Content Intelligence

If content is the king, who will become its emperor?

The Internet is changing everyday life for consumers: indeed, the number of people who are relying on digital media to communicate and guide them in the world is increasing. This transformation has been implemented by advances in new digital technology. It can offer brands remarkable opportunities to create deeper and more productive relationships with their customers. The latter increasingly want to have unique and personalised purchasing experiences, in which online and offline intertwine.

While surfing, users come into contact with the enormous quantity of digital assets that brands are finding themselves managing online. The digital content that emerges from the brands’ “forge”, or rather, HTML pages and multimedia files of various kinds, and the way in which people interact with it, contains often unexplored data on the brand’s audience that could allow them to anticipate the user’s real desires.

Indeed, people reveal a great deal about themselves through the content they choose on the various touchpoints (websites, e-commerce stores, mobile apps, social networks, in-store initiatives, etc.). The strategic data generated by the habits of users may be “extrapolated” by Content Intelligence (CI), thanks to support from Artificial Intelligence (AI), and used to strengthen the relationships between people and brands, if analyzed correctly. The potential of the data generated by content is a genuine gold mine that offers remarkable opportunities to companies, which can analyze them and significantly improve their digital marketing by reaching a wider audience and above all more a better targeted one.

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 uses 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.