ArticleFrontiers in psychology2017
Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising.
Article in Frontiers in psychology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Is EEG Suitable for Marketing Research? A Systematic Review.Frontiers in neuroscience · 2020Pooled it
- Adolescents' spontaneous recall of food and beverage advertisements on digital media: a cross-sectional survey in Montevideo, Uruguay.Public health nutrition · 2025Article
- The Neuroscience of Marketing: Noninvasive Neuromarketing Methods for Understanding Consumer Choice and Priorities.F1000Research · 2025Review
- A systematic review on EEG-based neuromarketing: recent trends and analyzing techniques.Brain informatics · 2024Review
- A Bibliometric Analysis of Consumer Neuroscience towards Sustainable Consumption.Behavioral sciences (Basel, Switzerland) · 2023Review
- DeePay: deep learning decodes EEG to predict consumer's willingness to pay for neuromarketing.Frontiers in human neuroscience · 2023Article
- Accurately predicting hit songs using neurophysiology and machine learning.Frontiers in artificial intelligence · 2023Article
- Article
- Central EEG Beta/Alpha Ratio Predicts the Population-Wide Efficiency of Advertisements.Brain sciences · 2022Article
- Consumer Behaviour to Be Considered in Advertising: A Systematic Analysis and Future Agenda.Behavioral sciences (Basel, Switzerland) · 2022Review
- A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research.Brain informatics · 2022Review
- What to Believe? Impact of Knowledge and Message Length on Neural Activity in Message Credibility Evaluation.Frontiers in human neuroscience · 2021Article
- Do You See What I See? Effectiveness of 360-Degree vs. 2D Video Ads Using a Neuroscience Approach.Frontiers in psychology · 2021Article
- A Literature Review of EEG-Based Affective Computing in Marketing.Frontiers in psychology · 2021Review
- Neuroergonomic Assessment of Hot Beverage Preparation and Consumption: An EEG and EDA Study.Frontiers in human neuroscience · 2020Article
- Whom to Believe? Understanding and Modeling Brain Activity in Source Credibility Evaluation.Frontiers in neuroinformatics · 2020Article
- Picking Your Brains: Where and How Neuroscience Tools Can Enhance Marketing Research.Frontiers in neuroscience · 2020Review
- Consumers Emotional Responses to Functional and Hedonic Products: A Neuroscience Research.Frontiers in psychology · 2020Article
- Neuromarketing as an Emotional Connection Tool Between Organizations and Audiences in Social Networks. A Theoretical Review.Frontiers in psychology · 2020Review
- Individual EEG measures of attention, memory, and motivation predict population level TV viewership and Twitter engagement.PloS one · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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% 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.