The past few years have been a rollercoaster ride for the retail industry. The pandemic and related supply chain disruptions led to shuttered storefronts and rampant bankruptcies. Then, last year, in-store sales grew faster than online sales, while e-commerce stocks took a big hit.
A survey from this year’s World Retail Congress suggests that the uncertain times are not over for the industry. Retailers cited rising costs, declining consumer spending and supply chain volatility as their top concerns. The survey also found that less than 13% of retail organizations are investing in technology to address these challenges, instead remaining focused on short-term solutions such as increasing prices and running marketing campaigns.
This is worrying in an increasingly competitive environment where customer engagement and user experience are becoming more important than ever. Technology – especially edge computing – forms the foundation for a better customer experience, real-time inventory management, improved security and loss prevention and in-store analytics.
It’s been five years since Amazon Go opened to the public, creating the template for the retail store of the future by letting shoppers skip the checkout altogether. Innovation has slowed since then, but edge computing will usher in a new wave of personalization and self-service for modern shoppers.
At the top of the list is computer vision – a field of artificial intelligence that enables computers to interpret digital images or video. Because it is not fast or cost-effective enough to send these images to the cloud for analysis, the processing of these images must be done at the edge.
Computer vision at the edge would create more personalized shopping experiences that synchronize in-person, online and mobile interactions. Your favorite store would recognize you when you walk in and already know your preferences (perhaps through information for a customer loyalty program), giving you an experience tailored to you. That could include customized digital signage and instant discount offers based on your purchase history.
The same cameras and sensors are also at the heart of the grab-and-go checkout system in Amazon Go stores. The store knows what you have taken off the shelf and put in your shopping cart and can charge you for it on your account linked to their system.
Edge technology gives retailers greater insight into what they have in stock, cuts inventory and provides real-time insight into best-selling items. Sensors, such as RFID tags, are attached to each product and communicate immediately when an item leaves the shelf. By continuously assessing and updating inventory levels, edge-enabled inventory management systems provide managers with valuable context for their purchasing decisions.
Unfortunately, theft is an inevitable aspect of retail. The National Retail Foundation estimates that retail losses are a nearly $100 billion problem, with evidence that the problem is growing. By taking advantage of the local processing of video feeds (rather than waiting for cloud access), security teams could act more quickly against suspicious activity or fraudulent behavior.
Self-checkout kiosks are ubiquitous today, but they add to the security challenges retailers face. The “banana trick”, where a customer calls a product using the code for something cheaper, is a real problem. In a case like this, computer vision combined with RFID sensors can make a real difference. A camera can detect the difference between a garment and a television, but probably not the difference between a Rolex and a Timex. AI models that can coordinate video feeds, RFID and transaction logs from point-of-sale, all processed at the edge in real-time, can help deal with price manipulation and ensure customers leave with the products the store thinks they have.
There is also the issue of securing the computer hardware that drives store operations. Many retailers use in-store computers as edge devices, but don’t lock them away. A sensitive piece of hardware can be compromised by something as innocuous as someone plugging in their phone. On the more sinister side, the hardware could be open to tampering and theft. That makes deploying edge devices designed to be managed remotely critical when considering deploying edge computing in a busy retail environment.
The World Retail Congress report is very telling about the current mindset of retail management. It is difficult to think beyond short-term solutions for pricing and marketing and plan for the company’s longer-term success. But the technology is available to address these long-term concerns while having a quick impact on the short-term problems. It is certainly worth noting that many retailers have invested heavily in legacy software and these systems cannot simply be abandoned. Any edge-native applications must be able to be integrated with existing systems.
It may not be particularly glamorous to admit, but the future of shopping is based on data. Retailers will use it to enable real-time interactions with their customers and automation that frees supply chain constraints. Moving retail infrastructure to the edge is key to making this future happen.
Said Ouissal is the CEO and founder of ZEDEDA. He founded the Edge software infrastructure company based on his strong belief that this decade will be about edge computing, and as with previous major shifts, this trend signals a new and radical change to existing OT, network and computing architectures.
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