How Brands Target Consumers Better and Sell More with Artificial Intelligence [Case Studies Included]
How do brands actually use artificial intelligence to improve their marketing? That’s the central question we created the Marketing AI Institute to answer.
Every week, we profile actual companies that use marketing artificial intelligence solutions. Artificial intelligence is a suite of technologies (e.g. natural language processing, machine learning, deep learning, image recognition) that use large datasets to perform activities better than humans or achieve goals humans can’t achieve.
Used effectively, AI improves personalization, prediction, productivity, and performance, while freeing up marketers to perform the high-value creative tasks they do best.
To bring you even more real use cases of marketing AI, we’ve investigated one area where firms actively use AI to create results—consumer targeting.
Consumer targeting, or the ability to find and reach potential customers. Marketers today are employing AI in two key areas to target consumers better: content marketing and digital advertising.
Read on to discover how.
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How to Target the Right Consumers with the Right Content Using AI
First, brands use AI to target consumers with the right content at the right time based on what consumers liked and engaged with in the past.
Plumbing equipment manufacturer Delta Faucet achieved this using OneSpot, a content marketing personalization platform.
OneSpot’s machine learning and natural language processing (NLP) algorithms—both types of AI—crunched Delta’s user data to predict which types of content users would most likely engage with. (For an idea of scope here, Delta gets more than 500,000 visitors per month.)
As a result, Delta Faucet boosted pageviews per user by 49%.
Delta Faucet sells a lot of different products to a lot of different people. A visitor looking for kitchen faucets might not be interested in shower equipment. Someone looking at appliances for a new bathroom might not realize Delta has tons of content to spark redesign ideas.
In every case, Delta can send that content to users in a “Recommended for You” section prominently displayed on the page. As a result, visitors consume more and engage more with the brand.
Another marketing AI company, Emarsys, also uses machine learning to personalize content and messages for consumers. The company’s AI marketing platform looks at consumer data and determines which messages are most likely to work best.
This gives marketers the ability to “send the most personally relevant messages and incentives to each individual at the times they are most likely to be receptive, using the channels where they will be most likely to engage,” says Sean Brady, the president of Emarsys Americas.
In one example, retailer Toys R Us used Emarsys to send highly targeted emails that delivered more personalized messages to specific customer segments. Customers were sent different emails depending on their levels of engagement, time since last purchase and other behavioral criteria.
This resulted in a 45% conversion rate and a 40% increase in average order volume, as customers received the right messages at the right times.
How to Target the Right People with the Right Ads Using AI
Better content targeting works if you have traffic already coming to your website. But what if you need new people to discover your brand? Paid advertising is one way to reach new consumers—and AI is used to optimize what can sometimes be a complex, confusing and costly process.
Going back to Delta Faucet, the company used OneSpot’s AI to drive new users to relevant, targeted content on-site. The users were sent ads for Delta’s “Inspired Living” articles across a variety of channels. A full 45% of these visitors clicked through ads and stayed on the article page for at least 40 seconds—and 37% went on to read additional articles.
Artificial intelligence can also find people online who have the same characteristics as your current customers, and target them with advertising.
A Harley-Davidson dealership used Albert, an AI ad optimization platform, to increase leads by almost 3,000%. Half of those leads were “lookalikes” who were identified by Albert. The platform automatically optimizes paid advertising campaigns using machine learning.
The platform completely automated the work of paid advertising, typically handled by a marketer, and made it better. But it also surfaced insights the humans never even discovered in the first place.
Reports the Harvard Business Review:
“While Jacobi [the dealership’s owner] had estimated that only 2% of New York City’s population were potential buyers, Albert revealed that his target market was larger – much larger – and began finding customers Jacobi didn’t even know existed.”
The platform performed these miracles by evaluating the dealership’s customer data using machine learning algorithms to figure out what worked, what didn’t and who was most likely to buy.
About Mike Kaput
Mike Kaput is Chief Content Officer at Marketing AI Institute and a senior consultant at PR 20/20. He writes and speaks about how marketers can understand, adopt, and pilot artificial intelligence to increase revenue and reduce costs. Full bio.