Cover
Volume 7, Special Issue 3 (2026)

Published: July 31, 2026

Pages: 54-65

Research articles

Integrating cognitive signals and machine learning to predict purchasing intent through algorithmic neural marketing

Ali A. Nehme 1
1Imam AL-Kadhim university college, Baghdad, Iraq
History
  • Received: May 12, 2026
  • Revised: June 7, 2026
  • Accepted: July 1, 2026
  • Available Online: July 25, 2026
DOI

https://doi.org/10.56967/ejfb2026861

Abstract

Neuromarketing is an emerging field that combines neuroscience and marketing to better understand the factors influencing consumer decisions. Consumer purchasing behavior has long been a focus for marketers seeking to create compelling advertisements and increase engagement. It relies on objective tools to identify consumer responses through physiological and neurological measurements. This research aims to apply brain science to marketing research, specifically using electroencephalography (EEG) and eye-tracking to determine whether a consumer will purchase a product. “The association between physiological reactions and self-reported purchase intention to marketing cues was investigated by analysing physiological data from 210 participants. The link between the independent factors (product category and advertisement type) and the dependent variable (purchase intention) was investigated using descriptive, correlational, and regression methods. The results confirm that knowledge of neuromarketing significantly boosts practicality (β = 0.726, p < 0.001), which enhances marketing efforts (β = 0.611, p < 0.001) and social media communication effectiveness (β = 0.712, p < 0.001).” The study found that both frontal lobe alpha and beta wave activity (neural reactivity) and fixation duration and number of fixations (visual attention) were strong predictors of purchase intention, with fixation duration being the strongest predictor. Results suggest that emotional advertising elicited greater purchase intention than informational advertising, with the effects of emotion moderated by product category. This research presents evidence for a model that uses EEG and eye-tracking in conjunction to develop insights into consumer behavior. The paper provides an immediately applicable framework for marketers trying to revamp their advertising strategy.

Keywords

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