The DOI matches its Crossref record; 96 of the 96 references it cites were found in a registry or an index.
Using Data Sciences in Digital Marketing: Framework, methods, and performance metrics
Open accessAbstract
In the last decade, the use of Data Sciences, which facilitate decision-making and extraction of actionable insights and knowledge from large datasets in the digital marketing environment, has remarkably increased. However, despite these advances, relevant evidence on the measures to improve the management of Data Sciences in digital marketing remains scarce. To bridge this gap in the literature, the present study aims to review (i) methods of analysis, (ii) uses, and (iii) performance metrics based on Data Sciences as used in digital marketing techniques and strategies. To this end, a comprehensive literature review of major scientific contributions made so far in this research area is undertaken. The results present a holistic overview of the main applications of Data Sciences to digital marketing and generate insights related to the creation of innovative Data Mining and knowledge discovery techniques. Important theoretical implications are discussed, and a list of topics is offered for further research in this field. The review concludes with formulating recommendations on the development of digital marketing strategies for businesses, marketers, and non-technical researchers and with an outline of directions of further research on innovative Data Mining and knowledge discovery applications.
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Cited by
Lin, X., Suanpong, K., Ruangkanjanases, A., Lim, Y.-T., & Chen, S.-C. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.634911 · Cited by 38
Yoo, J. J., Kim, H., & Choi, S. (2024) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2024.100616 · Cited by 22
Metadata
- Authors
- Saura, J. R.
- Venue
- Journal of Innovation & Knowledge
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 6
- Issue
- 2
- Pages
- 92-102
- ISSN
- 2444-569X (ISSN-L)
- OpenAlex
- W3049122368
- Cited by
- 473
- References
- 96
- FWCI
- 96.18
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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