<![CDATA[Purpose: The rapid growth of big data, artificial intelligence, and advanced analytics has transformed Data-Driven Decision Making (DDM) into a strategic capability for contemporary marketing. Despite the increasing volume of research, the literature remains fragmented across multiple disciplines and application domains, limiting a comprehensive understanding of its intellectual development and future directions. Research Method: This study systematically reviews the DDM literature through a PRISMA-guided systematic literature review (SLR) and bibliometric analysis of 426 Scopus-indexed journal articles published between 1993 and 2025. Results and Discussion: The findings identify eight major research clusters: Data-Driven Marketing and Decision Making, Digital Marketing and Artificial Intelligence, Big Data Analytics and Consumer Intelligence, Commerce and Predictive Analytics, Information Management and Machine Learning, Market Segmentation and Customer Analytics, Retail Analytics and Competitive Strategy, and Social Media Analytics. Overlay visualization reveals a clear thematic evolution from early research focused on big data, customer analysis, and market segmentation toward emerging themes such as artificial intelligence, digital marketing, privacy, sustainability, and data-driven strategy. Implications: Building on these findings, the study develops a future research agenda using the Theory–Context–Characteristics–Methodology (TCCM) framework, highlighting opportunities for stronger theoretical foundations, broader contextual applications, greater attention to ethical and sustainability issues, and more sophisticated methodological approaches. Originality: By consolidating the intellectual structure and evolution of DDM research, this study provides a foundation for advancing future scholarship and guiding the strategic application of data-driven marketing practices.]]>
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