IDEAS home Printed from https://ideas.repec.org/a/aza/ama000/y2023v9i1p73-83.html
   My bibliography  Save this article

Lengthen your attribution window: Which digital ads have most long-term impact?

Author

Listed:
  • Qin, Vivian

    (Senior Data Scientist, Amazon Ads, USA)

Abstract

Brands usually invest in a portfolio of digital ad products for brand consideration and conversion, and their performance is commonly evaluated with ad-attributed metrics. However, these metrics limit the measurement of advertising effectiveness within a short time window, typically of two weeks. Therefore, they could underestimate the total effect if some ad products' efficacy lasts beyond the measurement period. In particular, this could understate the impact from ad products aimed at awareness and consideration. In addition, this bias could manifest in product categories where shoppers' involvement is high because they are making deliberate purchase decisions. To solve these problems, the Vector Autoregressive Moving Average with Exogenous variables (VARMAX) model is applied, which allows flexibility in the length of the advertising measurement window, and thus can empirically quantify how long the effect of each ad lasts without `a priori` restrictions. For 15 US brands across three verticals (Hardlines, Softlines and Consumables) on Amazon, it was found that within the two-week attribution window, upper/middle-funnel ad products only materialise 30–50 per cent of the total effects, compared to lower-funnel at 60–90 per cent. Based on these results, it is recommended that advertisers and publishers lengthen the attribution window, and especially track their upper and middle-funnel ad products for at least a month to capture their longer-term effects.

Suggested Citation

  • Qin, Vivian, 2023. "Lengthen your attribution window: Which digital ads have most long-term impact?," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 9(1), pages 73-83, June.
  • Handle: RePEc:aza:ama000:y:2023:v:9:i:1:p:73-83
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/7754/download/
    Download Restriction: Requires a paid subscription for full access.

    File URL: https://hstalks.com/article/7754/
    Download Restriction: Requires a paid subscription for full access.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    digital ads; attribution window; performance metrics; long-term effects; e-commerce; ROAS;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

    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:aza:ama000:y:2023:v:9:i:1:p:73-83. 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: Henry Stewart Talks (email available below). General contact details of provider: .

    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.