Dynamic Analysis of Consumer Response to Marketing Strategies
AbstractThis paper develops a methodology for modeling consumer response that integrates previous research in stochastic brand selection, diffusion of innovation, test market analysis, and new product design. The methodology makes it practical to extend brand selection models to include diffusion phenomena such as awareness, trial, and information flow. Purchase timing and brand selection are interdependent and both phenomena depend jointly on managerial controls such as advertising, coupons, price-off promotion, product positioning, and consumer characteristics. Within this general structure, we provide practical estimation procedures (a least squares approximation to the maximum likelihood estimates) to determine the parameters which link managerial controls to consumer response. Closed form solutions are derived for cumulative awareness, cumulative trial, penetration, expected sales, and purchases due to promotion---all as a function of time. We also provide simplified expressions for equilibrium (t -> \infty ) market share. Tradeoffs among complexity of the diffusion process, number of managerial variables, nonstationarity, complexity of purchase timing, consumer segmentation, and sample size are made explicit so that the marketing scientist can customize his analyses to the managerial problems that he faces. The effects of sample size, data interval frequency, and collinearity in the explanatory variables are investigated with simulations based on a five-state consumer response process which depends on 8--10 marketing variables. The paper closes with a brief description of the application and predictive test of a consumer response model based on the methodology.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by INFORMS in its journal Management Science.
Volume (Year): 28 (1982)
Issue (Month): 5 (May)
marketing; consumer behavior; Markov analysis;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Kim, Sang-Hoon & Srinivasan, V. "Seenu", 2006. "A Conjoint-Hazard Model of the Timing of Buyers' Upgrading to Improved Versions of High Technology Products," Research Papers 1720r1, Stanford University, Graduate School of Business.
- Jan Kaluski, 2000. "An Analytical Method To Calculate The Ergodic And Difference Matrices Of The Discounted Markov Decision Processes," Computing in Economics and Finance 2000 235, Society for Computational Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc).
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.