As a marketer, you can start using AI in advertising to dramatically improve your performance today, even if you don't know the first thing about artificial intelligence.
At Marketing AI Institute, we're marketing professionals just like you. We got interested in AI because we were curious how the technology could drive results for our marketing team. So we spent years investigating AI use cases, experimenting with the technology, and tracking thousands of AI marketing and advertising vendors. And, in the course of our work, we found a number of ways marketing professionals can use artificial intelligence to advertise better.
This post details what we've learned about how marketers can use AI and advertising together to create massive success starting today.
A 2-Minute Definition of AI
You don't need to be a rocket scientist to understand the basics of AI.
If you ask 10 different experts what artificial intelligence is, you'll probably get 10 different answers. But one simple definition we like comes from Demis Hassabis, CEO of DeepMind, an AI startup acquired by Google.
Hassabis calls AI the "science of making machines smart."
We can teach machines to be like humans. We can give them the ability to see, hear, speak, move, and write.
Those machines would be called AI if they could then teach themselves to get better at seeing, hearing, speaking, moving, and writing-without human involvement.
That's exactly where we stand with AI capabilities today. You've likely encountered an AI tool or AI models that use speech recognition, computer vision, natural language processing, AI chatbots, or another AI capability to see, hear, speak, move, and/or write. These tools then get better at those things without being explicitly programmed to get better.
A voice assistant like Alexa is a great example of this.
Let's say you tell Alexa to "Play my workout playlist on Spotify."
Alexa hears your words, its AI algorithms process them, and then Alexa responds and takes action. At no point is Alexa being directly told by a human how to interpret your words, how to respond, and how to take action.
Alexa is using artificial intelligence to make predictions on its own about what your words mean, how to respond to them, and what action you're requesting.
Alexa is not being programmed explicitly to get better after each user's query. Instead, Alexa is using data from each interaction with users to improve its interactions with the next one.
Which is why, in December 2018, Alexa improved its answers to queries by 12 percentage points (up to 73% accuracy) compared with July of that year.
So, how is this different from traditional software?
Traditional software needs to be explicitly programmed to improve.
If Alexa were not powered by AI, it wouldn't exist as a consumer product. If you asked Alexa to play your workout playlist and it didn't understand, a human would have to manually correct it before it could improve and get it right next time.
That is impossible with millions of Alexa users giving millions of commands in real time.
But, with AI, Alexa can use machine learning algorithms to learn from data at scale, then improve at speed. And recent developments in deep learning (an advanced type of machine learning) may make these tools even more powerful in coming years.
AI is not traditional marketing automation. Unlike automation, it doesn't only follow rules hard-coded by humans. Instead, it has the potential to learn on its own, improving its accuracy at speed and at scale, which both destroys the traditional, non-AI competition (human or machine) and unlocks entirely new capabilities.
That's why AI advertising makes so much sense for your digital marketing and advertising plan.
How AI Is Used in Advertising Today
So, how is AI actually used in advertising?
We're seeing a few major use cases for AI-powered systems that are being deployed by marketers and advertisers today across platforms and channels.
Programmatic advertising exchanges and ad tech platforms use artificial intelligence and machine learning to regulate the purchase and sale of advertising in real-time. That includes nearly every ad exchange , third-party network, and advertising product on platforms like Facebook, Instagram, and Snapchat.
You won't find these exchanges, services, and platforms telling advertisers how their AI works anytime soon. But that's the point: Even behind the scenes, artificial intelligence dictates how your budget 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 (this resource is a great place to start) and ask the right questions about how the AI used by every ad platform 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 the algorithms that power Facebook ads 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.
The point here is this:
Advertisers ' campaign performance and budget effectiveness are likely dictated by the complex interplay of data points used in the AI systems that power today's ad exchanges.
Optimize Budget and Targeting
Artificial intelligence tools exist today that can automatically optimize advertising spend and targeting. AI can process your ad spend and targeting data, look at your results, then learn what actions (spending changes, targeting changes, etc.) will drive better performance. These actionable insights are provided and acted upon at scale across a large number of complex campaigns.
In one example we learned about, travel company RedBalloon used an AI platform called Albert to automatically optimize their digital ad spend and plan. The results were impressive.
Albert was able to identify ways to optimize spend and targeting that dramatically raised return on spend, and significantly beat out human agencies. The tool also, using the insights it learned from sufficient amounts of spend data, actually found new audiences for RedBalloon's wares that the company didn't even know were relevant customer segments.
Overall, the ability of AI to learn and improve without human involvement gave the brand a massive competitive advantage over both human-powered ad programs and those using traditional software.
Ad Creation and Management
AI dictates how your ads perform, and can even help you dramatically boost performance. But it's also used today to substantially streamline the work that goes into building ad campaigns.
Platforms with advertising components, notably Facebook , have AI that will help you create ad copy and ad variations much faster than through manual labor alone, using content you've already uploaded.
But, some commercially available tools take that one step further. AI-powered tool Phrasee actually writes Facebook and Instagram ad copy for you, from scratch, and the ads are designed to convert into clicks based on what's worked in the past. The tool gets better over time on its own, as it learns from each new ad what language leads to better performance.
(This is the same type of AI technology that powers content creation use cases for content marketing, too.)
An AI system can also help you save time on overall ad campaign management. WordStream uses machine learning to quickly and efficiently analyze your ad campaigns, then pairs it with the ability to make changes across ad campaigns on Facebook , Google, and Bing with a few clicks.
How to Get Started with AI in Advertising and Marketing
Make no mistake: AI is changing the marketing and advertising industry as we know it.
If you're an advertiser or marketer relying on paid ads, chances are that an AI solution can help you increase revenue and reduce costs. That means now is the time to leverage AI, no matter your skill or comfort level.
Forward-thinking brands are already embracing artificial intelligence marketing and advertising. And they're using it to build competitive advantages by combining customer data in brand new ways with the power of AI. Using it, they're optimizing every marketing campaign to dramatically increase customer engagement by creating a personalized experience at scale at each stage of the customer journey.
Good news, though.
There's a great way to accelerate AI adoption in your marketing strategy.
Access our AI Academy for Marketers, an online education platform that brings the power of artificial intelligence to you.
The Academy is designed for manager-level and above marketing professionals, and largely caters to non-technical audiences, meaning registrants do not need backgrounds in analytics , data science or programming to understand and apply what they learn to supercharge their marketing efforts.
Available now, the Academy features deep-dive Certification Courses (3 - 5 hours each), along with dozens of Short Courses (30 - 60 minutes each) taught by leading AI and marketing experts.
The Academy will have 25+ Courses, including at least five Certificates , all available on-demand. The content is structured by marketing categories, and we plan to offer recommended Learning Paths as well for specific industries and job roles.
New content will be regularly added to the platform , and all Members get access to an exclusive online community to foster collaboration and knowledge sharing with their peers.
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. An avid writer, Mike has published hundreds of articles on how to use AI in marketing to increase revenue and reduce costs. Mike is the co-author of Marketing Artificial Intelligence: AI, Marketing and the Future of Business (Matt Holt Books, 2022). He is also the author of Bitcoin in Plain English, a beginner’s guide to the world’s most popular cryptocurrency.