Content Marketing: Like so many things in life, it’s a double-edged sword. It’s both necessary and a real pain in the butt. It takes time, effort, and money, and the results can be slow.
It can be mundane, too. Think of how much time you’ve dedicated to banal tasks like researching topics and keywords. Think how much time you’ve spent writing and rewriting content, optimizing, and scheduling it.
Not to mention testing how different content performs across different platforms before reviewing your analytics.
Then there are marketers like Neil Patel who tell us that our rivals are pumping out a fresh piece of content every single day. That’s literally the last thing we want to read after we’ve just spent the last eight hours creating an epic piece of content.
We were so done with content for another week. And now Neil is telling us that if we don’t want to become obsolete and lose our audience, we’d better stay consistent each day.
In short, content marketing is exhausting us.
But here’s the good news: Machine learning — a field of Artificial Intelligence — is here to take a load off.
In this article, we’re going to plumb the depths of machine learning and explore how it’s shaping the future of content marketing; how it’s going to augment human efforts, and exactly how you can leverage it.
The Problem With Content Marketing As We Know It
Marketing god Seth Godin once said that content marketing is the only marketing we have left. Meanwhile, Google has since changed their algorithm (again) so that marketers have to produce more epic content that’s relevant and super duper valuable to their audience.
The problem here is that many businesses seem to be failing on the content marketing front, with 91% of B2B marketers saying that their efforts are less than effective. 2% even say their efforts are “not at all effective.”
These are strong, dismal words that might resonate with you.
Because the fact is that we’re at a new frontier; we’re living through the golden age of content marketing to some extent, and yet so many of us just aren’t grasping the opportunity, primarily because we know we need to pump out lots of content — but we don’t always know what content hits the spot with our readership, as well as how much content we need to produce and when we need to produce it.
This is where machine learning comes in.
What is Machine Learning?
According to TechMergence, “machine learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion by feeding them data and information in the form of observations and real-world interactions.”
How does this apply to content marketing? Machine learning is able to use algorithms to dive into a huge amount of data before learning from it — and showing you how to act on it.
For example, it can mine swathes of data on your targeted audience before showing you exactly to what type of content specific customers react better.
So Machine Learning Is Going To Replace Certain Content Marketing Skill Sets?
Before the scribes who write the actual content grow too alarmed, AI isn’t going write the kind of epic content that Google wants from you just yet.
Instead, at the moment it can augment your tasks, as opposed to automate them. It will also begin to change the way marketing channels work.
At some point in the future, machine learning will be able to optimize your paid and search campaigns. At this point, the skills that we’ve come to value in marketers will alter.
AI is already able to produce super insightful reports, and as a result, the type of analysis that’s currently valued by marketers will change. Moreover, if marketing machine learning is able to produce better basic content than us, content marketers will have to adapt.
Take a look at Chatbots. Already, they’re so well developed that they can deliver an insane amount of data in a fraction of a second.
Moreover, AI has already written whole blog posts, with tools like Automated Insights possessing the capabilities to write your posts for you.
However, what AI can’t yet do is produce quality content.
High-quality content is what separates the wheat from the chaff on Google, and it ranks better than low-quality content. It’s what Google wants from you. It’s epic, in-depth, long-form content that solves your customers’ problems and educates, informs, and engages.
AI can produce snippets of drab content that can educate and inform, but it can’t engage and it can’t create epic quality.
As such, there’s a clear discrepancy between what machine learning can do for content marketing and what Google actually wants to see from you. Machine learning can create content but its content that falls woefully short of the epic content Google wants.
So what can the machines do?
The Volume Problem
Creating quality content isn’t easy.
As Nicole Martin, vice president, strategy and analytics at Pace points out, “research and consumer insight gathering is a critical step missed by brands big and small.”
Just think how much time and effort it takes you to research and edit your content, let alone maintain it.
