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Artificial Intelligence

Content Intelligence Is Crucial For Keeping Up With B2B Buyer Demands

In B2B marketing, content intelligence isn’t just a buzzword. It’s the missing piece of the puzzle.

As B2B buyers rapidly adapt consumer-like behaviors and expectations, personalization has swerved from competitive advantage to table stakes. In fact, Salesforce reported that 56% of buyers now expect to find whatever they need from a company in three clicks or less. This might not be a tall order if your site is devoted to funny cat videos that half the planet will find adorable.

But B2B buyers aren’t here for cat videos. They’re looking for extremely specific information to help them make complex buying decisions. They also (usually) aren’t the only ones you need to convince — our recent survey of 500+ B2B marketing teams revealed that 75% of enterprise and mid-market deals involve a buying committee — and each stakeholder is likely at a different stage of the buyer’s journey when they land on your website.

It’s time to get real. You need a lot more than a savvy marketing team to deliver this level of personalized, relevant content experiences at scale. You need powerful, adaptive data. You need content intelligence.

This is a huge topic and it can be overwhelming to get started, which is why we’re breaking it all down for you. Here’s what you need to know about content intelligence: how it works, why it matters and which improvements you should prioritize to prompt meaningful engagement, drive massive growth and leave your competitors in the dust.

So, first thing’s first…

What is content intelligence?

Content intelligence is all about turning content into a data set that can be converted into insights, personalization, and performance analytics. This isn’t just a slightly better Google Analytics or more primitive content data we’ve relied on in the past (anyone remember those website hit counters back in the 90s?). Thanks to natural language processing, machine learning, and even AI, content intelligence can actually learn and adapt right alongside the marketers creating and distributing the content. As Ryan Skinner, Principal Analyst at Forrester, put it: content intelligence is “technology that helps content understand itself.”

So how does content intelligence actually work?

Technically speaking, content intelligence uses artificial intelligence, which the AI Marketing Institute defines as “the umbrella term for the algorithms, technologies and techniques that make machines smarter, and give them superhuman capabilities.” Fortunately for us, these superhuman capabilities don’t include overthrowing humanity à la The Matrix. Instead, we’re talking:

Natural language processing (NLP)

Intelligent systems which process human language, generate metadata (i.e. “data about data”) and build dynamic taxonomies — self-adapting information hierarchies.

Because NLP can understand granular topics related to a particular business or industry, it not only equips AI engines with the necessary data to tag and sort content, but also understand how different assets are actually related.

Machine learning

The process in which algorithms analyze content and learn from data inputs to make better predictions over time.

This means that websites backed by machine learning can respond to content consumption and engagement patterns of every individual user in real time (and at scale).

Content intelligence in practice

Understandably, NLP and machine learning both require vast amounts of data to function — data which can then be tracked, measured and analyzed to reveal profound insights on your content’s performance, utilization and audience.

“You can’t do anything well in marketing or business in a digital context anymore without metadata, technology and analytics,” Christine Polewarczyk, VP, Research Director — Content Strategy and Operations at Forrester, told PathFactory customers at Compass, our annual customer conference in December 2020. She observed that most B2B marketers are still focused on activity and output metrics, like content volume and budget, number of page views and leads generated from a specific content asset. “It’s important to track all of those things. But it’s really not giving you enough insight to make decisions about how to influence or optimize your content experiences.”

Content intelligence goes much further than other data, delving into the quality of engagement on an aggregate, individual and even account level. This includes how time was spent on a specific piece of content (right down to the second), viewing order of multiple assets and binge rates.

This wealth of information helps marketers avoid common gaps in surface-level data — like false buying signals — and effectively determine content performance patterns so they can optimize accordingly. Without a good understanding of your content and how it’s consumed on the other side, you’ll never be able to truly institutionalize your knowledge or drive any kind of continuous improvement.

Content intelligence doesn’t only empower marketers with invaluable insights. It can also supercharge website personalization through contextual content experiences, using data to offer specific recommendations, based on previous consumption and engagement behavior for each individual website visitor.

Optimizing content intelligence for maximum ROI

There’s a lot to unpack around content intelligence: guest speaker Christine Polewarczyk, Forrester VP, research director and content expert recently shared which content engine improvements B2B marketing organizations should prioritize to deliver data-informed, personalized content experiences that drive engagement and growth. You can read a recap of the webinar or watch the entire thing below.

P.S. Did you know we wrote the first-ever content intelligence guide for B2B marketers? It’s crammed with actionable insights to help you accelerate your digital transformation and turn your content engine into a major competitive advantage.