Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising.

ABSTRACT: The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% o

SUBMITTER: Guixeres J 

PROVIDER: S-EPMC5671759 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature