The estimation of pre- and postpromotion dips with store-level scanner data
One of the mysteries of store-level scanner data modeling is the lack of a dip in sales in the week(s) following a promotion. Researchers expect to find a postpromotion dip because analyses of household scanner panel data indicate that consumers tend to accelerate their purchases in response to a promotion that is, they buy earlier and/or purchase larger quantities than they would in the absence of a promotion. Thus, one should also find a pronounced dip in store-level sales in the week(s) following a promotion. However, researchers find such dips usually neither at the category nor at the brand level. Several arguments have been proposed for the lack of a postpromotion dip in store-level sales data. These arguments explain why dips may be hidden. Given that dips are difficult to detect by traditional models (and by a visual inspection of the data), we propose models that can account for a multitude of factors which together cause complex pre- and postpromotion dips. We use three alternative distributed lead- and lag structures: an Almon model, an Unrestricted dynamic effects model, and an Exponential decay model. In each model, we include four types of price discounts: without any support, with display-only support, with feature-only support, and with feature and display support. The models are calibrated on store-level scanner data for two product categories: tuna and toilet tissue. We estimate the dip to be between 4 and 25 percent of the current sales effect, which is consistent with household-level studies.
|Date of creation:||1999|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +31 50 363 7185
Fax: +31 50 363 3720
Web page: http://som.eldoc.ub.rug.nl/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hsiao, C. & Appelbe, T.W. & Dineen, C.R., 1992.
"A General Framework for Panel Data Models with an Application to Canadian Customer-Dialed Long Distance Telephone Service,"
90-92-15, California Irvine - School of Social Sciences.
- Hsiao, Cheng & Appelbe, Trent W. & Dineen, Christopher R., 1993. "A general framework for panel data models with an application to Canadian customer-dialed long distance telephone service," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 63-86, September.
- Foekens, Eijte W. & S.H. Leeflang, Peter & Wittink, Dick R., 1998. "Varying parameter models to accommodate dynamic promotion effects," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 249-268, November.
- Jeongwen Chiang, 1991. "A Simultaneous Approach to the Whether, What and How Much to Buy Questions," Marketing Science, INFORMS, vol. 10(4), pages 297-315.
- P. Leone, Robert, 1987. "Forecasting the effect of an environmental change on market performance: An intervention time-series approach," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 463-478.
When requesting a correction, please mention this item's handle: RePEc:dgr:rugsom:99b36. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joke Bulthuis)
If references are entirely missing, you can add them using this form.