The smart queue management platform brings numerous benefits for retailers. It can also identify cart abandonment actions, giving an exact estimate of revenue lost due to long lines. The platform uses AI and machine learning algorithms to track individual customers until they checkout, identifying their wait time as well as the size of the queue at any given time. The platform uses video surveillance cameras already installed at the checkout location and requires no extra hardware investment, as usually the checkout area is well surveyed. Computer vision turns video footage into actionable business analytics. These crowded retail environments require a different approach.Įnter the world of computer vision powered queue management software. However, they are ineffective in retail environments such as line management in grocery stores and supermarkets.
Token based queue management platforms can help quantify the wait times and customer numbers. Time to checkout is fundamental in optimizing retail store performance, as it affects so many performance indicators. Introducing Computer Vision Powered Queue Management Platform Ask the manager how much time customers wait in line during peak hours on weekdays or what is the average size of the queue – and you will get a puzzled look in return. Just ask a store manager what is the average number of items scanned by cashier per minute and you will get a precise number. Long queues at the supermarket cause shopper fatigue, decrease customer experience and result in shopping cart abandonment.Īlthough retailers turned so many business processes into exact science, queue management remains a mystery. That might add up to 6 months of waiting for things during a person’s lifetime!
According to research, people spend from 3 to 5 days per year queuing up.
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