This review uses an integrated bibliometric-LDA analysis of 341 publications (2008–2025) to summarize two decades of neuromarketing research within the domain of consumer behavior. The bibliometric mapping shows an exponential increase in publications after 2015 with a thematic shift from fundamental cognitive neuroscience to the incorporation of machine learning and artificial intelligence for predictive consumer analytics. Latent Dirichlet Allocation is used to identify five dominant and cohesive research streams: (1) Eco-Neural Analytics which uses EEG to decipher subconscious drivers of sustainable consumption (2) The Visual Gaze which integrates eye-tracking and neural metrics in digital branding (3) Cognitive Foundations which synthesizes theoretical and review-based literature (4) Neural Intelligence which uses AI to predict consumer choice in real-time from brain signals and (5) Behavioral Neuro-Nexus which connects neuroscientific methods with traditional marketing research. The results show how an emerging multidisciplinary field is moving from laboratory observation to intelligent predictive and ecologically valid applications. By filling in important gaps in theoretical integration and practical application this structured taxonomy offers a unified framework to direct future studies at the intersection of consumer behavior neuroscience and intelligent marketing systems.
Bashar et al. (Sun,) studied this question.