This article examines the revolutionary transformation of the retail industry through the convergence of cloud analytics and artificial intelligence-driven personalization. It explores how retailers are transitioning from traditional customer segmentation to sophisticated hyper-personalization strategies, enabled by modern data platforms, real-time processing capabilities, and advanced machine learning technologies. The article presents a comprehensive analysis of the critical components driving this evolution: cloud-native data architectures that provide unlimited computational resources, real-time personalization systems that dramatically compress the insight-to-action cycle, machine learning applications that enable prescriptive decision-making across various retail functions, and operational analytics frameworks that close the loop between data insights and frontline execution. Through empirical evidence from multiple research studies, the article demonstrates how these technological capabilities are creating measurable business value in areas such as customer retention, inventory optimization, marketing effectiveness, and overall operational efficiency. The article highlights that successful retail transformation requires not only technological investment but also organizational capability to operationalize insights and systematize the feedback loop between analytical findings and customer-facing actions.
Jimish Jitendra Kadakia (Mon,) studied this question.