Content Strategy: The Philosophy of Data

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Not that familiar with “content strategy?” That’s ok. It’s in my job title, and I struggle every time I’m asked what I do for a living. Many people have no idea what it means, but even more people bring their own (wrong) assumptions to the conversation. Usually they think it has something to do with writing copy. That’s not entirely false, but it’s kind of misleading.

The analogy I’ve been using recently is that content strategy is to copywriting as information architecture is to design. I find this analogy to be especially encouraging because six years ago, as the crest of the first wave of the web was about to break, people had no idea what “information architecture” meant either.

The irony of this communication challenge is that the main goal of content strategy is to use words and data to create unambiguous content that supports meaningful, interactive experiences. We have to be experts in all aspects of communication in order to do this effectively.

So, why has it been so hard for us to communicate what we do?

Perhaps the problem is that, because content is so pervasive, everyone thinks they know all there is to know about it. If you can read and write, you can make content, right? (Nearly 60 million blogs may prove that.) But the fact is, as interactive experiences become more complex, so does the nature of content. A superficial understanding of content isn’t going to cut it anymore. Content strategists in the digital age need to become data philosophers and explore the metaphysics of content, starting with the question “What is content?”

Everything is content

When we were developing a deep metadata system for the website of a national entertainment magazine, my colleague and friend, Chris Sizemore, would say, “Everything is content.” And I tend to agree.

Everything is content? What about design? Yes, it’s content. Structure? Content. Metadata? Also content. You probably expected a more incisive analysis than that. Well, how about, “Literally, everything is content.”

How did the need for detailed focus on content emerge in the heavily visually oriented field of web design? As website functionality has increased and web users have become savvier, sites have had to meet the demand for sophisticated interaction and more content to support it. But simply more content won’t do; it has to be accurate and relevant. It has to be meaningful.

There are many factors that determine whether something is meaningful, but the primary one, at least as far as web applications are concerned, is relationships. Is article Z related to the topic I clicked on? Show it to me. Is image B the same as the image I’m already looking at? For Pete’s sake, don’t make me look at it again! These and other subtle, dynamic, and complex relationships need to be expressed in precise ways that computers can translate into rules. As an example, let’s take the seemingly straightforward example of “sameness.” How do you determine when two pieces of content are the same?

You could say that every data record is unique and therefore distinct, but that doesn’t help us draw any kind of relationship between two chunks of text that are, in all ways, identical. So, maybe having exactly identical bytes makes two pieces of content the same. But, what about an article and a translation of that article? What about an image and a resized version of that image? To a reader, it looks the same, only smaller. How about a cropped version of that image?

The question “What constitutes sameness?” may seem somewhat academic, but it has very practical implications when you’re setting up a content management system (CMS). How you capture an article and its translation can make a huge difference in how that article is produced, published, and ultimately, used on the site. The way an image and its resized and cropped versions are stored in the CMS will likewise have a huge impact on both production and access.

Critical mass

If you’re presenting a very small amount of information you can (arguably) just put it out there and let people make sense of it.

A screen grab of a web browser showing the words "Hello World!"
A very simple website may not require much IA or content strategy.

Start adding more information and, pretty quickly, you’ll need to apply some structure to it to help people find their way around. This is where information architects come in, applying organizing principals and visual cues so that people can look at a site and quickly know what’s there, without having to think about it too much. If the information architect (IA) also happens to have an interest in words, she may carefully craft the labels that are used on the buttons and think about what sort of language best conveys the messages of the site. If she doesn’t have that interest or experience, this is a good place to get a content strategist (CS) involved. The CS will also work closely with the IA to make sure that the organization of the site makes sense and will be supported by the content that’s available.

An illustration showing a low-fidelity wireframe.
A more complex site requires some organization

As we start to design and build websites with massively larger volumes of content, we find that often they’ve outgrown the ability of individuals to manually organize them. Now we need automation and complex algorithms to find that needle in the haystack. We need the content to include inherent meaning that makes sense to machines, for example, to support data-driven applications based on search, browse, and related links. A content strategist is the person with specialized focus on making sure that the content is meaningful and the site is designed to make the best use of it.

Time to get practical

So, when we’re done philosophizing (for now) and we’ve figured out who’s going to be responsible for the content, how do we go about infusing it with meaning?

To make content that’s relevant to people, we choose the words and sentence structures that will best contribute to achieving our communication goals. The voice should be based on a deep understanding of the intentions of the content creators, as well as the needs of the content consumers. This approach can be captured in an editorial styleguide providing guidelines and examples that will help others craft content and messages in a similar voice.

To make content more useful to machines, we structure it and define standard elements so that the content can be used and reused dynamically. We write taxonomies and add metadata so that the content can be identified more easily. We create relationships between content so that it has more context and can support a variety of complex functions.

To make content more efficient to produce, we evaluate and recommend solutions for creating, enhancing, organizing, and using content, including content management systems, metadata tools, search engines, and faceted navigation applications. We establish business rules and workflows that will optimize the use of these tools and systems.

To make content comprehensive, we determine content requirements for a site, inventory existing content, identify gaps, evaluate possible sources for additional material, and manage the process of getting that content into production. Given the right background or source material, we can write labels, overviews, or even longer content if needed.

And don’t be surprised if, in the course of doing these tasks and creating these deliverables, those old philosophical questions pop up again to complicate seemingly straightforward issues. Here’s another brain teaser for you: “What distinguishable qualities indicate that some content items will be as relevant in three months as they are today, while other content will be out-of-date in a few hours?” (Hint: There’s no single correct answer.)

Strategies for working with content strategy

If you are a content strategist,

  • Start asking yourself and your colleagues the difficult questions about content (e.g., “What is content?”, “What would make it more meaningful?”).
  • Open dialogs about how to generate more meaning in your content and how to determine how much is enough. Develop models for cost/benefit analysis.
  • Look at different content models and determine appropriate uses.
  • Explore some of the emerging tools that can help reduce the burden of content production. Invent new uses and requirements for these tools and tell the developers so that they can make them better.

If you work with content strategists,

  • Find time to philosophize with them about content. Have patience with discussions of issues that may not seem like they’re leading directly to solutions–sometimes this perspective is needed to come up with the ideal content approach.
  • Involve them in the project as soon as you start analyzing what the site is going to be. Don’t wait until the site is structured and designed and you realize that you need some content to fill the pages.

If you don’t work with content strategists, but you think you would like to,

  • Demonstrate to your organization how this kind of role could save time and effort, help avoid problems, and make your end product better. After the conclusion of any project, you can probably come up with many examples of “If we had only realized this before…” Base your case on the content-related examples and you’re halfway there.
  • If that doesn’t work, figure out who in your organization is most interested in the theory of content, encourage them to get metaphysical about it, and then bring them back down to Earth so you can get to work on the practical stuff.

Content strategy may not be fully defined or widely understood, but that shouldn’t stop you from doing it. Make time in your projects to deeply consider the content requirements, and the content philosophers in your ranks will rise to the occasion.

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