A review on the use of eeg for the investigation of the factors that affect Consumer’s behavior

Panteli, Antiopi; Kalaitzi, Eirini; Fidas, Christos A.

doi:10.1016/j.physbeh.2024.114509

Physiology & Behavior

2024

DOI: 10.1016/j.physbeh.2024.114509

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A review on the use of eeg for the investigation of the factors that affect Consumer’s behavior

Antiopi Panteli,

Eirini Kalaitzi,

Christos A. Fidas

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Cited by 2 publications

References 114 publications

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Predicting consumer ad preferences: Leveraging a machine learning approach for EDA and FEA neurophysiological metrics

Marques,

Neto,

Silva

et al. 2024

Psychology and Marketing

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This research unveils to predict consumer ad preferences by detecting seven basic emotions, attention and engagement triggered by advertising through the analysis of two specific physiological monitoring tools, electrodermal activity (EDA), and Facial Expression Analysis (FEA), applied to video advertising, offering a twofold contribution of significant value. First, to identify the most relevant physiological features for consumer preference prediction. We integrated a statistical module encompassing inferential and exploratory analysis tools, which identified emotions such as Joy, Disgust, and Surprise, enabling the statistical differentiation of preferences concerning various advertisements. Second, we present an artificial intelligence (AI) system founded on machine learning techniques, encompassing k‐Nearest Neighbors, Support Vector Machine, and Random Forest (RF). Our findings show that the RF technique emerged as the top performer, boasting an 81% Accuracy, 84% Precision, 79% Recall, and an F1‐score of 81% in predicting consumer preferences. In addition, our research proposes an eXplainable AI module based on feature importance, which discerned Attention, Engagement, Joy, and Disgust as the four most pivotal features influencing consumer ad preference prediction. The results indicate that computerized intelligent systems based on EDA and FEA data can be used to predict consumer ad preferences based on videos and effectively used as supporting tools for marketing specialists.

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Predicting consumer ad preferences: Leveraging a machine learning approach for EDA and FEA neurophysiological metrics

Marques,

Neto,

Silva

et al. 2024

Psychology and Marketing

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Neuromarketing as a Mechanism of Communication with the Consumer: The Case for Small Business

Chygryn,

Shevchenko,

Tuliakov

2024

MMI

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Neuromarketing is a modern tool for researching consumer reactions to advertising stimuli and identifying relevant consumer behaviour patterns. Conducting neuromarketing research using eye tracking technology allows us to obtain objective data on consumer perceptions of advertising, websites, product packaging, etc. This article is devoted to studying the structural and content environment of the marketing category and neuromarketing research on advertised materials via the eye-tracking method. The analysis of publishing activity on the topic of neuromarketing carried out with the help of Scopus tools and the VOSviewer toolkit showed a trend of increasing interest from the scientific community in the use of neurotechniques and technologies in the study of consumer behaviour since 2004. The results of the analysis of the structural and content environment have shown the growing interest of scientists in the detailed study of consumer reactions to a product, brand, site, and advertisement, with further conclusions regarding their preferences and priorities. The work revealed that in the field of neuromarketing, there are methods that can be conditionally divided into those that register activity in the brain (neurological) and those that register activity outside the brain (biometric). The characteristics of these methods make it possible to choose the most appropriate method of eye tracking for evaluating consumers’ reactions to advertising posters. Pupil Labs Invisible mobile eyetracker was used as the main tool for neuromarketing research. According to the results of the two stages of the experiment, heatmaps were obtained, which are described by the key metrics of the study: fixations and points of view, heatmaps, areas of interest, and time spent. With the help of research, the most profitable designs of advertising posters for consumers were determined. The influence of different colors and their combinations on the brain activity of potential consumers was analysed. As a result, a conclusion was made regarding the optimal placement of such key elements on the poster as the logo, and the price, the colour range of the presented materials and the fonts that were used were determined. The application of the obtained results of marketing research made it possible to obtain information about how consumers perceive visual stimuli, which, in the future, will be the basis for perfecting marketing communication strategies with the target audience of consumers.

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A review on the use of eeg for the investigation of the factors that affect Consumer’s behavior

Cited by 2 publications

References 114 publications

Predicting consumer ad preferences: Leveraging a machine learning approach for EDA and FEA neurophysiological metrics

Predicting consumer ad preferences: Leveraging a machine learning approach for EDA and FEA neurophysiological metrics

Neuromarketing as a Mechanism of Communication with the Consumer: The Case for Small Business

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