H&M Digs Into Big Data From Returns And Receipts To Boost Store Sales

H&M Digs Into Big Data From Returns And Receipts To Boost Store Sales
Fashion & Apparel

Location-specific information from receipts, returns and loyalty cards will help the retailer provide an increasingly targeted product selection

Kim Windyka
  • 14 may 2018

To combat steadily decreasing sales and revenue—and to more prudently stock its stores—Swedish retailer H&M is utilizing a combination of AI and customer data from returns, loyalty cards and receipts. With this approach, the company will be able to customize each store’s offerings based on its individual profile with the ultimate goal of fewer markdowns, less unsold inventory and increased profits.

This new plan is in contrast to the brand’s longtime “one size fits all” strategy that saw it ordering relatively identical product sorts for every store. Thus far, data collected from one of H&M’s Stockholm, Sweden locations has revealed that trendier, more fashionable items like floral skirts are stronger sellers than basic pieces, and that female shoppers comprise the bulk of the store’s customers. As a result of changes based on these findings, the location has seen an uptick in sales, and the retailer plans to follow suit with the unique data from other outposts.

H&M

To combat steadily decreasing sales and revenue—and to more prudently stock its stores—Swedish retailer H&M is utilizing a combination of AI and customer data from returns, loyalty cards and receipts. With this approach, the company will be able to customize each store’s offerings based on its individual profile with the ultimate goal of fewer markdowns, less unsold inventory and increased profits.

+AI
+artificial intelligence
+Big Data
+Brand Introduction
+Europe
+Fashion
+fashion / apparel
+H&M
+inventory
+loyalty
+loyalty & membership
+merchandising & curation
+Personalized Loyalty
+retail

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