INVESTMENT OF BIOMEDICAL APPLICATIONS IN MARKETING: ELECTROENCEPHALOGRAM-BASED CONSUMER DECISION PREDICTION

Abstract

The neuroscience field provides extensive knowledge regarding cerebral activity principles. Therefore, it enables congregating consumer information and anticipating its preferences. Unlike classical marketing techniques, for instance, interviews with consumers, in which they usually do not communicate their real preferences, biomedical methodologies provide more powerful tools such as electroencephalogram signals and brain imaging, to explore the activity within the brain and examine its miscellaneous responses, which contribute efficiently to understanding human behavior related to its purchasing decision-making. Aiming to highlight the impact of neuroscience on marketing advancement, we first present in this paper a thoughtful background based on state-of-the-art studies to investigate the rate of several neurology techniques’ contribution to the advancement of the marketing field and their effect on purchasing decision-making. Second, we propose a predictive modeling framework based on the analysis of EEG signals recorded during decision-making in terms of “like” or “dislike” of specific consumer products. The discrete wavelet transform (DWT) and kNN classifier were combined to develop such an automated model. For evaluation purposes, the developed model was performed on a well-known and public EEG dataset collected for marketing studies. Achieving promising results confirms that the developed framework can be used as a reliable tool for market strategy development.