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Artificial intelligence (AI) is reshaping how advertising works in astonishing ways.
In 2018, Lexus released an advertisement completely scripted by AI. The company used IBM Watson, an AI system, to analyze 15 years of award-winning car ads. Watson identified which elements of successful ads resonated most with audiences.
That was just the beginning...
Today, AI is quickly becoming the future of advertising. Advertisers are already using AI to identify and segment audiences, build ad creative, test ads, improve ad performance, and optimize spend—all automatically, in real-time, at scale.
(In fact, Andrew Ng, who built Google and Baidu's AI systems, cites AI and advertising as major business opportunities in his famous AI for Everyone course.)
This is producing almost unbelievable results...
One industrial equipment supplier is using AI to crush its advertising goals.
A financial services company is using AI to personalize advertising messages to individual customers at scale.
One travel firm even used AI to find customers it didn't know it had.
Long story short...
If you're not using AI for digital advertising, you're at a competitive disadvantage.
We're here to help. At Marketing AI Institute, we've spent years researching and piloting AI marketing tools—including AI advertising tools. We've published over 700 articles on AI marketing and advertising. And we're actively tracking thousands of AI marketing and advertising companies with more than $6 billion in combined funding.
In this article, we'll:
- Help you understand what AI for advertising is—and why you need it
- Outline the top use cases for the technology
- Recommend the best tools for AI advertising, so you can get started with AI
Let's dive in.
What Is AI for Advertising?
You don't need to know everything about AI to use it in your advertising—you just need to know these basics.
The best definition of AI comes from Demis Hassabis, founder of AI company DeepMind, which was acquired by Google. He says:
AI is the "science of making machines smart."
That means making machines that can do intellectual tasks that humans can do. Tasks like: read, write, and understand text; see and identify objects; move around obstacles; hear and understand language; and sense the external environment.
Machines are able to do all of these things thanks to AI.
That's because AI allows machines to learn. Unlike traditional technology, AI can actually detect patterns in data, then learn to make predictions from those patterns. It can then learn from its outcomes to make better and better predictions over time.
Once trained by humans, AI can go learn and improve on its own. The more data you give an AI system, the better it can learn and improve.
Whether you know it or not, you use AI dozens or hundreds of times each day.
Gmail and Google Docs use AI to understand what you're typing, then predict what you want to type next. Every time you (and millions of others) use this feature, you train the AI to get better and better at predictive text.
Self-driving cars use AI to detect obstacles and drive safely. Every mile they drive gives them more data to improve their driving abilities.
Siri and Alexa use AI to understand voice commands and predict what responses make the most sense. Every time you talk to them, they learn to improve the quality of their responses.
In fact, AI isn't just one technology. It's an umbrella term that encompasses a range of smart technologies like these that can learn and improve on their own. Some AI technologies you might hear about are: machine learning, computer vision, natural language generation (NLG), natural language processing (NLP), deep learning, neural networks, and speech recognition. There are dozens of others, too.
You don't need to know every term to be successful with AI. You just need to understand that AI-powered technology has the revolutionary ability to learn and improve on its own.
The ability to learn and improve on its own is why AI gives you a huge competitive advantage in advertising.
Why Do You Need AI for Advertising?
AI is an absolute must if you want to win in the new landscape of modern programmatic advertising.
Thanks to the internet and programmatic advertising, we now have the ability to reach consumers across hundreds of digital platforms. We also have the ability to target them based on hundreds and thousands of demographic and behavioral data points. We can even test hundreds or thousands of different ads to see what they respond to best.
Unfortunately, humans aren't good at managing any of this.
Make no mistake, we're great at being strategic and creative. This served us well in the Mad Men days of advertising, when a smart idea and clever slogan meant your ad campaign would succeed. Today, we are still integral to strategizing and creating unforgettable ads.
But we're not good at the rest of it. We can't analyze all the data we now have quickly enough to take action to improve campaigns. We can't manage hundreds or thousands of ad, targeting, and budget variations to get the best results. And we certainly can't find new customer opportunities in a sea of data.
AI can do all of these things and more. That's why forward-thinking companies are using AI to:
- Allocate advertising budgets, both across channels and audiences
- Adjust advertising budgets automatically to hit KPIs
- Find new advertising audiences and conversion opportunities
- Build richer audience profiles
- Determine and hit campaign goals
- Gain insight into competitors' ad spend, creatives, and strategies
- Create ad copy
- Create visual ad creative
- Hyper-personalize ad messages and images to individual consumers
- Hyper-personalize ad targeting
- Predict ad performance before launching campaigns
- And much more
Your company can be doing this, too. In the rest of this post, we'll get you started with use cases and tools for AI in advertising.
