A Hit Sneaker Was Designed Using 100,000 Scans of Runners’ Feet

(Bloomberg Businessweek) -- On the list of endangered retail species, the local running store is right up there with the independent bookshop. We want it to exist, but the internet has made it too easy to buy whatever we want, whenever we want, at the price we want instead.

One of the last great names in running shops has survived, however, thanks to a bit of high-tech jiujitsu. Fleet Feet, which first opened in 1976 in Sacramento, began adding 3D scanners at its 177 franchise locations in 2017, using runners’ love of data to entice them into its stores and then keep them there long enough to buy something. “People who run enjoy going to a store, because it acts as a bit of a clubhouse,” says Huub Valkenburg, chief executive officer of Karhu, which three years ago cut a deal with Fleet Feet to become its exclusive in-house brand. “They want to connect with other runners.”

The foot-scanning strategy was originally implemented as a way to make it easier for salespeople to help a customer narrow down options more quickly. Measuring 12 data points, the scans give runners hard data on their own bodies that’ll help them find the right fit, whether it’s to accommodate an abnormally high arch or a propensity for extensor tendinitis on the top of the foot. Either way, the scanning process has been a hit, serving as an entertaining activity even for nonshoppers.

A Hit Sneaker Was Designed Using 100,000 Scans of Runners’ Feet

Buoyed by the program’s success, Karhu last year used foot scans from more than 100,000 customers to guide the creation of its latest shoe, the Ikoni. Technically and superficially, it evokes many of the so-called maximalist shoes—bulkier models focused on cushion and protection—that have come to market during the past decade. The movement was led by Hoka One One, founded in 2009 at the height of the barefoot running trend. (You remember Vibram FiveFingers, right?) Shoes in the Hoka lineup became popular with ultramarathoners looking for more support, and I count myself among that group with the brand in my running closet along with my Newtons and Asics.

The data from the scans—7 of the 12 points in particular—persuaded Fleet Feet and Karhu to redesign the “last,” a 3D mold that serves as the basis for a shoe’s dimensions, including its heel width, instep height, forefoot height, toe box depth, and other measurements.

A Hit Sneaker Was Designed Using 100,000 Scans of Runners’ Feet

Rethinking the model in a way that specifically applied to runners was a somewhat radical notion, says Valkenburg. “Lasts are a 60- to 80-year-old concept,” he says. “They come in standards that were never adopted for running.” The brand says its redesign distributes force to specific areas of the shoe, amplifying momentum and efficiency for longer and faster runs.

I can’t say that I’m actually running faster in them, but the Ikonis have worked their way into my regular rotation. The thick midsole gives a lot of protection, which is the way I like it. The narrower-than-most heel width gives better stability in the back of the shoe, while the deeper toe box provides a more natural footfall and doesn’t pinch at the point of impact.

The data-reliant nature of the Ikoni may help it stand out in a market overrun with choice. And while the idea of a crowdsourced shoe might run counter to how people personalize their gear, fitness mavens consider this just the beginning of a future in which a 12-point scan generates an entirely customized shoe, created in the store via 3D printing.

As it turns out, many of us runners have proven to be suckers for anything that can be measured and compared, which helps explain the explosion of GPS-enabled watches and social networks such as Strava. Fleet Feet expects to capitalize on that: This month it will scan its 1 millionth foot. Later this year it will introduce changes to two more Karhu models, the Fusion and the Synchron, shaped by that data.

To contact the editor responsible for this story: James Gaddy at jgaddy@bloomberg.net

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