Appeared In
Special Issue
Men'sWeek issue 04/03/2014

Technology that already exists in stores can generate data to ultimately boost the bottom line.

This story first appeared in the April 3, 2014 issue of WWD. Subscribe Today.

Steve Russell, chief executive officer and founder of Prism Skylabs, a San Francisco-based company that specializes in understanding and optimizing offline commerce, said companies that are open to using technology can “create a better experience for customers.” He pointed to three “interesting” technologies that fit that bill: computer vision, computational imaging and data visualization.

The first, computer vision, teaches computers to “see, and mind the store in ways you can’t,” Russell said. Computational imaging is a process to “make pretty photographs of stores that combine imagery and data,” and data visualization allows a retailer to extract “interesting and relevant insights and tidbits of data in a form that us mere mortals can understand.”

He said using video is a no-brainer because there are cameras “virtually everywhere” around the county. “On YouTube, we make a big deal out of the fact that people are globally uploading 100 hours of video a minute. But a single retailer like Wal-Mart blows that away by uploading 30,000 hours of video every minute. Across the entire retail industry, over 2 million hours of video are being recorded, but the cameras are being primarily used for security. Yet, hidden within that video is valuable information such as how many people are walking into your store, the areas they go to, how long they spend there, what products they interact with.”

Such “fertile evolution of analytics” can also be used on conversion reports, to determine staffing levels, etc.

Turning to computational imaging, Russell said people use it every day when they hit the HDR key on their iPhones or apply an Instagram filter to photos they shoot to “create a better image than the original.” Similarly, the video cameras that capture images may not be that good, but computational imaging can turn these grainy surveillance images into high-res, well-composed photos to use for visual merchandising, audits and other purposes, he said.

He cautioned retailers that they should also employ privacy protection so as not to open themselves up to issues down the road.

Finally, data visualization allows a computer to “generate a course map to determine where people walk when they come in” and the “dominant paths they take.” It can also create a “heat map to see where people are standing in the store and what product they’re interacting with.” Knowing where the “hot zones” are can help retailers with merchandising and store design. These decisions, which traditionally have been “based on gut,” can now be “more data-driven.”

Overall, using these technologies for commercial applications “can really help retailers drive the bottom line,” he said. Russell urged stores to turn their cameras into “sensors that can begin to create data,” and use “computational imaging to bridge the gaps between people who are making decisions about stores but can’t always be in stores, and data visualization to take complicated data and bundle it in a way that is simple and easy enough to use to push down into the field.”

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