Telefonica tech helps improve customer experiences using computer vision

SEP 01, 2021

Telefonica Tech is helping its customers realize the benefits of computer vision. It is partnering with Canada-based C2RO to offer enterprises an AI-based customer analytics solution that uses computer vision to understand the movement of people through spaces, with information segmented by demographics.

The C2RO PERCEIVE solution is designed to help organizations better understand customer behavior by providing insights into customer and visitor traffic patterns, dwell times, demographics (gender and age), and points of interest, as well as queue measurements. Telefonica Tech’s Smart Steps platform provides the socio-economic information. The solution targets venues, retail organizations, and governments, and is positioned as a solution that can help organizations improve the customer experience and optimize store and venue layouts.

Applications of computer vision are vast, ranging from quality control in the manufacturing process to monitoring of grape health in vineyards. It can also be used to analyze people, with applications ranging from determining building occupancy and traffic patterns, to ascertaining whether individuals are wearing face masks and adhering to safety protocols.

Computer vision is seen as being privacy sensitive

Artificial intelligence (AI) enables organizations to mine unstructured data for insights that can help enterprises improve the customer experience by enhancing efficiency and delivering more targeted content and communication. However, applications using computer vision are often more latency and privacy sensitive than other AI-based applications, such as predictive maintenance. They are therefore prime candidates for edge computing. Edge computing for AI processing offers lower latency than cloud computing, and therefore yields insights in near real time; it also enables analysis of data near the point at which it was generated or collected.

Many people are wary of the use of computer vision on individuals, especially when the technology is used to determine their whereabouts. Applications that identify a subject’s age or preferences using computer vision, or track individuals through a venue, may feel a bit invasive. However, if insights are used to reposition store layouts or reduce wait times, customers will reap the benefits.

Going forward, organizations will need to be discreet in their use of computer vision to analyze people and ensure that a multidisciplinary team has reviewed the ethical implications of new applications of the technology.