For content to perform, people must find it. So most of us dutifully fill in that metadata and do a little SEO on the headlines and images to give us a boost.

But with the evolution of a mobile and the semantic-driven web—where people are as likely to ask their phone a question like “What time is ‘American Sniper’ playing?” as do a traditional search—it’s structured data that’s emerging as key to content discovery.

Enter, a standardized way to mark up content to improve how it’s surfaced and promoted. came about as a collaboration by Google, Yahoo, and Microsoft back in 2011 and later joined by Russian search giant Yandex.

You’d think that with search formulas as closely guarded as the Colonel’s secret Kentucky Fried Chicken recipe, we’d all pay attention when rival tech titans team up on shared practices. But many organizations have yet to adopt markup.

For those that have, the benefits are bubbling up through improved search result displays, Google’s Knowledge Graph, and innovative search tools that rely on voice, location, and other emerging factors.

The upshot? If your enterprise hasn’t already adopted, now is the time. Here’s what you need to know to get started.

What do I mean by structured data?

Machines just don’t understand information the way people do. But by describing the information, we can provide context and connections that lead to a more human understanding of the information.

Take this sentence: “The Avett Brothers are playing in Santa Barbara Feb. 10.” On its own, that means nothing to a computer. But by telling the computer that the Avett Brothers is a band, and that Feb. 10 is a date, and that it’s the date of a concert in a place called Santa Barbara, you create structured data that the computer can work with.

So now, the computer’s algorithms can connect that content with other structured content around the web to piece together things such as:

  • What albums the band has released
  • Where you can listen to their songs
  • Where you can eat or stay in Santa Barbara
  • Where else the band has upcoming shows

So what can structured data do for you?

Structured data powers rich, actionable search results like the ones pictured below. Each element (including some not pictured, such as songs, albums, social media profiles, and similar artists) points to more information, related topics, or opportunities to listen or buy.

The Avett Brothers search results exemplifies use of structured data


If you search for Avett Brothers tour dates, you get the handy results shown below, which pull up a map and links to purchase tickets when you click a show.

The Avett Brothers tour dates search results


Here’s one more example, this one showcasing product content from shoe retailer FootSmart.

FootSmart search results

These rich search results up your odds of both connecting people with the specific content they’re looking for and driving additional discovery by surfacing potential items of interest such as reviews, additional context, or related topics.

Rich search results also represent the visual frontline of the search giants’ push to bring context and semantic understanding to the forefront of traditional search as well as promote new and emerging services such as voice answers, maps, and Google Now. Google’s Hummingbird algorithm and Knowledge Graph exemplify this push.

Google and the others also regularly build on Schema’s capabilities. Last year, they added support for user actions such as listening and buying, and just this month they expanded music and event options, debuted new documentation, and launched new help tools.

As voice, location-based, video, real-time, and other web tools progress, you can be sure they’ll build on structured data.

So how do we do it?

We’re going to talk just a bit of tech here, so bear with us. To structure your data, you essentially need to annotate it, marking it with the agreed-upon standardized vocabulary.

How do you do that? You’ll want to pull on your content engineering hat, get your techie colleagues together, and hash out what works best for your organization.

There are two ways to add Schema markup:

1. You can add Schema-defined tags describing the content throughout your content using either microdata or RFDa, which are similar formats that define new HTML attributes. Here’s an example using microdata tags:

An example of Schema-defined tags using microdata


2. You can include all the Schema descriptions in a single script on the page using a newer, simpler format called JSON-LD. This bulk approach makes it easier to add markup about a lot of related content at once, rather than sprinkling it throughout the content. Unlike the first option, the scripts also work with content that’s loaded onto the page dynamically, such as through Javascript or embedded widgets. Not all display features for products and reviews support this format yet, although Google is working to add them. Here’s an example of a JSON script:

An example of JSON-LD script

Tech-minded people can find extensive documentation and a get-started guide at, with additional ways to promote content through structured data at Google.

What other help is available?

Plenty. Google just released an updated suite of tools to help organizations succeed with structured data.

For those just getting started, there’s the Structured Data Markup Helper, which guides you in creating well-formatted markup.

Google's Structured Data Markup Helper

Once you have some marked-up content, check it with the Structured Data Testing Tool, which helps find and fix any problems with a page’s markup before you publish it.

Google's Structured Data Testing Tool

The Structured Data Dashboard, a Webmaster Tools feature, provides a picture of how Google uses and understands your structured data over time, with warnings about formatting mistakes or missing fields.

Other sites offer tutorials, how-to’s, and help for most any technical problem you might encounter.

Some last words to inspire your first tag

Intelligent and influential content isn’t just a nice idea—it’s what you actually get when you start deploying content structured so that machines can help promote human understanding.

The possibilities are vast. Content reuse within and across organizations. Custom content delivery. Augmented real-time and location-based experiences.

But it all begins with a single attribute tag.

The Author

Sally Taylor is an associate writer with Content Science Review. You can contact Sally at Content Science.

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