Current inflation rates and economic uncertainty have led to cost-cutting behaviors among 50% of consumers, resulting in a shift toward physical retail stores saving on the convenience costs of online shopping. This presents a significant opportunity for fast-moving consumer goods (FMCG) companies to boost sales in brick-and-mortar stores. Industry giants are leveraging computer vision and AI to redefine the retail shopping experience.
Here’s what the giants are up to.
Customizing Customer Experience
Hindustan Unilever Ltd (HUL) is customizing the assortment of products available at millions of stores based on the customers in the vicinity, their living standards, the product categories they have adopted and more.
Personalizing Customer Experience With Values Overlap
Kroger EDGE eliminates the need for printed price tags, cardboard promos and bright lighting, making it a cleaner and more environmentally friendly option. Customers appreciate the eco-friendly approach and find it to be a more efficient way to shop. Kroger EDGE can even interact with customers’ smartphones to highlight items on their shopping lists.
Ensuring On-Shelf Availability
The European Optimal Shelf Availability study found that average out-of-stock levels remain high at 7.1%, with store ordering, shelf replenishment and inventory inaccuracy as the main causes.
Image recognition can address this issue by detecting out-of-stock and misplaced products, counting front-facing products, detecting void spaces and calculating shelf share. On-field auditors can use smartphones to facilitate this approach, reducing infrastructure costs. They can also use the application to request inventory replenishment or place orders for out-of-stock goods.
Large FMCG firms are increasingly adopting image recognition to improve retail execution, increase brand visibility and enhance stock availability.
Reducing The Waste Of Perishable Goods
Supermarket chains such as Spain’s Dia, Italy’s Iper and Belgium’s Intermarche Jurbise use AI-based technology for grocery retail dynamic pricing to reduce food waste. The algorithm of this technology is integrated with an electronic shelf label (ESL) system that allows stores to seamlessly mark down soon-to-expire products, thereby helping to reduce the wastage of perishable items.
Minimizing Friction At Checkout
Standing in a queue is a frustrating experience for shoppers. Self-checkout is also not always easy, especially when scanning untagged produce items. Walmart’s RetailAI Fresh uses computer vision to identify products quickly, reducing average weighing time by about 40%.
Amazon introduced Amazon Go, the cashier-less store where shoppers enter the store, pick up the stuff and their bank cards get automatically charged for the purchase when they exit the store.
Kroger is also testing a new concept for their grocery stores. The store offers KroGO carts that have built-in scales and cameras. These carts allow customers to scan their groceries as they shop and pay at the cart, completely skipping the checkout line.
Blocking Organized Retail Theft
Macy’s employs facial recognition technology and other security measures in certain stores that experience high instances of organized retail theft and repeat offenders to prevent losses because of shoplifting.
Gartner’s 2022 Hype Cycle
While behemoths are rolling out many innovative technologies to redefine the customer experience in retail, here are some important things to note as per Gartner’s Hype Cycle for retail technologies, 2022.
Computer vision has evolved into advanced computer vision to encompass the growing usage and advancements of AI in analyzing real-world images or video streams, enabling real-time extraction of information from the physical environment.
Computer vision technology helps improve on-shelf product availability and store operations efficiency by utilizing real-time data gathered through in-store Internet of Things (IoT) solutions. Computer vision helps retailers make better decisions in various operational areas, such as merchandising, inventory management, customer service, pricing and promotional execution, store maintenance and loss prevention, by capturing real-time insights through advanced sensor fusion technology.
However, legacy cameras that are deployed in stores are typically not capable of running computer vision models necessary for on-shelf product recognition.
Retailers are increasingly deploying smart shelf technology as part of their efforts to digitize their stores, especially in categories like grocery, general merchandise, convenience, consumer electronics and home improvement.
Smart shelf technology can benefit retailers by improving in-store activities, increasing operational efficiency and providing real-time visibility to in-store availability. Smart shelf technology can address various use cases, such as out-of-stock detection, dynamic pricing management and product locating. Retailers can benefit from rich data monetization avenues and improve shelf space optimization.
However, smart shelves require upgrades to store infrastructure, custom shelving fixtures and network connectivity for reliable operation.
Augmented Reality, Virtual Reality And Mixed Reality
As of 2022, the utilization of AR/VR/MR in the retail industry has reached the “trough of disillusionment,” a stage in the hype cycle where early excitement about a new technology or invention has faded. However, the excitement generated by retailers’ trials of virtual environments and consumers’ fascination with immersive experiences has created some buzz. It is predicted that AR/VR/MR will gain momentum and achieve the “plateau of productivity,” a stage in the hype cycle where tech becomes widely adopted within the next decade.
In the coming years, several technologies will transition from their “peak of inflated expectations” phase, a stage where a new technology has created a lot of buzz into mainstream adoption and transformational change.
Computer vision and AI are revolutionizing the retail industry by optimizing inventory management, reducing stock-outs and enhancing shopper experiences. By understanding consumer behavior, retailers can offer personalized shopping experiences and increase sales.
The global market for image recognition software in the retail sector is anticipated to achieve a value of $3.7 billion by 2025, with a compounded annual growth rate of 22%.
However, implementing computer vision and AI technologies in retail operations may require a significant investment in infrastructure. For instance, Amazon is shutting some Fresh and Go stores as the company cuts costs. Retailers may also face challenges in integrating the technologies with existing systems and processes, resulting in longer set-up and ramp-up periods.
Despite these challenges, the benefits of implementing computer vision and AI technologies in retail operations are significant and can provide a competitive advantage.