Artikel

Using Data Sciences in digital marketing: Framework, methods, and performance metrics

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.

Language
Englisch

Bibliographic citation
Journal: Journal of Innovation & Knowledge (JIK) ; ISSN: 2444-569X ; Volume: 6 ; Year: 2021 ; Issue: 2 ; Pages: 92-102 ; Amsterdam: Elsevier

Classification
Management
IT Management
Marketing
Subject
Data Mining
Data Sciences
Digital Marketing
Knowledge discovery
Literature review

Event
Geistige Schöpfung
(who)
Saura, José Ramón
Event
Veröffentlichung
(who)
Elsevier
(where)
Amsterdam
(when)
2021

DOI
doi:10.1016/j.jik.2020.08.001
Handle
Last update
10.03.2025, 11:46 AM CET

Data provider

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Saura, José Ramón
  • Elsevier

Time of origin

  • 2021

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