Artificial intelligence is such a complicated and rapidly evolving technology that it can sometimes be difficult to envisage the practical applications it can have today. Some of the world’s most successful brands have already been using AI for several years and are reaping the rewards in terms of profits, brand reputation, and visibility. Check out Concured’s AI Recommendation Engine here.
The following are just a few examples of these brands and how they are leveraging machine learning and AI technology as an integral part of their marketing strategy.
Amazon
Amazon was one of the first companies to pioneer personalized shopping recommendations, and over the years its algorithms have become increasingly sophisticated. Suggestions are now based not only on past purchases, but also items that other customers have bought, searching and browsing behavior, and many other factors.
Amazon also uses artificial intelligence to drive dynamic pricing – reducing prices to elicit more sales when needed, and increasing prices when demand is high. The algorithm enables optimal sales and revenue automatically.
Still forging ahead as a leader in the use of technology, Amazon has now opened checkout-free physical stores in Seattle, Chicago, and San Francisco, which have AI-powered sensors and cameras. This technology can tell exactly which items a customer has picked up and will charge them automatically as they walk out of the store using the Amazon Go app.
The company is even getting in on the trend of using AI in the fashion industry with Echo Look – its AI-driven personal stylist that uses machine-learning algorithms to suggest individual outfit recommendations, thereby driving more sales of apparel, shoes, and accessories.
Starbucks
Starbucks presented a strategic plan for using AI and big data in 2016, and the brand has made good on its promises to investors by enhancing its reward program and personalization to connect more deeply with its customers.
Personalization has always been a key part of the customer experience at Starbucks, with the ability to customize drinks for your individual taste. Now the company is using its loyalty card and mobile app to collect and analyze customer data including purchases, where they are made, and at what time of day.
The company uses predictive analytics to process this data in order to deliver personalized marketing messages to customers including recommendations when they’re approaching their local stores, and offers aimed at increasing their average spend. A virtual barista service on the app powered by AI also allows customers to place orders directly from their phone via voice command.
As well as delivering a more personalized customer experience, Starbucks uses their data from 90 million transactions every week to inform business decisions such as where to open new stores, and which products they should offer.
Alibaba
Chinese retail and technology multinational, Alibaba Group, opened its first “FashionAI” store earlier this year. The store aims to streamline the fashion retail experience for customers with intelligent garment tags that detect when the item is touched, smart mirrors that display clothing information and suggest coordinating items, and future plans for integration with a virtual wardrobe app that will allow customers to see the outfits they tried on in-store.
This is not the company’s first foray into artificial intelligence. In 2015, Alibaba launched its smart customer service system, which automated customer service so well that it achieved satisfaction ratings higher than the human agents.
Alibaba also uses similar technology to Amazon to drive personalized recommendations and search results to shoppers, as well as automatically-generated storefronts that display the most appealing items for individual customers.
The company has a massive customer base, with 567 million active buyers and millions of visits across its website and apps each day. This massive amount of data on customer habits is ideal fodder for AI processing, and no doubt the company has more plans for how it can be utilized in the future.
Nike
Mega sports brand Nike has always embraced technology and created one of the first fitness tracking gadgets with the Nike+ sensor in 2006. It’s also a company known for innovation in marketing; they are now combining the two to deliver personalized customer experiences and improve their product offering.
Last year Nike launched a new system that allowed customers to design their own sneakers in store. Not only is this a great gimmick to drive sales, but it also collects a huge amount of useful data that machine learning algorithms can use to design future products and deliver personalized recommendations and marketing messages.
The company has recently acquired body scanning firm Invertex, a move that Nike Chief Digital Officer Adam Sussman said would: “deepen our bench of digital talent and further our capabilities in computer vision and artificial intelligence as we create the most compelling Nike consumer experience at every touch point.”
It’s clear that Nike has big plans from the data it collects and is certainly one to learn from in terms of the applications of AI both now and in the future.
BMW
Several different companies are already using AI to power self-driving cars, but BMW is truly embracing the technology and using it at the heart of its manufacturing processes and overall marketing plan.
BMW uses Big Data to power its design and engineering processes, sales, and customer support. Predictive analytics are used to create the car designs of tomorrow, and the company has already built an AI-enhanced sports car that learns about its driver to automatically adjust systems and the cabin experience to suit each individual.
Earlier this year, BMW launched an intelligent personal assistant that enables drivers to communicate with their cars in the same way that they do with their smartphones. The tool also acts as a voice-activated manual, predicts travel routes, delivers alerts, and integrates with other apps. In the future, this technology could be used for marketing for third-party businesses such as parking lots and gas stations, and there’s no doubt the data collected from each individual driver will be put to further use in the company’s marketing intelligence.
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