Earlier this month the National Retail Federation (NRF) held its annual Big Show in New York City. What used to be an old-guard show featuring some innovations in point-of-sale (POS) systems and displays has turned into a pageant of IoT, robotics, biometrics, payments, cloud and AI/ML riches, among other things. The technology world's most prominent playersβ€” including Google Cloud, Microsoft, Qualcomm, Nvidia and moreβ€”were there to show off new innovations for retail. There were plenty of startups and lesser-known brands on display, showcasing technologies that are poised to take retail to the next level, deliver more customized omnichannel shopping experiences, reduce payment friction and increase efficiencies throughout the buying lifecycle for brands and consumers.

As consumers return to in-store shopping in the wake of the Covid pandemic, retailers are focused on three crucial aspects of the shopping experience: inventory management, store (or site) productivity and seamless checkout. While consumers are used to the Amazon Prime-led convenience of the e-commerce experience, and companies continue to focus on e-commerce innovation, retailers want to draw shoppers back into physical stores because they make more money on average per trip than they do with online shoppers.

Here we'll look at some of the companies and products showcased at NRF 2023 that maximize the three pillars of an excellent shopping experience.

Inventory Management

Supply chain issues have hit the retail industry particularly hard. To stay competitive in this sector, businesses must have an up-to-date, comprehensive understanding of their inventory. When supply chain issues do arise, it is even more important to track inventory accurately, anticipate customer needs, and ensure that goods are in the right location at the right time.

During NRF, Microsoft unveiled two new Microsoft Cloud for Retail productsβ€”Store Operations Assist and AiFi Smart Stores Analytics.

Microsoft Store Operations Assist is a cloud-based software solution designed to help retailers streamline store operations and drive sales. It provides a unified view of store data, enabling retailers to manage inventory, pricing, promotions, customer relationships and more. The platform also offers advanced analytics to gain insights into customer behavior, sales trends and other vital metrics. By configuring Store Operations Assist in Microsoft Teams, leaders and managers can enhance collaboration, boost productivity and support store associates throughout the sales cycle and in every aspect of their performance.

Smart Store Analytics is a cloud service included in the Microsoft Cloud for Retail product suite, developed in collaboration with AiFi, an autonomous shopping technology startup. Smart Store Analytics gives retailers using AiFi's technology the ability to gain insights into shopper behavior and operations within their smart stores. I wrote about AiFi in a previous article, and offered my insights on the industry in a TechCrunch article covering the announcement of AiFi's Series B. Over the past year, I’ve watched the company rapidly expand its partnerships and frictionless shopping footprint, and I think this partnership with Microsoft paces them even further ahead of the competition.

Frictionless shopping or "autonomous shopping" and self-checkout have gained traction in the past year, particularly in Europe. However, retail theft is also at an all-time high, and increasing food prices have exacerbated shrinkage. A handful of major tech players have introduced AI-powered solutions to help retailers combat theft or mistakes at checkout that lead to losses. At the NRF event, Qualcomm showed off its partnership with Everseen, an AI and computer vision solution that addresses a full range of loss prevention needs. The partners demonstrated a visual AI solution powered by Qualcomm's Cloud AI 100 processor that virtually eliminates loss or theft at self-checkout. By detecting unscanned or scanned-and-switched items, the solution creates alerts that require manual override by an employee, eliminating costly theft and mistakes at checkout.

Also addressing the massive shrinkage problem in retail, Nvidia showcased its Retail AI Workflows to improve retail applications. The workflows come equipped with thousands of pre-trained images of commonly stolen products such as alcohol and can be trained on hundreds of thousands of additional items. The software can be incorporated into existing store applications at the point of sale and works by scanning and comparing the purchased item to a database of products, ensuring that the item and purchase price match. The workflows are compatible with servers from providers such as Dell and Lenovo, which run Nvidia GPUs in larger retail stores.

Store Productivity

Attrition has always been a pressing issue in retail that naturally affects productivity. According to a McKinsey study, nearly half of frontline retail workers and 63% of retail managers consider leaving their jobs within three to six months of being hired. Frontline retail attrition is often caused by employees feeling that their work could be more meaningful; this includes dealing with tedious tasks that have no social benefit or are not connected to the organization's mission. As with many industries, automation of mundane tasks will free workers to focus on more critical workβ€”in this case, delivering an exceptional shopping experience.

