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Retail Analytics

Retail analytics is the practice of collecting, processing, and analyzing data from retail operations to gain insights into customer behavior, sales performance, inventory management, and market trends. It involves using statistical methods, data mining, and business intelligence tools to transform raw data into actionable information for decision-making. This helps retailers optimize pricing, marketing strategies, supply chain efficiency, and overall profitability.

Also known as: Retail Data Analytics, Retail Business Intelligence, Retail Data Science, Retail Insights, Retail Performance Analytics
🧊Why learn Retail Analytics?

Developers should learn retail analytics to build data-driven applications for e-commerce platforms, point-of-sale systems, or inventory management software, enabling features like personalized recommendations, demand forecasting, and real-time sales dashboards. It is crucial for roles in retail tech, where skills in data processing, visualization, and machine learning are applied to solve business problems such as reducing stockouts or improving customer retention.

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