Data-Driven Insights with Predictive Marketing Analysis
A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 391
Special Issue Editors
Interests: marketing; knowledge management; intellectual capital
Interests: sustainability; data science; digital transformation; competitive strategy; competitive dynamics; strategic groups; marketing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In today's dynamic and highly competitive market environment, organizations are increasingly relying on data-driven decision making to gain actionable insights and optimize their marketing strategies. The integration of advanced analytical techniques, artificial intelligence, and big data technologies has revolutionized the way businesses approach customer segmentation, campaign management, and performance evaluation. This Special Issue aims to explore how systems thinking can enhance the effectiveness of marketing analytics by considering the complex interdependencies between data sources, customer behavior, and business objectives. The Issue welcomes contributions that emphasize the holistic and interconnected nature of marketing systems, addressing challenges such as data integration, real-time decision making, and ethical considerations. By bringing together perspectives from systems theory, decision science, and marketing analytics, this Issue seeks to provide valuable insights for academics and practitioners looking to leverage data-driven approaches in their marketing strategies.
Dr. Rui Nunes Cruz
Dr. Albérico Travassos Rosário
Guest Editors
Manuscript Submission Information
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Keywords
- marketing analytics systems
- data-driven decision making
- artificial intelligence in marketing
- complex adaptive systems in marketing
- systems thinking in marketing strategy
- customer data integration
- predictive analytics for marketing
- decision support systems for marketing
- business intelligence and marketing performance
- ethical considerations in data-driven marketing
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