At the Marketing AI Institute, we read dozens of articles on artificial intelligence every week to uncover the most valuable ones for our subscribers and we curate them for you here. We call it 3 Links in 3 Minutes. Enjoy!
McKinsey Predicts AI Value in Marketing
There’s been a lot of hype around the impact artificial intelligence will have on different industries, especially marketing. Luckily, McKinsey’s quarterly Five Fifty study, “Real-World AI,” cut through the hype and put some actual numbers (big numbers!) behind these claims.
According to McKinsey, AI’s application to real-world business problems extends across nearly every sector of the economy, but the biggest impact could arise in two particular business functions: AI in sales, and AI for supply-chain management and manufacturing.
McKinsey predicts there is $2.6 trillion (yes, trillion) of potential value to be unlocked by AI applications in the marketing and sales sectors. Supply-chain management and manufacturing follow right behind at $2 trillion.
Their recent analysis of more than 400 use cases across 19 industries and nine business functions points out the huge opportunity for businesses to leverage AI for personalization. Combining past transaction data, customer demographics and social media monitoring, recommending a “next product to buy” like Amazon and Netflix could lead to a twofold increase in the rate of sales conversions.
Read McKinsey’s full report, “Notes from the AI frontier: Applications and value of deep learning.”
We Met on Cars.com
Cars.com is jumping on the dating app bandwagon—kind of.
Announced this week, Cars.com is making it easier to find your next vehicle with an AI-powered vehicle matchmaking platform, reports Marketing Dive.
The AI tool uses a machine learning algorithm to make car recommendations based on users’ lifestyle preferences. Users take a quiz that provides the machine feedback on 15 different lifestyle preferences and Cars.com uses sentiment analysis to provide up to 20 recommendations.
In a pilot of the matchmaking model led to a 752% increase in profile creation, 87% increase in return visitors, a 225% boost in email lead, and two times more page views per visitor compared to the company’s traditional search function.
This isn’t Cars.com’s first dive into artificial intelligence. In April, the site introduced a “Hot Car” function that used machine learning to identify which vehicles are most likely to sell quickly.
Machine Learning Generates Persuasive Faces for Ads
We see hundreds of ads every day–in emails, on social media, as banner ads, and on billboards and busses. But, have you ever stopped to consider the faces in those ads? More specifically, the shape of their face, the color of their eyes, or their expression?
Advertisers use persuasive language and images to promote products and convey ideas. Faces, a key aspect of ads, are often portrayed differently depending on the product and message being communicated.
According to TechXplore, two University of Pittsburgh researchers have developed a machine learning model that generates persuasive faces catered to different types of ads.
Using a huge dataset, the researchers trained their model to understand facial expressions by representing facial features with numbers. For example, one number would control the shape of a face, another the shade of skin, and so forth. With this training, the model can tailor ads to individual customers, such as generating facial features that match those of the viewer, so they identify more with the ad.
"This kind of automatic, fine-grained ad customization could have huge implications for online advertisers," says one of the researchers, Christopher Thomas. "In addition, an advertiser who doesn't want to hire an extra model for their ad or to do manual editing may be able to transform an existing face from another ad into a face appropriate for their type of ad."
Ashley Sams is director of marketing at Ready North. She joined the agency in 2017 with a background in marketing, specifically for higher education and social media. Ashley is a 2015 graduate of The University of Mount Union where she earned a degree in marketing.