How AI Is Helping Shoe Retailers Solve One of the Biggest Consumer Pain Points
Jennie Bell
Deputy Managing Editor
Brent Hollowell remembers working at Foot Locker in the ’90s, when the retailer was approached by AOL to join its online mall. “There was so much to figure out, like, how would they pay us, how would we ship to them and how will we know we got their size right?” he recalled.
Three decades later, e-commerce has developed efficient solutions for two of the three issues. “But when it comes to picking our size, we’re still hovering our finger over the button and going ‘I’m guessing here.’ Customers are still buying two or three styles and sizes and sending the rest back,” said Hollowell, who is now chief marketing officer at fit tech company Volumental, based in Stockholm.
Experts believe the solution to online shopping challenges lies in the rapidly growing field of artificial intelligence.
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Paul Davis, chief commercial officer at Swiss tech firm ShoeAI, explained, “Retail is considered one of the top industries for AI because it has so many immediate uses. Are you asking it to do the customer service, freeing up a human agent to do something else? Or are you asking it to go and do something in the back end?”
Both Volumental and ShoeAI offer tech solutions that help customers find and select footwear that fits properly. But neither is new to artificial intelligence.
ShoeAI, a virtual sales assistant developed by ShoeSize.me, is based on 10 years of development. It uses machine learning that guides customers toward the right purchases based on data about the shoes they already wear, along with more than 58 million data points from shoe purchases collected around the world.
Volumental’s AI capabilities include both computer vision and machine learning. Alper Aydemir, who founded the company in 2012, has a PhD in computer vision and previously worked on the Mars helicopter at NASA’s Jet Propulsion Lab and contributed to the augmented reality tech at Google X. He’s now applying his talents to foot-scanning devices that Volumental supplies to retail stores globally.
The devices collect millions of pieces of data about customers and their feet, which is where machine learning comes in. “With machine learning, you’re training the database to understand the relationship between bits of data done at scale,” explained Hollowell. “We use that information to produce very high-quality recommendations. So if you don’t know what kind of shoe or brand or size you want, we can say, ‘well based on your feet, this is what would fit your foot the best.’”
Retailers and brands can partner with fit tech companies like Volumental and ShoeAI to incorporate these technologies into their physical and digital storefronts. As Davis explained, working with an established tech company is still the most efficient method to incorporate AI into your operations.
“If you work with somebody that’s got some experience, you can probably get something ready in a few months,” Davis said. By contrast, he recalled that one European e-tailer spent five years building a virtual fitting program from scratch, with a team of more than 100 people.
And AI development remains an expensive proposition. “It depends on people’s budgets, but whatever number is in their mind, you’ve got to [multiply] it by five and you might be there,” Davis said, adding that the “learning” process for new AI programs can also be very slow.
There are other limitations as well.
Volumental has a mobile app, which uses cell phone cameras to scan feet. However, Hollowell admitted that program is slower and less accurate than its in-store devices. “I don’t know when the technology will be as good on a mobile phone, but we’re a ways away from that. But the more mobile scans we get, the more the AI learns and you’ll see the accuracy improve.”
For companies that adopt these digital fit services, there are numerous benefits. Luxury boot brand Le Chameau installed ShoeAI on its e-commerce site and reported that in the first six months of the partnership, ShoeAI guided 38,400 shoppers and converted them with a 6.5 percent net conversion rate. That created an extra 2,668 orders worth 264,800 pounds.
“One of the key things for us is all our rubber products are handmade, so it does mean we’ve got slight variances in size and fit,” said Andy McCallum, chief marketing officer at Le Chameau. “Using ShoeAI was great because that demystified completely how we describe our boots in millimeters and inches.” He also noted that providing more-accurate fit guidance to customers helps the company cut down on returns, which are particularly expensive for boots.
Overall, fit tech companies are extremely bullish about the possibilities for AI in e-commerce. “I think we’re on the cusp of solving this massive industry problem — this shopper pain point that, like so many pain points, we just accepted because we had blinders on to what’s possible,” said Hollowell.
This story was reported by WWD and originally appeared on WWD.com.
