A Neuromarketing Approach to Identify Consumer’s Ties and Preferences Through Multivariate Data

In this paper, we present a study that uses multivariate EEG data through Principal Component Analysis (PCA) to be able to detect consumers’ neural response to functional products and predict their purchase decision. The degree of effectiveness of neuromarketing with respect to the taste preferences of 16 participants, whose ages ranged from 20 to 29 years based on the scores of the samples they evaluated. The authors analyzed 1,291 photos of tasted samples, which represented the subject/panelist’s behavior in terms of like or like. The results suggest that EEG can be a suitable device to assess taste preferences among consumers. Nonetheless, the results in this study show that facial expressions can be important in food preference evaluations because they provide important information complementary to the to the EEG data. Finally, it would be convenient to generate individual nutritional regimens according to the brain activity patterns to start integrating this line of research to the food industry, and, ultimately, offer nutritional support that can contribute to improving the diet of Mexicans and reducing the rate of the most important diseases for Mexico, such as obesity and overweight.