Neuromarketing and Decision-Making: A Machine Learning Approach Using EEG and Brain Region Analysis

Neuromarketing involves the study of brain responses that focuses on understanding how consumers' brains respond to products and services, and how these responses influence their behavior. One of the most common techniques used in neuromarketing is electroencephalography (EEG), which involves measuring the electrical activity of the brain's surface. This can provide valuable insights into consumer preferences and decision-making processes. The ultimate goal of this study is to assess the relative importance of right/left brain regions (including hemispheres, frontal, temporal, parietal, and occipital lobes) that might be associated with the consumer choice towards E-commerce products using a publicly available neuromarketing dataset. Change in EEG signal has been evaluated using a mixed model for repeated measures for all brain regions. The objective of this study is to build a classification system that can distinguishes the EEG characteristics of consumers' preferences between like and dislike based on different classifiers.

Neuromarketing

Decision-Making

Consumer Preference

Change in EEG signal

Classification

Mixed Model for Repeated Measures 

Expert

Machine Learning

Symposium on Data Science and Statistics (SDSS) 2023