International Journal of Management

Global enterprises collect both online and offline customer data—from digital footprints, CRM systems, IoT devices, retail transactions, and physical interactions. However, siloed data sources create fragmented customer insights, weak decision-making, and inaccurate personalization. This research examines frameworks, technologies, and governance models used to integrate offline and online data streams across international markets. Using case studies, system architecture analysis, and interviews with data engineers across nine multinational companies, the study identifies technical challenges including interoperability, latency, identity mapping, regulatory inconsistency, and multilingual dataset normalization. The paper proposes a Unified Global Data Fusion Framework (UGDFF) to integrate hybrid data streams at scale while preserving privacy, cultural context, and ethical compliance.