AI Case Study

"H&M, like most retailers, relies on a team of designers to figure out what shoppers want to buy. Now, it’s using algorithms to analyze store receipts, returns and loyalty-card data to better align supply and demand, with the goal of reducing markdowns. To detect trends three-to-eight months in advance, H&M is analyzing data on a large scale from blog posts, search engines and other sources rather than relying mainly on staff. With the help of about 200 data scientists, analysts and engineers—internal staff and external contractors—H&M also is using analytics to look back on purchasing patterns for every item in each of its stores. The chain uses algorithms to take into account factors such as currency fluctuations and the cost of raw materials, to ensure goods are priced right when they arrive in stores. But H&M’s strategy of using granular data to tailor merchandise in each store to local tastes, rather than take a cookie-cutter approach that groups stores by location or size, is largely untested in the retail industry, consultants say."