AI Customer Behavior Analytics System
- Multi-person Tracking – Track unlimited simultaneous customers in real time
- 17-point Pose Detection – Advanced skeletal tracking for precise behavior analysis
- Intent Scoring 85–95% – Predict customer purchase intent with high accuracy
- Area Heatmaps – Analyze a 3×3 grid of customer flow patterns
- Real-time 25–30 FPS – Smooth, instant processing for live analytics
Key Features
AI-powered analytics for a comprehensive understanding of customer behavior
Multi-person Tracking
Track unlimited simultaneous customers with robust ID management and occlusion handling
17-point Pose Detection
Advanced skeletal tracking analyzes body posture and movement patterns for deeper behavioral insights
Intent Scoring
85–95% accuracy in predicting customer purchase intent based on behavior patterns and dwell time
Area Heatmaps
3×3 grid analysis visualizes high-traffic zones and in-store customer flow patterns
Real-time Performance
25–30 FPS processing delivers smooth, instant analysis with no lag and high-precision tracking.
Analytics Dashboard
Comprehensive real-time dashboard with traffic statistics, heatmaps, and customer insights
Technical Specifications
Enterprise-grade technology stack for reliable, high-performance analytics
| AI Model | YOLOv8-Pose with custom fine-tuning for retail environments |
| Tracking Algorithm | Kalman Filter with DeepSORT for robust multi-person tracking |
| Computer Vision | OpenCV 4.9+ with GPU acceleration support |
| Programming | C++17 for high-performance real-time processing |
| Platform Support | Windows, Linux, NVIDIA Jetson (ARM-based edge devices) |
| GPU Requirement | NVIDIA GPU with CUDA support (GTX 1060 or above recommended) |
| Camera Compatibility | IP Cameras (RTSP), USB cameras, video file input |
| Data Output | CSV reports, heatmap images, real-ti |
Real-World Applications
Proven solutions delivering measurable ROI in retail environments
Retail Stores
Optimize product placement and store layout based on customer traffic, identify high-engagement zones, and increase conversion rates with data-driven decision-making.
Shopping Malls
Analyze foot traffic across multiple floors and zones. Measure tenant store performance, optimize promotional activities, and improve overall traffic flow.
Convenience Stores
Monitor peak hours and customer flow in compact retail spaces to optimize staff scheduling, allocate resources effectively, and improve service efficiency and checkout speed.
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