Artificial Intelligence Applied to Biometrics in Personalized Digital Marketing: A Systematic Review
Main Article Content
Abstract
The objective of this research was to analyze, through a
systematic literature review, the integration of eye-
tracking, voice analysis, and physiological biometrics
technologies with artificial intelligence algorithms for the
personalization of experiences in digital marketing. The
PRISMA methodology guidelines were followed. Searches
were conducted in Scopus, Web of Science, SciELO, and
Google Scholar, using combinations of keywords and
Boolean operators. Open-access articles published in the
last five years were selected. Of the total identified (n =
8,068), after removing duplicates and screening via
automation and title/abstract, 174 full-text articles were
evaluated; ultimately, 13 studies met the eligibility criteria.
The findings showed that the integration of eye-tracking,
voice analysis, and biometrics with AI improves
segmentation, optimizes creativity, and enables the real-
time personalization of ads using physiological and
behavioral signals. This enhances both the user experience
and campaign efficiency. Furthermore, benefits were
identified in the prediction of attention, brand recognition,
and emotional engagement, along with the ethical and legal challenges related to the handling of biometric data. It is
concluded that the integration of biometric technologies
with AI yields favorable results for the hyper-
personalization of the digital marketing experience;
facilitates the prediction of attention patterns and brand
recognition; and increases customers’ perception of trust
and the emotional effectiveness of campaigns. The study
stands out by framing the impact of these technologies on
emotional personalization, an aspect rarely addressed in
previous reviews. Furthermore, it proposes a critical-
ethical approach that opens new lines of research on trust
and regulation in neuromarketing.
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