Machine Learning system enters shopping centers

Machine Learning System Helps Detect Customer Moods and Identify Shoplifters

The Machine Learning system monitors customers in stores
– Detects gender, approximate age, and emotions
– Provides data for optimization

The Czech company Blue Dynamic has introduced its product eMotion, which counts visitors and recognizes their age, gender, and mood. The solution is built on Microsoft cloud services and machine learning technology. The system continuously refines and improves its output to better predict customer behavior and demographics.

The Machine Learning system delivers detailed marketing data on visitor structure and evaluates their emotions.

Whether it’s a shopping mall, retail store, bank, hotel, trade fair, or stadium, operators will have access to detailed marketing data about their visitors. Artificial intelligence evaluates emotions triggered by the services provided at a given place and time.

The system can also recommend the right clothing size for items a customer liked and assess satisfaction during checkout. Retailers can then adjust staff behavior or business processes based on typical customer emotions.

Retailers also gain insight into customer movement patterns within the store, identifying high-traffic areas. They receive heatmaps for analyzing changes over time or in response to store layout adjustments.

The collected data can also track conversion rates — how visitor numbers and time spent near a product relate to actual sales. Moreover, product presentation can be evaluated based on the emotions it evokes, providing a continuous overview of customer preferences.

The Machine Learning system can also detect suspicious or unusual behavior, helping identify potential shoplifters. It can assist shopping centers in tracking unwanted or VIP visitors by updating and sharing their profiles across stores, and alerting staff when such individuals enter the building.

The system can identify suspicious or abnormal behavior, helping prevent theft.

The solution can also integrate with IoT — for example, to display personalized ads to viewers. Imagine when the system recognizes that the same person has previously shown interest in a specific product — that’s a valuable opportunity for targeted marketing.