ON TREND
CAN RETAIL HANDLE THE DETAIL?
NOVEMBER 2026
COMMENT
CAN RETAIL HANDLE THE DETAIL?
“Retail is detail,” goes the prescription for successful shopkeeping but in a world in which everything is a data point is there a risk that retailers could drown in information? Certainly, real-time analytics are needed to manage the supply chain, track products, monitor store visitors and keep stock and employees secure, but when everything’s analysed right down to the level of a smart shelf, is it possible to collate all the details into a meaningful mélange of actionable insights?
The answer seems to be “yes and more than that.” These data points not only provide granular visibility to enable retailers to deliver improved experiences to customers, they also allow for automation of key operations, such as unmanned stores. To do this effectively and safely, the minutiae of every element of every retail operation from the point of manufacture to the point of payment needs to be tracked, analysed and acted upon.
AI technologies are indispensable in enabling the analytical and decision-making impulses and to ensure they are precise and accurate but it’s the fundamentals that retail IoT really relies on. That’s connectivity to link the supply chain with the store floor and devices to enable automated scanning of products, stock levels on shelves and in store’s backrooms and then the ability to make that information available.
Importantly, that isn’t only for the retailer. Today, modern retail relies on letting customers know that an item in their size and their selected colour is in stock on the day they plan to visit a retail location. Similarly, in food retail, consumers want all the detail. Where was the crop grown, how was it harvested, how many food miles have been involved in its delivery, was trade fair, what’s the shelf life and what’s the use by date?
Retailers have been handling greater and greater detail over the past three decades as systems become more powerful and customers become more demanding. Now, automation, AI and hyper-connectivity mean the answers systems need to provide are external as well as internal. Current technologies provide the tools to float across data lakes, harnessing insights to create value. Sometimes the seas will be choppy but there’s no reason for retailers to drown in the detail.
INTERVIEW
“Consumer mobile is more like a broadband internet service but IoT needs different types of packets, different frequency of delivery and different charging models.”
Paul Bullock
group chief product officer,
Wireless Logic
In the Q3 2026 issue of IoT Now magazine we looked extensively at mobile data packet gateway (PGW) services. Here, Wireless Logic’s Paul Bullock explains how enterprises can benefit.
IoT Now: How have PGW services developed to support IoT?
Paul Bullock: PGWs have evolved to be fundamental components of managed network services in mobile. In contrast to consumer mobile, IoT is a sophisticated managed network service with the same networking demands as large enterprise wide area networks. They also have developed to cope with specific constraints and design considerations of mobile networking and IoT devices. Consumer mobile is more like a broadband internet service but IoT needs different types of packets, different frequency of delivery and different charging models. For example, many IoT devices go to ‘sleep’ for long periods but the PGW needs to keep track of those devices so that when they wake up they’re handled properly.
IoT Now: What are the key benefits of PGW services for MNOs and MVNOs?
PB: PGWs allow differentiated traffic policies and customised network configurations for specific enterprise needs. Importantly, modern PGWs can be distributed around the world to improve latency and throughput for bandwidth hungry devices. A PGW is one of the things that allows an MVNO to differentiate in the way they deliver services.
IoT Now: Do PGWs level the playing field enabling smaller MNOs and MVNOs to offer the same global presence as the large multinational carrier groups?
PB: Yes, to some degree. Distributed packet gateways enable smaller organisations to have much bigger network footprints. They’re only one part of the story though; network management expertise, upstream suppliers and many other components of mobile cores are costly and complex and hard to deploy. If a small firm is advertising global presence, it’s worth close analysis of what’s really in place.
IoT Now: Do enterprises ever notice that their provider is delivering their service via PGWs?
PB: All mobile communications involve a packet gateway somewhere and enterprises usually only notice when they break. Sophisticated buyers want to understand network elements and policies. MVNOs with strong networking capabilities can often differentiate by customising services to a much greater extent than MNOs, so an enterprise notices that.
IoT Now: How important are PGWs to supporting the complex communication needs of AI workflows? Is AI used to optimise PGW usage?
PB: AI of the type we’re used to now – large language models (LLMs) – is still uncommon in network management because engineers don’t like hallucinations. Increasingly, machine learning AI is used in network management to automate tasks and respond to various situations. There is substantial use of AI in analytics and anomaly detection as well with the 5G network data analytics functions (NWDAF) which is a technology for handling network data for use by AI. There is discussion of moving more PGWs to the edge of networks to increase performance but this is still in the planning stages.
MARKET REPORT
Can retail IoT handle the detail?
