20 Innovative Examples of Artificial Intelligence in Retail
By Tricia McKinnon and Ben Rudolph
You may not realize this, but artificial intelligence is already impacting many steps along the buyer journey, from discovering new products to the in-store shopping experience. For example, while Amazon Go seeks to automate key functions within the shopping experience like the checkout, Walmart’s version of an artificial intelligence enabled store focuses on fixing the basics of inventory management to ensure the produce you want to is as fresh as possible.
Then there are those smart recommendations for what you should purchase when you are using your favourite shopping app. As artificial intelligence creeps into more and more of the retail sector you may be wondering where and how. Take a look at these 15 examples to see where retail is headed.
1. McDonald’s is using AI to transform the drive thru
In March of this year McDonald’s made its biggest tech investment ever. It acquired Dynamic Yield an artificial intelligence start-up based in Tel Aviv and New York for over $300 million. Dynamic Yield focuses on providing personalized customer experiences using AI. The acquisition is McDonald’s largest purchase in 20 years and is one of the largest tech investments in the retail sector. McDonald’s began working with Dynamic Yield in 2015 and the fast food chain believes that artificial intelligence will have a meaningful impact on the customer experience as well as the bottom line.
Since the acquisition McDonald’s has already changed digital displays in the drive thrus at 8,000 locations to dynamically provide customers with more customized recommendations. For example, data such as the weather, time of day, historical sales information and traffic patterns will be analyzed to make more meaningful food recommendations by store location. Other potential uses of the artificial intelligence recommendation engine may include providing simpler menu options when the drive thru is backed up to help reduce the backlog in the kitchen.
2. Stitch Fix is using your data to recommend the perfect outfit
Stitch Fix, the online personal styling company, has effectively been able to use artificial intelligence to provide personalization on a mass scale. To get started with Stitch Fix customers complete a detailed online questionnaire. The questionnaire covers a wide range of areas to provide an understanding of the customer’s style, size, price preferences and how often they need new clothing for various occasions (i.e. work, dates, events etc).
Stitch Fix employs over 100 data scientists with Phds in areas such as math, neuroscience, statistics, and astrophysics. Using over 85 meaningful data points provided by customers, merchandising algorithms based on artificial intelligence are built and are used to make personalized clothing recommendations for each customer. Then personal stylists enter the mix and can can override the recommendations made by the algorithms if necessary.
3. Lowe’s customer service robot helps you to find what you are looking for in-store
Lowe’s introduced LoweBot, a customer service robot in 2016. The robot uses natural language processing to answer customer questions. If you ask the LoweBot where can I find lightbulbs, the LoweBot will travel across the store to show you where lightbulbs are located. It can also provide information on what is in stock in-store. This information can be accessed by customers directly or by store associates.
One of the goals of the initiative is to provide store associates with readily available data so that they can better assist customers. The goal is to augment the work of sales associates (not to replace them) so that they are available for higher value tasks. When asked if the LoweBot could eventually eliminate jobs, Kyle Nel, Executive Director of Lowe's Innovation Labs said: “most definitely not — my phone doesn't make me obsolete."
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The LoweBot, Credit: Lowe’s
4. Walmart is making more intelligent product recommendations
In May of 2018 Walmart launched its Jetblack service in New York City. Jetblack is a personal shopping service that customers access via text message. The service’s tagline is: “Need It. Text It. Get It. Jetblack is the easiest way for busy parents to shop”. Jetblack is a standalone company within Walmart’s Store No. 8 tech incubator which is focused on helping Walmart stay ahead of retail trends.
The service costs $50 per month and all a customer needs to do is send a text with a shopping request. The service can fulfill almost any shopping request as long as it doesn’t involve food, alcohol or prescription drugs. Jetblack’s CEO Jenny Fleiss says that there are typically three use cases for the service. One is to reorder frequently purchased items such as toilet paper, another is to get a recommendation for something such as a birthday gift for a friend and the third involves sending a text message with a picture of a specific product (i.e. a screen shot of something a customer has seen online) but the customer does not want the hassle of finding the product online or they do not feel like taking the time to enter their payment information.
