H & M Turns to Big Data, AI to Tailor Store Offerings

Big DataFor ten straight quarters, H &M—the world’s largest clothing brand, suffered slumps in same-store sales and it still faces troubles with the clothing and fashion industry. In a bid to win back shoppers and reverse one of the worst slumps in its history, the company is now turning to artificial intelligence (AI).  Here’s how H &M plans to use AI to achieve its objective!

Whether it is the invention of the sewing machine or the rise of e-commerce, the fashion industry is one industry that has always been a hotbed of innovation. The fashion industry is huge. It is a $2.4 trillion market, which makes it one of the largest industries in the global economy. A major player in this industry is H&M—the world’s largest clothing brand.

Established in 1947, H &M has its presence in over 60 countries and generates yearly revenues in the billions. However, the company has seen a slight decline in sales during recent years. In fact, it has suffered a slump in sales for ten straight quarters and this has the company’s hierarchy worried. The executives have finally awakened to the fact that sales are going down and something needs to be done and fast.

The first measure that the company has taken to correct the slump is moving away from their usual approach to retail by monitoring customer data and implementing artificial intelligence in an attempt to comeback from their poor sales slump. Instead of stocking the same items in stores all over the world, H &M will now rely on AI and algorithms to better align supply and demand on a store-by-store basis. the company has 4,500 stores worldwide.

The retail chain is ramping up its use of data to customize what it sells in individual stores, which is a shift from its longstanding practice of stocking stores around the globe with similar merchandise. The company is breaking away from the above practices in hopes that it will help to arrest a slump in same-store sales that has lasted ten straight quarters. A spike in online shopping has led to fewer customers visiting stores, and digital startups are putting up fierce competition.

The fashion-industry giant has repeatedly slashed prices to clear out $4 billion of unsold inventory, and will now use data from store receipts, returns, and loyalty-card accounts to reduce markdowns. Like most retailers, H& M relies on a team of designers to determine what shoppers want to buy. But now it is 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 of this, some H&M stores have already started to carry more fashion and fewer basics such as T-shirts and leggings.

AI Analytics an Addition, Not a Replacement for H&M

Despite no longer depending on the intuition of their managers and merchandising heads, H&M realizes that the change doesn’t necessarily mean that they have to replace those positions. Instead, the company is focused on providing its managers and merchandising heads with the data and tools to better inform decisions moving forward.

According to Arti Zeighami—the head of H&M’s advanced analytics and artificial intelligence function, the shift is going to help the company. It is will interesting to see how the move will impact the overall approach of other retailers. However, one thing is for sure: as competition continues to grow, putting customer centricity at the forefront will be what helps companies stand out and offer value to both investors and shoppers alike.

While H&M believes that the shift to AI and analytics will rectify the slump in same-store sales it has suffered in the last ten quarters, analysts remain skeptical that the new strategy will pull H&M out of its slump. The analysts believe that data alone cannot pull H&M out of its slump as the company’s algorithms have previously failed to factor in considerations important for keeping store sales at a profit or even at break-even.

Also, analysts are worried that the strategy of H&M to use granular data to tailor merchandise in each store to local tastes, rather than a cookie-cutter approach that groups stores by location or size, is largely untested in the retail industry. Talking to journalists, Ludovica Dodero—a former retail executive of the company has the following to say:

Most companies are still used to taking decisions not driven by analytics at all, only based on the experience of the manager.’

Ludovica Dodero was pointing to the fact that we don’t really know the expected outcome of H&M’s new approach to stock and manage merchandise in store as the approach has not been tried a lot before. Not only is H&M’s new approach for stores relatively untested, getting every store right is a mammoth task for the company given its size. Compared to Zara’s 2,127 stores and Gap’s 1301 stores, H&M has 4500 stores worldwide.

H&M claims that the sales at the stores have improved since it began rolling out the AI technology globally. However, the company has declined to provide figures. 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 and external, H&M is using analytics to look back on purchasing patterns for every item in each of its stores. While the data has certainly help H&M to make financially viable decisions for its stores, it doesn’t always lead to sensible conclusion. We will just have to wait and see if the new approach helps to pull out H&M of its recent slump.

by Bobby J Davidson

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