Exciting new retail use cases are seeing connected experiences reinvigorate retail environments. Retailers are in a tense battle to attract customers back to their stores so the experience needs to be richer and also frictionless. Dropped connections that leave the shopfloor blind to stock levels or unable to process payments immediately, result in poor experiences and a return to online shopping.
At the same time, innovations such as unmanned stores fundamentally rely on cameras and scanners to accurately charge for purchases and prevent pilfering. Retailers therefore rely on a growing range of IoT-enabled devices from cameras to barcode scanners to temperature and shock sensors to ensure they can deliver an efficient, appealing and modern experience. Traditional data points are still essential for ensuring the supply chain is able to support the retail floor so technologies including barcodes, near-field communications (NFC) and Bluetooth Low Energy (BLE) are enablers of intelligent, connected retail.
The elephant in the room is, of course, AI. The application of AI to retail analytics helps eliminate wastage and optimise supply chains and retailers are increasingly utilising the technology to deliver richer in-store experiences. The move to AI-augmented experiences and further reliance on AI in store operations is seeing more intelligent retail and helping to underpin predictions for greater adoption of IoT technologies across the sector.
Connection growth
Analyst firm ABI Research has reported that the number of global Internet of Things (IoT) connections across the retail sector will increase from 419 million in 2025 to 583 million in 2030, growing at a compound annual growth rate (CAGR) of 7%. The firm says that while fixed line connectivity is and will remain, by far, the most common solution, accounting for 323 million connections globally by 2030, cellular connections remain distant followers. LTE Cat-1, achieving 86 million retail IoT connections, is a distant follower with LTE Cat-M, NB-IoT and LPWA-proprietary connections experiencing even lower adoption. 4G dominates the cellular technologies, with legacy standards, such as 2G and 3G, outdated and 5G often being overkill for retail applications, the firm concludes.
Grand View Research expects the global IoT in retail market size to grow from US$108.6 billion in 2026 to US$488.5 billion by 2033, at a CAGR of 24.5% from 2025 to 2033. North America has dominated the market, accounting for revenue share of 31.0% in 2024. Market growth is primarily driven by the increasing deployment of smart shelves and RFID technologies, rising demand for personalised shopping experiences, continuous advancements in cloud computing and edge analytics, and the expansion of omnichannel retail strategies that rely heavily on IoT-based insights, the firm says.
Figure 1:
Grand View Research has found rising demand for NFC technology, coupled with the increasing number of projects by mobile operators and device manufacturers to increase the coverage of NFC-based transactions. The rise of mobile wallets has modernised payment methods, boosting NFC adoption in the sector. Supermarkets and medical stores, for example, implemented NFC technology to accelerate check-out processes. The increasing application of this technology will contribute to segmental growth over the coming years, the firm says.
BLE is expected to see significant growth thanks to its low-power, cost-effective and versatile nature, making it a popular choice for connecting IoT devices. Bluetooth’s compatibility with smartphones and tablets contributes to its prominence.
Shoppers’ choice
In its recent report, ‘The Omnichannel Illusion: Customers can’t value what they don’t experience’, Sherwen Studios surveyed 2,000 UK shoppers to gauge their views on retail technology. The research confirmed that stock visibility was one of the key priorities for customers shopping in-store. The study uncovered that 28% of UK adults want real-time stock checks available directly from their phone, 26% would be more likely to visit a physical store if they could check real-time stock availability before travelling and 25% believe that real-time stock visibility between stores and online should be a standard retail feature.
“We discovered that customers are most receptive to connected experiences that make their shopping faster, easier, and more reliable, rather than innovation for its own sake,” says Matt Sherwen, the managing director of the digital consultancy. “Some of the most commercially valuable IoT technologies in the retail sector are not the newest, most sophisticated or the most attention-grabbing. Tools such as connected stock management systems, smart shelves and RFID tags have been around for years, but they remain among the most valuable because they solve the customer problems that matter. These technologies provide real-time stock updates to customers, so they know what they want is readily available, and help retailers reduce lost sales.”
Sherwen adds that retailers have also invested in smart checkouts that automatically recognise items and enable mobile scan-and-go checkouts. These rely on connected sensors, real-time data, and store navigation apps to reduce queue times and speed up the checkout process. They are also welcomed by customers who want seamless experiences every time they shop.
Physical meets digital
Enabling this in-store acceleration often starts with streamlining the supply chain to ensure stock is in the right place at the right time to meet customer demands. "What I’m seeing from our customers across the market is a real push to connect the physical product with its digital identity and data,” says Stephen Tagg, the global application sale manager for software at Markem-Imaje. “That connection has to start on the manufacturing floor – where the IT world of information finally meets the OT world of production. Manufacturers are realising that without itemlevel identity created at the source, all the downstream smart retail, traceability and consumer engagement promises fall apart.”
