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—The Power of CLV: Managing Customer Lifetime Value at IBM

Author

Listed:
  • V. Kumar

    (J. Mack Robinson College of Business, Georgia State University, Atlanta, Georgia 30303)

  • Rajkumar Venkatesan

    (Darden Graduate School of Business, University of Virginia, Charlottesville, Virginia 22904)

  • Tim Bohling

    (Americas Market Intelligence, IBM Corporation, New York, New York 10589)

  • Denise Beckmann

    (Americas Market Intelligence, IBM Corporation, Atlanta, Georgia 30327)

Abstract

Customer management activities at firms involve making consistent decisions over time, about: (a) which customers to select for targeting, (b) determining the level of resources to be allocated to the selected customers, and (c) selecting customers to be nurtured to increase future profitability. Measurement of customer profitability and a deep understanding of the link between firm actions and customer profitability are critical for ensuring the success of the above decisions. We present the case study of how IBM used customer lifetime value (CLV) as an indicator of customer profitability and allocated marketing resources based on CLV. CLV was used as a criterion for determining the level of marketing contacts through direct mail, telesales, e-mail, and catalogs for each customer. In a pilot study implemented for about 35,000 customers, this approach led to reallocation of resources for about 14% of the customers as compared to the allocation rules used previously (which were based on past spending history). The CLV-based resource reallocation led to an increase in revenue of about $20 million (a tenfold increase) without any changes in the level of marketing investment. Overall, the successful implementation of the CLV-based approach resulted in increased productivity from marketing investments. We also discuss the organizational and implementation challenges that surrounded the adoption of CLV in this firm.

Suggested Citation

  • V. Kumar & Rajkumar Venkatesan & Tim Bohling & Denise Beckmann, 2008. "—The Power of CLV: Managing Customer Lifetime Value at IBM," Marketing Science, INFORMS, vol. 27(4), pages 585-599, 07-08.
  • Handle: RePEc:inm:ormksc:v:27:y:2008:i:4:p:585-599
    DOI: 10.1287/mksc.1070.0319
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    References listed on IDEAS

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    1. Sunil Gupta & Valarie Zeithaml, 2006. "Customer Metrics and Their Impact on Financial Performance," Marketing Science, INFORMS, vol. 25(6), pages 718-739, 11-12.
    2. Ralf Elsner & Manfred Krafft & Arnd Huchzermeier, 2004. "The 2003 ISMS Practice Prize Winner: Optimizing Rhenania's Direct Marketing Business Through Dynamic Multilevel Modeling (DMLM) in a Multicatalog-Brand Environment," Marketing Science, INFORMS, vol. 23(2), pages 192-206, June.
    3. Roland T. Rust & Tuck Siong Chung, 2006. "Marketing Models of Service and Relationships," Marketing Science, INFORMS, vol. 25(6), pages 560-580, 11-12.
    4. Leonard M. Lodish, 1971. "Callplan: An Interactive Salesman's Call Planning System," Management Science, INFORMS, vol. 18(4-Part-II), pages 25-40, December.
    5. Bas Donkers & Peter Verhoef & Martijn Jong, 2007. "Modeling CLV: A test of competing models in the insurance industry," Quantitative Marketing and Economics (QME), Springer, vol. 5(2), pages 163-190, June.
    6. Andris A. Zoltners & Prabhakant Sinha, 2005. "The 2004 ISMS Practice Prize Winner—Sales Territory Design: Thirty Years of Modeling and Implementation," Marketing Science, INFORMS, vol. 24(3), pages 313-331, September.
    7. Kevin Lane Keller & Donald R. Lehmann, 2006. "Brands and Branding: Research Findings and Future Priorities," Marketing Science, INFORMS, vol. 25(6), pages 740-759, 11-12.
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