This story about how to reduce e-commerce returns—in this case, by a double-digit rate within a year—begins in a shoe store. Many shoe stores, in fact—hours upon hours spent inside shoe stores, often in the evenings after the workers who were trying to get e-commerce software provider Shoefitr Inc. off the ground finished shifts at their full-time jobs.
The task, typically done in break rooms, was to measure shoes and use 3-D imaging technology to scan footwear down to the tiniest increments, then arrange that data in a way that would help consumers buy the shoes that would fit best, says Shoefitr co-founder Nick End.
Say, for instance, that a soccer player owned a green-and-gold pair of the cleated Asics Lethal Flash DS IT but wanted a pair of shoes from a different brand, perhaps to use on a different playing field or for simple variety. By entering his shoe size and that make and model into the Shoefitr tool—displayed on a product page as a link that says "Show me how it fits" that, when pressed, produces a pop-up box—a consumer could learn what size in another brand would best match his fit. The same sizes in different brands, after all, often fit differently. A color-coded map-like image of the shoe, the fruit of all that scanning and measuring, tells shoppers where the shoe might pinch the foot (indicated by warmer colors such as red and yellow), and where toes might have too much wiggle room (icier tones of blue). Testing the accuracy of the system requires Shoefitr to send more workers into shoe stores to try on more shoes, End says.
---QIFENG SHOES MACHINE.