Not long ago, I predicted that content intelligence would emerge as an important, if not critical, practice. I didn’t have much room to explain my perspective on the topic–didn’t mean to leave you hanging. So, let’s take a closer look at what content intelligence is.

A Definition

After exploring different tacts on a definition, I arrived at this:

Content intelligence represents the systems and software that transform content data and business data into actionable insights for content strategy and tactics with impact.

I’ll be the first to admit no definition is perfect. But, the value I see in this definition is its focus on three things:

  • A systematic approach – Content intelligence is not a one-and-done proposition. It needs a framework, processes, and people.
  • Integrating software – It’s impossible to develop content intelligence without the right tools integrated into the framework and processes.
  • Content impact The lens through which to look at the data is content. And success is not getting the content created and launched. It’s making an impact.

I often find it helpful to define something in terms of what it is not. So, when I talk about content intelligence, I do not mean…

Artificial intelligence (AI)
AI using computer systems to do tasks that typically only humans have been able to do. A quintessential example is IBM Watson’s ability to learn games to the point of beating human chess and Jeopardy champions.

Business intelligence (BI)
BI is using systems and software to process business data and turn it into useful insights to inform business strategy and tactics. A recent report, Insights 2020, calls for shifting the focus of business intelligence to impact.

Intelligent content
Intelligent content is structuring content, especially modeling it with metadata, to optimize its performance with technology and, in turn, create better experiences for customers and more efficient content management for businesses.

The above areas complement each other and content intelligence. A few useful areas of overlap…

  • Data that informs business intelligence might also inform content intelligence.
  • When machines learn to write / create content, as we’ve seen from Narrative Science, or to hyperpersonalize content for more impact, we’re seeing artificial intelligence and content intelligence come together.
  • If content is not intelligent—well structured and tagged—tracking data about it to inform content intelligence will be difficult.

For me, content intelligence is an evolution of content evaluation, which I’ve discussed in both Clout and Does Your Content Work? Compared to content evaluation, content intelligence is a more comprehensive and sophisticated way of understanding whether your content works—and then doing something about it.

So, what does a content intelligence system look like? Let’s turn to a diagram.

A Diagram: Elements of Content Intelligence

To yield useful insight for impactful decisions about content, a content intelligence system must collect multiple sources of data and execute analyses and interpretation focused on questions about content. Looking at the data through the lens of content is key.

diagram of content intelligence by Content Science
A diagram of content intelligence practice

 

(This diagram represents some common data sources, but you could also fold in big data sources, if it made sense for your goals.)

From there, you can gain insights about whether your content is effective and what dimensions make it effective (or not). You potentially can predict how to make your content more effective. And you often also can gain insight to help calculate ROI or learn more about the preferences, concerns, and issues experienced by customers.

Now you might be wondering, why should you care about this at all, especially now? Let’s take a closer look.

Why Content Intelligence Now?

I see three related reasons to care about content intelligence now:

1. Make customer-centric content decisions that have impact.

Content intelligence empowers us to make smart strategic and tactical decisions that put customers (or users) first. Letting the doctors or engineers or other subject matter experts dump all of their knowledge on your website, for example, will be tough to justify. So will bombarding your customers with brand or marketing jargon.

As a participant explained in our study of What Makes Content Teams Thrive?

“We were able to achieve success on a particular content restructuring because we were given the time to establish proper data ahead of time, make recommendations, then measure the changes against the previously established baselines. By allowing for the process to be measured and iterative, we were able to provide a better solution.”

2. Make impact that drives business growth.

Growth is the holy grail of business. Growth also is often an important goal for other types of organizations. When we show that content decisions have an impact on business growth, the value of content practice becomes hard to dispute.

3. Understand return on assets (investment).

If content really is an asset (and I believe it is), then content intelligence helps us understand how well we use those assets to improve business or organizational performance and drive business growth. We gain compelling stories to tell to executives, which gives content a seat at the executive table.

Now, those are the strategic reasons to establish a content intelligence practice. But, there are a host of other benefits to a content intelligence practice, as well. Here are a few…

  • Bridge silos with data.
  • Gain confidence in the data and, consequently, your content decisions.
  • Motivate your team with evidence of your content’s impact.

Where does your organization stand on content intelligence? What are the benefits you’ve seen and the challenges you’ve experienced? You can bet I’ll be talking more about content intelligence this year, and I look forward to hearing your perspective.

The Author

Colleen Jones is the CEO of Content Science and cofounder of ContentWRX. She regularly consults with executives and practitioners to improve their strategy and processes for content. Colleen shares insights and guidance from her experience in these highly rated books:

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2 Comments on "What Is Content Intelligence?"


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Aligning Business Goals With User Goals in Content - Story Needle
3 months 6 days ago

[…] Jones refers to the feedback from customer interactions with content as “content intelligence,” a phrase that nicely captures the principle that the data organizations collect should make […]

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What Is Content Intelligence? - Content Science...
3 months 19 days ago

[…] Colleen Jones of Content Science explains what content intelligence is and why it matters.  […]

 
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