At times a real-life person is used to curate product recommendations for customers and other times artificial intelligence is used. For example, artificial intelligence is used to handle simple customer requests such as reordering items. Over time it is expected that Jetblack’s AI will be able to provide more recommendations based on the customer’s purchase history. Fleiss has suggested that in the future AI might be able to handle 95% of interactions with customers. This will allow Walmart to collect data from thousands of conversations and millions more in the future which will make Walmart’s predictive recommendations more accurate.
5. Kroger is changing what we see on shelf displays
Kroger has introduced new technology in its stores called Kroger EDGE. EDGE stands for Enhanced Display for Grocery Environment. The new technology enables Kroger to replace traditional shelves with digital shelves. These shelves display a product’s price digitally enabling Kroger to change prices in real time.
Instead of playing it safe and only providing relatively standard data on its digital shelving Kroger decided to go a step further. Earlier this year Kroger announced that it had teamed up with Microsoft to provide technology that enables personalized offers to be presented to customers as they approach a digital display. How exactly is this done? It is accomplished using Microsoft’s artificial intelligence technology that uses facial recognition to identify the age and gender of a customer as they approach a display. If a customer has not opted in to receive fully customized ads via Kroger’s app then a more generic message is presented on the digital shelf based on a prediction of the customer’s age and gender. But if the customer opts in they could be presented with a more tailored message based on their shopping preferences. Speaking about EDGE, Kroger’s Chief Information Officer Chris Hjelm said: "if you are standing in front of nutrition bars and you are gluten-free, we would highlight for you which of the gluten-free bars are good for you."
Currently the technology is being piloted in two stores in the US and the results of the test will determine if the technology is rolled out to more stores.
6. Walmart is fixing the basics of inventory management
After Amazon revealed its “store of the future” as Amazon Go, in April of this year Walmart did the same, with its Intelligent Retail Lab (IRL). This new experimental retail location in Levittown, New York, is a 50,000 sq. ft store that uses AI to ensure perishable products remain in stock and fresh. It may not have a flashy check-out, or lack thereof like Amazon Go, but IRL is able to track inventory in real time with unprecedented efficiency.
Similar to Amazon Go, IRL uses cameras throughout the store. Walmart collects a staggering 1.6 TB of data per second. When a customer picks up an item, such as the last package of a certain type of meat a text is sent to a sales associate to restock it. Previously, inventory proved difficult to track without the literal scanning of every barcode.
Mike Hanrahan, CEO of IRL, notes that “you can’t be overly enamoured with the shiny object element of AI. There are a lot of shiny objects out there that are doing things we think are unrealistic to scale and probably, long-term, [are] not beneficial for the consumer.”
7. Nike is making it easier for you to find the perfect fitting shoes
Recently Nike added a new feature in its app called Nike Fit. The feature allows customers to find their true shoe size using a mix of artificial intelligence and augmented reality to scan a customer’s foot digitally. To enable the app’s functionality all users have to do is point their phone’s camera at their feet and the app will determine their shoe size. All of this can be done from the comfort of the customer’s home in less than a minute.
Once the customer’s shoe size is determined it is saved in the app. If a customer shops in-store all a sales associate has to do is scan a QR code in the app and they can retrieve the customer’s size. With more than an estimated 60% of people wearing the wrong size shoe size this app will help customers to get the shoe that fits.
Nike Fit Credit: Nike
8. Amazon Go is letting us skip the line at the checkout
A sneak peek into the future was given when Amazon unveiled its first Amazon Go store to the public in 2018. Amazon Go is a convenience store that was first launched with no cashiers but instead uses machine learning and sensors to determine which items customers have taken off shelves. After customers have finished shopping they can walk out of the store without having to ever stand in a line or go through a checkout. When customers leave the store their Amazon account is automatically charged. However when the latest Amazon Go store recently opened in New York it accepted cash. According to Cameron Janes, Amazon's Vice President of Physical Stores: “adding more payment methods enables more customers to shop in the store. And that's great for customers and great for us."
