A privacy-compliant, visual tracking of customers’ shopping behavior in brick-and-mortar retail.
A stationary shopping experience with the advantages of individual product recommendations and active advice, analogous to the online store.
The stationary retailer can use data on his customers ad hoc and, based on this, place products optimally, deploy staff efficiently and avert shoplifting. All while the customer is still in the store.
Online retailers have a big trump up their sleeves: endless knowledge about their customers. In an interview with Marilyn Repp, Angela Promitzer of the August Wilhelm Scheer Institute reveals how brick-and-mortar stores can catch up.
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In a nutshell
The VICAR research project aims to record, analyze and visually display the shopping paths of consumers in stationary retail in real time. Based on this data, customers can be given individual product recommendations during their shopping trip and actively provided with consulting staff on the floor. For the retailer, the real-time customer flows are visualized in the VICAR system in compliance with data protection regulations. This can then be used to derive the optimal product placement, efficient staff deployment and anomalies such as attempted thefts. And all this while the customer is still in the store. In addition, a prediction of future behavior can of course also be made.
The basis for this data collection is video data that is currently used for theft protection. Using innovative technologies from the field of machine vision and learning, the existing movement data is captured and analyzed. The AI-based anomaly detection then identifies anomalies in customer behavior and walking routes where staff deployment would be helpful.
In various sectors, online retail is increasingly cannibalizing brick-and-mortar retail. According to the German Retail Association’s “Online Monitor 2019,” fashion retailers, electronics suppliers, and furniture stores in shopping streets and shopping centers in particular are suffering from the migration of customers to online stores. Generation Z (19-24 years old) already makes more than half and baby boomers (56-79 years old) a third of their spending online. And the trend is rising.
In addition to the economic advantages, eCommerce also has a clear competitive advantage, the evaluation of customer data in real time. Through various tracking options, customer behavior can be tracked and analyzed online. Products viewed, the contents of the shopping cart or the shopping history can still be analyzed directly during the shopping process and used for real-time recommendations, for example. In this way, individual tracking and future customer loyalty can also be implemented.
Electrical appliances online: 31 %
Fashion shopping online: 27,7 %
The August-Wilhelm Scheer Institute develops two basic components:
Camera-based tracking. Using innovative technologies from the field of machine vision, we enable the evaluation of existing video data as the basis for AI-driven anomaly detection.
AI based anomaly detection. Machine learning is the basis for evaluating customer behavior. AI-based anomaly detection shows anomalies in customer behavior, walking paths and identifies situations where staff deployment would be appropriate.
The VICAR project is funded by the German Federal Ministry of Education and Research.