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What is Artificial Intelligence? Dust Off Your Content Strategy With AI

Michael is the Content Strategist at Atomic Reach, an all-in-one enterprise platform built to boost content performance. He is on a mission to empower marketers with actionable data so they make more informed decisions about their content strategy.

Artificial Intelligence, often shortened to AI (we'll make some points about this later), seems like it is everywhere these days.

You can use big data and machine learning to boost your performance in almost every industry, including content marketing.

 

What is Artificial Intelligence?

Things have come a long way since we started trying to develop machine intelligence. The last decade has seen computers developed that can beat world chess and go champions. AI is now on par with human doctors when it comes to diagnosing medical conditions using medical imaging technology. 

According to Data Science Central, artificial intelligence is: 

“...a broader concept than machine learning, which addresses the use of computers to mimic the cognitive functions of humans. When machines carry out tasks based on algorithms in an ‘intelligent' manner, that is AI. 

Machine learning is a subset of AI and focuses on the ability of machines to receive a set of data and learn for themselves, changing algorithms as they learn more about the information they are processing.”

Artificial intelligence is the “science of making machines smart,” according to Demis Hassabis, CEO of DeepMind. 

There are a number of different technologies that combine to give us artificial intelligence, ranging from the simple through relatively advanced.  

From a content marketing perspective, we see everything from text optimization algorithms through to complex sentiment analysis and beyond. Outside of the content  world, AI has begun to infiltrate many parts of our lives, both at home and at work. 

Machine learning is largely where it is at, with many different systems able to self-train from large data sets, needing various levels of human expert support to do so.

Machine learning means computers are able to analyze large swathes of data and extract meaning and direction from what is learned.  Natural language processing (NLP) is also a key part of modern AI technology, forming the basis of many different AI-based services from sentiment analysis through to artificial customer service staff, alongside natural language generation (NLG). Predictive analytics is another core element of artificial intelligence, with systems able to learn from past events and use that data to shape future outcomes.

However, it's not always clear what is meant by the term "artificial intelligence".

While we're still a long way off of developing a self-aware "strong" AI, humanity continues to produce increasingly sophisticated "weak" AIs that are capable of parsing complex data and are able to use that data for sophisticated decision making which effectively mimics what a human would do in that situation.  

At the same time, various shady acronyms are used by developers to imply artificial intelligence where there is none. For example, when AI Ops was first announced, the "A" actually stood for "algorithm", with machine learning only coming in to play later on as the technology matured. 

This isn't to say that algorithms don't have their place. The data explosion brought about by improvements in technology and connectivity over the last few years has created a landscape where humans are unable to understand all of that information without help from machines, let alone gain benefit from it. 

 

Auditing Content

With over 2 million blog posts published every day, honing your content to get the results you want from your content marketing efforts is a steep task for unassisted humans. The sheer volume of the content you are in direct competition with when you publish a blog means it's essential that content marketers use every trick in the book to get ahead. 

You need to look at your content output holistically, taking into account the outcomes of previously published articles, and the number of different metrics that a single blog post can affect makes doing this unassisted a difficult task at best. 

AI can look back at the archive of your previously published content in an instant, giving you detailed insights into which posts performed well or achieved certain goals.

This will help you direct your content strategy by telling you which topics, writing styles, and even publication times work best for your target audience. Not only can you tell which posts generate the most leads, you can use this data to discover what else interests those leads. 

This data is used to do more than simply guide future content decisions. It can help you develop new products and services, map out which blogs generated discussions or where shared elsewhere, and more. Want a list of related topics that you haven't yet covered? Content auditing is here to help.  Ultimately, content auditing can make a hugely important first step towards utilizing AI in your content strategy, as well as for product development. 

An AI-powered content audit should:

  • List the topics covered by your currently published content, and suggest related topics that don't yet have content covering them
  • Provide you with a detailed keyword analysis
  • Tell you about the quality of your current content
  • Offer guidance on what content you should tackle next

All of this will help save time and money versus doing this all by hand, and will help you improve your ROI. This is also just the start of what AI can do for your content marketing. 

 

Personalizing Your Content

Artificial intelligence can help you automate changes to your content, including personalizing what your readers see. You wouldn't think computers could help you speak more directly to your customers on a personal level. In fact, by letting the right AI system tweak your content to target specific customer segments and interests, you can reach out to your readers on an individual basis. 

