Turning up the heat on video analytics

For the average person watching people come and go from a retail store, a sporting event or even a hotel lobby, the movements can seem random, with no apparent pattern behind them.

But for those who are deploying the latest in video analytics, those same travels within a defined space can be tracked and analyzed to allow store operators, arena owners and hoteliers to make key business decisions related to merchandising, personnel positioning and, of course, security.

Heat mapping — one of the newest analytic tools available — provides a visual interpretation of traffic patterns. The movements of those people who appear to be merely walking through the store are now captured and analyzed, and the resulting data can be looked at more closely.

video analytics heat mappingThis becomes important in a retail setting as stores look to maximize the effectiveness of their displays and increase overall store performance. A promotion may seem successful on paper, but if no one can find the display within the store, or they don’t stop to really look at it, then sales will suffer. Heat mapping can show retailers the traffic patterns within the store and help them determine where the items should be placed.

Beyond displays, stores and venues can also use heat mapping to help them determine where to place permanent items such as ATMs. It may seem logical to put the machine at the entrance, but if the goal is to get people into the building, and heat mapping shows that people use the machine but then turn away, it may be better to place it within the facility.

Closely aligned with heat mapping is another analytics tool that helps make sense of the traffic analytics. Once it’s established where and how people are moving within a retail venue, the next move is to see how long they dwell or linger within the area, checking out the products on display.

Looking at the retail example, once the display is in its optimal location, the goal is to get shoppers to look at the products being sold and make a purchase. Dwell data tells us how long someone is stationary; linger does the same, but the person is usually milling about, rather than standing in one spot.

By integrating dwell and linger information with Point Of Sale data, it is possible to determine how many people stopped in front of the display for several seconds, or moved within the general area, are converted to buyers.

Dwell and linger data can also be used to determine how to assign personnel within an area. If analytics show that people are milling in a specific spot within a store, it may be necessary to send over a salesperson to offer assistance or, in the case of hotel, an additional desk clerk. Analytics that show a group gathering for a pre-determined period of time could also be a sign that security needs to check out what is going on as it could indicate suspicious behavior, such as a shelf sweep.

Of course, all this information won’t be of much good if it isn’t easy for the system’s user to retrieve and analyze the data. While security personnel are familiar with analytics, it may be new to those on the operations side. But today’s analytics are tailored in such as way that the information is accessible to everyone, no matter their IT expertise and no matter the size of the operation.

 

Do you have any questions about Heat Mapping? Please ask in the comments section below.