IDEAS home Printed from https://ideas.repec.org/a/spr/comgts/v13y2016i4d10.1007_s10287-016-0266-1.html
   My bibliography  Save this article

On the customer lifetime value: a mathematical perspective

Author

Listed:
  • R. Ferrentino

    (University of Salerno)

  • M. T. Cuomo

    (University of Salerno)

  • C. Boniello

    (University of Salerno)

Abstract

The customer lifetime value (CLV) is an important concept increasingly considered in the field of general marketing and in the management of firms, of organizations to increase the captured profitability. It represents the total value that a customer produces during his or her lifetime, or better represents the measure of the potential profit generating by a customer. The companies use the customer lifetime value to segment customers, analyze probability of churn, allocate resources or formulate strategies and, therefore, they increasingly derive revenue from the creation and from sustenance of long-term relationships with their customers. For this reason, the customer lifetime value is increasingly considered a touchstone for the management of customer relationships. In this article, the authors deepen the concept and use of customer lifetime value and present some mathematical models for its determination. There is many models for this purpose but most of them are theoretic, complex and not applicable. Though not exhaustive, the major contribution of this paper is that it provides a general mathematical formulation to estimate the CLV and that it has a context less specific compared to papers, present in literature, on the customer lifetime.

Suggested Citation

  • R. Ferrentino & M. T. Cuomo & C. Boniello, 2016. "On the customer lifetime value: a mathematical perspective," Computational Management Science, Springer, vol. 13(4), pages 521-539, October.
    • Handle: RePEc:spr:comgts:v:13:y:2016:i:4:d:10.1007_s10287-016-0266-1
    DOI: 10.1007/s10287-016-0266-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10287-016-0266-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10287-016-0266-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. D. F. Benoit & D. Van Den Poel, 2009. "Benefits of Quantile Regression for the Analysis of Customer Lifetime Value in a Contractual Setting: An Application in Financial Services," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/551, Ghent University, Faculty of Economics and Business Administration.
    2. Sunil Gupta & Valarie Zeithaml, 2006. "Customer Metrics and Their Impact on Financial Performance," Marketing Science, INFORMS, vol. 25(6), pages 718-739, 11-12.
    3. Peter S. Fader & Bruce G. S. Hardie & Ka Lok Lee, 2005. "“Counting Your Customers” the Easy Way: An Alternative to the Pareto/NBD Model," Marketing Science, INFORMS, vol. 24(2), pages 275-284, August.
    4. 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.
    5. Stewart Pearson, 1996. "Building Business Brands Directly," Palgrave Macmillan Books, in: Building Brands Directly, chapter 15, pages 348-366, Palgrave Macmillan.
    6. Stewart Pearson, 1996. "Building Brands Directly," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-349-13771-8.
    7. Verhoef, P.C. & Donkers, A.C.D., 2001. "Predicting Customer Potential Value: an application in the insurance industry," ERIM Report Series Research in Management ERS-2001-01-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    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. Carlos Lamela-Orcasitas & Jesús García-Madariaga, 2023. "How to really quantify the economic value of customer information in corporate databases," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    2. Kati Stormi & Anni Lindholm & Teemu Laine & Tuomas Korhonen, 2020. "RFM customer analysis for product-oriented services and service business development: an interventionist case study of two machinery manufacturers," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 24(3), pages 623-653, September.
    3. R. Ferrentino & C. Boniello, 2020. "Customer satisfaction: a mathematical framework for its analysis and its measurement," Computational Management Science, Springer, vol. 17(1), pages 23-45, January.
    4. Mahsa Samsami & Ralf Wagner, 2021. "Investment Decisions with Endogeneity: A Dirichlet Tree Analysis," JRFM, MDPI, vol. 14(7), pages 1-19, July.
    5. Kessara Kanchanapoom & Jongsawas Chongwatpol, 2023. "Integrated customer lifetime value (CLV) and customer migration model to improve customer segmentation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 172-185, June.

