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Understanding the role of marketing communications in direct marketing

Author

Listed:
  • Naik, P.
  • Piersma, N.
Abstract
The standard RFM models used by direct marketers include behavioral variables, but ignore the role of marketing communications. In addition, RFM models allow customer responsiveness to vary across different customers, but not across diiferent time periods. Hence, the authors first extend RFM models by incorporating the effects of marketing communications and temporal heterogeneity. Then, using direct-marketing data from a Dutch charity organization, they calibrate the proposed model, and find that it better explains customer behavior because it includes information on both the past behavior and marketing communications. More specifically, they show that direct mail communication builds goodwill, which, in turn, enhances customer's likelihood to buy. However, cumulative exposure to direct mail creates irritation, and erodes goodwill. The two opposite effects induce a cyclic pattern of goodwill formation, which repeats over four quarters. Next, the authors find that, when they control for these communications effects, the standard result - customer's likelihood to buy increases as shopping frequency increases - reverses. That is, in contrast to the extant literature, customers who donate frequently are less likely to donate in the near future. These findings are not only stable over time, but also replicate across two large data sets. Finally, the authors discuss the need for implementing pulsing strategy to mitigate irritation, and the possibility of practicing one-to-one marketing by using information on customer responsiveness, which can be estimated for each customer via the proposed model.

Suggested Citation

  • Naik, P. & Piersma, N., 2002. "Understanding the role of marketing communications in direct marketing," Econometric Institute Research Papers EI 2002-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:571
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    File URL: https://repub.eur.nl/pub/571/feweco20020501140152.pdf
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    References listed on IDEAS

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    1. Burke, Marian C & Edell, Julie A, 1986. "Ad Reactions over Time: Capturing Changes in the Real World," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(1), pages 114-118, June.
    2. Rosbergen, Edward & Pieters, Rik & Wedel, Michel, 1997. "Visual Attention to Advertising: A Segment-Level Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 24(3), pages 305-314, December.
    3. Prasad A. Naik & Murali K. Mantrala & Alan G. Sawyer, 1998. "Planning Media Schedules in the Presence of Dynamic Advertising Quality," Marketing Science, INFORMS, vol. 17(3), pages 214-235.
    4. Füsun Gönül & Meng Ze Shi, 1998. "Optimal Mailing of Catalogs: A New Methodology Using Estimable Structural Dynamic Programming Models," Management Science, INFORMS, vol. 44(9), pages 1249-1262, September.
    5. Vijay Mahajan & Eitan Muller, 1986. "Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 89-106.
    6. Wedel, M, et al, 1993. "A Latent Class Poisson Regression Model for Heterogeneous Count Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 397-411, Oct.-Dec..
    7. Vijay Mahajan & Eitan Muller, 1986. "Reply—Reflections on Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 110-111.
    8. Jan Roelf Bult & Tom Wansbeek, 1995. "Optimal Selection for Direct Mail," Marketing Science, INFORMS, vol. 14(4), pages 378-394.
    9. Tanizaki, Hisashi, 1993. "Kalman Filter Model with Qualitative Dependent Variables," The Review of Economics and Statistics, MIT Press, vol. 75(4), pages 747-752, November.
    10. David C. Schmittlein & Donald G. Morrison & Richard Colombo, 1987. "Counting Your Customers: Who-Are They and What Will They Do Next?," Management Science, INFORMS, vol. 33(1), pages 1-24, January.
    11. Robert P. Leone, 1995. "Generalizing What Is Known About Temporal Aggregation and Advertising Carryover," Marketing Science, INFORMS, vol. 14(3_supplem), pages 141-150.
    12. Rosbergen, E. & Pieters, R. & Wedel, M., 1997. "Visual attention to advertising : A segment-level analysis," Other publications TiSEM c77552c4-5b16-4ecb-8a21-2, Tilburg University, School of Economics and Management.
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    Cited by:

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    2. van Diepen, Merel & Donkers, Bas & Franses, Philip Hans, 2009. "Does irritation induced by charitable direct mailings reduce donations?," International Journal of Research in Marketing, Elsevier, vol. 26(3), pages 180-188.
    3. 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.
    4. Vafainia, Saeid & Breugelmans, Els & Bijmolt, Tammo, 2019. "Calling Customers to Take Action: The Impact of Incentive and Customer Characteristics on Direct Mailing Effectiveness," Journal of Interactive Marketing, Elsevier, vol. 45(C), pages 62-80.

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