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SEO is not that complicated until it suddenly is. These complications manifest in various ways, ranging from the simple (prioritization based on impact) to the increasingly complex (TF-IDF, or term frequency-inverse document frequency). Structured data for SEO, also known as schema markup or structured data markup, falls somewhere in the middle.
According to W3Techs, approximately two-thirds of all websites leverage structured data in some format. It has become an increasingly important aspect of SEO, and a necessary weapon in every website’s arsenal to help remain competitive in an ever-evolving search landscape.
This post will provide you with a high-level introduction to the basics of schema markup, its benefits, and how to begin leveraging it to stay ahead of the curve.
In its simplest form, schema markup is a form of structured data that helps Google gain a better understanding of a webpage’s content. When a search engine understands content better, it can reward you with rich snippets and help return more relevant search results.
When Google crawls a website, it reads the HTML to parse out what the page is about. While the algorithm is getting pretty good at this (almost too good…), there is room for ambiguity. Schema.org uses the example of the movie Avatar. As the crawler moves about your website, it reads the HTML to determine what the page is about. In some cases, it might come across <h1>Avatar</h1>. While additional information on the page can help give the crawler clues, there is a risk of it not knowing 100% that you’re referring to the movie.
Enter structured data. Its use will allow you to specifically tell Google that the page is about the movie Avatar, and not the metal band. This thus allows Google to understand the content of the page better and deliver more relevant results. How does this work? With schema.org.
Schema.org is a “collaborative, community activity with a mission to create, maintain, and promote schemas for structured data on the Internet, on web pages, in email messages, and beyond.” In short, it’s the universal vocabulary used to “mark up” the structured data for your webpages to help search engines make sense of them.
Schemas are broken into Types (the entity you’re describing, such as a movie or person) and Properties (for example, the number of pages a book has). When compiled, it forms a hierarchy. At the time of this writing, the schema vocabulary consists of “841 Types, 1369 Properties, and 352 Enumeration values.”
The context provided to search engines by implementing schema markup confers upon the webpage a number of benefits. As we discussed above, their primary purpose is to provide additional context to search engines. What this additional context does, however, is improve your chances of standing out in a field of competition through several key benefits. This list is not comprehensive, but represents some of the most critical benefits structured data markup can confer to your website.
Rich Results are everywhere, and one of the main benefits of implementing structured data on your website. They are enhanced features of the traditional blue link in the SERPs, and can include everything from Knowledge Panels, video carousels, and reviews.
Here’s an example of a common one: a simple recipe for the best homemade baked mac and cheese:
It should be noted that schema markup does not guarantee rich results. In fact, if Google can understand your content without it, it may choose to show rich results on its own. This, however, is rare.
There are almost three dozen different types of rich results that can appear in the SERPs. I’m not going to go into detail on all of them, but some of the most common ones you might have seen around the ol’ interwebs include:
…and many more. Ondyr.com does a good job of breaking down each of them and what they look like. As I noted above, there are over 800 schema types available, and obviously, not all of them lead to rich results.
Voice search has been growing in popularity for the better part of a decade, and the Alexas and Google Homes and probably a billion others are certainly giving traditional searches using, you know, keyboards and a screen, a run for their money. Adding structured data markup to your website can help make voice search results more relevant, especially if you run a local brick-and-mortar business. Furthermore, structured data can help with the accessibility side of voice search by giving accessibility tools greater context. There’s even a speakable property that “indicates sections of a Web page that are particularly ‘speakable’ in the sense of being highlighted as being especially appropriate for text-to-speech conversion.”
Nope. The worst that can happen is you either leave potential rich snippets on the table or, in the case of misused or improperly used structured data, lose your rich snippets. Your rankings won’t be affected one way or the other.
Despite this, rich snippets can improve your click-through-rate. A study performed by Milestone Research analyzed over 4.5 million queries and found that rich results get clicked on 58% of the time. Compare that to non-rich results getting clicks 41% of the time, and you have a pretty solid argument for using structured data to try and earn those sweet, sweet snippy snips.
Structured data markup can typically be integrated into a web page in one of three formats: JSON-LD, microdata, and RDFa.
"breadcrumb": "Homepage > Category > Great Hypothetical Widget",
"name": "My Great Hypothetical Widget",
"description": "The description of the great
hypothetical widget and an overview of its
JSON-LD is Google’s preferred way of creating and integrating structured data markup on your website. It’s all we use here at Portent, as it allows for greater flexibility when making changes to the markup or the webpage as a whole.
Microdata and RDFa are now less common than JSON-LD, but they’re still used by some websites. They use HTML attributes to mark up the data, and are typically embedded directly in the HTML of the webpage. While they have their place in creating structured data, we recommend avoiding it altogether.
The fun part!
Kidding. Sorta. It’s tedious as Hell, but after getting the hang of it, it becomes kinda fun, making little changes, discovering and hunting down the source of errors, throwing your computer against the wall ‘cause you forgot a comma.
You know. Fun. But I digress.
The easiest way to write structured data is with a generator. There are countless available schema generators a mere Google search away, and almost all of them allow you to create basic structured data for the most popular schema Types (article, webpage, event, local business, recipe, et al). I’m partial to the one found at TechnicalSEO.com, as it contains the most options and is fairly simple to use.
This is a great place to start because it gives you a good introduction to how JSON-LD works and how the data is structured. Barring this, one of the best ways to help your write structured data, especially if you’re just getting started, is to find examples in the wild and analyze it on your own. Compare it to the information found on schema.org and simply deconstruct it. I highly recommend this excellent primer on JSON-LD implementation before you begin, as it breaks down the individual elements of the code and helps make them easier to understand.
Alright. You’ve written your code in your preferred format (I hope it was JSON-LD), and you’re ready to test it. The go-to way to do this was with Google’s Structured Data Testing Tool, but it is in the process of being deprecated and replaced with Google’s Rich Results Testing Tool.
Schema markup is not as complicated as it looks. Think of it almost like learning a new language. Complicated on the surface, maybe a little difficult to pronounce. But as you start understanding the vocabulary and its syntax, the pieces start to fall into place.
Unless you just suck at learning new languages.
That was a terrible analogy.
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