Three Artificial Intelligence Case Studies
Check out the three case studies below to find out how artificial intelligence and machine learning technologies are being used across industries to drive more intelligent business decisions. These examples share how real companies are obtaining actual benefits from technologies like advanced analytics and intelligent image recognition.
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Alibaba, the world’s largest e-commerce marketplace with more than $248 billion in transactions, is avidly investing in artificial intelligence and machine learning technologies. Alibaba has already made investments into seven research labs that focus on artificial intelligence, machine learning, network security, natural language processing, data intelligence, Internet of Things, financial technologies, as well as quantum computing.
Here’s how Alibaba enhanced its competitive edge with AI during “Singles’ Day” in 2018:
- Smart Selection: This AI-powered algorithm, backed by deep learning and natural language processing, helps recommend products to shoppers and then communicates with retailers to increase inventory to keep up with current demand.
- Customer Service Chatbot: This AI-powered chatbot can understand more than 90% of customer’s queries and serves more than 3.5 million users a day. The latest version of the chatbot can understand a customer’s emotion and can prioritize and alert human customer service agents if they need to intervene and take over.
- Robots & drones: More than 200 robots in automated warehouses can process 1 million shipments each day. Once the robots received the orders on Singles' Day, they packaged and shipped the goods, and, in some cases, their efficiency allowed same-day shipment. Alibaba also used drones for some deliveries.
These technological aids helped Singles’ Day last year bring in $25 billion in sales, up from $17.8 billion in sales for Single’s Day 2016, and nearly $20 billion more than Cyber Monday in the United States.
AI and machine learning powers three popular Amazon products: Alexa, the Amazon Go Store, and the Amazon recommendation engine.
Let’s take a more in-depth look at how they work:
- The Amazon Echo, which features AI bot Alexa, has been one of the company’s most popular ventures into machine learning. After the technology started to come together, divisions across the company realized that Alexa could be beneficial for their products. Some of the first skills for Alexa was integrations with Amazon Music, Prime Video, and personalized product recommendations from an Amazon account. Many companies now have Alexa skills that add value to the customer’s life such as Liberty Mutual and Capital One. Liberty Mutual provides auto insurance information and Capital One allows customers to make a payment through their Amazon device.
- The cashier-less Amazon Go store also took advantage of the wealth of data to track customer shopping trends. Data from customers’ smartphone cameras tracks shopping activities and not only helps Amazon Go, but can also be shared with the machine learning team for continued development.
- AI also plays a huge role in Amazon’s recommendation engine, which generates 35% of the company’s revenue. Using data from individual customer preferences and purchases, browsing history and items that are related and regularly bought together, Amazon can create a personalized list of products that customers actually want to buy.
Coca-Cola has been using artificial intelligence to solve a major problem the company has to deal with – marketing soft drinks around the world is not a “one-size-fits-all” affair. With products that are marketed and sold in over 200 countries, there are ranging differences between local tastes, concerning flavors, sugar and calorie contents, marketing preferences, and competitors faced by Coca-Cola. For the company to stay on top of the game in every territory, it must collect and analyze huge amounts of data.
Here's how Coca-Cola uses AI:
- Vending Machines: Coca-Cola serves a large number of its drinks everyday through vending machines. Newer machines allow for customers to interact through a touch-screen display, which enables them to select the product they want and even customize it with different flavor variations. Coca-Cola has fit these machines with AI algorithms to promote drinks and flavors that are the most likely to be well received in the specific locations where they are installed.
- Social Media: Coca-Cola also uses AI to analyze where, when, and how it’s customers like to consume its products through social media posts. With over 90% of consumers making purchasing decisions based on social media content, understanding how its billions of customers are discussing and interacting with the brand on platforms like Facebook, Twitter and Instagram is essential to its marketing strategy. To do this, Coca-Cola analyzed engagement with over 120,000 pieces of social content to understand the demographics and behavior of its customers and those discussing the products.
- Loyalty and Reward Schemes: The company transformed their loyalty and reward schemes by developing an image recognition technology that allows purchases to be verified by taking a single picture on a smartphone. Previously, customers had to manually enter a 14-digit product code that was printed on the bottle cap to redeem various promotions.