IDEAS home Printed from https://ideas.repec.org/p/ecl/stabus/2138.html
   My bibliography  Save this paper

Effect of Temporal Spacing between Advertising Exposures: Evidence from Online Field Experiments

Author

Listed:
  • Sahni, Navdeep

    (Stanford University)

Abstract

This paper aims to understand the impact of temporal spacing between ad exposures on the likelihood of a consumer purchasing the advertised product. I create an individual-level data set with exogenous variation in the spacing and intensity of ads by running online field experiments. Using this data set, I first show that (1) ads significantly increase the likelihood of the consumers purchasing from the advertiser and (2) this increase carries over to future purchase occasions. Importantly, I find evidence for the spacing effect: the likelihood of a product's purchase increases if the product's past ads are spread apart rather than bunched together, even if the spreading apart of ads involves shifting some ads away from the purchase occasion. Because the traditional models of advertising do not explain the data patterns, I build a new memory-based model of how advertising influences consumer behavior. Using a nested test, I reject the restrictions imposed by the canonical goodwill stock model based on the Nerlove and Arrow [1962] approach, in favor of the more general memory-based model. Counterfactual simulations using the parameter estimates show that not accounting for the features of the memory model might lead to significantly lower profits for the advertisers.

Suggested Citation

  • Sahni, Navdeep, 2013. "Effect of Temporal Spacing between Advertising Exposures: Evidence from Online Field Experiments," Research Papers 2138, Stanford University, Graduate School of Business.
  • Handle: RePEc:ecl:stabus:2138
    as

    Download full text from publisher

    File URL: http://www.gsb.stanford.edu/faculty-research/working-papers/effect-temporal-spacing-between-advertising-exposures-evidence-0
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anja Lambrecht & Avi Goldfarb & Alessandro Bonatti & Anindya Ghose & Daniel Goldstein & Randall Lewis & Anita Rao & Navdeep Sahni & Song Yao, 2014. "How do firms make money selling digital goods online?," Marketing Letters, Springer, vol. 25(3), pages 331-341, September.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ecl:stabus:2138. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/gsstaus.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.