IDEAS home Printed from https://ideas.repec.org/a/eee/joinma/v27y2013i1p28-35.html
   My bibliography  Save this article

The Geometric Law of Annual Halving

Author

Listed:
  • Malthouse, Edward C.
  • Raman, Kalyan

Abstract

We propose and test an empirical generalization: the probability that a customer will be active in a future window is reduced by half for every additional year the customer is inactive. We test this model over 6 nonprofit organizations and 30 B2C retail companies, and find that it fits very well. No significant differences in the decay constant were found between nonprofits and retailers, different customer groups defined by the frequency of previous purchases, or the length of the future period. The effect of frequency on the probability of future activity is empirically shown to follow the exponential learning curve. Norms are provided for asymptote, intercept and steepness coefficient.

Suggested Citation

  • Malthouse, Edward C. & Raman, Kalyan, 2013. "The Geometric Law of Annual Halving," Journal of Interactive Marketing, Elsevier, vol. 27(1), pages 28-35.
    • Handle: RePEc:eee:joinma:v:27:y:2013:i:1:p:28-35
    DOI: 10.1016/j.intmar.2012.08.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1094996812000485
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intmar.2012.08.001?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. Robert C. Blattberg & Richard Briesch & Edward J. Fox, 1995. "How Promotions Work," Marketing Science, INFORMS, vol. 14(3_supplem), pages 122-132.
    2. Lee, Hyoung-joo & Shin, Hyunjung & Hwang, Seong-seob & Cho, Sungzoon & MacLachlan, Douglas, 2010. "Semi-Supervised Response Modeling," Journal of Interactive Marketing, Elsevier, vol. 24(1), pages 42-54.
    3. Naik, Prasad A. & Peters, Kay, 2009. "A Hierarchical Marketing Communications Model of Online and Offline Media Synergies," Journal of Interactive Marketing, Elsevier, vol. 23(4), pages 288-299.
    4. Malthouse, Edward C. & Derenthal, Kirstin M., 2008. "Improving predictive scoring models through model aggregation," Journal of Interactive Marketing, Elsevier, vol. 22(3), pages 51-68.
    5. McCarty, John A. & Hastak, Manoj, 2007. "Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression," Journal of Business Research, Elsevier, vol. 60(6), pages 656-662, June.
    6. Blattberg, Robert C. & Malthouse, Edward C. & Neslin, Scott A., 2009. "Customer Lifetime Value: Empirical Generalizations and Some Conceptual Questions," Journal of Interactive Marketing, Elsevier, vol. 23(2), pages 157-168.
    7. Raman, Kalyan & Mantrala, Murali K. & Sridhar, Shrihari & Tang, Yihui (Elina), 2012. "Optimal Resource Allocation with Time-varying Marketing Effectiveness, Margins and Costs," Journal of Interactive Marketing, Elsevier, vol. 26(1), pages 43-52.
    8. Roland T. Rust & Peter C. Verhoef, 2005. "Optimizing the Marketing Interventions Mix in Intermediate-Term CRM," Marketing Science, INFORMS, vol. 24(3), pages 477-489, December.
    9. Fader, Peter S. & Hardie, Bruce G.S., 2009. "Probability Models for Customer-Base Analysis," Journal of Interactive Marketing, Elsevier, vol. 23(1), pages 61-69.
    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. Blattberg, Robert C. & Malthouse, Edward C. & Neslin, Scott A., 2009. "Customer Lifetime Value: Empirical Generalizations and Some Conceptual Questions," Journal of Interactive Marketing, Elsevier, vol. 23(2), pages 157-168.
    2. Verhoef, Peter C. & Venkatesan, Rajkumar & McAlister, Leigh & Malthouse, Edward C. & Krafft, Manfred & Ganesan, Shankar, 2010. "CRM in Data-Rich Multichannel Retailing Environments: A Review and Future Research Directions," Journal of Interactive Marketing, Elsevier, vol. 24(2), pages 121-137.
    3. Lee, Hyoung-joo & Shin, Hyunjung & Hwang, Seong-seob & Cho, Sungzoon & MacLachlan, Douglas, 2010. "Semi-Supervised Response Modeling," Journal of Interactive Marketing, Elsevier, vol. 24(1), pages 42-54.
    4. Risselada, Hans & Verhoef, Peter C. & Bijmolt, Tammo H.A., 2010. "Staying Power of Churn Prediction Models," Journal of Interactive Marketing, Elsevier, vol. 24(3), pages 198-208.
