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Moment-to-Moment Optimal Branding in TV Commercials: Preventing Avoidance by Pulsing

Author

Listed:
  • Thales S. Teixeira

    (Marketing Unit, Harvard Business School, Boston, Massachusetts 02163)

  • Michel Wedel

    (Smith School of Business, University of Maryland, College Park, Maryland 20742)

  • Rik Pieters

    (Department of Marketing, Tilburg University, 5000 LE Tilburg, The Netherlands)

Abstract

We develop a conceptual framework about the impact that branding activity (the audiovisual representation of brands) and consumers' focused versus dispersed attention have on consumer moment-to-moment avoidance decisions during television advertising. We formalize this framework in a dynamic probit model and estimate it with Markov chain Monte Carlo methods. Data on avoidance through zapping, along with eye tracking on 31 commercials for nearly 2,000 participants, are used to calibrate the model. New, simple metrics of attention dispersion are shown to strongly predict avoidance. Independent of this, central on-screen brand positions, but not brand size, further promote commercial avoidance. Based on the model estimation, we optimize the branding activity that is under marketing control for ads in the sample to reduce commercial avoidance. This reveals that brand pulsing--while keeping total brand exposure constant--decreases commercial avoidance significantly. Both numerical simulations and a controlled experiment using regular and edited commercials, respectively, provide evidence of the benefits of brand pulsing to ward off commercial avoidance. Implications for advertising management and theory are addressed.

Suggested Citation

  • Thales S. Teixeira & Michel Wedel & Rik Pieters, 2010. "Moment-to-Moment Optimal Branding in TV Commercials: Preventing Avoidance by Pulsing," Marketing Science, INFORMS, vol. 29(5), pages 783-804, 09-10.
  • Handle: RePEc:inm:ormksc:v:29:y:2010:i:5:p:783-804
    DOI: 10.1287/mksc.1100.0567
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    References listed on IDEAS

    as
    1. Sueyoshi, Glenn T, 1995. "A Class of Binary Response Models for Grouped Duration Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 411-431, Oct.-Dec..
    2. 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.
    3. Michel Wedel & Rik Pieters, 2000. "Eye Fixations on Advertisements and Memory for Brands: A Model and Findings," Marketing Science, INFORMS, vol. 19(4), pages 297-312, October.
    4. Paul Gustafson & S. Siddarth, 2007. "Describing the Dynamics of Attention to TV Commercials: A Hierarchical Bayes Analysis of the Time to Zap an Ad," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(5), pages 585-609.
    5. S. Siddarth & Amitava Chattopadhyay, 1998. "To Zap or Not to Zap: A Study of the Determinants of Channel Switching During Commercials," Marketing Science, INFORMS, vol. 17(2), pages 124-138.
    6. Monica Billio & Roberto Casarin & Domenico Sartore, 2007. "Bayesian Inference on Dynamic Models with Latent Factors," Working Papers 2007_34, Department of Economics, University of Venice "Ca' Foscari".
    7. Gustav Feichtinger & Richard F. Hartl & Suresh P. Sethi, 1994. "Dynamic Optimal Control Models in Advertising: Recent Developments," Management Science, INFORMS, vol. 40(2), pages 195-226, February.
    8. Martin, Andrew D. & Quinn, Kevin M., 2002. "Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999," Political Analysis, Cambridge University Press, vol. 10(2), pages 134-153, April.
    9. Mohamed Lachaab & Asim Ansari & Kamel Jedidi & Abdelwahed Trabelsi, 2006. "Modeling preference evolution in discrete choice models: A Bayesian state-space approach," Quantitative Marketing and Economics (QME), Springer, vol. 4(1), pages 57-81, March.
    10. Frank M. Bass & Norris Bruce & Sumit Majumdar & B. P. S. Murthi, 2007. "Wearout Effects of Different Advertising Themes: A Dynamic Bayesian Model of the Advertising-Sales Relationship," Marketing Science, INFORMS, vol. 26(2), pages 179-195, 03-04.
    11. Janiszewski, Chris, 1998. "The Influence of Display Characteristics on Visual Exploratory Search Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(3), pages 290-301, December.
    12. Fred M. Feinberg, 2001. "On Continuous-Time Optimal Advertising Under S-Shaped Response," Management Science, INFORMS, vol. 47(11), pages 1476-1487, November.
    13. Minhi Hahn & Jin-Sok Hyun, 1991. "Advertising Cost Interactions and the Optimality of Pulsing," Management Science, INFORMS, vol. 37(2), pages 157-169, February.
    14. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
    15. Rik Pieters & Michel Wedel, 2007. "Goal Control of Attention to Advertising: The Yarbus Implication," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(2), pages 224-233, June.
    16. Rik Pieters & Michel Wedel & Jie Zhang, 2007. "Optimal Feature Advertising Design Under Competitive Clutter," Management Science, INFORMS, vol. 53(11), pages 1815-1828, November.
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