The influence of neuromarketing: machine learning based empirical analysis

Abstract

This study attempts to investigate the topic of neuromarketing and how it has be come an emerging topic that might be used as a tool for market research. Both academic writing and real-world marketing are embracing neuromarketing. Addi tionally, it applies brain science to a management setting. It looks after the theoret ical contribution of neuromarketing which comprehends modern consumer response to marketing stimuli. Again, the research in the field of neuromarketing looks at how people’s brains respond to marketing strategies. Researchers use methods like FMRI, EEG and eye tracking to study why consumers may claim to desire one thing but ultimately make choices depending on their feelings. In order to under stand how customers’ bodies, thoughts, emotions and inner selves are engaged in decision making, the research will use neuromarketing strategies. Additionally, it covers the expanding use of neuromarketing across sectors and lists the top neu romarketing firms in each. Also, it analyzes the expanding use of neuromarketing across a range of sectors and lists the top neuromarketing firms currently operating. The study examines the equipment and methods used in neuromarketing, such as eye tracking, galvanic skin reaction, EEG analysis and cognitive analysis. These approaches can be combined to create a comprehensive understanding. That can allow the customers to respond to marketing stimuli. Overall, this study adds to the expanding body of information on neuromarketing that leads to creating interest in this particular area. Besides, it’s potential for use in brand management, advertis ing, and marketing. Explores the potential of EEG technology in neuromarketing which is emphasizing the ethical considerations. It highlights the role of machine learning algorithms. In terms of analyzing consumer responses to marketing stim uli through EEG signals.Through, suggesting the field is on the verge of significant breakthroughs. It focuses on the empirical approaches in neuromarketing applied to food choices. Therefore, it presents a comprehensive approach to predict consumer emotions. Through EEG signal analysis, it can achieve a remarkable accuracy of approximately 96.89% in predicting consumer preferences.