress toward the goal induces purchase acceleration (e.g., customers who receive a 12-stamp coffee card with 2 preexisting "bonus" stamps complete the 10 required purchases faster than customers who receive a "regular" 10-stamp card) and (4) a stronger tendency to accelerate toward the goal predicts greater retention and faster reengagement in the program. The conceptualization and empirical findings are captured by a parsimonious goal distance model, in which effort investment is a function of the proportion of original distance remaining to the goal. In addition, using statistical and experimental controls, the authors rule out alternative explanations for the observed goal gradients. They discuss the theoretical significance of their findings and the managerial implications for incentive systems, promotions, and customer retention.

Suggested Citation

  • 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.
  • Handle: RePEc:feb:natura:00658
    as

    Download full text from publisher

    File URL: http://s3.amazonaws.com/fieldexperiments-papers2/papers/00658.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hsee, Christopher K, et al, 2003. "Medium Maximization," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(1), pages 1-14, June.
    2. Klaus Wertenbroch, 1998. "Consumption Self-Control by Rationing Purchase Quantities of Virtue and Vice," Marketing Science, INFORMS, vol. 17(4), pages 317-337.
    3. Ayelet Fishbach & Ravi Dhar, 2005. "Goals as Excuses or Guides: The Liberating Effect of Perceived Goal Progress on Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(3), pages 370-377, December.
    4. J. Tobin, 1958. "Liquidity Preference as Behavior Towards Risk," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 25(2), pages 65-86.
    5. Seetharaman, P B & Chintagunta, Pradeep K, 2003. "The Proportional Hazard Model for Purchase Timing: A Comparison of Alternative Specifications," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 368-382, July.
    6. Richard J. Herrnstein & Drazen Prelec, 1991. "Melioration: A Theory of Distributed Choice," Journal of Economic Perspectives, American Economic Association, vol. 5(3), pages 137-156, Summer.
    7. Kristiaan Helsen & David C. Schmittlein, 1993. "Analyzing Duration Times in Marketing: Evidence for the Effectiveness of Hazard Rate Models," Marketing Science, INFORMS, vol. 12(4), pages 395-414.
    8. 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.
    9. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    10. Dilip Soman & Mengze Shi, 2003. "Virtual Progress: The Effect of Path Characteristics on Perceptions of Progress and Choice," Management Science, INFORMS, vol. 49(9), pages 1229-1250, September.
    11. Huber, Joel & Payne, John W & Puto, Christopher, 1982. "Adding Asymmetrically Dominated Alternatives: Violations of Regularity and the Similarity Hypothesis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(1), pages 90-98, June.
    12. Bruce G. S. Hardie & Eric J. Johnson & Peter S. Fader, 1993. "Modeling Loss Aversion and Reference Dependence Effects on Brand Choice," Marketing Science, INFORMS, vol. 12(4), pages 378-394.
    13. David R. Bell & James M. Lattin, 2000. "Looking for Loss Aversion in Scanner Panel Data: The Confounding Effect of Price Response Heterogeneity," Marketing Science, INFORMS, vol. 19(2), pages 185-200, May.
    14. Thaler, Richard, 1980. "Toward a positive theory of consumer choice," Journal of Economic Behavior & Organization, Elsevier, vol. 1(1), pages 39-60, March.
    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. Nicolau, Juan L., 2011. "Differentiated price loss aversion in destination choice: The effect of tourists’ cultural interest," Tourism Management, Elsevier, vol. 32(5), pages 1186-1195.
    2. repec:cup:judgdm:v:1:y:2006:i::p:23-32 is not listed on IDEAS
    3. David Gal, 2006. "A psychological law of inertia and the illusion of loss aversion," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 1, pages 23-32, July.