9. Sam’s Club is automating grocery shopping lists
Last November Sam’s Club opened up its version of the store of the future in Dallas called Sam’s Club Now. At 32,000 sq. ft the store is smaller than the average Sam’s Club store which is 100,000 sq. ft on average. The retailer is using the store to test a number of technologies from digital wayfinding to augmented reality to artificial intelligence.
Customers use the Sam’s Club Now mobile app to scan items they wish to buy and skip the checkout. The app also uses machine learning to mine purchase data to create a “smart” auto filled grocery shopping list for the customer. The customer has the option to add or remove items from the list as they see fit. After an item is scanned the customer’s grocery list is automatically updated.
10. Starbucks is making it easier to place orders
Starbucks’ popular mobile app features My Starbucks Barista which allows customers to place and pay for their orders by having a conversation with a virtual barista. Then customers can pick up their order at a nearby Starbucks. The feature is so popular that some Starbucks stores have lost business from walk-in customers that do not want to wait in long line ups caused by virtual orders.
The app also provides customers with personalized recommendations for additional products they may want to purchase based on their purchase history. According to Starbucks' Chief Technology Officer they use “a data-driven AI algorithm based on your own preferences, your own behavior as well as behaviors that [Starbucks is] trying to drive”. Starbucks has said that its personalization initiative “is the single biggest driver” of improved spend per customer it has seen.
11. Amazon is changing the way we shop for clothing
Trying to buy that cool outfit you saw on your Instagram feed? Amazon’s new StyleSnap feature, in its mobile app, which launched in early June of this year will let you do that by uploading a photo. Called the Shazam of shopping the artificial intelligence powered tool uses machine learning to provide recommendations for similar items on Amazon.com based on a photo a user uploads. Speaking about the launch of the new feature Amazon’s Consumer Worldwide CEO Jeff Wilke said: “when a customer uploads an image, we use deep learning for object detection to identify the various apparel items in the image and categorize them into classes like dresses or shirts. We then find the most similar items that are available on Amazon.”
12. Neiman Marcus is making it easier to find the clothing we want
Neiman Marcus launched a feature within its mobile app called Snap. Find. Shop in 2014. Customers use the feature by taking a picture of an item using their smartphone camera while using the app. The app then scans its inventory to see if Neiman Marcus carries a similar shoe or handbag. If it does it makes a product recommendation which the customer can then purchase. The innovative app has increased customer engagement and overall app usage. Scott Emmons, Head of the Innovation Lab at Neiman Marcus calls the functionality the “Shazam for shopping.”
13. Target is making online shopping more visual
According to an eMarketer report, the majority of US internet users (52.3%) would like to see related products after using a retailer’s mobile app to take a picture of an item. Betting on the future of this technology, Pinterest launched Pinterest Lens in 2017. It uses artificial intelligence to show similar products after a user has taken a photo of an object. Ben Silbermann, CEO of Pinterest said: “I really believe that the camera will be the next keyboard. It will be a fundamental tool you use to query the world around you, discover things around you, or visualize how something might fit into your life”.
Recognizing the potential of this technology Target became the first retailer to incorporate Pinterest’s Lens technology into its own mobile shopping app. Initially launched for products within Target’s registry, customers could take a picture of a crib and receive recommendations for similar products that customers can purchase at Target. The hope is for customers, while conducting their day-to-day activities, even when they are not shopping, to see an item they like, take a picture of it using Target’s app and then they can find similar items to purchase at Target.
14. Alibaba is reimagining the in-store shopping experience
Last July Alibaba, in collaboration with GUESS, opened a FashionAI concept store on the campus of Hong Kong Polytechnic University. The purpose of the store was to give customers a sneak peak into what the store of future powered by artificial intelligence (AI) will look like. The store combined GUESS’ latest collections and retail expertise with advanced artificial intelligence and other technologies from Alibaba.
Customers checked into the store using their mobile shopping app. With RFID tags purposely built into the clothing hangers customers were able to use their app to see all of the merchandise they looked at during their shopping trip. Merchandise picked up by customers also immediately showed up on smart mirrors located adjacent to clothing racks. The smart mirrors provided customers with personalized recommendations for how they could mix and match other items with the merchandise they selected. The mirrors also showed customers the location of where complimentary merchandise could be found in the store. According to Alibaba with “fashion AI you never have to worry about how to put an outfit together.”
