Marketing Science
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


MARKETING SCIENCE
Vol. 26, No. 2, March-April 2007, pp. 179-195
DOI: 10.1287/mksc.1060.0208
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Bass, F. M.
Right arrow Articles by Murthi, B. P. S.
Right arrow Search for Related Content

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

Frank M. Bass, Norris Bruce, Sumit Majumdar, B. P. S. Murthi

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

mzjb{at}utdallas.edu
norris.bruce{at}utdallas.edu
majumdar{at}utdallas.edu
murthi{at}utdallas.edu

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.

Key Words: Bayesian dynamic linear models; Gibbs sampling aggregate advertising models; wearout effects; forgetting effects; copy effects; scheduling of ad copy
History: Received: June 30, 2005;


This article has been cited by other articles:


Home page
Marketing ScienceHome page
Y. Chen, Y. V. Joshi, J. S. Raju, and Z. J. Zhang
A Theory of Combative Advertising
Marketing Science, January 1, 2009; 28(1): 1 - 19.
[Abstract] [PDF]


Home page
Marketing ScienceHome page
M. C. W. Janssen and M. C. Non
Going Where the Ad Leads You: On High Advertised Prices and Searching Where to Buy
Marketing Science, January 1, 2009; 28(1): 87 - 98.
[Abstract] [PDF]


Home page
Marketing ScienceHome page
S. D. Jap and P. A. Naik
BidAnalyzer: A Method for Estimation and Selection of Dynamic Bidding Models
Marketing Science, November 1, 2008; 27(6): 949 - 960.
[Abstract] [PDF]


Home page
Marketing ScienceHome page
M. B. Ataman, C. F. Mela, and H. J. van Heerde
Building Brands
Marketing Science, November 1, 2008; 27(6): 1036 - 1054.
[Abstract] [PDF]


Home page
Marketing ScienceHome page
T. Erdem, M. P. Keane, and B. Sun
A Dynamic Model of Brand Choice When Price and Advertising Signal Product Quality
Marketing Science, November 1, 2008; 27(6): 1111 - 1125.
[Abstract] [PDF]


Home page
Marketing ScienceHome page
N. I. Bruce
Pooling and Dynamic Forgetting Effects in Multitheme Advertising: Tracking the Advertising Sales Relationship with Particle Filters
Marketing Science, July 1, 2008; 27(4): 659 - 673.
[Abstract] [PDF]


Home page
Management ScienceHome page
P. A. Naik, A. Prasad, and S. P. Sethi
Building Brand Awareness in Dynamic Oligopoly Markets
Management Science, January 1, 2008; 54(1): 129 - 138.
[Abstract] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2007 by INFORMS.