It could be said that the Expo floor at the NRF Big Show in New York channels a mass retail environment: wares presented in vibrant displays; sales people eager to engage; swarms of prospects stalking the aisles.

According to the National Retail Federation, some 25,500 people packed the January event. It was the best turnout in years, maybe ever, and the atmosphere was electric.

As several fellow aisle walkers observed, NRF has become primarily a retail operations show. Apparently the austerity of the recent economy led to some pent-up demand among retail CIOs, and exhibitors were ready to jump in with solutions.

These fell into several thematic categories. Oft-heard attributes included:

  • “Insights” (every retail software solution promises better ones)
  • “Analytics” (every retail software solution promises faster ones)
  • “Business Intelligence” or BI (how every solution promises to deliver the insights and analytics)
  • “Big Data” (what accrues from gathering so many insights and analytics)
  • “Cloud” (the place in cyberspace where more and more vendors propose to house Big Data)
  • “Dashboards” (screens where retail practitioners are expected to access their BI)
  • “Omni-Channel” (a state of retailing where online commerce coexists with mobile commerce and bricks & mortar, empowered by – you guessed it – insights, analytics, Big Data and BI.)

And of course, all of this know-how will increasingly be accessed and manipulated over mobile devices.

Tracking the Trackers

As some readers may be aware, I am professionally obsessed with in-store. True to form, I hunted down solutions which can deliver better and more continuous in-store and shopper insights. There was a lot to choose from, and to my great interest, solutions that track, count, and even classify shoppers electronically were present in abundance. Notable players included Countwise, ShopperTrak, RetailNEXT (BVI) and Axis Communications.

Shopper tracking has a long history. Electronically tracked carts were a feature of the original VideOcart system,  tested in supermarkets between 1989 and 1994. It employed PathTracker® software used to generate graphic representations of many carts’ paths. The resulting chart was described as a “heat map” – areas with the greatest traffic were more densely highlighted, and less-traveled areas were less so. The information may be used to determine optimal locations for displays, to streamline traffic flow, and for other aspects of macro space planning.

At NRF, a variety of updated versions of this concept were on display. They employ a variety of sensing and people counting methods, ranging from digital video cameras and electric eye infrared beams to infrared cameras and the old standby – attaching a transponder to the shopping cart. The tech was definitely more sophisticated than ever, but the output was more often than not, that old standby, the heat map of shopper movement, on a vibrant color screen.

The application of digital video to this objective is probably the breakthrough here. Cameras are increasingly deployed in stores for both security and research purposes. Images of shoppers moving and dwelling in the aisles can be analyzed at varying levels of sophistication to generate those all-important heat maps. But that’s just the start.

Big Brother – Big Data?

Say you have 20 fish-eye cameras mounted in the ceiling of your store running 24 hours a day for this purpose. That’s 480 hours of video per day to analyze – way beyond human capability.  Algorithms can convert and collate that pile of unstructured data into something that can be housed in a data mart (that’s one reason why “Big Data” is becoming all the rage.) Then they can extract measures of shopper dwell times at key locations, sort shoppers by visible demographic traits, and relate in-aisle behavior to the contents of the shopping baskets.

How will all these insights be used? Simple answers involve setting efficient staff levels, queue management, and determining how to charge manufacturers for choice display locations. In-store media networks will use the data to verify audience metrics. One vendor showed off an empirical test of store layout impact on sales.

This area is moving very fast and it promises to deliver a trove of in-store sensing information to retail marketers and category planners. If retailers apply these insights to deliver a superior experience, shoppers will get past the feeling that Big Brother is looking over their shoulder.

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