"The biggest IoT innovations in retail right now are realtime inventory visibility, dynamic pricing, recall management, personalised customer engagement, autonomous store operations and endtoend supplychain transparency,” adds Tagg. “One of the innovations is the shift from traditional 1D barcodes to GS1 Digital Link-enabled 2D codes. This shift is changing the role of packaging from a static information carrier into a connected access point for retailers, brands and consumers.”
"For retailers, GS1 Digital Link 2D barcodes can support more efficient inventory management by enabling access to product information such as inventory levels, sell-by dates and recall notices,” he explains. “This creates opportunities to reduce manual labour, improve data accuracy, support dynamic pricing and manage products more effectively according to shelf life. A clear example is the use of 2D barcodes to help retailers discount and move products based on sell-by dates, reducing waste from in-store expirations. They can also facilitate real-time recall alerts, helping prevent compromised products from leaving the store and extending notifications to consumers if the product has already been purchased.”
Create connected environments
While innovations are coming through in function-specific areas, retailer attitudes are moving away from discrete solutions and looking to put in place holistic systems that meet the changing needs of consumers and the business while integrating the supply chain and embracing the potential of AI.
“One of the biggest changes we're seeing is that retailers are moving away from thinking about individual technologies and towards the store as a connected environment, where technologies increasingly work together,” says Mark Duckworth, the UK country manager at SOLUM. “Using electronic shelf labels (ESLs) as an example, they started primarily as a way to display pricing digitally, but they're increasingly turning the shelf edge into a connected execution layer for pricing, promotions, inventory and customer-facing information. That gives retailers greater visibility over what's happening in store and, importantly, allows them to act on that information much faster.”
“We're also seeing growing use of sensors, digital displays and other connected technologies that can help retailers understand and respond to what's happening across the store,” he adds. “As these technologies come together, the opportunity is to create a much more responsive environment where information can move between central systems and the shop floor in real-time.”
“Retailers already have huge amounts of information available to them,” explains Duckworth. “Now, what’s changing is their ability to connect those signals with the people, devices and systems that can act on them while the information is still useful. That's particularly important as retailers adopt more AI. AI can make a sophisticated recommendation around pricing, inventory or promotions, but that recommendation only creates value if the retailer can translate it into action quickly and accurately in-store.”
Product provenance
Another key driver is that consumers want to know the provenance of the products, particularly food, that they buy. "Consumers are demanding deeper visibility into how products are manufactured, what materials were used and where those materials originated,” says Tagg. “Recent food recalls have only intensified the need for full supplychain transparency – from farm inputs all the way to the consumer’s hands.”
"From a technical standpoint, this transparency is only achievable when product identity is created and bound to operational data at the OT layer, not bolted on later,” he explains. “The manufacturing environment generates the critical events – batch genealogy, process parameters, quality checks, equipment states and environmental conditions. However, historically, this data has remained trapped inside PLCs, SCADA systems and MES silos.”
"Our role is to unify these OT event streams with IT data models and expose them through a persistent, standardsbased product identity,” Tagg adds. “By linking serialised identifiers to structured manufacturing and supplychain data, the final product becomes a digital anchor that carries its entire lifecycle history.”
Autonomous AI agents
While unification of OT and IT is an important enabler of product identity and it’s obvious that long-established technologies from barcodes to short range wireless technologies are enabling enhanced retail, the revolutionary step is the application of AI to retail processes. “One of the most significant innovations we are seeing in the retail market is agentic commerce,” confirms Lawrence Roycroft, the vice president for EMEA at KIBO Commerce. “This technology addresses the struggles of data overload and reactive decision-making by deploying autonomous artificial intelligence agents that connect, interpret and act on vast quantities of retail data to guide intelligent and timely actions.”
“AI agents unify data to provide a single source of truth and an actionable view of the business and, because systems continuously scan data streams for changes and patterns, they anticipate and streamline manual processes and address any issues. These include updating pricing and promotions, engaging with shoppers and handling demand spikes or impending stockouts before they become problems,” he adds. “Instead of sifting through dashboards and reports, businesses can rely on the technology to act when an opportunity or risk is detected, for example pricing optimisation or stock replenishment. The AI agents will continuously learn from outcomes to refine their actions.”
There are numerous areas in which AI can be applied. “AI is obviously playing a growing role, particularly in areas such as demand forecasting, pricing, inventory management and promotions,” confirms Duckworth. “The important point is that these technology stacks don't operate in isolation. As stores add more connected devices and richer data, the underlying connectivity architecture becomes just as important. Different applications place different demands on coverage, capacity, responsiveness and power, so there isn’t necessarily one connectivity technology that is right for every workload.”