This is what machine learning can help you with. As Vedant Misra, founder of Kemvi put it:
“Machines will help us produce content. Machines will suggest assets to include in the content you’re making, or subsets of content to include. Executive control will remain with the creators, but the ideation and production process will become increasingly automated.”
In other words, content creators aren’t about to go out of business anytime soon. What will happen instead is that AI will help you hit the spot with your audience better.
And this is exactly what we all want.
In other words, machine learning is going to save us from the sheer mass volume of redundant content that we’re all drowning in. Marketers are drowning in its creation, while our audiences are drowning in its publication.
There is literally so much content out there that no one wants.
As we pointed out earlier, we’re pumping out lots and lots of content but so much of it is decidedly “meh.”
Why? Because we’ve never been 100% sure what content our audience actually wants from us, as well as when they want to see it, how often and on what device.
So we get a bit panicky as we do all that we can to rank on Google. We look over our shoulder and see our rivals are pumping out fresh content each day, and decide that we must do the same.
As such, we’re all contributing to the “content shock” that sees us collectively produce 2.5 quintillion bytes of data each day.
Things can be different now. Less content can produce the greatest results if you put the right amount of effort in. If you produce epic content, your content will be king.
And machine learning can help with this. Atomic AI is one example of machine learning that’s able to crunch data about your audience before calculating readability. This then allows you to produce better, more customized content that will hit the spot with your readers.
Machine learning analyses thousands of data points about your users, from interactions with your website to the device they use, before recommending you the type of content that will fit each user best.
Then, once you’ve created your hyper-personalized content, AI will tell you when, where and with what frequency you need to be publishing the content if you want to have as much impact as possible.
Once your audience has interacted with your new content, the cycle begins again.
One of the reasons only 9% of B2B marketers say their content is highly effective is because most of the content they produce just isn’t personalized enough.
What your audience wants in 2018 and beyond is content that’s tailored to them and their wants and needs specifically. A “one-size-fits-all” generic piece of content no longer cuts it.
Machine learning can help with your email marketing campaigns, too, making it simpler than ever to create personalized emails that make a connection with your subscribers. This means you can create better segments, while your key metrics — open rate, click through rate and conversion rate — will all go up.
How Machine Learning Can Assist Your Content Marketing Efforts
Machine learning is going to shape the future of content marketing but it all starts right now. Here are a few ways that you can get ahead of the curve:
1. Plan, create, optimize, personalize, measure, analyze, and promote content. All of this takes up a lot of time. As we mentioned earlier, Automated Insights is a neat tool that can help you to create content, while a tool such as Acrolinx can help with the planning and optimizing stages. OneSpot, meanwhile, helps you to personalize and promote your content.
2. Find opportunities so that you maximize your data. Armed with the right type of data (as well as the right amount), you can find insights, put together strategies, forecast outcomes and personalize content. To find the right opportunities from the right data, you should involve machine learning in the process.
3. Take a look at the marketing tech you already use. If you run content marketing campaigns, there’s a chance you already use platforms like HubSpot.
If so, see if they have integrated machine learning into their products yet. This will allow you to get to grips with AI before fully exploring the true potential of machine learning.
There’s an insane amount of content out there, and many of us are working ridiculously hard to produce content that won’t even engage our audience. Some of our content will, but most of it won’t.
In a nutshell, machine learning is here to make your life a whole lot easier. It isn’t going to replace you as a content marketer; it’s going to work with you and assist you.
It’s going to help you level up. It can’t produce epic, high quality, valuable content all by itself, but it can help you create the best content ever and it can show you exactly who wants to read it, when and on what device.
Machine learning is going to save both businesses and readers from poor-quality content. It’s going to help reverse the noise problem. Could it be the perfect solution that’s going to rescue content marketing?
What do you think? Let us know if the comments!
About the Author – Aljaz Fajmut is a digital marketer, internet entrepreneur, and the founder of and Nightwatch— a search visibility tool of the next generation. Check out Nightwatch blog and follow him on Twitter: @aljazfajmut