How to Avoid Epic Content Marketing Fails with AI

You are probably making one or more epic fails in your content marketing.

Good news: you’re not alone. Plenty of marketers make some big, common mistakes when trying to build effective content marketing programs.

Bad news: that doesn’t change the fact you’re still making mistakes that prevent your brand’s content from connecting with people and converting them into customers.

Better news: help is on the way.

AI in content marketing offers a smarter way to work. Combined with human intelligence and creativity, AI can help you learn more about your target audiences and build a strategy that actually works.

We spoke to Bart Frischknecht, CEO of Cobomba, a company that offers an AI-powered content strategy tool. He’s an engineer-turned-marketer now working at the cutting edge of content marketing and AI, so he knows a thing or two about how this topic.

Here, he reveals the exact mistakes content marketers need to avoid, how to fix your content marketing with AI, and how to get the most out of AI-powered tools.

What is the most common mistake you see content marketers making today?

The most common mistake is not settling in on your ideal customer profile. Content marketing is super powerful when you connect with your audience. But, it’s easy to feel so much pressure just to get content out the door, to sit down and start creating content based on a vague idea about who your audience is.

How do you define an ideal customer profile?

We’re talking about identifying some basic targetable characteristics. So, can I find this person out in the real world? That usually comes down to demographics or firmographics. You can begin testing your ideas with tools like LinkedIn or Facebook, or wherever you find your audience. Even if you’re not running paid, you can use these tools to figure out the size of your audience, and start thinking about their roles, activities, and preferences.

You can also start thinking through the audience’s key behaviors, motivations, and needs. Writing those down forces you to be a lot clearer with who you think this person is. There are obviously a lot of ways to go deeper than that, but this is a good start.

What mistakes do you see content marketers make after they have an ideal customer profile?

It’s easy to let the content calendar lead rather than the strategy. Once you’re dialed into your customer, it’s easy to think about blocks that you need to fill, then schedule out blog topics for the month. Then, you layer on top of that activities like webinars — and work to get the content out the door. But, it’s actually more helpful to take a step back and think about the content strategy: how the content aligns with your overall business objectives.

I think there are lots of marketers out there who are executing great, even complicated, content calendars. But can they tell the story internally about who their audience is, why they’re important to the business, and how they’re reaching them with engaging content?

What are some signals of a strong content strategy?

You know your target audiences. If you have more than one persona, you know something about how each is different. You also have a concept of the buyer journey.

Once you have those, you can then think about your content capabilities. What types of content should you produce? What velocity of content should you have? What is your timeframe? What content investments are you going to make?

These questions help you connect the dots between the needs of your audience, your own capabilities, your timing, and how you can use content to move people through the buyer journey.

All of these elements combined result in a great content strategy.

How can artificial intelligence help create content strategy?

I see an explosion of AI tools across the content spectrum. But one of the main ways AI can help is to close the loop on all the analysis tools we have. Marketers don’t have the ability or desire to wrangle all the data they need. And they don’t have the time to think holistically about all the content that’s gone out, its impact on their strategy, and how that impacts the overall content marketing process.

I think that feedback loop is a big part of the AI opportunity. Effective tools surface that feedback to the marketer. AI can help you understand how you’re performing and how to make better decisions based on that performance.

I also think we’re going to see more and more AI tools take advantage of Google data, survey data, and review data. The data is already out there, and it shows you what customers already search for and care about. When you’re dialed into that data, it gives you a window into what really matters.

What types of AI tools should marketers be looking into?

I think it’s really important to think about where you are as an organization and not try to bite off too much. Break down each task you’re trying to do using AI to make it manageable. Chances are, you’ll end up using one tool for content planning, another for feedback on your marketing copy, and another for the creation of content. There are also tools to then personalize and distribute that content.

Think about your current processes and look for the biggest bottlenecks. Is there a tool to address the bottleneck that you can adopt?

One area we find critical is planning. We feel there is a lot of value for marketers to be more proactive in their planning. We all live and die by our marketing automation tools these days, but those tools assume we show up with a really good strategy.

But how do you come up with a good strategy to begin with? At Cobomba, that’s one of the pain points we set out to solve with AI.

What questions should marketers be asking about AI and AI tools?

It’s important to understand how the technology and specific tools will fit into your current workflows. If the tool is going to require a bunch of additional work to get value, it may be hard to take advantage of it.

You also need to check if the tool is bringing its own data with it. Some AI tools use widely available data to function, like Google and search engine results, so you can use them out of the box. Others require you bring your own data to the table, so you need to ask about the quantity and quality of data required.