Intelligent Marketing Management: A Bibliometric Analysis of AI-Driven Technologies in Marketing

Wahyudin Rahman; Sutrisno Djawa

doi:10.37641/jimkes.v13i6.3940

Authors

Wahyudin Rahman Universitas Muhammadiyah Luwuk, Indonesia
Sutrisno Djawa Universitas Muhammadiyah Luwuk, Indonesia

DOI:

https://doi.org/10.37641/jimkes.v13i6.3940

Keywords:

Artificial Intelligence, Bibliometric, Intelligent Marketing, Machine Learning, Natural Language Processing

Abstract

The integration of AI-based technologies, such as machine learning and natural language processing, is crucial for intelligent marketing management. This study explores market intelligence, encompassing marketing insights, alliance-centric focus, services, and marketing transformation to address dynamic consumer preferences and technological advancements. This study examines the application of AI in marketing through bibliometric analysis and evaluates the effectiveness of market intelligence components. The method used was a comprehensive bibliometric analysis using performance metrics and science mapping conducted on publications from the Scopus and Web of Science databases (2020–2024), using VOSviewer for network visualization. The findings revealed that a total of 9,067 papers from 63 countries were published between 2022 and 2024, with the largest contribution from the United States. Publications were categorized as mathematical modeling (18.9%), exploratory (16.5%), conceptual (17.3%), theoretical review (20.8%), case study (13.8%), and simulation (12.5%). Between 2020 and 2022, 254 articles were identified, highlighting the role of AI in hyperpersonalization, predictive analytics, and chatbots. AI improves marketing efficiency and personalization, but requires an integrated framework for adoption. Future research should focus on industry-specific AI implementations to address barriers such as ethical issues and technology adoption.

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