Authors: Santhosh Reddy BasiReddy
Abstract: Customer Relationship Management (CRM) systems have evolved from simple data repositories into complex enterprise platforms that support decision making, automation, and customer engagement across multiple business functions. Despite these advances, most CRM architectures remain constrained by relational data models that limit contextual awareness, restrict flexible relationship exploration, and hinder real time insight generation. This paper examines the embedding of knowledge graphs within CRM systems as an approach to enabling semantic data integration, dynamic relationship discovery, and real time analytics over customer and enterprise data. Drawing on established research in semantic networks, enterprise knowledge graphs, and graph traversal models, the study outlines an architectural perspective for incorporating knowledge graphs into CRM platforms. The proposed approach illustrates how graph-based representations can enhance operational intelligence, improve contextual decision support, and support adaptive; insight driven CRM workflows in enterprise environments.
DOI: http://doi.org/10.5281/zenodo.18014115
