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All Journal Annals of Management and Organization Research
Chikwesiri, Nwachukwu Peter
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Economics, Econometrics & Finance

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Journal : Annals of Management and Organization Research

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Artificial Intelligence Personalized Marketing Content and Consumer Behavior in Nigerian SMEs Nnanna-Ohuonu, Okwudiri; Chikwesiri, Nwachukwu Peter; Okudo, Amarachukwu; Chikwesiri, Izuka Vivian
Annals of Management and Organization Research Vol. 7 No. 3 (2026): February
Publisher : goodwood publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/amor.v7i3.3418

Abstract

Purpose: This study examined how AI-driven personalization of digital marketing content influences consumer behavior in Nigerian Small and Medium Enterprises (SMEs). Research Methodology: A Systematic Literature Review (SLR) of 30 empirical studies published between 2015 and 2025 was performed. Data were sourced from peer-reviewed journal articles, conference papers, review studies, and industry reports that specifically examined AI-driven personalized marketing tools, particularly, product recommendation systems. Results: The findings indicate that 60% of the reviewed studies reported moderate-to-high adoption of AI-driven personalized recommendation systems among digitally mature Nigerian SMEs in the retail and e-commerce sectors. Across studies, AI-enabled personalization produced an average 15.8% increase in consumer purchase intention, with a strong mean correlation (r = 0.60) between personalized product recommendations and purchase intentions. Conclusions: AI-driven personalization significantly improves marketing effectiveness and positively shapes consumer purchase intentions in Nigerian SMEs. Limitations: The exclusive use of secondary data and SLR-based synthesis limits the generalizability and real-time assessment of AI adoption and its impact on consumer behavior. Contributions: This study consolidates empirical evidence on AI-personalized marketing in Nigerian SMEs, highlighting its impact on consumer purchase intention, while underscoring the need to address adoption barriers and ensure ethical data practices.
Co-Authors Chikwesiri, Izuka Vivian Nnanna-Ohuonu, Okwudiri Okudo, Amarachukwu