A Smart Ad Display System

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.

History: Ravi Bapna, Senior Editor; Jason Chan, Associate Editor.

Funding: This work was supported by the National Natural Science Foundation of China [Grants 72072037 and 72132008].

Supplemental Material: The e-companion is available at https://doi.org/10.1287/isre.2020.0128.