Use Technology Wisely to Reduce Friction for Your Customers

If you’re a retailer thinking about how to best use technologies such as AI, computer vision, and analytics, I encourage you to pause for moment to consider something else first: friction.

Today’s consumers want you to make their shopping experience easy. Why walk to the far corner of a grocery store for a gallon of milk when you can order it with one touch online and have it delivered right to your front door? Customers are pushing back against friction, and your first challenge is to identify friction points and eliminate them. Optimizing customer experiences is not just about using the latest, greatest technology. It’s about using the right tools to streamline everything from online browsing to in-store pickup.

Reducing friction for your customers should factor into the equation as you think about what technology will best enable you to optimize store experiences. We’re not just talking about being able to greet loyalty customers by name, although that’s a good start. You need to be thinking about harnessing deep learning for insights into consumer buying behavior and using robots for ensuring that your in-store inventory is up-to-date, and that your shelves are stocked.

Learning from Digital Natives

When it comes to best practices for using technology to optimize experiences, many of the most successful examples are from digital native retailers. Retailers that were born in the digital era have been thinking about and analyzing consumer behavior from day one.

One example of a digital native that is putting its expertise to work in the physical world is Lolli & Pops. At the NRF 2018 show, the retailer of gourmet candies demonstrated how it plans to use technology to personalize the customer experience for loyalty members who opt-in.

Using computer vision and facial recognition technology, the Lolli & Pops “Magic Makers” program, still under development, will recognize loyalty members in real-time as they enter a store. AI-enhanced analytics will instantly provide store associates information about individual preferences, and that will lead to personalized product recommendations. It should be a pretty sweet system for both the customer and the store.

While digital natives have an edge in the marketplace, legacy retailers are moving quickly to implement new technology, too. Big box stores, for example, are working with Hershey’s to implement Intel-powered “smart shelf” technology, which processes real-time data on both customer preferences and inventory to ensure that the right product mix is always available on store shelves.

Solving the Inventory Problem

Accurate inventory control and up-to-date shelf stocking are huge opportunities in the bricks and mortar retail world. This also relates to eliminating friction for your customers. If customers can’t find what they are looking for it results in a negative experience. Moreover, the vast majority of shoppers who can’t find what they want on the shelf will not ask someone check to see if an item is in stock, resulting in lost sales. In many cases the retailer might have plenty of SKUs in the back, but their shelves are out of synch with their inventory.

One of the most innovative robotic applications for retail is addressing the inventory problem. Bossa Nova Robotics has developed an autonomous on-shelf inventory-scanning robot that uses Intel computer vision technology integrated with RFID. The robots use both 2D and 3D cameras to identify products on store shelves. Data is instantly shared with a server that uses AI to analyze what’s on the shelf. Details such as location, price, and out-of-stock status are instantly assessed, and stocking or re-order actions are taken automatically. Powered by Intel Xeon processors, each robot is like a roving in-store data center.

While there is plenty to learn from digital natives, the proving ground for autonomous shelving technology is going to be in the aisles of Walmart stores. The retail giant has already started deploying Bossa Nova robots in its stores, and it won’t be long before they are in a location near you. Inventory is a $1.1 trillion a year problem for the retail industry, and only about 60 percent of items in any given store are correctly counted. That helps provide some context to explain why Walmart is investing in robotics technology for inventory management.

Recent breakthroughs in deep learning and computer vision are helping to facilitate this new wave of technology for retail. The connecting thread is, of course, IOT. According to McKinsey & Co., the economic impact from IoT on the retail industry could reach $1.2 trillion by 2025.

To realize the potential of this technology, think customer first. That will help you to start improving customer experiences by putting the power of data to work using tools like analytics, smart shelves and robots to ensure that shoppers in your stores find what they are looking for when and where they want it.

Learn more about Intel technology for retail.

Joe Jensen is Vice President and General Manager of Intel’s Retail Solutions Division, Internet of Things Group

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Published on Categories Embedded, RetailTags , , ,
Joe Jensen

About Joe Jensen

General Manager, Retail Solutions Division (RSD), Intel Corporation: RSD is bringing the Internet of Things to retail by developing the hardware, software and analytics technologies that will enable brands and retailers to deliver the perfect personalized shopping experience. RSD owns point-of-sale, ATM, Kiosks, Digital Signage, Intelligent Vending, and Micro Digital Signage for Intel. In prior roles Joe directed the Strategic Planning, Marketing, and Operations for Intel's Consumer Electronics Group. Before that he was the General Manager of the Embedded Intel Architecture Division within Intel Corporation. Intel’s Embedded Intel Architecture focus is the development of new market segments and applications for Intel core PC and Server technologies. These market segments include communications, point of sale, industrial computer, and educational computing. Joe has a BS in Electrical Engineering from South Dakota State University and an MBA from Arizona State University. He started with Intel in 1984 in engineering and has worked in all aspects of the semiconductor business from product design, through manufacturing and to marketing.

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