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

6533b824fe1ef96bd12800c6

RESEARCH PRODUCT

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

Mariano Alcañiz Raya Enrique Bigné Adrián Colomer Granero Félix Fuentes Hurtado Jaime Guixeres Valeriana Naranjo Ornedo Jose Manuel Ausín Azofra

subject

EXPRESION GRAFICA EN LA INGENIERIA lcsh:BF1-990 Internet privacy Neuromarketing Context (language use)eye tracking Correlation 03 medical and health sciences 0302 clinical medicine TEORIA DE LA SEÑAL Y COMUNICACIONES 0502 economics and business Psychology Neuromarketing Brain response Heart rate variability General Psychology Original Research Eye tracking Artificial neural networks Artificial neural network Recall business.industry YouTube 05 social sciences heart rate variability Online advertising lcsh:Psychology brain response Eye tracking 050211 marketing neuromarketing business Psychology Consumer neuroscience artificial neural networks 030217 neurology & neurosurgery Cognitive psychology

description

[EN] 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% of average accuracy) and estimate the number of online views (mean error of 0.199). The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube.

year	journal	country	edition	language
2017-10-31	Frontiers in Psychology

https://doi.org/10.3389/fpsyg.2017.01808