A new startup company has developed biometric identification techniques to extract customer data using existing in-store cameras.
One way for businesses to optimise their products and performance is knowing exactly who their customers are and how they spend their money. We have already seen software to help businesses know more about their customers. These include geo-targeted pricing and a B2B marketing platform. But collecting this type of data is easier for online businesses than for bricks-and mortar stores. Recently, machine learning experts at the UK’s University of Southampton developed a deep learning technology that can capture data from video footage. The start-up, Aura Vision Labs, is now progressing from Southampton’s Future World Incubator and joining the Collider accelerator, after completing a GBP 100,000 seed investment deal.
Furthermore, Aura founders Jaime Lomeli and Daniel Martinho-Corbishley have developed tech that can analyse video footage to track people in real-time, without relying on visible faces. From any camera, the technology can detect the gender, age and clothing style of every person in a crowd. There are more than 245 million video surveillance cameras in operation globally. Aura’s technology can use these existing security systems to provide retailers with a cost-effective way to gain accurate, real-time information on their customers.
Aura Vision’s technology can be used to link customer demographics to their shopping journeys through the store. Unlike loyalty cards, Aura is able to protect customer identities, as the system doesn’t rely on accessing sensitive personal information. According to Martinho-Corbishley, “Our cloud-based visitor analytics platform gives retailers a live view of visitor numbers by demographic. Also accompanied by a detailed understanding of their dwell time, the products they interact with and products they go on to buy”.