IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v35y2024i4p1873-1889.html
   My bibliography  Save this article

A Smart Ad Display System

Author

Listed:
  • Li Xiao

    (School of Management, Fudan University, Shanghai 200433, People’s Republic of China)

  • D. J. Wu

    (Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia 30308)

  • Min Ding

    (Smeal College of Business and College of Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania 16802)

Abstract

This paper proposes a smart ad display system to provide personalized delivery of video ads. The proposed system records consumers’ facial expression and eye gaze stream data as they watch an ad and analyzes data at the frame level. The recognized facial expression and detected eye gaze are matched to the corresponding frame of the video ad, thereby linking facial expressions to specific visual objects appearing in the ad. By tracking a consumer’s facial expressions in response to various visual objects in real time, the system learns the consumer’s individual preferences toward different ads, searches the ad pool, and selects and subsequently displays a new ad that is most likely to elicit positive attitudinal and behavioral responses. We demonstrate the feasibility and effectiveness of the proposed system with two empirical studies. The results show that by tracking a consumer’s facial responses to only one ad or even part of an ad, our proposed system is able to make reasonably accurate inferences about a consumer’s ad preferences, with or without using information about other consumers. These inferences are used to make personalized recommendations that help enhance consumers’ ad viewing experiences and elicit favorable responses.

Suggested Citation

  • Li Xiao & D. J. Wu & Min Ding, 2024. "A Smart Ad Display System," Information Systems Research, INFORMS, vol. 35(4), pages 1873-1889, December.
  • Handle: RePEc:inm:orisre:v:35:y:2024:i:4:p:1873-1889
    DOI: 10.1287/isre.2020.0128
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.2020.0128
    Download Restriction: no

    File URL: https://libkey.io/10.1287/isre.2020.0128?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:inm:orisre:v:35:y:2024:i:4:p:1873-1889. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.