    4. Dan Ariely & Kristina Shampan'er, 2006. "How small is zero price? : the true value of free products," Working Papers 06-16, Federal Reserve Bank of Boston.
    5. Meloria Meschi & Carla Pace, 2012. "Accounting for Behavioral Biases for Non-biased Demand Estimations," Chapters, in: Michael A. Crew & Paul R. Kleindorfer (ed.), Multi-Modal Competition and the Future of Mail, chapter 24, Edward Elgar Publishing.
    6. Toshiaki Iizuka & Hitoshi Shigeoka, 2020. "Asymmetric Demand Response when Prices Increase and Decrease: The Case of Child Healthcare," NBER Working Papers 28057, National Bureau of Economic Research, Inc.
    7. Moon, Sangkil & Voss, Glenn, 2009. "How do price range shoppers differ from reference price point shoppers?," Journal of Business Research, Elsevier, vol. 62(1), pages 31-38, January.
    8. Peggy J. Liu & Kelly L. Haws & Cait Lamberton & Troy H. Campbell & Gavan J. Fitzsimons, 2015. "Vice-Virtue Bundles," Management Science, INFORMS, vol. 61(1), pages 204-228, January.
    9. Robert Slonim & Ellen Garbarino, 2009. "Similarities and differences between stockpiling and reference effects," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 30(6), pages 351-371.
    10. Hsiaw, Alice, 2018. "Goal bracketing and self-control," Games and Economic Behavior, Elsevier, vol. 111(C), pages 100-121.
    11. Katharina Dowling & Daniel Guhl & Daniel Klapper & Martin Spann & Lucas Stich & Narine Yegoryan, 2020. "Behavioral biases in marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(3), pages 449-477, May.
    12. Chunhua Wu & Koray Cosguner, 2020. "Profiting from the Decoy Effect: A Case Study of an Online Diamond Retailer," Marketing Science, INFORMS, vol. 39(5), pages 974-995, September.
    13. Necati Tereyağoğlu & Peter S. Fader & Senthil Veeraraghavan, 2018. "Multiattribute Loss Aversion and Reference Dependence: Evidence from the Performing Arts Industry," Management Science, INFORMS, vol. 64(1), pages 421-436, January.
    14. Kwangpil Chang & S. Siddarth & Charles B. Weinberg, 1999. "The Impact of Heterogeneity in Purchase Timing and Price Responsiveness on Estimates of Sticker Shock Effects," Marketing Science, INFORMS, vol. 18(2), pages 178-192.
    15. A. Ye(scedilla)im Orhun, 2009. "Optimal Product Line Design When Consumers Exhibit Choice Set-Dependent Preferences," Marketing Science, INFORMS, vol. 28(5), pages 868-886, 09-10.
    16. Chakravarthi Narasimhan & Chuan He & Eric Anderson & Lyle Brenner & Preyas Desai & Dmitri Kuksov & Paul Messinger & Sridhar Moorthy & Joseph Nunes & Yuval Rottenstreich & Richard Staelin & George Wu &, 2005. "Incorporating Behavioral Anomalies in Strategic Models," Marketing Letters, Springer, vol. 16(3), pages 361-373, December.
    17. M. Keith Chen & Venkat Lakshminarayanan & Laurie Santos, 2005. "The Evolution of Our Preferences: Evidence from Capuchin-Monkey Trading Behavior," Cowles Foundation Discussion Papers 1524, Cowles Foundation for Research in Economics, Yale University.
    18. Kopalle, Praveen K. & Kannan, P.K. & Boldt, Lin Bao & Arora, Neeraj, 2012. "The impact of household level heterogeneity in reference price effects on optimal retailer pricing policies," Journal of Retailing, Elsevier, vol. 88(1), pages 102-114.
    19. Pranav Jindal, 2015. "Risk Preferences and Demand Drivers of Extended Warranties," Marketing Science, INFORMS, vol. 34(1), pages 39-58, January.
    20. Tovar, Patricia, 2009. "The effects of loss aversion on trade policy: Theory and evidence," Journal of International Economics, Elsevier, vol. 78(1), pages 154-167, June.
    21. Dmitri Kuksov & Kangkang Wang, 2014. "The Bright Side of Loss Aversion in Dynamic and Competitive Markets," Marketing Science, INFORMS, vol. 33(5), pages 693-711, September.

    More about this item

    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:feb:natura:00658. 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: Francesca Pagnotta (email available below). General contact details of provider: http://www.fieldexperiments.com .

    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.