Leveraging Big Data Analytics for Understanding Consumer Behavior in Digital Marketing: A Systematic Review
Open accessAbstract
The integration of big data analytics in digital marketing has fundamentally transformed how organizations understand and influence consumer behavior. This systematic review explores the potential of big data to offer deep insights into consumer preferences and behaviors. The current literature on big data and consumer behavior showcases its potential in enhancing marketing and customer experiences. However, significant gaps exist, such as longitudinal studies on how continuous big data–driven personalization affects consumer trust and loyalty over time. Addressing these gaps will advance academic understanding and offer practical insights for optimizing marketing strategies and improving customer experiences ethically. Focusing on these areas will contribute to a holistic view of big data’s responsible use in digital marketing. By utilizing large datasets, businesses can now tailor their marketing strategies to individual consumers, enhancing customer satisfaction and engagement. Adopting the PRISMA methodology, this review synthesizes recent literature to evaluate the benefits of big data in digital marketing. The research was conducted through a rigorous five‐stage process, encompassing the identification of key research questions, database searches, and the critical analysis of selected articles: (1) defining the initial topic, (2) developing the appropriate research questions, (3) identifying the necessary keywords, (4) identifying and searching databases, and finally (5) accessing and reading the articles. The databases that were searched were as follows: Scopus, Web of Science, Emerald Insight, Springer Link, and ScienceDirect. The articles that were selected were 19, in a total sum of 265 identified articles. The findings consolidate current knowledge on how big data analytics can optimize marketing strategies and consumer experiences. Ultimately, this review underscores the transformative potential of big data in digital marketing, highlighting its role in enhancing customer insights and driving more effective marketing strategies.
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Gartner estimates annual losses of USD 12.9 million per organization, while IBM reports that U.S. businesses lose over USD 3.1 trillion annually.
“Gartner estimates annual losses of USD 12.9 million per organization, while IBM reports that U.S. businesses lose over USD 3.1 trillion annually[67-70].”
From Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles (2025) · cites this paper as [70]
Cites
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The use of machine learning algorithms in recommender systems: a systematic review
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Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles
Guillen-Aguinaga, M., Aguinaga-Ontoso, E., Guillen-Aguinaga, L., Guillen-Grima, F., & Aguinaga-Ontoso, I. (2025) · Data · doi:10.3390/data10120201 · Cited by 37 · see citing works
- Authors
- Theodorakopoulos, L., & Theodoropoulou, A.
- Affiliations
- University of Patras (GR)
- Corresponding author
- Theodorakopoulos, Leonidas
- Venue
- Human Behavior and Emerging Technologies
- Publisher
- Wiley
- Published
- 2024-01
- Volume
- 2024
- Issue
- 1
- ISSN
- 2578-1863 (ISSN-L)
- OpenAlex
- W4403706662
- Cited by
- 153
- References
- 10
- Citations by year
- 2026: 60 · 2025: 84 · 2024: 9
- FWCI
- 15.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Human Behavior and Emerging Technologies (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Keywords
- big data analytics, consumer behavior, digital marketing, personalization, customer experience, consumer trust, customer loyalty, marketing strategy, data ethics, customer satisfaction
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