IDEAS home Printed from https://ideas.repec.org/a/aza/ama000/y2024v10i2p103-115.html
   My bibliography  Save this article

Embracing cookieless advertising with AI

Author

Listed:
  • Thomas, Ian

    (Founder/Chief Data Officer, Yew Tree Data Consulting, UK)

Abstract

After several delays, the end of unrestricted use of third party cookies is now drawing near, forcing all parts of the digital advertising industry to reconsider how they can drive campaign performance and inventory monetisation without gathering user data. Major browser-makers such as Google are deploying and testing technologies to replicate some of the key capabilities of cookies to enable advertisers to continue working as they have before but the industry needs to find a new way of thinking about driving campaign performance which relies less on the idea of finding the perfect audience and more on implementing a set of connected optimisation techniques that drive performance while maintaining privacy. Fortunately, recent developments in AI (artificial intelligence), especially Generative AI, provide some valuable techniques for achieving this, while at the same time improving the online experience for consumers by serving them more relevant ads that more closely match the context in which they are seen.

Suggested Citation

  • Thomas, Ian, 2024. "Embracing cookieless advertising with AI," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 10(2), pages 103-115, September.
  • Handle: RePEc:aza:ama000:y:2024:v:10:i:2:p:103-115
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/8684/download/
    Download Restriction: Requires a paid subscription for full access.

    File URL: https://hstalks.com/article/8684/
    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

    AI; cookies; optimisation; targeting; creative automation; privacy; Google;
    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:2024:v:10:i:2:p:103-115. 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.