‘Big Data’ is one of those hot ‘buzzwords’ that seems to be everywhere at the moment. It is, according to the dictionary “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.” And more and more companies are attempting to harness its power to increase their bottom line.
H&M, a company that has had a very turbulent year, is one of the major players in fashion who are hoping big data can help save what, in their case, is a sinking business. They are making use of it in an attempt to more accurately predict the coming trends and to customize the clothing selections individual stores to better suit the regional audience, something they have never done before.
This recent piece from the WSJ journal explains in depth just how H&M are using big data as well as taking a look at what some other players in the fashion retailing space are doing with their data.
H&M Pivots to Big Data to Spot Next Big Fast-Fashion Trends
Instead of cookie-cutter stores, the H&M chain is using granular data to customize the offerings in each one of its 4,200 locations
WSJ: May 7, 2018
STOCKHOLM—The world’s largest clothing brand is turning to artificial intelligence to win back shoppers, as it works to reverse one of the worst sales slumps in its history.
Hennes & Mauritz AB’s H&M HMB -2.91% retail chain is ramping up its use of data to customize what it sells in individual stores, breaking with its longstanding practice of stocking stores around the globe with similar merchandise.
The 71-year-old fast-fashion chain is aiming to arrest a slump in same-store sales that has lasted 10 straight quarters as it faces problems bedeviling the industry: A spike in online shopping has led to fewer customers visiting stores, and digital startups are putting up fierce competition. H&M has repeatedly slashed prices to clear out $4 billion of unsold goods, and its shares are down 56% in the past three years.
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. As a result, some stores have started carrying more fashion and fewer basics such as T-shirts and leggings.
“You are much more vulnerable today if you don’t have the right product at the right price because I can search the world for the right product,” says Erik Sjöström a portfolio manager at Skandia Investment Management AB, a longtime investor that has slashed its H&M position to 2% of its equity portfolio, down from 10% at its peak.
Analysts remain skeptical that the new strategy will pull H&M out of its slump. Almost half of analysts who cover the stock have a “sell” recommendation on it compared with 36% a year ago, according to data provider FactSet.
“It will likely be a long road to recovery for the main H&M brand,” said RBC analyst Richard Chamberlain, pointing to intense competition in the sector. Read More