Top Use Cases for AI in Advertising
There are dozens of use cases for AI in advertising—here are some of the most powerful ones.
Buy and Place Programmatic and Digital Ads
Today's advertising relies on programmatic to target and deliver ads in real-time across the internet. AI is critical to the infrastructure that underlies advertising products on many platforms, though you may not always see it. Modern programmatic platforms often use AI to manage real-time ad buying, selling, and placement.
In fact, all digital advertising exchanges and platforms use artificial intelligence to regulate the purchase and sale of advertising in real-time. That includes programmatic exchanges, third-party networks, and advertising on platforms like Facebook, Instagram, and Snapchat.
You won't find these exchanges, services, and platforms revealing how their AI algorithms work anytime soon though. But that's the point: Even behind the scenes, artificial intelligence dictates how your ad spend gets used, who sees your ads, and how effective your overall campaigns are. That means if you run paid advertising, you need to understand the terminology around artificial intelligence and ask the right questions about how the AI used by ad platforms may be affecting your spend.
A very basic example of this is:
Facebook advertising, specifically ad frequency and relevance score. These two numbers are key pieces of data that Facebook's algorithms use-without human involvement-to dictate how much you pay and how your ads are displayed.
You might think showing your ad more frequently is good. But it's not. As Social Media Examiner puts it:
Traditional advertising research has shown that optimal ad frequency is at least three exposures within a brand purchase cycle. Traditional advertising schools say that you need to "hit" your audience with the same ad as many times as possible. However, repeat exposure on Facebook might actually hurt your campaign.
That's because Facebook's algorithms take into account user feedback. If you show your ad too often, and it's rated poorly by users, your relevance score may go down. "In most cases," says Social Media Examiner, "the higher the frequency, the lower the relevance score."
A high relevance score means your ad is more likely to be shown to a target audience than the other ads you're competing with. That translates into better performance and lower costs.
In modern advertising, you need to try to understand the algorithm as much as you understand your audience.
Optimize Advertising Budget and Performance
Performance optimization is one of the key use cases for AI in advertising. Machine learning algorithms are used by commercially available solutions to analyze how your ads perform across specific platforms, then offer recommendations on how to improve performance.
In some cases, these platforms may use AI to intelligently automate actions that you know you should be taking based on best practices, saving you significant time. In other cases, they may highlight performance issues you didn't even know you had.
In the most advanced cases, AI can automatically manage ad performance and spend optimization, making decisions entirely on its own about how best to reach your advertising KPIs and recommending a fully optimized budget.
In another case, there exists at least one platform that allocates ad dollars automatically across all channels and audiences, so human beings can focus on higher-value strategic tasks, rather than manual guesswork about what works and what doesn't.
Your ad targeting matters just as much as, if not more than, your ad copy and creative.
Thanks to platforms like Facebook, LinkedIn, Amazon, and Google, you have a seriously robust set of consumer data with which to target audiences, both through desktop and mobile advertising. But manually doing so isn't always efficient.
AI can help here. We know of at least a few AI systems that look at your past audiences and ad performance, weigh this against your KPIs and real-time performance data coming in, then identify new audiences likely to buy from you.
Create and Manage Ads for You
AI-powered systems exist that will actually partially or fully create ads for you, based on what works best for your goals. This functionality is already present in some of the social media ad platforms, which use some intelligent automation to suggest ads you should run based on the links you're promoting.
But it also exists in some third-party tools, which actually use smart algorithms to write ad copy for you. These systems leverage natural language processing (NLP) and natural language generation (NLG), two AI-powered technologies, to write ad copy that performs as well or better than human-written copy-in a fraction of the time and at scale.
See AI for Advertising in action!
If you're a brand marketer handling your paid spend, see how AI-powered AiAdvertising can help you at every stage of the advertising cycle from persona building to analysis.
You can make informed decisions through interactive and dynamic dashboards, get more from your marketing budget and increase your return on ad spend. Kevin Myers, AiAdvertising's Chief Product and Marketing Officer, dives into the platform.
Real-World Examples of AI in Advertising
AI advertising is reshaping how brands do business.
