Artificial Intelligence and Marketing Strategies: Systematic Insights on Predictive Analytics, Segmentation, and Personalization

  • Authors

    • Rey Y. Capangpangan Graduate School of Business, University of the Visayas, Jakosalem St., Cebu City, Philippines and College of Fisheries and Marine Sciences, Mindanao State University at Naawan, Poblacion, Naawan, Misamis Oriental, Philippines
    • Arnold C. Alguno Graduate School of Business, University of the Visayas, Jakosalem St., Cebu City, Philippines and College of Engineering, Mindanao State University-Iligan Institute of Technology, Iligan City, Philippines
    • Yuri U. Pendon Graduate School of Business, University of the Visayas, Jakosalem St., Cebu City, Philippines
    • Rosemarie Cruz-Español Graduate School of Business, University of the Visayas, Jakosalem St., Cebu City, Philippines
    https://doi.org/10.14419/negfns98

    Received date: September 10, 2025

    Accepted date: October 23, 2025

    Published date: November 2, 2025

  • artificial intelligence, marketing, predictive analytics, customer segmentation, personalization, strategies

  • Abstract

    Although artificial intelligence (AI) has become a powerful driver of innovation in marketing, existing research often treats its applications in predictive analytics, customer segmentation, and personalization as fragmented domains. This lack of integration limits a comprehensive understanding of how AI can shape modern marketing strategies. To address this gap, this study conducted a systematic review of 20 peer-reviewed articles published between 2020 and 2025, following PRISMA guidelines. Bibliometric techniques and thematic content analysis were employed to identify intellectual structures, citation patterns, and emerging research themes. The analysis revealed four thematic clusters: (1) AI for personalization and customer relationship management (CRM), (2) predictive analytics and strategic marketing, (3) global and supply chain applications of AI, and (4) bibliometric and conceptual foundations. Keyword and trend mapping highlighted dominant themes such as machine learning and customer behavior, while new areas of interest—including emotion AI, federated learning, and AI ethics—are gaining prominence. This review not only synthesizes dispersed literature but also provides a roadmap for future research, emphasizing explainable AI, adaptive models, ethical governance, and interdisciplinary collaboration to support responsible and innovative AI adoption in marketing.

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  • How to Cite

    Capangpangan, R. Y. ., Alguno, A. C. ., Pendon, Y. U. ., & Cruz-Español, R. (2025). Artificial Intelligence and Marketing Strategies: Systematic Insights on Predictive Analytics, Segmentation, and Personalization. International Journal of Basic and Applied Sciences, 14(7), 58-68. https://doi.org/10.14419/negfns98