Modern AI marketing systems can extract your reader's interests, recent purchases and site visits, and more, using this data to present the perfect mix of products or content to attract and keep that customer. Of course, customers will always return to sites they think cater to their personal needs, making this a win-win situation. 

According to Salesforce, by 2020, 51% of consumers want companies to anticipate their needs. Now that personalized content is so common, consumers are likely to think of companies that don't tailor their content as ignorant of their needs. 

 

Types of Content AI Impacts (and How)

Blog Posts

The mainstay of online content, it's a rare company that doesn't have a blog these days.

The quality of your blog content has a huge impact on Google rankings, as well as providing an important resource for your customers. Creating blog content that stands out against a background where every single one of your competitors also has a blog is challenging. 

This is where AI marketing analytics can help.

By analyzing which topics and individual posts have been successful in the past, and predicting which topics haven't been covered in enough depth yet, you can get a head start on your competition. At the same time, AI will tailor blog content to specific users, creating a more personal experience that really speaks to your readers. 

 

Marketing Emails

Email is one of the first areas of marketing content to utilize AI, so if you're not yet using AI for your marketing emails, you're behind the times. In fact, some scientists believe that spam filters are some of the first self-aware software, given the depth of understanding and levels of learning these types of program throw at each other constantly in an eternal spam war. 

Of course as a business you want to avoid the "eternal spam war", and get talking directly with your customers. One way to make sure more of your marketing emails are read by your customers is by using AI to analyze and segment your marketing lists.  

A recent study shows that marketers who used segmented email lists saw a 760% increase in conversion rates. No small change as you can appreciate. 

Even the same newsletter might be more likely to be opened by your customers by using different headlines and opening paragraphs. Doing this by hand would be nigh-on impossible, but AI powered analysis and automation makes it far more difficult not to use this technology. 

 

Search Ads

There's been a huge move to use AI to optimize search ads over the last few years, with Google itself at the forefront with its responsive search ads now able to automatically adjust to meet user's interests and goals. Bing isn't far behind in the AI search ad race, and there are multiple other platforms offering varying degrees of AI insights, adjustments, and keyword bidding control. 

If you use PPC advertising, then these days you must use AI to optimize your campaigns. Out there in the cut and thrust of the online advertising world, humans can't cut it on their own anymore. You need to keep up with what your competitors are doing, as well as the rapid speeds that consumer sentiment changes at. 

 

Landing Pages

We all know about A/B testing. Take advantage of AI, and this could easily become testing with landing page content constantly optimized, tweaked, and re-tested without the need for time-consuming human input.

AI-powered landing page analysis is becoming increasingly popular, and is used to suggest effective tweaks based on past performance and current trends, saving marketers a lot of time and stress. 

 

Product Descriptions

Writing product descriptions that can cut through the dross and reach out to customers through search engines is challenging, and until recently it was a challenge that was often outsourced to the lowest level of remote freelance writers.

Paying less experienced writers a pittance is never a way to get the best results for anything. Luckily wages aren't an issue for AI systems, at least compared to the volume of work that is automated for the costs involved. 

Auto-generation of product descriptions doesn't just mean you get one description per product either. Freed from the need to pay a real person, you can generate descriptions that are tailored to different client segments, making a purchase all the more likely. 

 

Measuring Your Content

Let's talk about metrics and analysis.

You need to know your strategies are working, and more importantly, you need to feed back into your AI-driven systems to keep them up to date with how the world is responding to the content they help produce. 

AI analytics can tell you far more about your content than traditional metrics.

You can find out more than just whether a given piece of content is performing well or not, AI can help you delve into why that content performed as it did, and what you can do to change that. 

With no bias bleeding through from individual marketers, AI-driven insights are purely data-driven. This means they form a much better basis for future content development. The speed that AI can process and analyze content is also orders of magnitude more than humans can manage on their own.

 

How to Implement AI In Your Organization

You may find that your marketing team is concerned about their future in an organization that relies heavily on AI for content, but this need not be the case. Where AI really comes in to its own is in taking on repetitive tasks, and helping hone strategy. 

This leaves your writers and marketers free to innovate and create. In fact, the increase on returns should mean there's more money and work for skilled marketers and content producers.

It's vital that you make this clear as you implement AI in your content marketing efforts.





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