UWB technology and AI have been hot topics in the retail industry for a while now. If you’re only recently becoming aware of it, you’ve got some catching up to do. In particular, UWB’s potential to add value in retail technology applications is very exciting right now. In this article, we’ll take a look at five ways these technologies are being used to improve the retail experience and drive real value to retailers and consumers alike.
Wireless and AI: A Perfect Pairing
Two relatively recent developments in the wireless industry – UWB and machine learning – will converge at a pivotal moment for retailers. Moving forward, we’ll see more of these two technologies coming together to drive a new level of customer engagement. The result will be smarter, faster, and more actionable insights for retailers. Because the two technologies are being developed in parallel, this convergence won’t happen immediately.
UWB Showing Retailers the Way to New Customers
Until recently, UWB was mostly used by industrial customers for machine vision purposes. That’s where machine learning is useful as well – being able to analyze images coming from industrial machinery that are trying to figure out if there are any quality problems with their product. Think about an airplane manufacturer trying to inspect a wing. If they send a human out to take a look, they’re going to miss defects. UWB and machine learning has been used for this purpose, but it’s also being implemented in retail applications as well.
UWB is already being used by retailers for things like location-based engagements with customers. An example would be the in-store signage that changes depending on what is in your shopping cart or your location within a store.
A retailer could use UWB to upgrade their current digital signs to ones that are location-aware and connected to their systems. And it’s not just signage – this technology can be used for things like interactive displays, kiosks, mobile apps . . . even the shopping cart handle could give customers personalized information about products they might be interested in buying or learning more about thanks to machine learning.
Current State of Retail Technology
The retail industry has been facing a lot of changes in recent years and is struggling to keep up with the times. From an evolutionary perspective, we’ve seen some truly impressive breakthroughs in retail technology over the last 5-10 years . We’re getting better at delivering personalized experiences with things like recommendation engines and technologies such as Radio Frequency Identification (RFID) tagging. But until now, retailers have been mostly using these technologies in isolation.
For example, the RFID tag tells the retailer how often a product is selling and can tell them who bought it (and thereby made other purchases), but it doesn’t tell them much about what other products that person might be interested in buying or which promotions would appeal to them.
We’ve talked about how UWB can provide real-time information on product movement, but it also does a much better job tracking customer behavior and location. If a retailer knows that their customer is nearby, they can deliver relevant information at just the right moment – whether it’s recommendations on what to buy, where to go next or even simply an upsell of similar products.
This new kind of retail tech will also lead to more personalized experiences with things like IoT. Right now, IoT is primarily used for efficiency and crowdsourcing. But you can combine this technology with machine learning to get a much more powerful kind of insight. For example, retailers could use IoT sensors in the shopping cart handle that know when it’s moving (and where) and then deliver personalized messages such as coupons or even push notifications about nearby deals like a “buy-one-get-one” offer.
5 Ways UWB and AI Will Improve Retail Technology
Retail is a top contributor to the global economy and it’s growing rapidly. Here are some ways UWB and AI are helping the industry evolve.
#1 : Optimizing for Product Colocation
One big problem in retail is that there are all sorts of products in the store that aren’t moving. They’re sitting on a shelf, but they’re not seeing any action because they’re either in the wrong spot, mislabeled or simply weren’t recommended to customers. UWB and AI might be able to help with this by optimizing product colocation so customers’ entire shopping experience is more meaningful.
This data can also be used to identify which products are most attractive to customers and where they’re located in the store, so retailers can place them closer together or design more effective displays/promotions. It’s not just for display purposes either – if a product is frequently bought with another, retailers could even use this information to create “customer combos” that can be automatically created when customers are near one of the items.
#2 : Unlocking Predictive Demand Forecasting
We already have demand forecasting that tells us how much inventory will sell during an upcoming season, but UWB and AI can help us get an even more accurate sense of what people are going to buy before they even think about shopping.
Again, this kind of information is mostly used for analysis right now, but combining it with machine learning could create a powerful way to connect big data sets and derive actionable insights that can be acted on in real-time or at least significantly faster than most retailers can do now.
#3 : Avoiding Out of Stock Items
Retail is all about the supply chain, but it’s easy for small mistakes or setbacks to cause big problems. One of these is out-of-stock items – if a retailer doesn’t have something in stock when a customer wants to buy it, they’ll usually just go somewhere else. This is particularly troublesome with fast-moving items, so it’s important to avoid out-of-stock items with AI and UWB that can help with demand forecasting and product colocation.
#4 : Reducing Product Returns
Returns are expensive, especially if they’re brand new products that customers simply didn’t like or want. Luckily there are ways to figure out if a product will have returns before it’s even shipped, thanks to machine learning and big data sets that can reveal customer preferences. Learning how customers shop for similar products is also helpful – many return policies are based on the idea that shoppers would rather keep an item they already own or something very similar, rather than the one they’re returning.
#5 : Decreasing Wait Times in Checkout Lanes
If you go to a store and there’s a long checkout line, you’ll probably just leave and go somewhere else because it seems like such an unnecessary waste of time. But if stores can use UWB and machine learning to deliver personalized offers to customers even before they get to the check-out line, it might make people more willing to stick around.
This information can also be useful for analyzing customer behavior and improving the customer experience in other ways. For example, if you know what items are most popular with certain demographics, you can create more effective layouts or product displays designed specifically towards people most likely to be interested in the items.
Of course, this kind of technology won’t eliminate all types of lines and wait times, but with UWB and AI, retailers can use data sets to optimize the way they handle retail transactions so customers never feel like they’re spending more time than necessary. These technologies can also help stores stay competitive by identifying, collecting and analyzing important data sets that drive sales.
The Future of Retail Technology
The retail industry is ripe for change, and AI and UWB are among the most exciting new technologies being developed to improve customer experiences, increase sales volume, reduce wait times in checkout lines, decrease product returns and more.
While some of these applications are still relatively “under construction,” so to speak, it won’t be long before they’re built and ready for customers. How we shop for products, what we buy and how we handle retail transactions will drastically change over the next few years, but these advances in AI and UWB technology are sure to make that journey much easier.
Retail is changing rapidly, which means that companies will need to adapt or risk being left behind. With AI and UWB, shops of all sizes can get ahead of the game and give their customers an amazing experience.
Sunvera Software develops next-level software applications from start-to-finish. We are a premier software and mobile app development agency specializing in healthcare mobile app development, custom mobile app development, telehealth software, sales dashboards, custom mobile app development services, retail software development, supply-chain software, ecommerce, shopify, web design, iBeacon apps, security solutions and unified access software.
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