Security cameras in retail outlets are an accepted part of the shopping experience. You expect to be monitored, and the footage is generally only used to bring shoplifters or those that cause a public disturbance to justice.
However, the vast amount of shopper data which is available due to these cameras may also soon have other purposes. In the same manner that online stores, such as Amazon, track customer preferences, habits, and alter their business strategy or recommended products based on this data, perhaps brick-and-mortar stores will now begin to follow suit.
Prism Skylabs, based in San Francisco, now allows retail owners to mine extra information from their shop footage through the use of new scanning software. The company installs the software on computers that link to a store’s security camera system, compresses the gained information, which is then sent to cloud servers. Once the raw data is uploaded in to the cloud, Prism sends back extracted data, including statistics and visualizations.
This can be used to count, log, and track people in-store. The software is able to analyze customer density, where shoppers deviate most to when they are present in the store, and track browsing habits. Anything from the length of a checkout queue to recording the most popular products or showrooms can be tracked and analyzed in retail through normal CCTV footage.
Steve Russell, CEO of Prism says:
“There’s a lot of wonderful information locked up in video, and 40 million security cameras in the U.S. collecting it, but it’s data that’s not been available. We want to free up that information.”
Although the software turns the usual low-resolution footage available in to a higher resolution version, in order to maintain personal privacy individual features are blurred. Human figures are given a ‘ghostly’ image, or removed completely, leaving colored spheres in their place. This can also be used to generate ‘heat maps’ to track crowd density in specific areas, and give retailers more of a glimpse in to the patterns of their customers.
Image credit: Shaun Greiner
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