Equipment Company Attracts Top Talent Using AI Advertising
HOLT CAT is a heavy equipment company that was interested in attracting talent across a specific line of business. Limited talent was delaying work for customers and slowing down new sales. HOLT CAT turned to AI to create an ad campaign that could attract talent quickly and effectively.
Using employee data and AI-powered ad platform AiAdvertising, HOLT CAT was able to personalize ad messages to appeal to top candidates for open positions. Using the tool, they were also able to get clarity on exact ROAS, and lower their cost per hire by 20%. Not to mention, the company hired 270 new people since the start of the campagin—and, on average, 40% of those hires report being influenced to join the company by the advertising.
One of World's Largest Investment Firms Uses AI to Boost Ad Conversion Rates by 15%
Vanguard, one of the world's largest investment firms ($7 trillion in assets under management), turned to AI language platform Persado to conduct highly personalized advertising.
The company's Vanguard Institutional business faces a heavily regulated advertising environment, and was only able to run ads on LinkedIn. Due to regulations of what companies could and couldn't say in ads, the financial services ad landscape lacked easy ways to stand out.
Using AI from Persado, Vanguard was able to hyper-personalize its ads and test them at scale to see exactly what approaches resonated with consumers—a level of personalization and testing impossible without AI. As a result, the company saw conversion rates go up by 15%.
Ecommerce Company Gets 3,000% Return on Ad Spend Using AI
In one high profile example we covered, an AI advertising system helped an ecommerce company achieve a 3,000% return on ad spend—while reducing costs.
Entrepreneur Naomi Simson, a host on Shark Tank Australia, owns a company called RedBalloon, which sells gifts and experiences online (think: an experience-focused Groupon). She was spending $45,000 per month on ad agencies alone to run digital advertising for the brand. She was paying over $50 to acquire a single customer at the time.
Desperation drove her to investigate every possibility. She found an AI tool for advertising called Albert. The tool uses sophisticated AI to analyze ad campaigns, then manage targeting, testing, and budgets.
The tool was able to do things humans couldn't. In one day alone, it tested 6,500 variations of a Google text ad and learned from the experiment. Over time, the tool was so effective at learning from data to improve performance that it skyrocketed RedBalloon's return on ad spend. At one time, the company was getting a whopping 3,000% return on ad spend. They also cut marketing costs by 25% thanks to improved efficiency.
Top AI Advertising Tools
Here are some of the top AI advertising tools to look into for smarter, scalable ad campaigns.
Tools like AiAdvertising take the guesswork out of getting ROI from your ads...
The company's solution uses proprietary machine learning at every stage of the advertising process and is customized to each brand's specific KPIs.
As a result, marketers can predict, scale, and execute hyper-personalized campaigns. In the process, they eliminate waste and supercharge performance. The company even says it can convert what used to take 24,000 hours of human work into less than three days of effort.
This eliminates human guesswork, and provides data-driven insights and performance gains during each phase of an advertising campaign.
Persado is an AI content generation and decision platform that hyper-personalizes language in ads to boost conversion rates across LinkedIn ads, Facebook ads, and other types of advertising and content marketing.
OneScreen uses AI for out-of-home ad delivery, targeting, and measurement. The company's machine learning algorithm automatically optimizes which content and ads get shown to audiences, taking the guesswork out of out-of-home advertising.
Pathmatics uses AI to bring transparency and insight to advertising.
The tool shows you exactly how your ads perform across channels and gives you competitive intelligence about how your competitors' ads perform, fueling ideas for effective creative and placement.
Beam.city helps clients affordably and quickly acquire customers with AI-powered ads on millions of sites.
The company uses AI to do automatic ads setup, monitoring, learning, and optimization pattern recognition. They also use AI to create predictive datasets for targeting personas based on where they live and work in Canada and the US.
As mentioned, Albert is a player in the AI-powered advertising space. The company's AI platform analyzes data across your ad accounts and customer databases, then uses sophisticated machine learning to target, run, and optimize your ad campaign.
Another AI-powered tool is GumGum, which uses computer vision technology to learn from images and videos across the web, then help you place ads in the exact spots consumers will see them.
This content is presented by:
As Chief Content Officer, Mike Kaput uses content marketing, marketing strategy, and marketing technology to grow and scale traffic, leads, and revenue for Marketing AI Institute. Mike is the co-author of Marketing Artificial Intelligence: AI, Marketing and the Future of Business (Matt Holt Books, 2022). See Mike's full bio.