Advanced Certificate in Retail Data Strategies for Innovation
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⢠Advanced Retail Analytics: Understanding the use of data analytics in retail to drive innovation and improve business performance. This unit covers topics such as data mining, predictive analytics, and prescriptive analytics.
⢠Retail Data Management: This unit focuses on the collection, storage, and organization of retail data. It covers best practices for data governance, data quality management, and data security.
⢠Retail Customer Analytics: This unit explores how to analyze customer data to gain insights into customer behavior and preferences. Topics covered include customer segmentation, customer lifetime value, and customer journey analysis.
⢠Retail Inventory Management: This unit covers how to use data to optimize inventory levels and reduce stockouts and overstocks. It includes topics such as demand forecasting, inventory turnover, and safety stock management.
⢠Retail Pricing Strategies: This unit covers the use of data to develop effective pricing strategies. It includes topics such as price elasticity, price optimization, and dynamic pricing.
⢠Retail Marketing Analytics: This unit explores how to use data to optimize marketing campaigns and improve customer engagement. It includes topics such as marketing mix modeling, customer response modeling, and marketing attribution.
⢠Retail Supply Chain Analytics: This unit covers how to use data to optimize supply chain operations and improve efficiency. It includes topics such as demand planning, supplier relationship management, and logistics optimization.
⢠Retail Sales Analytics: This unit explores how to use data to improve sales performance. It includes topics such as sales forecasting, sales force optimization, and sales performance management.
⢠Retail Data Visualization: This unit covers how to present retail data in a clear and concise manner to facilitate decision-making. It includes topics such as data visualization best practices, data storytelling, and dashboard design.
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