Are you looking to learn more about what artificial intelligence can do for your marketing?
Look no further...
This post has you covered.
What is AI marketing?
Artificial intelligence is the process of making machines smart. We give machines the ability to perform intelligent tasks like seeing, hearing, speaking, writing, listening, or making predictions.
AI has transformed numerous industries and led to astonishing breakthroughs. It powers everything from self-driving cars to your home smart speaker. And it's unlocking unprecedented capabilities in marketing.
AI marketing is the process of applying artificial intelligence to your marketing efforts.
By using AI, companies are increasing revenue from marketing and reducing the costs associated with marketing activities.
That's because AI is able to make predictions. These predictions power marketing outcomes.
AI can assess data from your marketing efforts (ad performance, contact behavior, content performance, etc.), and then predict which activities will produce optimal performance.
Examples of AI marketing
Today, AI is used across the following marketing functions:
- Advertising — AI is used to manage ad campaigns, predict ad performance, and allocate budget.
- Analytics — AI is used to analyze data and predict what actions to take next.
- Communications and PR — AI can write and edit communications, as well as do social listening.
- Content marketing — AI can generate content at scale and make predictions about content performance.
- Customer service/customer journey — AI is able to converse with customers and make recommendations that improve how customers interact with your brand.
- Ecommerce — AI can recommend products and services based on purchase history.
- Email marketing — AI can write subject lines and newsletters for you, as well as optimize email send time based on user behavior.
- Sales — AI can nurture sales leads for you and identify which leads are most likely to close.
- SEO — With AI, you can determine how to highly rank a piece of content on any given topic.
- Social media — AI is used to create social media posts at scale based on your existing content and messaging.
AI marketing can be used across every single industry that does any of the marketing actions above.
AI marketing tools
There are thousands of AI marketing tools. Here at Marketing AI Institute, we've spent years vetting marketing technology. The tools below are some of the ones we've found to accelerate your marketing with AI—broken out by the categories above.
- Advertising — Pattern89 uses AI to predict your advertising performance on Facebook and Instagram, before you launch a campaign.
- Analytics — Google Analytics is a popular marketing analytics tool, but not everyone realizes it has sophisticated machine learning that can help you ask smarter questions about your data.
- Communications and PR — Grammarly is an AI-powered tool that checks your grammar, tone, and writing style for you on every single document, offering writing suggestions as you go.
- Content marketing — HyperWrite uses AI to actually write full sentences and paragraphs of content for you.
- Customer service/customer journey — Zendesk is a popular customer service platform that heavily leans on AI to provide customers with better answers to their questions.
- Ecommerce — Amazon uses AI in its own business to recommend you products you might like, and it also enables brands to do the same by selling its recommendation AI capabilities through Amazon Web Services.
- Email marketing — rasa.io uses AI to automatically create email newsletters with personalized content for every single recipient.
- Sales — Drift uses AI chatbots to help your sales team accelerate revenue and build pipeline.
- SEO — MarketMuse uses AI to predict the topics you need to cover in order to rank highly in search results.
- Social media — Lately is an AI solution that automatically turns blogs into social media posts.
How to get started with AI for marketing
“How do I get started with AI?” This is one of the top questions we get from marketers.
A lot of professionals want to understand and apply AI to their work. But they don't know where or how to start.
It's understandable. There is a lot of content out there on AI. And there's a ton of hype.
So I want to walk marketers through how I would approach this process, using mock examples.
The goal? Show you how a brand could actually go from conception to reality with marketing AI.
Let's say I'm a marketing manager at a large manufacturing company. Our business is largely B2B, selling widgets for machinery used in the oil and gas industry.
I’ve been tasked by our CMO to investigate the potential of AI to improve our marketing operations. We're not the most sophisticated marketing department around. But we're doing OK:
We use marketing automation software to manage our contact database. We have a content marketing program. And we use some basic lead scoring and email marketing to qualify leads.
But, we still invest a lot in trade shows. We sell a lot based on relationships and referrals. And the other departments we work with don't really get the whole point of "online" marketing. Our team is talented, but still learning advanced content marketing and inbound marketing.
So, we're still working to bring our marketing into the modern world.
Now, we're hearing all about artificial intelligence and how it's the future.
