IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v26y2007i2p179-195.html
   My bibliography  Save this article

Wearout Effects of Different Advertising Themes: A Dynamic Bayesian Model of the Advertising-Sales Relationship

Author

Listed:
  • Frank M. Bass

    (School of Management, The University of Texas at Dallas, Richardson, Texas 75083-0688)

  • Norris Bruce

    (School of Management, The University of Texas at Dallas, Richardson, Texas 75083-0688)

  • Sumit Majumdar

    (School of Management, The University of Texas at Dallas, Richardson, Texas 75083-0688)

  • B. P. S. Murthi

    (School of Management, The University of Texas at Dallas, Richardson, Texas 75083-0688)

Abstract

Models of advertising response implicitly assume that the entire advertising budget is spent on disseminating one message. In practice, managers use different themes of advertising (for example, price advertisements versus product advertisements) and within each theme they employ different versions of an advertisement. In this study, we evaluate the dynamic effects of different themes of advertising that have been employed in a campaign. We develop a model that jointly considers the effects of wearout as well as that of forgetting in the context of an advertising campaign that employs five different advertising themes. We quantify the differential wearout effects across the different themes of advertising and examine the interaction effects between the different themes using a Bayesian dynamic linear model (DLM). Such a response model can help managers decide on the optimal allocation of resources across the portfolio of ads as well as better manage their scheduling. We develop a model to show how our response model parameters can be used to improve the effectiveness of advertising budget allocation across different themes. We find that a reallocation of resources across different themes according to our model results in a significant improvement in demand.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:ormksc:v:26:y:2007:i:2:p:179-195
    DOI: 10.1287/mksc.1060.0208
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1060.0208
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.1060.0208?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
    ---><---

