Today’s marketers are all looking for new ways to find and attract their ideal audience. But in the fast-paced and ever-evolving digital marketing landscape, it’s getting harder and harder to reach your people and get results.
Enter AI in marketing.
What is artificial intelligence marketing?
Artificial intelligence marketing (AI Marketing) is a method of leveraging customer data and AI concepts like machine learning to anticipate your customer’s next move and improve the customer journey.
Advancements in Artificial Intelligence are offering companies better ways to do just that. AI can help build more effective marketing strategies, improve the customer journey, and change the way businesses attract, nurture, and convert prospects. The graphic below shows how AI and machine learning can be incorporated into every step in the customer’s lifecycle.
Source: Smart Insights
AI in marketing may feel more science fiction than fact to many, but Artificial Intelligence is no longer a far-off concept. In fact, by 2021, companies are expected to be spending $57 billion on AI platforms. It’s time for businesses of all sizes to think about how artificial intelligence can help them stand out from the competition.
To help you get started, we’ve compiled 10 impressive examples of AI in marketing.
1. Magnolia Market Bridges Online-to-Offline
Magnolia Market, the brick-and-mortar shop owned by Joanna and Chip Gaines, is known for their stellar customer experience. The mission of Magnolia’s physical location is to “inspire you to own the space you’re in.” To achieve this goal, the space they’ve created is a true brand experience that combines food, games, shopping, and a garden.
Because not everyone is able to visit the Magnolia Silos, the team felt that its e-commerce operation also needed the capacity to deliver the same experience. Magnolia worked with Shopify Plus to create a storefront and an augmented reality app that allows users to view products in 3D and “place” them in their home. AR allowed Magnolia to render its products with the highest-possible photo-realism. The results set Magnolia apart from the competition and strengthened their e-commerce arm, which is a key driver for company growth.
2. Chase Achieves More Humanity in its Copywriting
Chase Bank signed a five-year deal with Persado, a New York-based company that applies artificial intelligence to marketing creative. After testing Persado’s solutions, Chase found that using machine learning in their copywriting actually helped them achieve more humanity in their marketing.
For example, one digital ad written by humans read: “Access cash from the equity in your home.” Persado’s version, on the other hand, read: “It’s true—You can unlock cash from the equity in your home.” The latter version actually performed better with customers.
Chase is the first to engage in this type of large scale machine learning copywriting, but other brands are planning to expand the use of Persado’s technology. According to Persado, the company already works with 250 marketers across categories including retail, finance, and hospitality.
3. Starbucks Uses Predictive Analytics to Serve Personalized Recommendation
According to the research firm Aberdeen, companies that are identifying customer needs and wants through predictive analytics are able to increase their organic revenue by 21% year-over-year, compared to an average of 12% without predictive analytics.
Starbucks is one example of a brand that is using its loyalty card and mobile app to collect and analyze customer data. They announced plans for personalization back in 2016.
Since then, they’ve built quite the app experience. It records the details of purchases, including where they are made and at what time of day. Starbucks uses predictive analytics to process this data and serve customers with personalized marketing messages. These messages include recommendations when they are approaching a local store as well as offers that are aimed at increasing the customer’s average order value.
4. Alibaba Opens a FashionAI Store
Retail giant Alibaba opened a physical “FashionAI” store in Hong Kong with the goal of streamlining the fashion retail experience through the use of Artificial Intelligence. The store is equipped with intelligent garment tags that detect when the item is touched and smart mirrors that display clothing information and suggest coordinating items. Alibaba also has future plans to integrate the brick-and-mortar store with a virtual wardrobe app that will allow customers to see the outfits they tried on in-store.
Alibaba’s use of technology is a response to the consumers’ shifting expectations. According to a recent report by Retail Dive, 46% of those surveyed said positive experiences with technology give them more confidence in a particular brand, while 44% said that satisfying experiences would make them want to visit a business more frequently.
