Blog · 22 Mar 2022

Why computer vision is a game-changer for retail and consumer goods

Computer vision technology offers exciting benefits to both retailers and consumer goods organisations across every level of their operations.

Matt Forde
Sales Director EVERYANGLE and Computer Vision Evangelist

At the forefront of visual innovation, computer vision uses Artificial Intelligence (AI) to interpret images and videos, creating actions or recommendations based on what’s happening at that moment in time.

It’s a disruptive technology for retail and consumer goods companies, offering powerful insights to drive better decision making across every level – whether in the store, factory, or warehouse.

For too long, the retail industry has been reliant on aging and siloed CCTV systems to observe where humans can’t – with only the ability to resolve problems in retrospect, when it’s often too late. Applications of computer vision technology can help retail and consumer goods companies understand exactly what’s going on in their business and make better informed decisions using live analytics. These insights will be hugely valuable at a time when customer behaviour is changing and the focus on keeping people inside physical stores is greater than ever.

So, as more organisations start to deploy this exciting new technology across their operations, what are some of the key benefits they can expect? Let’s take a look at four key areas:

1. Reduced financial losses

Instore fraud often goes undetected, but the financial loss it causes many organisations doesn’t. Just recently, a major retailer estimated it’s cost them around $550 million. On the shop floor, fraudulent cashiers give out unauthorised discounts and refunds, activate gift cards without sale or even skip products on the scanners, also known as ‘scan avoidance’. But by syncing footage up with a cash register feed, real time detection of who was present at the point of transaction can flag up suspicious activity for further review.

Elsewhere, insurance disputes over damaged goods and careless delivery staff are a regular cause of financial loss for logistics companies, who struggle to prove when or how an item was damaged along the product journey. But to verify or disprove customer complaints, a short piece of video analysis can now capture every time an item is scanned, recording the condition, and reducing the likelihood of false claims.

2. Improved safety and protection

Since the pandemic, we’ve unfortunately seen increased reports of security threats for retailers. To improve instore safety and vigilance, computer vision applications can be deployed to look out for suspicious activity. This technology can be linked with IoT such as smart alarm systems and shutters, to trigger alerts based on the level of risk observed at the time. For example, the application might set off sirens and flashing lights if a weapon or a customer deliberately concealing their face is detected. But if a situation is less urgent, it also understands when something more subtle like an email notification or message to a member of staff is more appropriate.

In the factory or warehouse, similar detection features can make sure employees are using the right protective equipment while they’re at work. And, if necessary, this can then alert safety managers, or be integrated with the door access systems to refuse entrance to anyone not properly equipped.

3. Optimised workforces

Widespread shortages of staff are also affecting many retail organisations, and managers are now preoccupied with finding ways to use their people wisely, by streamlining and optimising their processes. This can help increase sales by making sure you have the right staff, in the right place, at the right time. Fortunately, computer vision has the potential for high accuracy people counting, to observe traffic patterns in store and identify peak business times, so that shifts can be organised accordingly.

But for manufacturers, seamless productivity has always been a high priority – regardless of their staffing situation. Before computer vision, they would rely on complex supply chain analytics software to understand their operations and streamline processes. Now, real time object detection can be combined with barcode search capabilities, so that factories can accelerate flow paths, decrease picking times, optimise their layouts and reduce overall downtime.

4. Store performance analysis

Computer vision technology can also be used on the shop floor to see how customers are behaving. Retailers will soon have the ability to gather advanced insights into the age, demographic, and gender of every customer who visits. This offers the exciting potential to measure the success of targeted advertising campaigns, based entirely on the footfall analysis of the customers instore. You can also use this data to refine how you organise your store and its stock to help increase revenue.

One of our customers managed to reduce the number of abandoned baskets by 92%, using a similar function to drive performance improvements at service level. Through the application they could detect and monitor how long people waited in line and could send out message alerts to prompt their staff into assisting them.

Always looking ahead

We’re constantly discovering the possibilities of this new technology and we’ve only just scratched the surface in this blog post. Along with BT, EVERYANGLE are proud to offer cutting edge innovations, like computer vision, that help our retail and consumer goods customers do things simply and effectively. Because we recognise the importance of responding to the evolving needs of the industry, we’re constantly updating our offerings and improving our service. By partnering with BT, our customers have a choice of connectivity, platforms and software and access to their extensive ecosystem of partners for support. Plus, they can manage your service end-to-end on your behalf.

If you’d like to find out how we can help your organisation experience the benefits of computer vision technology, please don’t hesitate to get in touch.

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