Online retailers have long had a major advantage in that they can see exactly what shoppers do on the ecommerce site day-on-day. Every click, search, product view, abandoned basket and completed purchase can be tracked and analysed. Brick-and-mortar retail, however, has traditionally relied on much more basic measures to understand shopper behaviour.
Footfall counters, heatmapping systems, and phone-tracking sensors can provide useful information, but they often tell retailers where people are rather than what they are doing and why. Entrance footfall counters, for example, can measure how many people enter a store, but they cannot tell you which departments they visited or whether they actually engaged with products on the shelves.
Heatmapping can show areas of high and low traffic, but it doesn't necessarily explain shopper intent or connect movement with purchasing behaviour. Phone-tracking technology and Wi-Fi beacons can provide information about movement patterns, but it depends on shoppers having detectable devices and can raise privacy and accuracy challenges.
More recently, the likes of Apple and Samsung have made updates to send out multiple IP signals per minute in order to scramble unsolicited attempts at phone-tracking. Insufficient results from the above solutions tends to lead to a significant analytics gap between the online shopping world and that of physical brick-and-mortar retail.
Bringing online-level intelligence into the store
Computer-vision along with AI data processing is changing how retailers view their in-store operations. Rather than simply counting people or tracking movement, AI-powered computer-vision can analyse shopper behaviour in real time. Retailers can understand how shoppers move through a store, which areas attract attention, how long they spend in different departments and, crucially, how many shoppers convert into customers. This creates an opportunity to bring the same level of measurable insight that online retailers have enjoyed for years into the physical store.
The added benefit of live data allows for much more proactive decision making in-store. Stores can be alerted to any number of custom KPI’s to do with shopper activity. For example, a grocery store that wanted to alert a staff member to a popular fruit section could set a KPI for staff to attend the category for every 100 shoppers that have dwelled in that zone. Similarly, a fashion retailer could have staff check a changing room area for every 20 people that have used it, in order to collect and reorganise any unbought items from the cubicles.
VisionR: Plug-and-play intelligence for physical retail
VisionR provides a simple way for retailers to make that transition. Its plug-and-play smart camera solution turns existing store environments into measurable sources of shopper intelligence without requiring complex infrastructure.
VisionR can help retailers understand conversion by department, revealing where shoppers are entering, browsing and ultimately purchasing thus helping identify missed opportunities that traditional footfall systems will not be able to see.
The platform can also provide live alerts to store staff, allowing teams to respond to issues as they happen rather than discovering them later through reports. Whether that means responding to customer demand, addressing a busy area or identifying an operational issue, real-time intelligence can help stores become more responsive.
But having the technology alone isn't really enough, as many retailers have discovered through legacy solutions. When retail operations and customer insights teams are busy enough every day, how can they be expected to sit down and decipher actions from pages and pages of data, and then present solutions to their teams.
VisionR can combine the data with consultation and practical recommendations, helping retailers turn insights into action across merchandising, replenishment and staff tasking. Highlighting the sales drop off at certain points in the day could be because of a fail to replenish rather than a lack of shopper interest. Areas could be suffering due to staff not checking on whether price indicators are clear enough to the public or whether merchandise has been altered, blocking product visibility.
The future of physical retail isn't about replacing stores with technology. It's about giving stores the same depth of intelligence that online retailers already take for granted. For retailers looking to close the gap between online and in-store analytics, computer vision and AI provide a powerful next step and VisionR makes that intelligence accessible through a simple, no fuss, plug-and-play solution.
