Back to home page
Object detection for retail analytics and product management
Object detection for retail analytics and product management is used for automating the identification and tracking of products within retail environments, enabling inventory management, customer behavior analysis, and targeted marketing strategies.
Use case examples:
Retail Analytics
Object detection can track customer movement and behavior within stores, providing insights into foot traffic patterns, dwell times, and popular areas. Retailers can use this data to optimize store layouts, improve product placement, and enhance the overall shopping experience.
Shelf Monitoring and Product Placement
Object detection enables retailers to monitor shelf availability and product placement in real-time. By identifying empty shelves or misplaced products, retailers can ensure optimal inventory levels, reduce stockouts, and maximize sales opportunities.
Inventory Management
Object detection automates inventory management by accurately counting and tracking items on store shelves. Retailers can use this technology to streamline inventory audits, reduce manual labor costs, and minimize discrepancies between stock levels and sales data.
By using the deep learning-based model our demo allows you to accurately identify and locate the objects within the image, providing clear detection results.
Follow these steps to test the demo:
1
Upload your image.
2
Click "Process file" and get the result.