Artificial intelligence and content strategy

Content strategy is about measuring what content provides a meaningful ROI and marketing value, enabling content managers to double-down on producing content that generates leads and customers, and scale back on content that doesn’t provide good results.

Search engines like Google are now focused on providing search results of high quality. Their search algorithms are becoming good at finding high quality content, and it is becoming increasingly hard to trick them (this is called black hat SEO).

To this end, content strategy tools have started to emerge.

For example, HubSpot measures domain and page authority (these are SEO metrics) and use artificial intelligence to recommend topics on which to produce content. They promote the concept of content clusters, where supporting content (often a number of blog posts) links to a piece of long-form pillar content to help push its authority in the eyes of search engines.

AI and machine learning can be used to help improve the quality of the content as well, either for better SEO ranking or to provide readers with exactly the content they are looking for (and are thus more likely to engage with).

AI and machine learning can be used to help improve the quality of the content

Software tools can use AI to model a topic and build content briefs that show exactly how to write to systematically cover a topic in the best way. For example, what are the relevant concepts to mention in the content? What are the questions to answer? How should content be written to make it rank in search engines?

One company offering a solution for this is MarketMuse. Their tool enables the creation of better articles, increases topic coverage across a website, observes and analyzes the competitive landscape, and discovers content improvement priorities.

I discussed their tool with Aki Balogh, the company’s co-founder and CEO. He describes his product in this way:

By using the MarketMuse methodology, marketers can build more comprehensive content and establish authority on topics relevant to their business, resulting in enhanced organic website traffic, improved thought leadership and improved rates of customer conversion.

MarketMuse is interesting because it scours massive amounts of web content to look for the coverage around a focus topic. It builds a topic model that helps a marketer write like a subject matter expert.

This enables the creation of high-quality content that ranks in search engines. In effect, the platform helps connect the dots between what the content marketers want to write about and what the users want to know. This helps improve engagement, increases search rankings, and develops thought leadership.

Large corporations with many employees can have different problems, including adhering to a consistent voice or brand guidelines.

By now, it may come as no surprise to learn that AI can gather brand and audience goals and help ensure your content complies with those goals. After all, most corporations want to give a consistent message.

AI can gather brand and audience goals and help ensure your content complies with those goals

Such tools use AI for content scoring and brand compliance checking, enabling all different pieces of content to be coherent across offices or content producers.

Other content strategy tools help with auditing your content, understanding how people behave in relation to your content, benchmarking your competitors’ content, and generating data-driven content ideas.

Some content strategy tools optimize what and how you should write, as well as where and when it should be published for the best return on investment. Several tools on the market address such problems, for example Acrolinx, BrightEdge, Concured, and Atomic Reach.

Magnus Unemyr

Author, speaker and consultant in the aras of marketing automation, artificial intelligence, and the Internet-Of-Things. Contact me if you need help! Learn more.