IDEAS home Printed from https://ideas.repec.org/h/spr/seschp/978-3-032-05730-3_10.html
   My bibliography  Save this book chapter

Analysis of Hyperpersonalization in Digital Marketing Through Artificial Intelligence

Author

Listed:
  • Ibai Urbea Gonzàlez

    (EAE Business School)

  • Armando Salvador

    (EAE Business School)

  • Paulo Sartorato

    (EAE Business School)

Abstract

This research paper aims to analyze how hyperpersonalization in digital marketing, powered by artificial intelligence, is transforming brands’ communication strategies and relationships with consumers. To do so, a qualitative methodology based on interviews with industry experts is employed. It addresses issues such as how to ensure ethical management of AI in digital marketing personalization, and analyzes the impact on consumer perception and trust. The main results reveal that AI-driven hyperpersonalization improves the effectiveness of marketing strategies, enabling more precise segmentation and a more engaging user experience. However, challenges related to data privacy, ethics, and the need to build user trust are also highlighted. The study provides insight into how to balance technological innovation with responsibility. It offers a reflection on the role of creativity in hyperpersonalized campaigns and the importance of consumer trust in an AI-driven digital environment.

Suggested Citation

  • Ibai Urbea Gonzàlez & Armando Salvador & Paulo Sartorato, 2025. "Analysis of Hyperpersonalization in Digital Marketing Through Artificial Intelligence," Studies on Entrepreneurship, Structural Change and Industrial Dynamics,, Springer.
    • Handle: RePEc:spr:seschp:978-3-032-05730-3_10
    DOI: 10.1007/978-3-032-05730-3_10
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:spr:seschp:978-3-032-05730-3_10. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.