Advanced AI Facial Recognition Technology
Utilizing advanced AI facial recognition technology with a high accuracy rate of 85–99%.
The camera’s built-in NPU (Neural Processing Unit) enables on-device deep learning processing, reducing bandwidth usage and eliminating dependence on internet connectivity.
Operating Principle
- The camera is installed at a location where customers pass through, facing directly towards them to capture the best possible facial images.
- Each customer entering the store is recognized and assigned a unique Face ID, stored for a duration equal to a single customer visit session. Once this time expires, the Face ID is deleted.
- If a customer passes in front of the camera multiple times, the system will record only one Face ID and will not count them multiple times.
- The system can generate statistical reports based on specific time frames or daily data.
Report Data Export
- Visual Reports for easy daily management.
- Ability to integrate raw data with ERP platforms.
Benefits of the Solution
Conversion Analysis
Analyze conversion percentage for orders (measured as number of orders or revenue per store visitor).
Comparative Analysis
Analyze and compare store visitor counts across multiple time frames (hourly, daily, monthly, yearly).
Performance Evaluation
Evaluate the effectiveness of campaigns and compare performance across different store locations.
In-Depth Analysis
Demographic and behavioral analytics: gender, age groups, behaviors and customer habits.
Who Is This Solution For?
The customer footfall counting (traffic counting) solution is ideal for large retail chains that need to gather store visit data to improve and optimize management KPIs, adjust performance metrics, and refine operational policies.
It is suitable for:
- Stores, shopping malls, restaurants, and other businesses that value customer visit statistics.
- Businesses seeking to integrate visitor traffic data into their operational platforms via the solution’s open API.
Implemented Clients
Customer Counting Solution