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Updates in the evolution of AI-driven digital marketing practices: a literature review with bibliometric analysis

Mohammad Faruk et al.

International Journal of Technology Marketing2025https://doi.org/10.1504/ijtmkt.2025.147357review
AJG 1ABDC C
Weight
0.37

What the paper says

This study aims to present an update on the evolution of AI-driven digital marketing practices by determining the thematic development and identifying research clusters that have been developed over time. Adopting an objectivist research philosophy, this study employs the bibliometric analysis method on 206 identified research papers from the Scopus database based on the PRISMA framework from 2000 to 2024. The findings identify that the most contributing author is Dwivedi, while the Journal of Business Research is the most contributing journal and the USA is the most contributing country in the research related to AI-driven digital marketing practices. Furthermore, the findings reveal that the research in AI-driven digital marketing practices is grouped into four clusters. In addition, the evolutionary trends are moving toward integrating the Metaverse and generative AI in digital marketing practices for providing immersive (phygital) experiences to customers and building competitive advantage, leading to an exponential growth of research on these topics. This study contributes to the existing knowledge by providing updated AI-driven digital marketing practices in nine categories.

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https://doi.org/https://doi.org/10.1504/ijtmkt.2025.147357

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@article{mohammad2025,
  title        = {{Updates in the evolution of AI-driven digital marketing practices: a literature review with bibliometric analysis}},
  author       = {Mohammad Faruk et al.},
  journal      = {International Journal of Technology Marketing},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijtmkt.2025.147357},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.