5. Customers Create Custom Nikes in 90 Minutes
In 2017, Nike launched a system that allowed customers to design their own sneakers in-store. The “Nike Makers’ experience” allows customers to put on blank Nike Presto X sneakers and choose their own graphics and colors. Using augmented reality and projection systems, the system then displays the design on the blank shoes. The designs are printed on the sneakers and available to the customer in about 90 minutes.
This customer engaging feature not only drove sales but more importantly, it allowed the sneaker brand to collect data about customer preferences. Nike then used this data with machine learning algorithms to design future products and deliver personalized product recommendations and marketing messages.
6. BMW Builds An AI-Enhanced Sports Car With a Personal Assistant
BMW’s AI-enhanced sports car is a product designed for the car and technology enthusiast who values exclusivity and early adoption. (Prices for the BMW I8 start at $150,000.) The car has the technology to learn about its driver and then automatically adjust systems and cabin experience to suit each individual.
The car brand also launched an intelligent personal assistant that enables drivers to communicate with their cars in the same way that they do with their smartphone. The tool acts as a voice-activated manual, can predict travel routes, deliver alerts and integrate with other apps.
BMW’s focus on technology-enabled cars is a play to keep its customers loyal. According to a survey by Cox Automotive, more than half of drivers are willing to sacrifice vehicle color, style and brand to get the latest technology.
7. Stitch Fix Pairs Human Stylists with Artificial Intelligence to Refine Customer Recommendations
Source: Bernard Marr
Stitch Fix is an online styling service that delivers a personalized assortment of fashion products to customers each month. The brand combines personal (human) stylists with the insight and efficiency of Artificial Intelligence. AI analyzes the data on style trends, body measurements, customer feedback, and preferences and delivers a narrowed down set of possible recommendations to the human stylist. The stylists then use their expertise to handpick clothing and accessories for the individual customer.
Managing return costs and warehouse space are key components of profitability for Stitch Fix. Incorporating AI into their systems allows them to invest in merchandise with more confidence. As Eric Colson, Chief Algorithm Officer at Stitch Fix, said, “Our business is getting relevant things into the hands of our customers.”
8. Unilever Helps Ben & Jerry’s Identify the Trend for “Ice Cream for Breakfast”
Consumer Goods company Unilever is using AI data centers across the globe to synthesize insights from a range of sources including social listening, CRM, and traditional marketing research. Using this technology, Unilever discovered a link between ice-cream and breakfast: there are at least 50 songs in the public domain where the lyrics talk about “ice-cream for breakfast” and businesses like Dunkin Donuts are already selling ice cream in the morning.
Unilever took this insight and developed a range of cereal flavored ice creams (including Fruit Loop and Frozen Flakes) for the Ben & Jerry’s brand.
9. Amazon Launches Personalize
Amazon was a pioneer of using machine learning to offer personalized product recommendations, but it has been a challenge for the brand to extend these capabilities to companies that are running their sites on Amazon Web Services.
This June, Amazon announced the general availability of Amazon Personalize, which brings the same machine learning technology used by Amazon.com to AWS customers for use in their applications.
Brands including Domino’s, Yamaha, Subway, and the wedding company Zola are already using Personalize to highlight musical instruments in-store catalogs, deliver ingredient and flavor recommendations, and devise individualized style combinations.
10. Sephora Chatbots
By 2020, it is predicted that 85% of consumer interactions will be handled without a human agent. Beauty brand Sephora was an early adopter of AI. They began using a chatbot to dispense beauty advice on Kik in 2017.
Sephora’s chatbot helped consumers narrow down choices, beginning with a quiz about their product preferences. This was especially helpful in the cosmetics industry, where the options can be overwhelming and difficult to purchase without testing a product in person. Sephora gained valuable insights from their chatbot and saw enough engagement from that experiment that it’s since launched more chatbots on Messenger.
From valuable insights to personalized product recommendations and technology-enabled assistance, AI in marketing is already driving some of the biggest advances in overall customer experience. What impressive examples of AI in marketing have you seen lately?
If you’re interested in learning more about how new technologies can help improve your customer engagement strategies, check out our social media strategy conference!