Multivariate Data Analysis of Consumer Behavior of Functional Products: A Neuroscience and Neuromarketing Approach to Improve Decision-Making
DOI:
https://doi.org/10.13053/cys-27-4-4690Keywords:
Brain–Computer Interface (BCI), analysis of EEG signals, neuromarketing, principal component analysis (PCA), functional products, consumer behaviorAbstract
In the functional products market, identifying consumer tastes and preferences is crucial for defining marketing strategies because of its difficult-to-penetrate nature. This article presents a study using multivariate data by means of Principal Component Analysis (PCA) and Electroencephalogram (EEG) to detect consumers' neuronal response to functional products and predict their purchasing decisions. The usefulness of neuromarketing was examined to evaluate the preferences of 16 subjects aged 20 to 29 years, who evaluated a series of samples through the sense of taste. Due to PCA being associated with frontopolar 1 located in the prefrontal cortex, we used PCA to reduce the dimensionality of the data obtained from EEG, finding that the low beta and low gamma frequency bands, along with the percentages of attention and meditation of the panelists, are the main factors in decision making. In addition, we used some digital image processing tools to support the evidence that there is a difference in the brain activity of the panelists when they taste functional products that they like and dislike. This finding can improve our understanding of decision-making and can be used in the food sector to generate a commercial strategy.Downloads
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2023-12-17
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