    References listed on IDEAS

    as
    1. Kamel Jedidi & Carl F. Mela & Sunil Gupta, 1999. "Managing Advertising and Promotion for Long-Run Profitability," Marketing Science, INFORMS, vol. 18(1), pages 1-22.
    2. Lambin, Jean-Jacques, 1969. "Measuring the Profitability of Advertising: An Empirical Study," Journal of Industrial Economics, Wiley Blackwell, vol. 17(2), pages 86-103, April.
    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. John D. C. Little, 1975. "BRANDAID: A Marketing-Mix Model, Part 1: Structure," Operations Research, INFORMS, vol. 23(4), pages 628-655, August.
    5. David B. Montgomery & Marian Chapman Moore & Joel E. Urbany, 2005. "Reasoning About Competitive Reactions: Evidence from Executives," Marketing Science, INFORMS, vol. 24(1), pages 138-149, September.
    6. Winer, Russell S, 1979. "An Analysis of the Time-varying Effects of Advertising: The Case of Lydia Pinkham," The Journal of Business, University of Chicago Press, vol. 52(4), pages 563-576, October.
    7. Michael L. Ray & Alan G. Sawyer, 1971. "Behavioral Measurement for Marketing Models: Estimating the Effects of Advertising Repetition for Media Planning," Management Science, INFORMS, vol. 18(4-Part-II), pages 73-89, December.
    8. Robert C. Blattberg & Abel P. Jeuland, 1981. "A Micromodeling Approach to Investigate the Advertising-Sales Relationship," Management Science, INFORMS, vol. 27(9), pages 988-1005, September.
    9. Vijay Mahajan & Eitan Muller, 1986. "Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 89-106.
    10. John C. Liechty & Duncan K. H. Fong & Wayne S. DeSarbo, 2005. "Dynamic Models Incorporating Individual Heterogeneity: Utility Evolution in Conjoint Analysis," Marketing Science, INFORMS, vol. 24(2), pages 285-293, November.
    11. Lester G. Telser, 1964. "Advertising and Competition," Journal of Political Economy, University of Chicago Press, vol. 72, pages 537-537.
    12. Peter Doyle & John Saunders, 1990. "Multiproduct Advertising Budgeting," Marketing Science, INFORMS, vol. 9(2), pages 97-113.
    13. Fred M. Feinberg, 1992. "Pulsing Policies for Aggregate Advertising Models," Marketing Science, INFORMS, vol. 11(3), pages 221-234.
    14. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
    15. Ramya Neelamegham & Pradeep K. Chintagunta, 2004. "Modeling and Forecasting the Sales of Technology Products," Quantitative Marketing and Economics (QME), Springer, vol. 2(3), pages 195-232, September.
    16. Belch, George E, 1982. "The Effects of Television Commercial Repetition on Cognitive Response and Message Acceptance," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(1), pages 56-65, June.
    17. Frank M. Bass & Robert P. Leone, 1983. "Temporal Aggregation, the Data Interval Bias, and Empirical Estimation of Bimonthly Relations from Annual Data," Management Science, INFORMS, vol. 29(1), pages 1-11, January.
    18. 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.
    19. Joseph O. Eastlack, Jr. & Ambar G. Rao, 1989. "Advertising Experiments at the Campbell Soup Company," Marketing Science, INFORMS, vol. 8(1), pages 57-71.
    20. Kristian S. Palda, 1964. "The Measurement of Cumulative Advertising Effects," The Journal of Business, University of Chicago Press, vol. 38, pages 162-162.
    21. MacInnis, Deborah J & Price, Linda L, 1987. "The Role of Imagery in Information Processing: Review and Extensions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(4), pages 473-491, March.
    22. M. L. Vidale & H. B. Wolfe, 1957. "An Operations-Research Study of Sales Response to Advertising," Operations Research, INFORMS, vol. 5(3), pages 370-381, June.
    23. Prasad A. Naik & Kalyan Raman & Russell S. Winer, 2005. "Planning Marketing-Mix Strategies in the Presence of Interaction Effects," Marketing Science, INFORMS, vol. 24(1), pages 25-34, June.
    24. Vijay Mahajan & Eitan Muller & Subhash Sharma, 1984. "An Empirical Comparison of Awareness Forecasting Models of New Product Introduction," Marketing Science, INFORMS, vol. 3(3), pages 179-197.
    25. J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
    26. Jean-Pierre Dubé & Puneet Manchanda, 2005. "Differences in Dynamic Brand Competition Across Markets: An Empirical Analysis," Marketing Science, INFORMS, vol. 24(1), pages 81-95, September.
    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. 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.
    2. Norris I. Bruce, 2008. "Pooling and Dynamic Forgetting Effects in Multitheme Advertising: Tracking the Advertising Sales Relationship with Particle Filters," Marketing Science, INFORMS, vol. 27(4), pages 659-673, 07-08.
    3. Chan, Tat Y. & Narasimhan, Chakravarthi & Yoon, Yeujun, 2017. "Advertising and price competition in a manufacturer-retailer channel," International Journal of Research in Marketing, Elsevier, vol. 34(3), pages 694-716.
    4. Mesak, Hani I. & Ellis, T. Selwyn, 2009. "On the superiority of pulsing under a concave advertising market potential function," European Journal of Operational Research, Elsevier, vol. 194(2), pages 608-627, April.
    5. 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.
    6. Navdeep Sahni, 2015. "Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 203-247, September.
    7. Huang, Jian & Leng, Mingming & Liang, Liping, 2012. "Recent developments in dynamic advertising research," European Journal of Operational Research, Elsevier, vol. 220(3), pages 591-609.
    8. Navdeep S. Sahni, 2015. "Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 203-247, September.
    9. Gijsenberg, Maarten & Nijs, Vincent R., 2018. "Advertising Timing," Research Report 2018004-MARK, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    10. Gijsenberg, Maarten J. & Nijs, Vincent R., 2019. "Advertising spending patterns and competitor impact," International Journal of Research in Marketing, Elsevier, vol. 36(2), pages 232-250.
    11. Dengpan Liu & Subodha Kumar & Vijay S. Mookerjee, 2012. "Advertising Strategies in Electronic Retailing: A Differential Games Approach," Information Systems Research, INFORMS, vol. 23(3-part-2), pages 903-917, September.
    12. Mesak, Hani I., 1999. "On the generalizability of advertising pulsation monopoly results to an oligopoly," European Journal of Operational Research, Elsevier, vol. 117(3), pages 429-449, September.
    13. Mesak, Hani Ibrahim & Bari, Abdullahel & Lian, Qin, 2015. "Pulsation in a competitive model of advertising-firm's cost interaction," European Journal of Operational Research, Elsevier, vol. 246(3), pages 916-926.
    14. Ashwin Aravindakshan & Prasad Naik, 2011. "How does awareness evolve when advertising stops? The role of memory," Marketing Letters, Springer, vol. 22(3), pages 315-326, September.
    15. S. Sriram & Pradeep K. Chintagunta & Ramya Neelamegham, 2006. "Effects of Brand Preference, Product Attributes, and Marketing Mix Variables in Technology Product Markets," Marketing Science, INFORMS, vol. 25(5), pages 440-456, September.
    16. Mesak, Hani I. & Calloway, James A., 1995. "A pulsing model of advertising competition: A game theoretic approach, part B -- Empirical application and findings," European Journal of Operational Research, Elsevier, vol. 86(3), pages 422-433, November.
    17. Luzon, Yossi & Pinchover, Rotem & Khmelnitsky, Eugene, 2022. "Dynamic budget allocation for social media advertising campaigns: optimization and learning," European Journal of Operational Research, Elsevier, vol. 299(1), pages 223-234.
    18. Fred M. Feinberg, 2001. "On Continuous-Time Optimal Advertising Under S-Shaped Response," Management Science, INFORMS, vol. 47(11), pages 1476-1487, November.
    19. Jianan Wu & Victor J. Cook & Edward C. Strong, 2005. "A Two-Stage Model of the Promotional Performance of Pure Online Firms," Information Systems Research, INFORMS, vol. 16(4), pages 334-351, December.
    20. Michael Braun & Wendy W. Moe, 2013. "Online Display Advertising: Modeling the Effects of Multiple Creatives and Individual Impression Histories," Marketing Science, INFORMS, vol. 32(5), pages 753-767, September.

    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:inm:ormksc:v:26:y:2007:i:2:p:179-195. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.