| Neuro-Marketing Insights: Assessing Cognitive Engagement and Advertising Effectiveness in Esports Using EEG Analysis |
| Paper ID : 1295-SPORTCONGRESS |
| Authors |
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zahra asgari gandomani1, Sajjad abdolahi *2, alireza elahi3 11. PhD in Sports Management, University of Kharazmi Tehran, Tehran, Iran 2PhD Candidate, Department of Sport biomechanics, Faculty of Sports Sciences, Bu-Ali Sina University, Hamedan, Iran 3Associate Professor in Sport Management, Kharazmi University, Tehran, Iran |
| Abstract |
| Introduction: The rapid evolution of esports has created a new frontier for sports management and digital marketing, where audience engagement and brand interaction are mediated by complex neurocognitive processes. Understanding how players and spectators respond to digital advertising within competitive gaming environments is essential for developing data-driven management strategies. This study applies artificial intelligence–based EEG analysis to evaluate advertising effectiveness and cognitive engagement in esports, providing actionable insights for sport managers and marketing professionals. Methods: Thirty experienced esports participants (aged 18–30) were exposed to a series of branded video stimuli during professional-level gameplay scenarios. Electroencephalography (EEG) signals were recorded from frontal and parietal regions to measure neural indices of attention, motivation, and mental workload. The data were processed using Fast Fourier Transform (FFT) to extract power spectral density features in the alpha, beta, and gamma frequency bands. These features were then analyzed through machine learning classifiers—specifically Random Forest and Support Vector Machine (SVM)—to predict advertising recall and engagement level. Results: The Random Forest model achieved 88.6% classification accuracy (AUC = 0.912) in distinguishing high-engagement from low-engagement advertising stimuli, while the SVM reached 85.2% accuracy. Increased beta and gamma activity was significantly correlated (p < 0.01) with higher ad recall and positive affective response, indicating elevated cognitive engagement. These findings validate EEG as a reliable tool for quantifying consumer responses within digital sports ecosystems. Conclusion: Integrating AI-driven neuroanalytics into sports management offers a novel, objective framework for evaluating advertising effectiveness and audience engagement in esports. The proposed model enhances decision-making for marketers and event organizers by linking neural data to behavioral outcomes, contributing to the advancement of intelligent management systems in the global esports industry. |
| Keywords |
| Artificial Intelligence, EEG, Neuro-marketing, Esports, Cognitive Engagement |
| Status: Abstract Accepted (Oral Presentation) |
