VCA technologies have come a long way since the initial days when they were just a part of security solutions. Today’s analytic systems are technologically advanced enough for better gesture recognition, improved classification based on age, gender, build etc. and for more precise location data.
VCA technologies have come a long way since the initial days when they were just a part of security solutions. Today’s analytic systems are technologically advanced enough for better gesture recognition, improved classification based on age, gender, build etc. and for more precise location data.
“The ability to recognize more complex gestures and better classification arise from higher resolution cameras and more affordable, higher performing computer processors, which in turn provide a cost effective means to host CPU intensive video analytics algorithms,” said Eric Olson, VP of Marketing at PureTech Systems. “For the retailer, this provides usable demographic data, more precise buying data and increased protection against theft.”
In addition to customer behavior, these advancements can also increase employee safety, ensure level of compliance and measure the effectiveness of training, Olson added. For example, in retail food handling, today’s VCA can be used to determine whether gloves, hairnets or hats are being worn at food handling stations. It also has the capability to monitor for food that has been sitting out of freezer for too long or if a particular food item been under the warming lamps for too long. These capabilities would not have been possible a few years back.
Jason Luther, Head of Products at RetailNext, agreed that while the fundamental concepts of VCA have been around for a while, steady advances in technology have now made them more precise, more accurate and cost effective to deploy at scale.
“A few years ago it was not possible at scale to measure the path of a shopper as she journeyed from one camera zone or location to another,” Luther said. “Leading store IoT platforms like RetailNext can now do this as well as tie other sensor data to the paths to segment the journeys by age, gender, employee vs. customer status, buyer vs. non-buyer, etc. Technology is evolving even further to ingrate real time RFID data with video to understand not just how people move, but how the product itself moves throughout the store, and together it adds additional texture to shopper activity data.”
Uma Welingkar, VP of Product Management at
3VR, explained further on the role these solutions play in the larger picture that includes other devices and systems.
“Some new trends we are seeing include the integration of customer behavior with mobile shopping technologies such as beacons, sensors and RFID chips,” Welingkar said. “Beyond collecting demographic data about mass market shoppers, retailers are moving to more personalized experiences for loyal shoppers, such as a promotion delivered to a mobile phone when that shopper enters the store. Research has shown that a majority of shoppers are willing to provide detailed personal profiles in order to have a more personalized shopping experience. Mobile applications are transforming from just another shopping channel into a platform for obtaining customer insights.”
Brien TerBush, Global A&E Manager at
Aimetis pointed out that the major advancement in VCA over the years is that it has become more cost effective. He further gave other examples of the technology having evolved.
“The biggest factor in why there’s been growth in VCA solutions has been because they have been proven cost effective,” TerBush said. “There are several case studies out there that highlight success which has driven demand. Loitering/dwell time was once viewed to be mainly for theft detection, but has become an effective tool used to alert store personnel to offer assistance and improves customer service. Heat maps and people counting can highlight areas in a store that help can help optimize store layout and identify what items are most popular.”