3 Key Technologies for Traditionally Brick Retailers
One of the best parts of my job is seeing all the latest tech being applied to retail. I’m always seeing something new, something amazing, and thinking about what the future of retail could look like. But that’s also the challenge: in a sea of innovations, which ones should a traditionally brick retailer prioritize? What tech will make shopping better for consumers?
Walmart’s global network helps my team learn more about the habits and needs of millions of customers worldwide; with them in mind, we’ve invested in and developed a number of technologies to make their lives easier. What we’ve learned, basically, is that shoppers want to “shop” less. The focus is convenience, convenience, convenience. Here are the three technologies traditional retailers should build up to streamline shopping.
1. An Oldie but a Goodie: The Phone
Don’t dismiss it, there’s no denying it. The phone — really the app — is and will remain the cornerstone of a shopper’s mobile experience. Most retailers under invest here, and do not keep their apps up-to-date or on the edge. There is no device out there that is more personal or pervasive than a smartphone, allowing retailers, to be in customers’ hands 24 hours a day. Its clear phones give retailers the best opportunity available to stay close to consumers.
For Walmart, we want our app to be such an essential part of customers’ experience that those who leave their phones in their car turn around to get it because they know that shopping is faster and easier (and maybe even more fun) with the Walmart app.
Features make things easier for the shopper, with things like store-mapping, that show a consumer where to find an item in a store or Mobile Express Returns to make it simple to start a return before heading to the store. Or things like Walmart Pay to pay for items, using multiple payment methods if wanted on their phone. And we have expanded features to include those requested, such as pharmacy quick pickup, grocery curbside, quick money transfers, easy reorder to our app — and we continue to innovate and update.
The phone’s ubiquity is its strength and a retailer can easily boost its app’s efficiency so that it becomes a customer service representative and a cash register simultaneously. And one other thing, you have to ‘earn’ your way onto a customer phone — the app must be sticky enough for customers to invest in installing the app. Recent research from AppAnnie shows that the average smartphone user only uses 9 apps per day, and 30 a month. How do you rise to become one of those 9 (or 30)?
2. Machine Learning; Customers Get What They Want When You Want It
So many processes in retail get better with Machine Learning (ML). By finding patterns, machine language personalizes the retail experience from item selection to the last-mile delivery. We are able to do more with data and merge the customer-retailer digital relationship with the in-store experience.
Replenishment has always been complex at our scale. Regional trends, weather, demographics, and even local sporting events can dramatically change demand on thousands of items. For years we’ve been getting better with this at the store level, as we’ve been adding data for millions of individual customers. This changes ML from macro trends to thousands of micro trends, and showcases amazing data on how people shop.
We’re also using ML for last-mile delivery. Store associates can sign up to deliver orders to their neighbors as they travel to and from work. ML is used to determine which associates live along the route of which customers, taking into account package timing, size, and even if the ice cream might melt. There’s upside for everyone: customers receive their orders more quickly, costs are lowered as is the environmental impact of deliveries, and associates have the opportunity to increase their take-home pay.
With ML, it’s about scale. Data becomes actionable when you automate it, and the more data the better. Walmart has 11,700 physical stores in 28 countries with about 140 million shoppers every week, and customer relationships that go back before the advent of the personal computer. Because of advances in digital capabilities, that data can be analyzed to the smallest detail. Rather than querying data, retailers (and everyone else) can take a “data first” approach and let the data query itself and determine the conclusion.
3. Computer Vision & Deep Learning; Knowing What to Look For
I want your shoes! Where did you get that table? Do you have this in blue? We’ve all said similar things at a store or to a friend, but the future is computer vision and deep learning that is changing visual search and how we will shop. Like those shoes? Take a picture or scan the item, and find the same item or something similar.
Computer Vision is the ability of a machine to receive and analyze visual data and make decisions about it. Camera-toting, 6-foot tall robots rove the aisles of about 50 Walmart stores, taking photos and scanning shelves to check stock. They then notify store associates of any inventory issues.
Walmart helped revolutionize the use of computer vision when we rolled out bar codes chain wide with expensive equipment and sophisticated scanner beds. Today, you can do all that with a Raspberry Pi and a few lines of code. We have reached a point that there are bar codes invisible to the human eye, on the packaging and able to be scanned. You can see a day soon where barcodes won’t be needed at all, as the entire package can be ‘seen’ by the computer and has everything you need to identify the price (we are, however, still trying to figure out how to detect the difference between organic and regular carrots).
Deep learning backs up computer vision by teaching the camera to recognize items, people, spills, traffic, theft, and by analyzing millions of images and tagging the correct situations — the key to deep learning is training data, something that Walmart has, and continues to generate more each day.
Computer vision applications for retail will be all over the brick location — from checking how old strawberries are, to packing boxes and pallets more tightly, to looking for dead spots in store layouts by analyzing customer navigation. Visual search continues to advance, from the endless aisle where we “show more items like this picture,” to being able to order right from a photo if the product is the same. And the tech is getting better, cheaper and will open up all kinds of new doors for many retailers. In the meantime, there are excellent use cases in warehouses and stores that will help improve our costs, which will be passed on to the consumer with lower prices for all.
These technologies point to the same thing: that technology is useful if, ultimately, it’s giving people more time to live their lives. Whether it’s by speeding returns, guaranteeing food safety, streamlining inventory, or eliminating the checkout line, customers will adopt the great technology quickly and shed the concerning ones quickly.
I’m looking forward to seeing retail innovations and disruptions with these technologies. They offer opportunities to build on the existing relationships of traditional brick-and-mortar retailers with customers, suppliers, and shippers, and to revolutionize age-old processes. It’s an exciting time to move forward.