Data-Driven Decision-Making in Marketing

Data-driven decision-making (DDDM) has emerged as a transformative force in marketing, enabling organizations to leverage data analytics, artificial intelligence, and big data to enhance customer engagement and gain a competitive edge. This study investigates the potential of DDDM to optimize personalization, predict consumer behaviour, and align marketing strategies with sustainability and innovation goals. Researchers conducted a systematic literature review and analyzed case studies to explore how industries integrate DDDM practices. The research examined practical applications, identified key challenges, and assessed emerging marketing analytics and decision-making trends. The findings demonstrate that DDDM enhances marketing precision and operational efficiency, significantly improving customer segmentation, campaign effectiveness, and lifetime value management. Additionally, the study identifies challenges such as data privacy concerns, ethical considerations, and the complexity of integrating diverse data sources across omnichannel platforms. The study proposes strategies for balancing automation with human creativity and ensuring ethical data use. DDDM holds transformative potential for the marketing domain, fostering innovation and long-term value creation. Aligning DDDM practices with organizational goals and ethical standards is essential for sustainable success. This study offers a comprehensive framework and actionable insights for academics and practitioners to harness the full potential of data-driven approaches.