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How to Get Results from your Big Data with Retail AI

Retalon

Businesses collect more data than ever before and from every aspect of the supply and demand chain—logistics; vendor compliancy/lead times; POS data; inventory levels; traffic cameras; prices; markdowns; consumer behavior; demand forecasts; and more. Consider the way retailers traditionally forecast fulfillment.

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5 Vital Considerations for Big Data Analytics in Retail

Retalon

Retail businesses collect more data than ever before, and from every aspect of the supply chain, including: Logistics data (vendor compliance, lead times, etc.). Prices (markdowns, promotions, competitor prices, etc.). Consider the way retailers traditionally forecast fulfillment. POS data (sales, returns, etc.). The result?

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How Smaller Assortments, Lower Inventory Levels Can Maximize Post-COVID Success

Retail TouchPoints

By creating narrower product assortments and limiting inventory levels — especially for product shipments headed to brick-and-mortar stores —merchants would gain the ability to react more quickly to changing consumer trends, and even potentially reduce their need for markdowns. Richard Maicki. Keith Jelinek.