What is structured data markup and why should sites use it?
Getting your head around structured data can be tricky, but if you’re involved in SEO, it’s something you need to get to grips with. A significant increase in Knowledge Graph entries and Featured Snippets was observed by Moz on the 6th of March and it certainly seems that this is going to be a trend we’re going to see in 2016 and beyond.
Whilst some basic HTML knowledge doesn’t go amiss, you don’t need to be a developer to use and understand structured data. This guide will give you an overview of structured data markup, why it should be in every SEO toolkit, and how you can start marking up your sites.
What is structured data markup?
Structured data markup is a way of annotating the content on your website so search engines, such as Google, can understand it better. For example, if you use the Local Business schema, you’re telling search engines that – you guessed it – your website is for a local business!
Marking up data can make your website/content more prominent within the search engine results via Rich Snippets and Knowledge Graph entries. In theory, the more prominent your site is within the SERPs and more information presented to the user, the more click-throughs you’ll receive. You’ve probably come across Rich Snippets plenty of times – star ratings, YouTube video previews, and event links are often dotted around the SERPs. Take a look at how the Viagogo website appears within the SERP for the term “Glasgow concerts”:
This looks much more appealing and presents you with a lot more information if you’re looking for events in Glasgow. It doesn’t appear like that is a coincidence, either – if you view the page source, you’ll see numerous Schema markup in place – MusicEvent and Offer are both present for all of the events. This information is then pulled through into the search results into what we see above.
Schema.org is a collaboration between the four major search engines – Google, Yahoo!, Yandex, and Microsoft Bing. Its purpose is to provide a collection of shared vocabularies for developers and SEOs to use to markup the data on their websites. Consider it an alliance between four search engines to bring structured data to the masses (and by masses I mean, the search results).
So why is structured data important?
Take one look at the number of results returned for any search query. Millions, right? How do search engines interpret these and how can they return the most accurate results for our query? Well, as Google say, the relevancy is determined by over 200 factors. Search engines try to understand page content but they have a limited understanding, and certainly can’t understand semantics like humans can.
We know that HTML tells a browser how to display information. Take the word “boots”, for example. When this word is placed in a
tag, the browser is told to render this word in the heading 1 format. However, this is where things get a bit messy. A browser can’t interpret what this word actually means and what it refers to – does it mean a pair of boots you put on your feet? Car boots? Boots as in the company? Something else?
That’s why we should use structured data on the websites we create. If we use the Product schema, we can tell search engines that the boots we’re talking about is actually a pair of boots. If we were talking about Boots the company, we’d use the Organization schema. Problem solved! Of course, your site still needs to pay attention to the ranking factors to climb the search results, but one thing at a time, eh?
Another reason structured data is important is because it may become a ranking factor in the future. John Mueller from Google has stated that structured data is not part of the ranking algorithm, however, “over time”, it might be. It makes sense – we may well see Google and other search engines reward websites that present their content in a way that they can understand.
How can I start marking up data on my site?
Before you begin, think about the pages on your site that you want to markup. There’s a huge range of schema types so there’s sure to be one that covers your business or website – you can find the full list on this page. At the very minimum, though, you’ll want to at least have an Organization Schema, as this helps to enhance your brand or website’s Knowledge Graph entry and isn’t limited to a specific industry. For Ecommerce sites, you’ll also want to use the Product and Offer Schemas. LocalBusiness is also a must for sites that have a physical store presence.
When it comes to marking up data, there are three supported formats: Microdata, JSON-LD, and RDFa. There’s no right or wrong format – Schema.org supports all three. Microdata and RDFa are slightly different to JSON-LD, and these differences are explained below.
Microdata and RDFa
Microdata and RDFa are both markup syntaxes that involve adding Schema.org attributes to the existing data on a page. This is simple to implement if you’re able to update the code yourself, and you can use the structured data markup helper in Google Search Console to avoid fiddling with the HTML.
However, for sites you don’t write or update the code for, it can be tricky. Not only that, but because it wraps around specific elements within the page, you might spend a significant amount of time adjusting the HTML to make it look good on the page.
Here's an example of a Local Business Schema using Microdata:
<div itemscope itemtype="http://schema.org/LocalBusiness"> <h1><span itemprop="name">Beachwalk Beachwear and Giftware</span></h1> <span itemprop="description"> A superb collection of fine gifts and clothing to accent your stay in Mexico Beach.</span> <div itemprop="address" itemscope itemtype="http://schema.org/PostalAddress"> <span itemprop="streetAddress">3102 Highway 98</span> <span itemprop="addressLocality">Mexico Beach</span>, <span itemprop="addressRegion">FL</span> </div> Phone: <span itemprop="telephone">850-648-4200</span> </div>
JSON-LD uses the same Schema.org values as Microdata and RDFa, but it is separate from the HTML, meaning that you don’t need to amend individual elements. Instead, the data is embedded in a