Apparent Age Estimation

Shopping behaviors and product preferences vary among age groups. Capitalizing on trends within these groups requires an accurate, privacy-compliant profile of visitors to a designated space—be it a traditional department store showroom or a pop-up retail space.  

Accurate statistics on the age of potential customers can be the difference between retail success and sub-par performance, which is why demand for precise demographic data is high. Unfortunately, manual counting is invasive and inaccurate, CCTV is a privacy concern, and the point clouds from LiDAR are difficult to verify.

Data-driven businesses, retail or otherwise, that want to understand the behavior of visitors from different age groups need an automated system that can provide accurate, real-time data without offending privacy rules or expectations.   

Xovis sensors automatically detect the apparent age of visitors within a representative range with a high degree of accuracy. The result of advanced Machine Learning algorithms, the AI extension:

• Automatically counts and estimates the apparent age of anyone passing within the sensor view
• Statistical data is registered and can be communicated on a KPI dashboard
• Visitor counts and demographic data can be subsequently verified, if needed  

AI-powered Xovis sensors are embedded processing devices, which means algorithms run on the device with no need for external processing power.

Reliable and secure, Xovis sensors provide retail managers and executives with the privacy-compliant data they need for better decision-making.