Neural Network to Analyze Shopper Behavior in Stores
Developed by researchers in Novosibirsk, the system could give marketers new insights into how customers move through retail spaces.
Researchers at Novosibirsk State Technical University NETI have developed a neural network designed to analyze shopper behavior in supermarkets, the university’s press service said. Conventional monitoring systems in stores typically count how many people enter the premises. The new system developed by the Novosibirsk team tracks detailed movement trajectories and generates a heat map. The visualization makes it possible to see which store displays attract the most attention.
Monitoring Museums as Well
One of the developers, fourth-year student Dmitry Gordienko, said the neural network helps determine where people spend the most time and how effective product placement is. Based on this information, retailers can adjust the layout.
According to Gordienko, the technology could also be used in other public venues, such as museums, to determine which exhibits attract the most visitor interest. In the future, the system could be adapted for more complex tasks and integrated with video surveillance systems.
