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Incorporating Satisfaction into Customer Value Analysis: Optimal Investment in Lifetime Value

Author

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  • Teck-Hua Ho

    (Haas School of Business, University of California, Berkeley, California 94720-1900)

  • Young-Hoon Park

    (Johnson Graduate School of Management, Cornell University, Ithaca, New York 14853-6201)

  • Yong-Pin Zhou

    (Business School, University of Washington, Seattle, Washington 98195-3200)

Abstract

We extend the Schmittlein et al. model (1987) of customer lifetime value to include satisfaction. Customer purchases are modeled as Poisson events, and their rates of occurrence depend on the satisfaction of the most recent purchase encounter. Customers purchase at a higher rate when they are satisfied than when they are dissatisfied. A closed-form formula is derived for predicting total expected dollar spending from a customer base over a time period (0, ]. This formula reveals that approximating the mixture arrival processes by a single aggregate Poisson process can systematically underestimate the total number of purchases and revenue. Interestingly, the total revenue is increasing and convex in satisfaction. If the cost is sufficiently convex, our model reveals that the aggregate model leads to an overinvestment in customer satisfaction. The model is further extended to include three other benefits of customer satisfaction: (1) satisfied customers are likely to spend more per trip on average than dissatisfied customers, (2) satisfied customers are less likely to leave the customer base than dissatisfied customers, and (3) previously satisfied customers can be more (or less) likely to be satisfied in the current visit than previously dissatisfied customers. We show that all the main results carry through to these general settings.

Suggested Citation

  • Teck-Hua Ho & Young-Hoon Park & Yong-Pin Zhou, 2006. "Incorporating Satisfaction into Customer Value Analysis: Optimal Investment in Lifetime Value," Marketing Science, INFORMS, vol. 25(3), pages 260-277, 05-06.
  • Handle: RePEc:inm:ormksc:v:25:y:2006:i:3:p:260-277
    DOI: 10.1287/mksc.1050.0158
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    3. Romero, Jaime & van der Lans, Ralf & Wierenga, Berend, 2013. "A Partially Hidden Markov Model of Customer Dynamics for CLV Measurement," Journal of Interactive Marketing, Elsevier, vol. 27(3), pages 185-208.
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    5. Steven M. Shugan, 2007. "—It's the Findings, Stupid, Not the Assumptions," Marketing Science, INFORMS, vol. 26(4), pages 449-459, 07-08.
    6. Eric T. Anderson & Gavan J. Fitzsimons & Duncan Simester, 2006. "Measuring and Mitigating the Costs of Stockouts," Management Science, INFORMS, vol. 52(11), pages 1751-1763, November.
    7. Gui Liberali & Alina Ferecatu, 2022. "Morphing for Consumer Dynamics: Bandits Meet Hidden Markov Models," Marketing Science, INFORMS, vol. 41(4), pages 769-794, July.
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    9. Ekinci, Yeliz & Ülengin, Füsun & Uray, Nimet & Ülengin, Burç, 2014. "Analysis of customer lifetime value and marketing expenditure decisions through a Markovian-based model," European Journal of Operational Research, Elsevier, vol. 237(1), pages 278-288.
    10. Yeliz Ekinci & Füsun Ulengin & Nimet Uray, 2014. "Using customer lifetime value to plan optimal promotions," The Service Industries Journal, Taylor & Francis Journals, vol. 34(2), pages 103-122, January.
    11. Shaohui Ma & Joachim Büschken, 2011. "Counting your customers from an “always a share” perspective," Marketing Letters, Springer, vol. 22(3), pages 243-257, September.
    12. 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.
    13. Mika Sumida & Guillermo Gallego & Paat Rusmevichientong & Huseyin Topaloglu & James Davis, 2021. "Revenue-Utility Tradeoff in Assortment Optimization Under the Multinomial Logit Model with Totally Unimodular Constraints," Management Science, INFORMS, vol. 67(5), pages 2845-2869, May.
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    16. Albert C. Bemmaor & Nicolas Glady, 2012. "Modeling Purchasing Behavior with Sudden "Death": A Flexible Customer Lifetime Model," Management Science, INFORMS, vol. 58(5), pages 1012-1021, May.

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