The retailer is employing 200 internal and external data scientists, analysts and engineers to use the analytics to review purchasing patterns of every item in each store. The data includes information from 5 billion visits last year to its stores and websites, as well as data from external sources. The chain uses algorithms to take into account factors such as currency fluctuations.

By analyzing purchases and returns in a more granular way, H&M discovered that the store's customer base was primarily women, and that fashionable items like floral skirts in pastel colors and higher-priced items sold better than the retailer expected. Sales at the store, have improved significantly.

H&M is breaking from its past practice of stocking its stores with similar merchandise, which resulted in repeatedly cutting prices to clear out some $4 billion of unsold product. Last year, H&M cut the number of pieces in inventory in the stores by 40%, and eliminated most menswear products. In its place, crockery was added, as well as $118 leather bags and $107 cashmere sweaters alongside $6 T-shirts and $12 shorts.