• Jonas Mathew
• Harsh Kamble
• Mohit Patel
• Sneha Burnase
• Dr. Poonam Sonar

In our research, we propose a practical methodology for product development by integrating electroencephalography (EEG) data with machine learning techniques. EEG signals provide a rich source of neurological data, offering insights into consumer behavior, preferences, and emotional responses to marketing stimuli.Utilizing advanced machine learning algorithms, including support vector machine (SVM), random forest classifier, k-nearest neighbors (KNN), convolutional neural network (CNN), and other classifiers, we aim to process and analyze EEG data to uncover hidden patterns, correlations, and predictive features. Notably, our SVM classifier achieved an accuracy of 98\%, the random forest classifier attained 99\%, the KNN classifier yielded 98\%, and the CNN achieved 99\% accuracy, demonstrating improved performance over prior research.This methodology facilitates a deeper understanding of consumer behavior compared to conventional marketing research methods. Practical applications include refining marketing strategies, product development, and advertising campaigns. By deciphering real-time neural responses, businesses can tailor their marketing efforts more effectively, resulting in increased customer engagement and satisfaction.Moreover, we address ethical considerations and privacy concerns associated with EEG-based neuromarketing, emphasizing the importance of upholding ethical principles and safeguarding data privacy in this evolving field.In summary, our study presents a practical and ethically sound approach to neuromarketing, leveraging EEG signal analysis and machine learning to transform how businesses comprehend and influence consumer behavior, while achieving superior accuracy rates compared to previous approaches.

neuromarketing, electroencephalography, electroencephalogram, machine-learning

"Neuromarketing using EEG signals and Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.o109-o121, April-2024, Available :http://www.jetir.org/papers/JETIR2404F16.pdf

"Neuromarketing using EEG signals and Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppo109-o121, April-2024, Available at : http://www.jetir.org/papers/JETIR2404F16.pdf