Abstract: Marketing campaigns that promote and market various consumer products are a well-known strategy for increasing sales and market awareness. This simply means the profit of a manufacturing unit would increase. "Neuromarketing" refers to the use of unconscious mechanisms to determine customer preferences for decision-making and behavior prediction. In this work, a predictive modeling method is proposed for recognizing product consumer preferences to online (E-commerce) products as “Likes” and “Dislikes”. Volunteers of various ages were exposed to a variety of consumer products, and their EEG signals and product preferences were recorded. Artificial Neural Networks and other classifiers such as Logistic Regression, Decision Tree Classifier, K-Nearest Neighbors, and Support Vector Machine were used to perform product-wise and subject-wise classification using a user-independent testing method. Though, the subject-wise classification results were relatively low with artificial neural networks (ANN) achieving 50.40 percent and k-Nearest Neighbors achieving 60.89 percent. Furthermore, the results of product-wise classification were relatively higher with 81.23 percent using Artificial Neural Networks and 80.38 percent using Support Vector Machine.

Asad Ullah, Gulsher Baloch, Ahmed Ali, Abdul Baseer Buriro, Junaid Ahmed, Bilal Ahmed and Saba Akhtar, “Neuromarketing Solutions based on EEG Signal Analysis using Machine Learning” International Journal of Advanced Computer Science and Applications(IJACSA), 13(1), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130137

@article{Ullah2022,
title = {Neuromarketing Solutions based on EEG Signal Analysis using Machine Learning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130137},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130137},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {1},
author = {Asad Ullah and Gulsher Baloch and Ahmed Ali and Abdul Baseer Buriro and Junaid Ahmed and Bilal Ahmed and Saba Akhtar}
}