In stationary trading, no individual data about the personal purchasing behaviour of the customers is collected during the purchase - contrary to online trading. Only customer cards offer an individual source of information, which is only supplemented with new data at the end of the purchase. It is one of the great advantages of online shopping: data is stored automatically so that new product or service offerings can be customized individually for each customer. Thus, stationary trading lacks the option for personalised services: a major disadvantage.
The new project VICAR will work out this disadvantage.
A software tool is intended to analyze the shopping of customers in the shop in real time through video recordings. A system that analyzes data through video surveillance is already used at AmazonGo: a proof of the potential of the process. The analyses are edited by machine learning algorithms, by means of predictive algorithms the customer is to be offered other services on the way through the supermarket. The aim is to counteract market gaps, such as adapted advertising, in stationary trade.
This project is carried out with the AWS Institute for Digital Products and processes gGmbH, is predict GmbH and Schirra it E.K.. In addition, data protection law concerns are examined by the Dury law firm. Supplementary to our partners Globus SB-department Store Holding GmbH & Co. KG, Stein Promotions GmbH will accompany the work of the project as an associative partner.