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Advisor(s)
Abstract(s)
This study assesses how Data-Driven Decision-Making (DDDM) impacts marketing practices and research. Using the PRISMA 2020 protocol, this research conducted systematic
reviews of 94 peer-reviewed articles and utilized bibliometric and thematic analyses. From this, four major themes emerged: improvement in the customer experience via the personalization of marketing; marketing driven by innovation through data resource versatility, Machine Learning, analytics, and Artificial Intelligence; performance enhancement through the optimal allocation of resources; and the data governance and ethical use of such resources, and the use of such data resources. This study illustrates how the combination of multi-level theory and methodical stricture accounts for the systemic influence of DDDM in marketing. This study adds to these theories by proposing a cohesive and synthesized understanding of the interplay of the technological, organizational, and governance elements in data-driven marketing. This research provides organizations with actionable guidance aimed at increasing effective analytics-driven decision-making, while also ensuring the responsible use of data.
Description
Keywords
Data-driven decision-making Marketing Systematic literature review Bibliometric analysis PRISMA Systemic framework
Pedagogical Context
Citation
Cruz, R. N., & Rosário, A. T. (2025). Data-driven decision-making in marketing: a systematic literature review of emerging themes and research gaps. Systems, 13(12), 1114. https://doi.org/10.3390/systems13121114
