Abstract—This paper provides a comprehensive academic review of how machine learning (ML) is leveraged for predictive analytics within big data-driven marketing strategies. It defines the foundational concepts of ML, predictive analytics, and big data, elucidating their synergistic relationship in modern marketing. The report explores key applications, including advanced customer segmentation, precise churn prediction, hyper-personalized recommendations, and optimized campaign management, supported by illustrative case studies. Furthermore, it critically examines the inherent challenges such as data quality, model interpretability, privacy concerns, and algorithmic bias. Finally, the paper discusses emerging trends and future research directions, including Explainable AI (XAI), Causal AI, Multimodal AI, and responsible AI frameworks, underscoring the transformative potential and strategic imperative for businesses to navigate this evolving landscape 1, 2. Keywords—Algorithmic bias, Big data, Campaign optimization, Causal AI, Churn prediction, Customer lifetime value, Customer segmentation, Deep learning, Explainable AI, Machine learning, Marketing strategies, Multimodal AI, Personalized recommendations, Predictive analytics, Privacy-preserving machine learning, Responsible AI.
Rakesh Kumar Saini (Tue,) studied this question.