IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

The estimation of pre- and postpromotion dips with store-level scanner data

  • Heerde, Harald J. van
  • Leeflang, Peter S.H.
  • Wittink, Dick R.

    (Groningen University)

Registered author(s):

    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.

    If 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.

    File URL: http://irs.ub.rug.nl/ppn/188209727
    Download Restriction: no

    Paper provided by University of Groningen, Research Institute SOM (Systems, Organisations and Management) in its series Research Report with number 99B36.

    as
    in new window

    Length:
    Date of creation: 1999
    Date of revision:
    Handle: RePEc:dgr:rugsom:99b36
    Contact details of provider: Postal: PO Box 800, 9700 AV Groningen
    Phone: +31 50 363 7185
    Fax: +31 50 363 3720
    Web page: http://som.eldoc.ub.rug.nl/
    Email:


    More information through EDIRC

    References listed on IDEAS
    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.:

    as in new window
    1. 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," Papers 90-92-15, California Irvine - School of Social Sciences.
    2. 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.
    3. 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.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    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 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.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.