[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/aza/airwa0/y2023v2i2p138-144.html
   My bibliography  Save this article

AI, marketing technology and personalisation at scale

Author

Listed:
  • Tinkler, Allan

    (Level 4, Endeavour House, UK)

Abstract
From increased consumer demand for privacy and the deprecation of third-party cookies to expectations for more relevant and personalised advertising, the dynamics of the digital advertising industry are quickly evolving. Marketing technology today is challenged with bringing the digital ecosystem together responsibly, aligning what consumers want with what brands can offer in real time. Artificial intelligence (AI) has proven to be an effective tool for synthesising the data needed to accomplish these tasks and deliver results. How exactly is AI bridging the gap between attitudes about privacy and the need for personalisation at scale? What role do deterministic and probabilistic data have in creating a more trustworthy and relevant digital experience? And how can marketers use AI to respond to real-time events and shifts in consumer preferences? This paper will address how AI can help marketers achieve scale without third-party cookies, and why consumer preferences, varied types of data and real-time measurement are central to achieving personalisation in advertising today.

Suggested Citation

  • Tinkler, Allan, 2023. "AI, marketing technology and personalisation at scale," Journal of AI, Robotics & Workplace Automation, Henry Stewart Publications, vol. 2(2), pages 138-144, December.
  • Handle: RePEc:aza:airwa0:y:2023:v:2:i:2:p:138-144
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/7568/download/
    Download Restriction: Requires a paid subscription for full access.

    File URL: https://hstalks.com/article/7568/
    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

    artificial intelligence (AI); machine learning (ML); digital advertising; data privacy; personalised advertising;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • G2 - Financial Economics - - Financial Institutions and Services

    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:airwa0:y:2023:v:2:i:2:p:138-144. 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.