AUTHOR=Höfling T. Tim A. , Alpers Georg W. 

TITLE=Automatic facial coding predicts self-report of emotion, advertisement and brand effects elicited by video commercials

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 17 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2023.1125983

DOI=10.3389/fnins.2023.1125983

ISSN=1662-453X

ABSTRACT=Consumers' emotional responses are the prime target for marketing commercials. Facial expressions provide information about a person's emotional state and technological advances have enabled machines to automatically decode them. With automatic facial coding we investigated the relationships between facial movements (i.e., action unit activity) and self-report of emotional responses to video advertisements, ad likeability, brand likeability, and purchase intention of a particular brand. We recorded and analyzed the facial responses of 219 participants while they watched a broad array of advertisements. Facial expressions significantly predicted self-report of emotion as well as branding effects. Interestingly, facial expressions had incremental value beyond self-report of emotion in the prediction of branding effects. Hence, automatic facial coding appears to be useful as a non-verbal quantification of advertisement effects beyond self-report. This is the first study to measure a broad spectrum of automatically scored facial responses to commercials. Automatic facial coding is a promising non-invasive and non-verbal fashion method to measure emotional responses in marketing.