    5. Peter S. Fader & Bruce G. S. Hardie & Jen Shang, 2010. "Customer-Base Analysis in a Discrete-Time Noncontractual Setting," Marketing Science, INFORMS, vol. 29(6), pages 1086-1108, 11-12.
    6. M. Ballings & D. Van Den Poel, 2012. "The Relevant Length of Customer Event History for Churn Prediction: How long is long enough?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/804, Ghent University, Faculty of Economics and Business Administration.
    7. Thomas Niemand & Sascha Kraus & Sophia Mather & Antonio C. Cuenca-Ballester, 2020. "Multilevel marketing: optimizing marketing effectiveness for high-involvement goods in the automotive industry," International Entrepreneurship and Management Journal, Springer, vol. 16(4), pages 1367-1392, December.
    8. Thomas Niemand & Sascha Kraus & Sophia Mather & Antonio C. Cuenca-Ballester, 0. "Multilevel marketing: optimizing marketing effectiveness for high-involvement goods in the automotive industry," International Entrepreneurship and Management Journal, Springer, vol. 0, pages 1-26.
    9. Lesscher, Lisan & Lobschat, Lara & Verhoef, Peter C., 2021. "Do offline and online go hand in hand? Cross-channel and synergy effects of direct mailing and display advertising," International Journal of Research in Marketing, Elsevier, vol. 38(3), pages 678-697.
    10. George, Morris & Kumar, V. & Grewal, Dhruv, 2013. "Maximizing Profits for a Multi-Category Catalog Retailer," Journal of Retailing, Elsevier, vol. 89(4), pages 374-396.
    11. Jaiswal, Anand K. & Niraj, Rakesh & Park, Chang Hee & Agarwal, Manoj K., 2018. "The effect of relationship and transactional characteristics on customer retention in emerging online markets," Journal of Business Research, Elsevier, vol. 92(C), pages 25-35.
    12. Gázquez-Abad, Juan Carlos & Canniére, Marie Hélène De & Martínez-López, Francisco J., 2011. "Dynamics of Customer Response to Promotional and Relational Direct Mailings from an Apparel Retailer: The Moderating Role of Relationship Strength," Journal of Retailing, Elsevier, vol. 87(2), pages 166-181.
    13. V. Kumar & JeeWon Brianna Choi & Mallik Greene, 2017. "Synergistic effects of social media and traditional marketing on brand sales: capturing the time-varying effects," Journal of the Academy of Marketing Science, Springer, vol. 45(2), pages 268-288, March.
    14. Feld, Sebastian & Frenzen, Heiko & Krafft, Manfred & Peters, Kay & Verhoef, Peter C., 2013. "The effects of mailing design characteristics on direct mail campaign performance," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 143-159.
    15. G. A. Verhaert & D. Van Den Poel, 2012. "The Role of Seed Money and Threshold Size in Optimizing Fundraising Campaigns: Past Behavior Matters!," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/815, Ghent University, Faculty of Economics and Business Administration.
    16. Hache, Emmanuel & Leboullenger, Déborah & Mignon, Valérie, 2017. "Beyond average energy consumption in the French residential housing market: A household classification approach," Energy Policy, Elsevier, vol. 107(C), pages 82-95.
    17. Chen Zhou & Shrihari Sridhar & Rafael Becerril-Arreola & Tony Haitao Cui & Yan Dong, 2019. "Promotions as competitive reactions to recalls and their consequences," Journal of the Academy of Marketing Science, Springer, vol. 47(4), pages 702-722, July.
    18. David R. Bell & Jeongwen Chiang & V. Padmanabhan, 1999. "The Decomposition of Promotional Response: An Empirical Generalization," Marketing Science, INFORMS, vol. 18(4), pages 504-526.
    19. Philipp Afèche & Mojtaba Araghi & Opher Baron, 2017. "Customer Acquisition, Retention, and Service Access Quality: Optimal Advertising, Capacity Level, and Capacity Allocation," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 674-691, October.
    20. 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.

    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:eee:joinma:v:27:y:2013:i:1:p:28-35. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-interactive-marketing/ .

    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.