15. The North Face is helping customers find the perfect fitting coat
In 2016 The North Face partnered with IBM’s Watson, an artificial intelligence platform, to help customers find the perfect coat. Using Watson and its cognitive computing abilities, The North Face developed an in-store app to ask customers questions about where they plan on wearing their desired coat and what activities they will be doing while wearing it. Watson Analytics uses this customer information and makes a personalized recommendation. As The North Face’s app continues to build on previous customer information, it pairs that data with in-store and eCommerce purchases and activity, to offer The North Face customers even more personalized product recommendations.
16. Adidas is helping you to pick out the perfect outfit
Adidas partnered with artificial intelligence platform Findmine to reduce the time it takes to generate recommended outfits for customers that are shopping digitally. Prior to using the Findmine solution Adidas’ merchants manually put outfits together for Adidas online “complete the look” recommendation feature. This activity took 27 steps and 20 minutes. Adidas also found that it generated a materially larger amount per order when customers were provided with a recommendation that featured a complete outfit instead of just one product like a t-shirt, making this activity an ideal candidate for process improvement.
Adidas conducted a test with Findmine’s AI solution and after a six week period found that neither customers nor merchants could discern between the outfits recommended by AI versus those recommended by Adidas’ merchants. “Findmine has helped us reduce the amount of manual work and has helped us ensure that our newest products have cross-selling from day 1, improving conversion, average order value, and customer satisfaction better than any other solution we’ve tried,” said Brian Klavitter, Senior Director, Adidas Consumer Experience.
17. Ulta Beauty is giving you beauty advice digitally
Ulta Beauty has invested in virtual beauty advisors that customers access both at ulta.com and through Ulta Beauty’s mobile app. The virtual beauty advisor asks a customer a set of questions then provides recommendations tailored to the customer’s wants and needs. “We…continue to leverage augmented reality and artificial intelligence to create compelling beauty experiences for our guests to drive stronger brand loyalty” said Mary Dillon, Ulta Beauty’s CEO. “We also continue to experiment and learn as we create more virtual beauty advisors. In addition to the existing skincare advisor, we recently launched foundation finder and mascara lash advisor to help our guests find what works best for their needs,” Dillon further added on a third quarter earnings call last November.
18. Chipotle is automating parts of the the ordering process
In 2018 Chipotle started testing an artificial intelligence powered voice assistant for customer orders made over the phone. The voice assistant makes recommendations to customers such as suggesting they add extra guacamole or extra sour cream to their order. The recommendations improve over time as more customers make orders and provide more data. The goal is to make the ordering process more seamless but Chipotle is likely also banking on its intelligent recommendations to increase average order value as customers agree to add on extras as recommended by the voice assistant. This system has now been rolled out across the United States.
19. Domino’s is using AI to make you a better pizza
In Australia and New Zealand Domino’s uses an artificial intelligence powered pizza checker. In a statement, Domino’s Pizza said the DOM Pizza Checker: “uses advanced machine learning, artificial intelligence and sensor technology to identify pizza type, even topping distribution and correct toppings”. The pizza checker has scanned more than 13 million pizzas to see if they match the customer’s order and quality standards, if not the pizza is remade. Domino’s says that product quality scores, as rated by customers, have increased by 15% since the pizza checker has been in place. “Our team always strive to get it right, but the reality of a busy store can sometimes mean pizzas go out which are below the high standards we pride ourselves on – and we want to fix that,” Nick Knight, CEO of Domino’s Pizza in Australia and New Zealand said.
20. Home Depot is making it easier for you to find the perfect product
In Home Depot’s mobile app there is a visual search function. To use it simply take a picture of a piece of merchandise you are interested in, perhaps a mirror you saw while eating at a restaurant for dinner. Or upload a photo you have already stored on your phone. Home Depot’s app then uses artificial intelligence to provide product recommendations that you can buy from Home Depot that are similar to the item you are looking for.
Home Depot’s app also uses machine learning to get a sense of the type of projects customers are working on then it provides the customer with project and buying guides to ensure that customers have the materials and insight they need to complete their DIY project.
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