What exactly is AI? Is it right for us? How do we even go about applying it?
We know we need to do something here. We just don’t know exactly what.
Step 1: Evaluate your use cases.
In fact, I would start by looking at my actual use cases. Notice I didn’t say “use cases for artificial intelligence.” (That comes later.)
I want to define my problems, then see how AI might help. That way, I don't overfit AI to a use case it might not apply to.
How would I do that? I'd list out all the repetitive tasks my marketing team does every day. Then, I'd break them down into repeatable steps.
Use your best judgment, but you probably have a pretty good idea of what activities take up the most time. For my made-up marketing department, these tasks look like the following:
- Create and edit content for our blog and for social media.
- Create premium content to generate leads and support our sales team.
- Promote content of all types using social posts and paid promotion.
- Strategize and launch formal marketing campaigns in our marketing automation software.
- Send marketing emails to our database of contacts.
- Pull performance reports on various campaigns and marketing’s overall success against KPIs.
Now, I’m sure there are plenty of other things we do. But these take up 90% of my team’s average day.
Step 2: Pick a single use case.
All these use cases might be useful to intelligently automate with AI. But if I can use AI on even one of them, I'd be in good shape. I'd free up tons of time and improve team performance.
To keep it simple, pick a single use case from the list to start exploring.
In this scenario, I’m going to start with something that takes up a ton of my team’s time:
Step 3: Break down the use case into repeatable steps.
Something like “creating content” is a pretty broad use case. So I want to break it down as much as possible. There are plenty of repeat tasks that we do to create content:
- Brainstorm topics.
- Pick topics that will perform well.
- Build an editorial calendar or plan of those topics.
- Outline each topic.
- Write posts on each topic.
- Edit posts.
- Upload posts to marketing automation software.
- Publish posts to blog.
With these repeatable steps, I have a starting point to research AI applications.
Step 4: Do initial research.
I’d begin my initial research by conducting some basic searches for my use case and its repeatable steps. For the above, consider some of the following types and formats of searches:
- “AI for content marketing”
- “Create content with AI”
- “AI for blogging”
- “AI for content topics”
- “AI for content performance”
- “Build content calendars with AI”
- “AI for writing”
- “AI for blog writing”
- “AI for editing”
- “AI in marketing automation software”
I'll pull my most promising links into a common repository. As I read and research, I'll also note names of interesting solutions that come up.
Hint: You'll find a lot of this on the Marketing AI Institute blog, including specific solutions. And to truly understand, pilot and scale AI—while learning from anywhere—check out the AI Academy for Marketers.
Step 5: Narrow down possible solutions.
By now, I have a better idea of what's out there. I also have some names that jumped out during my research:
- Phrasee, a content strategy platform powered by AI
- Crayon, a competitive intelligence platform that uses machine learning
- BrightEdge, an AI-powered SEO platform
- HubSpot, the marketing automation software we already use, which may be using some type of AI
I don’t know a huge amount about each of these solutions just yet. So the first thing I’d do is check out each of their websites to learn more about them.
I would also look for articles and reviews about them.
Step 6: Demo and test technology.
It looks like all of these tools could potentially benefit my content creation in some way. But to be sure, every marketer should demo or test drive tools for themselves.
Because AI tools have pretty specific applications. You need to make sure your brand actually has the data required to make the tool work. And you want to confirm it has the capabilities the vendor says it does.
There's no substitute for this step. AI has a lot of hype and buzz: it's easy to get sucked in by bold claims about capabilities.
This is why having a specific use case you can bring to vendors is essential. You'll be able to tell readily if the solution does what you need it to do.
Many vendors offer free trials and demos. Take advantage of them.
Step 7: Build an AI strategy.
Let’s say you’ve vetted some tools and like what you see. You’re ready to secure budget and start rolling some of these out.
You need an AI strategy. A formal one that's documented and vetted by key stakeholders. This strategy is going to formalize how you rollout these tools. It's going to streamline implementation. And it's going to help you understand where your team is going with all this.
Now, you don't need this document before you test drive any AI tool. You could even start piloting one or two tools while you create your strategy. But the document is a must earlier rather than later in the process. It'll take some time to create, too, so the sooner you start, the better.
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.