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Revolutionising consumer engagement through cutting-edge marketing strategies

Krishnabhaskar Mangalasserri et al.

International Journal of Electronic Customer Relationship Management2025https://doi.org/10.1504/ijecrm.2025.148919article
ABDC C
Weight
0.50

What the paper says

Digital marketing is rapidly changing, with new methods using technology to engage consumers replacing old ones. This research study covers cutting-edge marketing tactics that can improve consumer engagement, including artificial intelligence in marketing, data analytics for personalised marketing, and marketing research and practice. This study examines new marketing applications to determine if they improve customer interactions and business success. The paper reviews relevant literature, proposes a rigorous research strategy, and discusses sampling data results. The collected data are based on 500 consumer surveys, 20 individual interviews with marketing professionals, and secondary data comprising industry reports and scholarly articles. The data was analysed using statistical analysis software, AI-driven analytics software, and data visualisation tools. This utilised a robust pool of data to provide a comprehensive overview of consumer engagement with digital marketing and their perspectives on the use of AI and other personalisation methods. The current report concludes by considering the prospects for future marketing and how these concepts can be further advanced as technology continues to evolve.

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Cite this paper

https://doi.org/https://doi.org/10.1504/ijecrm.2025.148919

Or copy a formatted citation

@article{krishnabhaskar2025,
  title        = {{Revolutionising consumer engagement through cutting-edge marketing strategies}},
  author       = {Krishnabhaskar Mangalasserri et al.},
  journal      = {International Journal of Electronic Customer Relationship Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijecrm.2025.148919},
}

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Evidence weight

0.50

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

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
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.