Computer vision in retail is creating frictionless shopping experiences and unlocking new capabilities for what brick-and-mortar retailers can offer. Ultimately, waiting in queues should be prevented for your shoppers, but how do we do this without having too many resources potentially wasted with a just-in-case-it-gets-busy mentality?

We’re living in an age of convenience. Shoppers can press a few buttons and have their items delivered to them the very next day. This means that in-store retailers need to prioritise experience and efficiency to match the online digital experience, and for retailers a big part of this is well-managed queues.

Computer vision is enabling advanced queue detection through the use of algorithms and image processing to automatically identify and analyse queues in real time. In this article, we’ll explore the importance of queue detection for retailers and how computer vision offers a solution that will help avoid shopper discontent.

How is computer vision being used in retail?

Computer vision is a field of artificial intelligence that enables machines to interpret and make decisions based on visual data. It mimics the human eye by effectively interpreting visual data.

When we apply this to retail, its easier to achieve enhanced customer experiences through features such as personalised recommendations, smart inventory management, virtual mirrors, and efficient checkout processes that don’t involve a cashier. These are all things online retail can’t replicate.

The best examples of queue detection uses computer vision through pre-existing security cameras, to automatically identify and analyse lines of people in various settings, such as retail stores, but it can also be used in airports, public spaces, and any other area you can think of.

The goal, ultimately, is to monitor and manage the flow of people, so you can optimise service efficiency and improve the overall customer experience. Real-time insights and data analytics reveal things like queue lengths, waiting times, and customer patterns, so we can make adjustments to counteract any bottlenecks.

What is the impact of long queues?

When retailers neglect queue management it can result in negative consequences such as increased customer frustration, longer waiting times, decreased customer satisfaction, potential loss of sales, and an overall negative shopping experience.

Shoppers often feel annoyed, impatient, and dissatisfied when confronted with poorly managed or long queues, leading to a negative perception of the retail establishment.

Imagine that after a long day hunting down each item on their shopping list, your customer has one more to go. Their legs are beginning to ache after walking 10,000 steps aimlessly around a busy, frustrating retailer environment. Your customer walks past the final shop, only to find a long queue circled around the displays. Is it really worth it? They go home without making that purchase, choosing to order the item online instead. Next time, they may remember that negative experience and complete the whole transaction online in order to avoid queues and frustrating wait times.

Shopping in brick-and-mortar stores is all about experience and how the shopper feels. Therefore, retail management and queue detection should enhance this experience, not sour it.

The business impact

Poorly managed queues have a detrimental impact, not just on brand awareness, but on sales. It has been reported that long wait times have caused 86% of US consumers to walk out of the store.

In a world full of online options, your customers won’t hesitate to put their items down and leave. This has a knock-on effect of retailers employing more staff without knowing what times they should work, based on queue trends, crowds, and busy periods. In other words, without effective queue detection analytics, it’s hard to make cost-effective decisions for the business.

Computer vision offers data analytics opportunities that we would easily miss by simply observing the shop floor. This data should be fed into all retail strategies because it tells us what customers expect from you, and what their needs are.

Through the use of computer vision, you can easily understand customer behaviour, wait times, peak traffic hours, and queue patterns. Neglecting queue detection means you’re missing out on these important insights that have the power to improve your operational efficiency.

How does computer vision for queue detection work?

Queue detection using computer vision involves the use of cameras and image analysis algorithms to automatically identify and monitor queues or lines of people in various environments.

The system recognises the presence, positions, and movements of individuals within the queue. Then, by analysing this visual data, the system can accurately determine metrics such as queue length, wait times, and overall congestion.

This real-time information is invaluable for businesses because it helps organisations optimise resource allocation, adjust staffing levels, and improve the visitor experience.

Queue detection with computer vision contributes to a smoother and more responsive customer experience by enabling timely interventions and adjustments to minimise wait times and enhance the overall service delivery.

Applying queue detection to CCTV footage

With the powerful AI of Fyma, you can use your existing CCTV cameras to effortlessly understand queue, wait times, and much more besides. Through demographic identification – without compromising on privacy – the platform can understand when a long queue is present taking into account who is together as a group and therefore is only one transaction.

Once the queue reaches a specific length, a notification can be triggered prompting the need for an additional employee to jump on the tills. Or retrospectively, you can look back over previous periods to plan better resource allocation. Fyma continuously monitors and analyses the findings to provide insights on average queue lengths, peak hours, wait times, customer density, and more.

One of the benefits of using your existing hardware with Fyma is that you don’t need to go through a time-consuming process of camera installation which may cause downtime. You can unlock insights from queue detection almost immediately.

Other best practices to manage queues

To prevent the negative impact that queues have on your sales, here are some additional tips to implement alongside Fyma’s computer vision technology:

  • Regular staff training - Ensure staffare trained to efficiently manage queues, address customer concerns, and maintain a positive and helpful demeanour.
  • Queue entertainment: Provide distractions such as digital displays, interactive screens, or music to make waiting more enjoyable and reduce perceived wait times.
  • Self-service options: Integrate self-checkout kiosks and other self-service options to give customers more control over their queuing experience.
  • Mobile queue management: Implement mobile apps or SMS notifications to inform customers of wait times and allow them to join virtual queues, enhancing convenience.

Key takeaways

Let’s be honest, no one likes to queue. By using computer vision in retail for queue detection, you can build brand awareness and increase sales by perfecting the shopper experience. Actively eliminate queues with Fyma to elevate the shopping experience and stay ahead of emerging retail trends. Explore the platform today.