Recreational and service facilities such as restaurants, cafes, malls and shops spend large sums on "feasibility" studies to determine the turnout, and set mechanisms to improve services in order to attract more customers.
To minimize these expenses, a research team from the Russian State University of Management has developed a new technique that monitors and analyzes people's emotions and behaviors in public places.
The data provided by the new technique could help the owners of these places estimate the turnout, preferences among customers, and the fans of a given meal or a special ambiance in restaurant or cafe.
Mikhael Sotolov, director of the university's digital economy and accurate technologies department, said the technology in question is a program or application that processes the images it receives from cameras installed around restaurants or cafes.
The algorithms used in this technique analyze the reaction of customers sitting in a specific place, identify permanent customers who frequently visit the restaurant (mall or any other places) and analyze their behavior.
Sotolov explained that for restaurants in particular, this new program helps assess the satisfaction and happiness of customers, as well as their emotions when tasting meals, and thus helps improve performance to meet the clients' demands, without having to ask them, but by reviewing the data after each update at work, whether on the level of service or menu.
Sotolov stressed that the restaurants and cafes that adopt the "reward" system for permanent customers are interested in the new program, because it helps them identify those customers, and serve them additional services and special meals by monitoring their emotions.
At the same time, managers of restaurant chains can benefit from the program, which enables them to "realistically" assess the quality of service, and the performance of staff in different branches across the city.
The technique is not just a video surveillance feature, but a source of analytical facial expressions that help evaluate the mood and emotions of employees during working hours.
This can contribute to addressing situations that workers may face, and to determine whether they are under stress, or face problems in their personal lives and help them when they need.
