H&M harnesses AI to test online tailoring feature
By Weixin Zha
15 Apr 2019
With a little help from algorithms and artificial intelligence, accessible and affordable tailored clothing might soon become a reality. Swedish fast fashion retailer H&M and Berlin-based start-up ZyseMe have partnered up to test an offering for tailor-made clothing online.
The new Just.Perfect project, which has been trialled exclusively in Germany since January, allows customers to receive men’s fitted white shirts without having to leave the comfort of their own home. So how does it work exactly? Rather than taking extensive time-consuming measurements normally associated with tailoring, customers simply need to enter information – such as height, weight, size and shoe size – into the H&M app. Then, ZyseMe’s software uses algorithms and historical data to turn the customer measurements into information that is sent to H&M suppliers in Turkey.
Within two weeks, the customer will then receive a fitted men’s white shirt for 39.99 euros. ”It makes getting a customized product more accessible to more people“, Bobby Östberg, founder and chief executive of ZyseMe said in an interview. Ordering a shirt online is also simpler than going to a tailor and encourages people to try, he added.
Tailoring for the mass market
The Just.Perfect project by H&M and ZyseMe might at first seem like just another tech-powered new product, but along with the rise of tailoring and personalization, it suggests another sign of the turning tides within the apparel industry.
Picture: H&M test shirt/ H&M Germany
For the first time, one of the world’s biggest mass-market garment producers - one that once spearheaded fast fashion’s skyrocketing ascent - turns to individual tailoring with the help of technology. As consumer wardrobes continue to fill with clothes and as prolonged sales periods weigh on profits, companies hope that moving closer to the individual needs of consumers could help avoid producing overstock and returns.
Algorithms beat measurements
H&M’s long-standing collaboration with manufacturers makes it possible to offer tailoring services at the current delivery speed of two weeks, and at a price of 39.99 euros, said Oliver Lange, head of H&M Lab Germany by email. When surveyed, customers expressed willingness to pay 30-40 percent more for a perfectly fitted shirt rather than a ready-made one. The average prices for tailored shirts in Germany starts at around 70 euros online.
Östberg said he used to order a lot of tailored shirts on the internet when he was working as a consultant in New York, but grew frustrated with what he received. At one point he even created a spreadsheet of his various orders to figure out which sizes worked best for him. Convinced that there must be a way to make the process more efficient, and after years of learning about the tailoring business, Östberg founded ZyseMe in 2017.
Picture: ZyseMe tables
”We actually had better results using algorithms than when we did with body measurements, which may sound very surprising at first,” he said.
Producing on demand to save resources
While the test with H&M is only currently being used to deliver white cotton shirt, ZyseMe’s software already offers customization for different fabrics and buttons. Next, Östberg plans to expand his collaboration to more fashion companies, and also wants the range of apparel to include men’s suits, t-shirts, sweaters, pants and someday also women's wear.
H&M’s customers have already showed interest in tailored trousers, suits and dresses, said Lange. When the current tests end in April, the company has to decide whether to continue the trial or introduce the product. Tailored solutions won’t work for every product and customers will want to purchase basics and childrenswear as they’re used to, he said. But Lange believes that some customers will value personalised products and that well-fitted garments will have longer lifespans.
“The vision for the future is to offer all customers who value individual measurements their desired H&M products individually tailored, thereby minimizing returns and also reducing the use of resources,” he said.
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