This document provides an overview of retail analytics. It discusses key retail data elements that can be analyzed, including point-of-sale data, customer transactions, loyalty programs, and external sources like social media. Business drivers for retail analytics are listed as delivering personalized experiences, increasing loyalty and conversion rates, and optimizing inventory and supply chain. Example use cases discussed include store analysis, revenue prediction, marketing spend optimization, and customer analysis. A sample architecture is shown utilizing Power BI and Azure ML. Case studies demonstrate analytics solutions for a global retail chain.
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