Guest post by Seth Grimes

While I don't buy the saying "you can't manage what you don't measure," data certainly helps, in content management and publishing just as in managing sales, spending, personnel performance and a host of other business functions.  

Of course, we do have content-related measurement in the form of web analytics (studying site visits) and search engine optimization (related to keywords and links). These techniques help us drive customers to our websites and optimize their experience (and our profit, however measured) once there, but we can and should do much more to promote effective content strategy, to ensure effective, profitable content use and reuse, not just on the web but also in the enterprise. How? With content analytics and semantics.

I asked a few experts to explain how content analytics and semantics can inform better content strategy: Randall Snare and Elizabeth McGuane of Dublin based iQ Content, and Rachel Lovinger of Razorfish in New York, speakers at the up-coming Smart Content conference, Oct. 19 in New York. I'll offer a bit of context and then relate their responses.

By way of background...

By way of background: The term "semantics" is often associated with the Semantic Web, but semantics is about a lot more than just an effort to create a linked data web. Semantics means rich content--topic- and theme-annotated, with sentiment and opinions about products and services, integrating data and text from structured databases and unstructured sources--as generated by content- and text-analytics tools and services and associated with content-usage measurements.  

Content analytics is a term for techniques and software that create statistics about content and content consumption, and that generate descriptive metadata and meaning-enriched content, however the content is produced, published or consumed: As web pages, certainly, but also email, text messages, on social platforms, within the enterprise.

The media veterans

Randall Snare and Elizabeth McGuane are media veterans turned content strategists. As they see it:

"Of the many, many benefits analytics provides for content strategists, our favorite is the 'told you so.' We've worked with people who think that content is subjective, but so often it's not. Analytics can show point blank that a piece of content isn't working, or is in the wrong place, or is too long or too short.

"Analytics measures how users understand and interact with content and interface. And content is the biggest part of the interface. Without it, design is meaningless--semantically speaking.

"So analytics is both an engine that proves the need for a strategy, and a framework for the measurement of that strategy's success. It provides focus for a web team (content strategist included) and helps them make informed content and design decisions.

"As for semantics: Content strategists need to understand the development of the semantic web, because it simply makes the web a far more powerful tool for the dispersal of content. Text is no longer just inserted into code. Text--information--is the code. Most importantly: The semantic web forces content strategists to consider content not just one website at a time, but as part of the development of the web as a whole."

The last few sentences are quite interesting. We have the notion that meaning informs content strategy and content strategy can help create meaning that goes beyond any one document or web site, that analytics and semantics help create a content big picture from what were previously disjointed bits of information.

The semanticist

While Rachel Lovinger says she was doing Content Strategy long before she realized it was an actual field, her background is decidedly on the technical side. She founded and leads the Semantic Web Affinity Group at Razorfish. She is lead researcher and author of Nimble, a Razorfish report on publishing in the digital age, which seeks to chart how media and publishing companies are adapting to the demands of the digital content landscape. You can download the report here.  

Rachel is "especially interested in relevance, findability, signification, and inherently funny words" as reflected, minus the funny-words part, in her response to my question, How can analytics and semantics help content strategists? According to Rachel:

"Every piece of information we could possibly want is out there on the Internet, but too often not findable, primarily due to poorly organized sites with flat, static, unstructured content. Further, many companies have huge amounts of institutional knowledge--both documented and undocumented--with no way to share it, find it, or identify experts within their ranks. As we try to find ways to optimize business operations it has become critical to be able to unlock any and all available resources.

"The volume of digital content we're now facing is both the boon and the bane of the information age. In most organizations, the body of content now exceeds our ability for an individual (or even a moderately sized team of individuals) to manually inventory, review, audit, tag and revise every item. There are two options. Get a MUCH bigger team (perhaps by crowd-sourcing), or automate as many parts of the process as possible.

"This juncture is where technologies that help analyze, interpret and augment content become invaluable to the content strategist. Analytics tools help us understand how our content is used and shared by our audience. Semantic tools help us understand what the content is about and how it is related to other content and people in our systems (or on the open web). Tools that combine both capabilities can help us more thoroughly wrap our minds around what content we have and how we can use it better. And then our audience will have a much better chance of finding what they're looking for."

So for Rachel, analytics and semantics create meaningful context for information that can benefit content producers, strategists and consumers alike. Like Randall and Elizabeth, Rachel sees these technologies as exposing relationships and creating findability in large, even web-scale, information systems.

Beyond content management

I hope these insights have helped you understand the basic "what" and "why" of moving beyond content management, steps you can take to exploit the full value of content, to optimize content findability, reusability, usefulness and overall business value. Beyond content management, we have content strategy by the numbers, powered by semantics. It wasn't my purpose in this brief article to explain "how." You can find plenty of material on that topic by following the link in my bio and by joining me, Randall, Elizabeth, Rachel, and other experts and peers on Oct. 19 at Smart Content.

Seth Grimes is an analytics visionary: A consultant, writer, and industry analyst working in text analytics, business intelligence, data analysis and visualization, and information strategy as applied to information-age challenges. Seth founded consultancy Alta Plana in 1997 and is a long-time contributing editor at TechWeb's IntelligentEnterprise.com, a channel expert at TechTarget's BeyeNETWORK, and founding chair of the Text Analytics Summit, Sentiment Analysis Symposium and Smart Content conference.

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