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In this paper, we present the first bibliometric analysis of the use of machine learning (ML) in marketing: namely, the growth, trends, and impact of this disruptive technology from 2010 to 2025. Based on Scopus database, this study assesses the progress of ML in marketing research with a focus on research output trends among selected publishers and top authors, institutions, and countries. Our results show strong growth in ML research, especially post-2015, spurred by increases in compute power, accessibility of large datasets and the invention of powerful algorithms. The results highlight the globalization of ML research, with substantial contributions from the U.S., China and India. Important types of research are customer segmentation, predictive analytics, and personalized marketing. The findings of this study serve as a useful reference for researchers, marketers, and policymakers alike; Provides a foundation for further research on how the current challenges in marketing can be addressed using ML techniques.

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Machine Learning in Marketing: A Bibliometric Analysis of Trends, Applications, and Future Directions

  • 章节

  • 发表日期：

    2026年

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  • Anber Abraheem Shlash Mohammad,
  • Suleiman Ibrahim Shelash Mohammad,
  • Asokan Vasudevan,
  • Khaleel Ibrahim Al-Daoud,
  • Sharmila Devi Ramachandaran,
  • Anas Y. AlHadid,
  • Manal Mizher,
  • Ammar Salah,
  • Muhamad Saufi Che Rusuli

摘要

In this paper, we present the first bibliometric analysis of the use of machine learning (ML) in marketing: namely, the growth, trends, and impact of this disruptive technology from 2010 to 2025. Based on Scopus database, this study assesses the progress of ML in marketing research with a focus on research output trends among selected publishers and top authors, institutions, and countries. Our results show strong growth in ML research, especially post-2015, spurred by increases in compute power, accessibility of large datasets and the invention of powerful algorithms. The results highlight the globalization of ML research, with substantial contributions from the U.S., China and India. Important types of research are customer segmentation, predictive analytics, and personalized marketing. The findings of this study serve as a useful reference for researchers, marketers, and policymakers alike; Provides a foundation for further research on how the current challenges in marketing can be addressed using ML techniques.