In an effort to reverse the decline in its worldwide sales, H&M is using technology that will help the world’s largest clothing brand stock its stores more efficiently, sell more effectively and adapt more quickly to current consumer trends.
Largely untested
Hennes & Mauritz has set its hopes on algorithms to get its worldwide sales figure back on track and adapt more effectively to consumer habits and trends which are changing at an ever increasing pace. The algorithms take into account external information from blog posts and search engines, as well as the fashion chain’s own sales data to determine what sells best, or is likely to sell best within a three-to-eight month time frame, in any given H&M store around the globe.
With the help of some two hundred data scientists and engineers, the Swedish fashion giant hopes to optimise first and foremost its store stocks: clear-outs of unsold clothing have been negatively impacting its turnover for at least two quarters straight. “The algorithms adapt continuously to what customers want to wear and what they are willing to pay,” said H&M’s investor relations head Nils Vinge. As a result, some stores have started carrying more fashion and fewer basics such as T-shirts and leggings.
H&M is not the first retailer to turn to technology to help boost sales, but relying on statistics rather than on experience and gut feeling is a still largely untested strategy in the industry, experts say. Whether algorithms will provide the ultimate key to recovery is unclear, furthermore, as H&M continues to struggle with fierce competition from digital startups and consistently fails to convince investors: shares in the Swedish company are down 56% in the last three years.
