NeuroAd: EEG-Driven AI for Ad Engagement Prediction

Abstract

NeuroAd is a web-based platform designed to objectively evaluate advertisement engage ment by analyzing brainwave data captured from viewers using a 14-channel EMOTIV EPOC headset. The platform processes EEG signals to extract cognitive and emotional engagement indicators from frequency-based features, which are then classified using a Random Forest machine learning model to label advertisements as engaging or non engaging with high accuracy. By measuring subconscious neural responses in real time, NeuroAd addresses the limitations of traditional survey-based marketing research. It offers a secure, role-based web interface where authorized users can upload EEG datasets, run engagement analyses, and access detailed interactive reports. By combining neuroscience, advanced data processing, and web technologies, NeuroAd provides an accessible, scal able, and cost-effective neuromarketing solution that enables advertisers to design more impactful advertisements based on real neural activity rather than subjective feedback.