“We're also seeing greater intelligence being pushed closer to where retail actually happens,” he says. “Sensors and computer vision can capture and interpret conditions in the store, while electronic shelf labels, digital displays and other connected endpoints help translate that intelligence into action at the shelf edge. There isn’t necessarily one technology that solves every connected-store challenge. Different store formats and applications have different requirements, so retailers need to think about how connectivity, devices, software, and existing systems work together across the physical environment. The real innovation is increasingly in connecting intelligence with consistent execution.”
By the numbers
0 million
global IoT connections across the retail sector in 2030, rising from 419m in 2025. (ABI Research)
0%
of survey respondents say stores being too crowded puts them off physical shopping. Long checkout queues (33%) and out of stock products (26%) are further barriers. (Sherwen Studios)
US$0 billion
global IoT in retail market value in 2033, increasing from US$108.6bn in 2026 (Grand View Research)
0%
of UK adults would be more likely to visit a physical store if they could check real-time stock availability before travelling (Sherwen Studios)
Experiences versus operations
There are two key drivers for retailers. One is to optimise operational efficiency, the other is to provider richer, more appealing experiences to customers. The two aren’t necessarily in conflict and sometimes technical solutions can overlap, serving both aims simultaneously.
“Our research confirms that IoT adoption in the retail sector is simultaneously improving operational efficiency and enhancing customer satisfaction,” confirms Sherwen. “That’s because the technologies that enable retailers to work better are the ones customers value most. It became clear to us that customers appreciate the outcomes of connected experiences enabled by IoT because they can see how these experiences improve their shopping journeys.”
“One finding that really jumped out to us was that 12% of shoppers would be more likely to visit a physical store if better store navigation or product-finding tools were available,” he says. “While that may appear to be a relatively small proportion of shoppers, it demonstrates how IoT technology can create real value for retailers and customers. For retailers, this requires sensors, digital displays, smart shelves, location services, and mobile apps to work together in real-time. However, improving product discoverability can boost sales and reduce the demand on shop-floor staff for routine assistance. For customers, it reduces the frustration of searching for specific products in large stores.
“These are all examples of connected retail experiences where operational improvements will almost certainly translate into better customer experiences,” Sherwen concludes. “Retailers don’t need to choose between operational efficiency and customer needs, because successful IoT adoption can address both.”
For Tagg at Marken-Imaje, enhanced retail experiences start at the manufacturing facility. "For manufacturers, the next step is also about closing the IT/OT gap,” he says. “Enterprise systems, production equipment, coding infrastructure, verification tools and operators need to be connected so information can move reliably across the factory and into the wider retail ecosystem. The future will not be defined only by more machines, more automation or more software. It will be defined by how well information moves from production to retail to the consumer."
The retail industry has embraced new technologies for decades adopting self-service, contactless payments and new in-store technologies. “In-store retail tech is already proliferating at speed, so the technology is there,” says Duckworth. “The next phase will be connecting and scaling what is already there. Retailers are building increasingly sophisticated capabilities around AI, forecasting, pricing, inventory and retail media. As those capabilities scale, they will increasingly have to consider whether the infrastructure underneath them can support more device fleets, larger volumes of data and more frequent interactions across the store.”
Shelf-edge intelligence
“We'll see more intelligence reaching the shelf edge, with connected technologies helping retailers act on information faster and giving them better visibility into what's happening in store,” he adds. “Just as importantly, the information coming back from the shop floor can help inform the next decision. The store of the future will be defined not only by how much intelligence it contains, but by how effectively technology works together, allowing retailers to understand what's happening in real-time and respond faster to both operational and customer needs.”
For Roycroft at KIBO Commerce, it’s the combination of data integration, simple automation and robust governance that will build the foundation to extract maximum value from retailers’ investments in agentic commerce. “With AI increasingly being used across multiple applications, from email to CRM, ERP to warehouse management, interoperability is a vital consideration,” he says. “While there are a few very large companies reliant upon a single vendor ecosystem for the entire tech stack, the vast majority of organisations have a complex mix of vendors. Cross business AI adoption will by default demand integration with diverse systems – and that means organisations need the freedom to choose between AI models that best meet operational needs today and in the future. A Bring Your Own AI Model (BYOM) not only allows organisations to choose whichever LLM is best suited to a specific requirement today but it also provides the opportunity to embrace new technologies both as they emerge and as they support business opportunities.”
EDITORS TAKE
CAN RETAIL HANDLE THE DETAIL?
Have your say
Give us your opinion on the topic. Leave a voice note and hear back from George