Automation in retail spans from workforce scheduling tools to picking and packing to robotic floor scrubbers and everything in between. Google Cloud showcased several new and enhanced offerings that help retailers with shelf checking, personalized search and making better product suggestions.

Google Cloud and Brain Corp, an AI core technology robotics company, announced a partnership to offer an end-to-end in-store shelf analytics solution, BrainOS Inventory Insights, for retailers utilizing Google Cloud's Vertex AI Vision platform and BrainOS-powered inventory scanning robots. The proprietary solution will deliver next-generation in-store inventory data analytics to retailers. Combining AI and data analytics gives retailers actionable insights on store inventory, product location, planogram compliance and other data to optimize operations and sales. Not only does this give retail workers and managers data to improve efficiency, but it also frees their time to better serve customers and engage in more meaningful work that is crucial to their workplace satisfaction.

At the show, Google Cloud focused on the online shopping experience and delivering that same "store productivity" to e-commerce. Research by Google Cloud revealed that most (75%) shoppers prefer companies that tailor their interactions and contact them, while an even higher proportion (86%) seek out brands that understand their interests and needs. Google Cloud's Discovery AI solution for retailers has a new feature called Browse AI, which uses machine learning to determine the best ordering of products for an e-commerce site when shoppers select a category. This process is typically manually done and based on bestsellers or seasonal items. With Browse AI, shoppers on a retailer's site essentially have an AI acting as a personal shopper choosing things based on their behaviors and taste. Browse AI is API-driven, making it easy for retailers to integrate into their existing technology.

Seamless checkout is king

While inventory management, store productivity and other factors are critical to a retailer's success, checkout can be a make-or-break experience. Retailers may have an exceptional omnichannel experience, all the proper inventory and a high level of operational efficiency. Still, if a customer is ready to check out and the line goes halfway to the back of the store, that customer may not return. What's worse, they may walk out.

Amazon actually encourages consumers to walk out with its Just Walk Out technology featured in its NRF booth. Just Walk Out uses computer vision, sensor fusion and deep learning to enable a checkout-less experience. Amazon derived its Just Walk Out technology and learnings from its own physical stores and now offers it to third-party retailers, travel concessions and stadium environments. The payment process is initiated at the store entry, either with a card swipe or using your palm if the store is equipped with Amazon One. Customers can then choose their items and walk out.

Retailers increasingly use mobile POS (mPOS) to streamline the checkout process. Rather than standing in a queue, customers at Lululemon, The Gap and other retailers can check out, order online or process returns from wherever they are as they interact with a salesperson in the store. During peak hours and seasonal rushes, these transactions can also happen outside the store, offering even more convenience and social distancing if required, as during some periods of the pandemic.

Another partnership that Qualcomm highlighted at NRF was with Xenia Retail; the Xenia Contactless Shopping solution enables AI-driven contactless shopping and payments. It allows consumers to use a white-label ScanPayGo app to scan and pay for items autonomously without having to check in or out. The solution has other slick features that allow customizable delivery options, list builders and an in-app wallet for the most secure payment processing. While the features make for a really personalized experience for the customer in the long run, the onboarding might feel slightly clunky, depending on which integrations are used.

Many consumers rank how they can pay as highly as where they shop or the price they are willing to pay. For example, if I'm out without my wallet and I know I can "pay with my palm" with Amazon One at Whole Foods, I'm willing to spend a little extra for the milk I need on my way home. My 13-year-old son will readily choose a burger stand that takes Apple Pay over a pizza joint that takes only cards or cashβ€”even if he prefers the pizza. Retailers with multiple payment options and checkout methods will reduce consumer frustrations and increase loyalty and return trips.

Checking out

As Google Cloud said during its analyst briefing, "Digital retail transformation is not a journey; it's a race." Retailers have many new technologies available and quite a few problems to solve, yet many still rely on antiquated foundations. According to the Food Industry Association, less than one-third of food retailers currently use AI, but 71% report that they plan to increase spending on AI.

Retailers need to drive and derive value across the retail value chain by using better data, improving and automating existing operations and removing friction in every transaction and interaction. Brands and retailers have tools and information at their fingertips like never before, and the ones who invest in the right technologies and optimize for the best consumer experience will ultimately win.