A Beginner’s Guide to Schema MarkupGet a free consultation
Just look back seven years ago and marketers were more concerned with gaming the results by quantifying their link portfolio and saturating content with keywords.
Unfortunately, a lot of off-page SEO slowly turned spammy and many off-site ranking factors were disavowed. This is why search marketers can’t have nice things.
While meta tags were essentially dropped as a ranking factor, years of practice and possibly instinct led SEO experts to keep preaching the importance of metadata for indexation and improving user experience.
We at LSEO agree with this notion and know first hand that meta tags still affect paid and organic search performance. This is why we recommend using schema markup and optimizing all meta tags to improve your organic click-through-rate and increase your SERP real estate.
Here, we’ll discuss what schema markup is and how you can use schema markup to improve the appearance of your rich snippets and increase leads through your organic search campaign.
What’s the Difference Between Structured Data and Microdata?
There’s a lot of confusion surrounding the difference between structured data, schema, rich snippets, and microdata.
Structured data is a data pairing between a name and an input value that is inserted into your content to help search engines categorize and index content based on their semantic vocabulary.
Structured data is a universal language of its own that can be understood by any structured data format and is mainly used to help search engines interpret the purpose and context of a webpage.
Microdata is a structured data format that works with HTML5 and is preferred by Google. Microdata is only one structured data format and others include RDFa and other microformats. It’s essentially HTML5’s form of structured data.
What is Schema Markup?
Schema markup is an entire index of structured data terms and vocabulary understood by major search engines. There are currently hundreds of markup data for structured data that even contain specific sitelink extension types and expected properties to make your schema markup more personalized.
So what does all of this mean?
Essentially, schema.org provides semantic terms that can be placed directly in your website’s code to provide clear terms for search engine categorization/indexation. Pair schema markup with microdata tags to provide a more in-depth description of content for search engines.
Search engines will then pull information found in microdata values to display in your rich snippet. Depending on the markup you place in your HTML code, search engines may pull a whole list of information to be displayed in your rich snippets, such as a name, address, phone number and images.
This is critical for precise indexation. For example, if you hosted a webpage about the movie Casino then you would use the markup ‘movie’ to differentiate your page from local area casinos.
For a full list of schema markup types you can go here.
The schema markup list is composed of agreed upon microdata terms and continues to grow each year. So how did it start?
What Search Engines Use Schema Markup?
In 2009, Google unveiled its fancy rich snippets to help marketers better advertise their content and improve search engine indexation. Yet, a problem persisted. Every time a search engine would run into an HTML code, it wasn’t always possible to decipher.
Two years later, Google, Bing, and Yahoo (later joined by Yandex) came together to create the schema.org resource. The schema.org resource was an effort to produce greater semantic results across the web and deliver users higher quality search results.
The schema markup library is understood by all four search engines and can work with alternative forms of structured data.
How Many Websites Use Schema Markup?
A 2014 Searchmetrics study found that 99.7% of domains did not even include a single piece of schema markup in their source code. The number of domains using schema markup has not increased significantly since this was recorded and providing schema markup to improve your rich snippets will only provide your website a competitive advantage.
Is Schema Markup a Ranking Factor?
Schema markup and meta tags are not a direct ranking factor in Google’s algorithms. Some SEO experts recommend the use of schema markup for greater search visibility and there are multiple benefits associated with a more complete rich snippet.
What are the Benefits of Using Schema Markup?
Mainly, schema markup provides richer search results for users and more detailed information to advertise your content organically. For e-commerce platforms, using schema markup may allow you to display the price, rating, size, and other associated characteristics of your products without investing in a PLA.
Schema markup also enables websites to create detailed sitelink extensions for greater click-through opportunity and the chance to be featured in Google’s Knowledge Graph. This all adds up to having far greater SERP real estate or visibility.
Optimizing your rich snippet meta tags improves your click-through-rates and provides a better description of your webpages for users and search engines. Consider the fact that exact match keywords are bolded in meta descriptions that match the user’s search terms. This also qualifies your webpages to drive impressions for more relevant searches.
With richer results, we can assume that websites will enjoy less bounces by being paired with more relevant searches. Unfortunately, these benefits are only really accrued by web page listings that rank very highly, as your snippets won’t be viewed as much if you don’t rank in the top 6.
While schema markup is certainly not a direct ranking factor, it’s influence may provide indirect positive results if used correctly.
How to Use Schema Markup
Schema markup offers a broad range of item types to categorize information. The most popular include:
Schema markup requires webmasters to manually enter each semantic attribute within their source code. For example, you may start by entering “itemscope” between two <div> tags to create an HTML block referring to a particular item.
Next, you insert the itemtype to specify the item the web page is discussing, such as a barbershop.
<div itemscope itemtype=”https://schema.org/barbershop”>
The itemtype will always appear as a URL directly referring back to the schema markup index. The itemscope tag within the previous code tells search engines that all of the content on this web page is related to the itemtype.
Look through the schema library’s full hierarchy to discover the different item types most relevant to your content. There are even specific extensions to find the itemtype you are searching for.
Finally, the itemprop tag can be inserted to label items. In the example of a barbershop, you would place the “itemprop” tag between the <h1> tags to label the name of the barbershop. The “itemprop” tag will be used to give specific labels for phone numbers, address, etc.
An important item type is the event type. This will help you tell search engines the specific time and place an event will occur. Search engines, and generally computers, have an incredibly difficult time interpreting time.
The schema markup library also offers custom enumerations for item values with limited properties.
Consider using Google’s Structured Data Markup Helper or Raven Tools Schema App for simple tagging. Simply click on the item type and then paste in your content’s URL to highlight different elements you wish to tag to that page. Google offers a rich snippet tool to check if you inserted your schema markup correctly.
Schema markup can be used in conjunction with other structured data, even though microdata is the most popular format. Schema markup may also work with social media cards, such as Twitter Cards to provide better search indexation for individual posts.
Furthermore, users can add a relevant subtype to their snippets for greater detail by inserting a backslash after the itemtype and adding a relevant semantic term to the schema library. Raven Tools also offers a Schema Creation tool to prevent markup errors.
Simplify Structured Data with JSON-LD
Domains still apply site wide schema markup to simplify the indexation process. Unfortunately, this hurts blogs posts and individual webpages who don’t receive a unique rich snippet.
On the other hand, manually inserting schema markup to a website with hundreds of blog posts is out of the question.
While microdata is fairly easy to use, manually inputting each tag across different web pages may result in some missteps. This is why JSON-LD was created to contain all of the necessary item types and attributes in one single element. This structured data format condenses nearly all of the extensions from a core vocabulary phrase into a single header.
If you are specifying that your content is about a restaurant with JSON-LD, you’ll also be able to label your store hours and NAP information in a single tag, regardless of theme development.
Outshine Other Search results
Consider enlisting the help of Raven Tools or Google’s Structured Data Helper Tool to provide clear and easy structured data markup across your site. Leveraging these strategies to create richer search results and clearer indexation will not only drive more traffic to your website, but better business opportunities.