Store traffic includes all types of visitors, not just customers. Employees, delivery personnel, and repeated visitors can inflate traffic numbers without contributing to sales. This is why raw traffic often does not match revenue. Valid Footfall helps align traffic data with actual sales performance.
AI improves people counting by using computer vision techniques such as object detection, tracking, and re-identification. These technologies help identify individuals, track movement, and reduce duplicate counting. The final output is more accurate when converted into Valid Footfall, which represents unique customer visits.
Retailers use people counting systems to understand store performance, peak hours, and customer flow patterns. However, traditional systems only provide raw data, which can be misleading. Modern analytics enhances this by introducing Valid Footfall, which filters out non-customer traffic and provides a clearer picture of real customer behavior.
Invalid traffic refers to non-customer entries such as employees, delivery riders, and repeated visits by the same person. These entries do not represent purchasing intent but are still counted in raw footfall systems. Valid Footfall removes this noise to ensure accurate retail analysis.
Valid footfall is a refined retail analytics metric that represents the number of unique customers visiting a store after removing noise such as staff entries, delivery personnel, and duplicate visits. Unlike raw footfall, which simply counts all detected entries, valid footfall focuses on real customer traffic. This makes it a more reliable foundation for calculating conversion rate, store performance, and retail ROI.
People counting in retail stores refers to the process of detecting and measuring the number of people entering or exiting a physical store using sensors or AI systems. These systems can be based on infrared sensors, video analytics, or AI-powered cameras. However, raw people counting does not distinguish between customers, staff, or delivery personnel. This is why many retailers are now shifting toward a more refined metric called Valid Footfall, which focuses only on unique customer visits after filtering non-customer traffic.
Footfall refers to all detected human entries in a store, while customer traffic refers to actual potential buyers. The key difference is that footfall includes non-customer activity such as employees and couriers. To bridge this gap, modern retail systems use Valid Footfall, which filters raw data and isolates real customer visits for accurate business analysis.
