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Structured Data for SEO: What It Is and Why You Should Use It

Published January 9, 2018
Have you ever wished you could talk to Google? Not with voice search like “Ok Google, find the closest Pizza Hut.” But communicate with Google about your content and what your website has to offer? Well, in a manner of speaking, that’s what some kinds of structured data are for.
Webopedia defines structured data as “any data that resides in a fixed field within a record or file.” For their purposes, Google explains structured data as “a standardized format for providing information about a page and classifying the page content.” So, while structured data, in general, has a much broader application to data models and programming, for today’s post we’ll be looking at it more from Google’s perspective and how it works with SEO.

Structured Data or Schema, Microdata, Rich Snippets and OpenGraph

There’s a lot to keep straight when it comes to marking up your HTML. So let’s get into the vernacular a little.

  • Structured data is marked up code that is a system for matching data with a value.
  • Microdata is one component of structured data.
  • Schema (from Schema.org) is a form of microdata, that is a vocabulary or kind of semantic markup that can be used with various encodings. Those include microdata (with HTML5), RDFa and JSON-LD.
  • JSON-D is often a preferred form of markup as it is a bit friendlier to implement.

Structured data uses a set of tags that help define and organize properties, from the nature of a website itself to elements of the content contained within a page.

Schema defines a standard set of tags and formatting that is agreed upon by applications like Google, Microsoft, Pinterest and Yandex as a common language for describing and interpreting rich text. A common schema helps all participants better understand the nature and context of websites and page content. When Schema is implemented on a website, then search results are more likely to show Rich Snippets. These are the enhanced results page listings that may include additional features like star ratings, like these:

 

How Google Works

 

But what about OpenGraph (OG)? Often we’ll see elements of OG markup on a page, but this is not the same as Schema. OG is a form of markup that is used by social media platforms like Facebook and Twitter. It does not provide the same communication with search engines as Schema markup.

Why Does It Help

That seems like a lot. But the core of it is that structured data for SEO involves using Schema tags to mark up the HTML of your pages to provide greater clarity around your content for search engines. But what does that actually mean for a site owner?

Despite Google’s assertions that using schema alone won’t help a website rank better, in 2016 Google’s John Mueller implied that structured data markup could become a part of the already complex ranking algorithm. The most likely reasons for this are that marked up data can be better understood by search engines, which can result in a better match to a search query. But also, the use of markup for rich snippets can result in a better user experience for searchers.

So while we shouldn’t assume that structured markup means higher rankings, it can make for better results.

The results of using schema can produce search results that include breadcrumbs, product rankings, more detailed knowledge graph results and in-depth articles among other classifications depending on the nature of the content. These more detailed results can be more eye-catching and improve click-through rates while also giving users more immediate access to and details about your content.

Who Should Use It

Any website can make use of some form of schema. Schema.org notes that the “core vocabulary currently consists of 597 types, 867 properties, and 114 enumeration values.” That’s a lot to choose from, but not every tag is applicable for every site. The primary schema types all fall into three main categories that most of us are already familiar with. Back when we were kids we learned that a noun is a person, place or thing, and schema types break down the same way. This means that schema can be used to classify any person, place or thing associated with a website. From denoting the author of an article, identifying the geographical location of a place or identifying a particular kind of content, like a recipe, as a thing.

Getting started with schema, a business can first focus on the types that are most commonly in use and are appropriate for the business. Google’s Structured Data Markup Helper can help identify what those are and create the necessary HTML. This tool can help create a number of different types of schema, but a local business for example would likely want to start with properties like:

  • Email
  • Address
  • Street address
  • Locality or city
  • Region or state
  • Country
  • Postal code
  • Opening hours
  • Open days of the week
  • Closing times
  • URL

 

Megalytic Markup Helper

 

This main page markup can also include components like aggregate ratings or reviews if they are available. Aside from tagging the primary identifying elements of your business, like those above, the best way to determine which schema you should be using is to identify the content you want to markup. Use other categories in the Structured Markup Helper, dig into Schema.org or use other resources to find the relevant properties associated with your content. There are hundreds of types and properties, so take some time to browse through and find the ones that really help distinguish your content and business.

How To Implement It

The first step to implementing structured data markup is to create it. Schema markup can absolutely be written by hand, but generators like Google's Google Structured Data Testing Tool to make sure your structured data is valid.

Once you have used the Google Structured Markup Helper, or otherwise written or generated code, it can be added to the HTML of a website by a developer. But it can also be added using Google Tag Manager. With a WordPress site there are plug-ins to help with implementation. Once the markup is on the site, take another visit to Google’s Structured Data Testing Tool to make sure it’s working properly.

Conclusion

Structured data may sound complicated and, to be fair, it can be. There are intricate and diverse options that can be applied to multiple aspects of a page. But the opportunity to delineate and attribute entities and components of content to help explain who you are and what you offer to users is extremely valuable. This level of clarity, and the potential it offers to create more accurate and engaging search results are well worth the effort.

ALSO IN THIS BLOG

Remember how your mom told you not to stand too close to the television because it might hurt your eyes?
The same rules can apply to data. If you’re too close, you may miss the patterns and trends that are crucial to understanding your website’s performance. You can’t judge a site’s performance looking at data in the bubble of a single day, you must consider any day’s traffic compared to the days before and after.
Google Analytics makes it fairly easy to analyze trends over long periods of time. But it also allows you to stand right in front of that TV, to look at more granular levels of time, right down to the hour.
There’s a better way to get that close to the data, without burning your retinas. We’ll cover how to analyze traffic effectively in today’s post.

 

 

When the client first came to you, you talked up the value of Google Analytics. You emphasized the importance of seeing where your traffic was coming from. You went on and on about how Google Analytics can show traffic sources to pinpoint whether people came from search, social media or a specific site referral, and how valuable this data was. You sold them on it, so much so that your client looked forward to receiving that first report, the magical day when they would finally understand where visitors were coming from.
But then the report came, and it looked like this:

 

 

It showed that 10% of your client’s traffic came from “(direct)/(none)”. What does this label mean? How do you explain Direct traffic to your client? Better yet, how do you explain “none”?
Let’s take a closer look at understanding Direct traffic in Google Analytics and how we can address it with clients.
One of the most exciting and important aspects of digital marketing is the ability to understand exactly how your customers are finding you. It informs every single part of integrated campaigns and helps determine which efforts are working and which ones need to be revisited. Google Analytics allows you to zero in on the performances of different marketing channels to evaluate everything from brand awareness to social media messaging. To get the most insight from that data, it’s crucial to understand exactly how Google sorts your traffic.
Channels in Google Analytics are high-level categories indicating how people found your site. While the Source/Medium report shows you in more detail where people came from, Channels are broader, more “user-friendly” names lumping visits together in buckets useful for high-level reporting categories.
For instance, Facebook Sessions often show up in multiple ways in the Source/Medium report. They may appear as facebook.com, m.facebook.com, and l.facebook.com, all of which are variations of the same source. The Channels report will include all of these in the Social bucket, so you can see less granular, aggregate numbers on social media performance.