    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. Polo, Yolanda & Sese, F. Javier & Verhoef, Peter C., 2011. "The Effect of Pricing and Advertising on Customer Retention in a Liberalizing Market," Journal of Interactive Marketing, Elsevier, vol. 25(4), pages 201-214.
    2. Rahim A. Ganiyu, 2016. "Perceived Service Quality and Customer Loyalty: The Mediating Effect of Passenger Satisfaction in the Nigerian Airline Industry," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 52(1), pages 94-117, December.
    3. R. Ferrentino & C. Boniello, 2020. "Customer satisfaction: a mathematical framework for its analysis and its measurement," Computational Management Science, Springer, vol. 17(1), pages 23-45, January.
    4. Rajagopal, 2005. "Measuring Variability Factors in Consumer Value for Profit Optimization in a Firm - A Framework for Analysis," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 1(1), pages 85-103, January.
    5. Sharan Jagpal & Feihong Xia, 2019. "Coordinating Marketing and Production with Asymmetric Costs: Theory and Estimation," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 6(1), pages 1-12, June.
    6. Evelyn Toh Bee Hwa Author_Email: toh.evelyn@taylors.edu.my & Eva Lim Wei Lee & Robin Cheng, 2011. "Generation Y And Choice Of Mobile Service Provider: A Study On Their Purchasing Decisions In Choosing A Mobile Service Provider," 2nd International Conference on Business and Economic Research (2nd ICBER 2011) Proceeding 2011-226, Conference Master Resources.
    7. Demirci Orel, Fatma & Kara, Ali, 2014. "Supermarket self-checkout service quality, customer satisfaction, and loyalty: Empirical evidence from an emerging market," Journal of Retailing and Consumer Services, Elsevier, vol. 21(2), pages 118-129.
    8. Zhenning Xu & Colin Vail & Amarpreet S. Kohli & Saeed Tajdini, 2021. "Understanding changes in a brand’s core positioning and customer engagement: a sentiment analysis of a brand-owned Facebook site," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(1), pages 3-16, March.
    9. Bo-Chiuan Su & Li-Wei Wu & Ying-Chi Yen, 2021. "Antecedents and Consequences of Trust and Loyalty in Physical Banks Affecting Mobile Payments," Sustainability, MDPI, vol. 13(22), pages 1-27, November.
    10. Korneta Piotr, 2018. "Net Promoter Score, Growth, and Profitability of Transportation Companies," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 54(2), pages 136-148, June.
    11. Dissakoon Chonsalasin & Sajjakaj Jomnonkwao & Vatanavongs Ratanavaraha, 2020. "Key Determinants of Airline Loyalty Modeling in Thailand," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
    12. 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.
    13. Meade, Nigel & Islam, Towhidul, 2010. "Using copulas to model repeat purchase behaviour - An exploratory analysis via a case study," European Journal of Operational Research, Elsevier, vol. 200(3), pages 908-917, February.
    14. Reimer, Kerstin & Albers, Sönke, 2011. "Modeling Repeat Purchases in the Internet when RFM Captures Past Influence of Marketing," EconStor Preprints 50730, ZBW - Leibniz Information Centre for Economics.
    15. Rajkumar Venkatesan & Alexander Bleier & Werner Reinartz & Nalini Ravishanker, 2019. "Improving customer profit predictions with customer mindset metrics through multiple overimputation," Journal of the Academy of Marketing Science, Springer, vol. 47(5), pages 771-794, September.
    16. L C Thomas, 2010. "Consumer finance: challenges for operational research," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 41-52, January.
    17. Mark, Tanya & Lemon, Katherine N. & Vandenbosch, Mark & Bulla, Jan & Maruotti, Antonello, 2013. "Capturing the Evolution of Customer–Firm Relationships: How Customers Become More (or Less) Valuable Over Time," Journal of Retailing, Elsevier, vol. 89(3), pages 231-245.
    18. Adela-Laura POPA & Dinu Vlad SASU & Teodora Mihaela TARCZA, 2021. "Investigating The Importance Of Customer Lifetime Value In Modern Marketing - A Literature Review," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 30(2), pages 410-416, December.
    19. Song, Tae Ho & Kim, Sang Yong & Kim, Ji Yoon, 2016. "The dynamic effect of customer equity across firm growth: The case of small and medium-sized online retailers," Journal of Business Research, Elsevier, vol. 69(9), pages 3755-3764.
    20. Hasebur Rahman, 2013. "Customer Satisfaction and Loyalty: A Case Study from the Banking Sector," Central European Business Review, Prague University of Economics and Business, vol. 2013(4), pages 15-23.

    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:spr:comgts:v:13:y:2016:i:4:d:10.1007_s10287-016-0266-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.