ABSTRACT
Predictive analytics has emerged as a pivotal tool in modern business strategies, enabling organizations to leverage vast amounts of data to make informed decisions. In this study, we delve into the intricate relationship between Customer Relationship Management (CRM) data and human-centric strategies in predictive analytics. We explore the significance of CRM data as a foundation for predictive modeling and how a human-centric approach can enhance its effectiveness. By examining real-world applications and best practices, we aim to provide insights into the evolving landscape of data-driven modeling in CRM and predictive analytics. Focusing on investigating existing literature, this studyprovides a perspectiveon a body of knowledge on what already exists and then concludes with gaps that need further exploration to further understand the need for human-centricity in predictive analytics modeling. Focusing on key themes of consumer decision-making, consumer segmentation, advertising protocols, and also the notion of proper CRM data collection and management, this researchexposes the synergies between these key factors with recommendations of best practices for more efficient data modeling in this context.
