AI in content marketing presents opportunities for brands to create, promote and optimize their content marketing at scale. But finding the right tools and strategies to get started can be challenging.
Thankfully, AI Academy for Marketers is here to help.
In case you aren’t familiar: AI Academy is an online educational platform that helps you understand, pilot, and scale AI. We created this platform to help marketers gain access to affordable, AI-focused education that advances learning and aids in AI implementation.
AI for Content Marketing 101 is one of the Academy’s deep-dive certification courses for members. In the course, Mike Kaput (@MikeKaput) of Marketing AI Institute dives into the opportunities and potential impact of implementing AI into your content marketing.
Keep reading for more on the course, plus some course insights to get started with AI and content today.
What to Expect from the Course
This course shows you exactly how to start using AI in your content program. The result? A potentially insurmountable advantage over competitors still creating content campaigns in a completely manual fashion.
Today, we see AI as an opportunity to help you transform your business. For content marketers, AI has the ability to decrease costs and prove ROI.
In this beginner-level, 2.6-hour certification, you will:
- Create intelligent content strategies that target the right people, talk about the right topics, and get audiences to take action.
- Augment your current content production teams with robust AI tools, so they can produce better assets in less time.
- Scale your content marketing programs by using AI to create, test, and optimize.
What is AI?
Before we plunge into AI and content marketing, it’s crucial to have a basic understanding of what AI is. Luckily for us non-data scientists, you don’t need a degree in computer science or machine learning to understand what AI is, and how it can help you as a content marketer.
At MAII, we like this definition from Demis Hassabis, Co-Founder and CEO of DeepMind, “AI is the science of making machines smart.”
Making machines smart means that we teach machines to be more human. We give them the ability to see, hear, speak, move, write, and in some capacity, understand. AI is designed to make predictions and AI technology is able to successfully do these tasks because of this predictive power.
For example, your Google Home Assistant. The designers of Google Home tell the machine to interpret what you’re saying so it can predict what you’re asking for. The outcome? The machine gives you the answer you want, completes a shopping order, turns on music, or assists you with whatever you want it to do.
Now that we understand AI conceptually, what is it physically?
AI is Smart Software and Hardware
Physically, AI is just smart software and hardware. AI makes it “smart” because of the specific and complicated mathematical algorithms that power these systems.
The difference between non-AI software and AI is that the non-AI software follows a set of rules designed by a human and it has to consistently follow those rules. For AI, the machine can create its own algorithms, determine new paths, and unlock unlimited potential. It is this ability that makes AI different and special.
To understand if something is truly AI, we have to ask ourselves, “Is the machine getting smarter on its own? Or does it have the potential to get smarter on its own?” If the answer is no, you’re dealing with traditional non-AI technology. If the answer is yes, then congratulations, you’re looking at a type of AI that you can potentially leverage.
How Can AI Benefit Content Marketers?
So we’ve discussed AI and what it is, but how do you implement it as a content marketer? AI can help drive content marketing success, and by understanding this, you’ll have more of an idea of how it can benefit you.
Every content marketer knows that content is not cheap. Blogging, email, social, brainstorming, and reporting takes a lot of our time. The financial commitment is only increasing as businesses find that content drives more leads, traffic, and revenue for less than other marketing tactics. Content Marketing Institute reported that 56% of B2B marketers report increased spending on content creation.
AI doesn’t just cut costs for content marketers, it also makes them more money.
AI drives revenue by improving your ability to make predictions about content marketing. Using data, AI tools give you the ability to better predict content performance. AI tools can look at your website and data from other websites to guess with a high degree of accuracy what works and what doesn't. For example, AI can help predict which topics lead to higher search ranking and predict site pages that are most relevant to your consumer based on search history.
AI is valuable to content marketers because it helps us predict content performance, and as a result, you get better ROI for your content marketing initiatives.
How to Approach AI
It’s time to turn this theory into practice. During the course, Kaput addresses the question: How do you approach AI as a content marketer?
For most organizations, the best way to get started with AI will be quick-win pilot projects with narrowly defined use cases and high probabilities of success.
Quick-win pilot projects are small projects that use AI to address narrowly defined use cases with high probabilities of success. Narrowly defined use cases make sure that your time, energy, and attention are focused on narrowly defined problems that can impact your business. Without a clearly defined use case, you’ll have trouble understanding which tools are right for you and your business.
Below are three questions to ask to identify an AI use case (Kaput covers these in more depth throughout the course):
1. Is it data driven?
Does the task rely on data of any kind? For instance, you may rely on data from your analytics system to create content performance reports every quarter. This could be an interesting use case for AI because it uses data to make predictions. Anything that is data driven is potentially a great AI use case.
2. Is it repetitive?
Pay attention to those tasks you do regularly in the same way or similar way every time you do it. For example, writing blogs. When you write a blog, they follow similar formats (list articles, how-tos, overviews). We are repeating the same content formats so this could be another potential use case for AI.
3. Does it require you to make a prediction about an outcome?
Anything that you’re doing that is trying to predict outcomes could be a great use case for AI. For example, when you’re creating content calendars you’re constantly trying to predict which pieces of content will get the most traffic and engagement.
Ready to discover these and other important AI concepts? Sign up for the AI Academy below.
Gianna is an intern for Ready North and Marketing Artificial Intelligence Institute. She is a senior at Ohio University studying Management Information Systems, Analytics, and Marketing.