In several cases you might need to mix structured data using different formats like microdata and json-ld; in this article we review the do’s and don’ts for these edge cases.
Can I mix microdata and json-ld?
Yes,it is totally fine to use both syntaxes side by side on the same page but Google will not be able to merge attributes for the same entity using the item ID unless you are using json-ld ONLY.
Let’s get into the details:
I can have on the same page both syntaxes (microdata and json-ld); for instance I might use microdata to render WebPage and use json-ld for Organization;
I can also merge attributes related to the same entity when all the data is available in json-ld but …
I cannot combine information related to the same entity by item ID when this information is written in microdata and json-ld. While this is possible in principle, and a pure RDF application would be able to do it, Google does not support it, which means properties won’t be merged and, most importantly, this won’t satisfy the Rich Snippets‘ requirements.
This topic is particularly relevant as microdata remains today the most widely used format for structured data (see data below collected by Aaron Bradley from the 2019 Common Crawl’s sample) and there is a huge demand to improve structured data to gain additional visibility on Google’s SERP.
Before engaging with the community we created two examples HTML pages:
json-ld + microdata: here is the result validated with the Google Structured Data Testing Tool (where you will see the “Unspecified Type” error since GSDTT cannot merge the two syntaxes);
json-ld + json-ld: here we can see that GSDTT supports the merge by type ID when data is written in json-ld
Interesting enough the first example would be properly rendered by the Structured Data Linter: a tool designed to help webmaster validate structured data markup. Here follows the information from the Twitter thread and the messages by Dan Brickley and Jarno van Driel:
in general you can use both syntaxes side by side, but you won’t get the fine-grained merging of triples by ID that a pure RDF application might expect
If you are confused about meta descriptions in SEO, why they are important and how to nail it with the help of artificial intelligence, this article is for you.
If you are eager to start experimenting with an AI-writer, read the full article. At the end, I will give you a script to help you write meta descriptions on scale using BERT: Google’s pre-trained, unsupervised language model that has recently gained great momentum in the SEO community after both, Google and BING announced that they use it for providing more useful results.
I used to underestimate the importance of meta descriptions myself: after all Google will use it only on 35.9% of the cases (according to a Moz analysis from last year by the illustrious @dr_pete). In reality, these brief snippets of text, greatly help to entice more users to your website and, indirectly, might even influence your ranking thanks to higher click-through-rate (CTR).
While Google can overrule the meta descriptions added in the HTML of your pages, if you properly align:
the main intent of the user (the query you are targeting),
the title of the pageand
the meta description
There are many possibilities to improve the CTR on Google’s result pages. In the course of this article we will investigate the following aspects and, since it’s a long article, feel free to jump to the section that interests you the most — code is available at the end.
As usual I tend to “ask” “experts” online a definition to get started, and with a simple query on Google, we can get this definition from our friends at WooRank:
Meta descriptions are HTML tags that appear in the head section of a web page. The content within the tag provides a description of what the page and its content are about. In the context of SEO, meta descriptions should be around 160 characters long.
Here’s an example of what a meta description usually looks like (from that same article):
A rich snippet is a specialized form of snippet result that seeks to provide information and deliver answers to inquiries directly in the SERP. Rich snippets are generally considered more reliable and engaging compared to regular blue links. These snippets can be interacted with and provide a variety of differing functions. While these snippets are more convenient and useful, they can also be more complicated and require some work to implement them. Often times, they may require structured data markup in order for a website’s content to appear in a featured snippet.
How a Rich Snippet differs from a Regular Blue Link
While the standard blue links can be found all over the SERP and contain little more than a title, URL and meta-description, a rich snippet provides much more specialized results. They can feature more information, a longer description, pictures, ratings, sitelinks and more. Rich snippets almost always appear at the very top of the SERP, even above the first blue links results. Rich snippets are more engaging and appealing to users as they both deliver queries directly and are more trusted by Google compared to standard blue links.
Types of Rich Snippets
There are a wide variety of rich snippet types and even more variations of these types to perform different functions. There are a few primary ones that carry over into many subcategories and varying types. Among these include:
People Also Ask – A Question and Answer type that asks commonly inquired questions from other users and answers using information from third-party websites.
FAQ – A Question and Answer type that provides questions and direct answers from a specific website.
HowTo – A box providing a step-by-step instructions to a problem, commonly provides technical answers and advice.
Knowledge Card – A card displaying the entity of a search query from the Google Knowledge Graph. Applies to people, brands, companies, organizations, sports teams, events and media properties.
Carousel – A selection of scrollable cards displaying entities of people, locations, dishes, or other objects tied together by a shared entity or piece of information.
SiteLinks – Links to different sections on a single website.
A SERP featuring many different types of rich snippets, like a knowledge card, video carousel, image carousel, and people also ask.
There are also many, many more types of featured snippets for more specialized functions. Examples can include: Movie Carousels for movies of a specific genre or feature the same actress, Recipes to display different online recipes for a specific dish, or Flights which display a series of flights to a specific destination or similar destinations. Each have their own use and their own requirements for your content to be featured on the SERP.
The Relationship between Rich Snippets and Structured Data
While some content can be featured on it’s own or through information from existing entities, others require structured data in order to be utilized. In the latter case, a specific type of structured data must be added using the required markup from schema.org. You can do this with WordLift, which makes things far easier than having to code everything yourself.
Different types of rich snippets may require different markup for structured data. Some types may match the name of the rich snippet, like the HowTo snippet uses HowTo markup. However, others may use less obvious types or multiple markup types at once. What you need depends on the kind of content you want to provide and what rich snippet you want to feature. You can search for different vocabulary types on the Schema glossary.
If you would like to learn more about rich snippets and how to implement them using the schema markup on your website using WordLift, check out our spectacular guide here on the WordLift blog.
In WordLift, a Context Card is a preview of the content of the page of an entity that is linked to another page.
What is it for and how does it work?
The Context Card opens when the mouse is hovered over the link and provides the user with some initial information before even clicking on the link, helping him to decide whether to investigate the topic or not.
An optimal context card includes a short and direct definition of the entity and a representative image. In this way, the user can get an idea of the content at a glance and immediately identify which concept, person, place or whatever is talking exactly.
Just as semantic markup has the function of disambiguating the content for search engines, the context cart offers the reader a more precise contextualization. Moreover, thanks to its captivating format, the context card encourages the reader to deepen the topic to which the entity refers.
How are the context cards produced?
To show user context cards, WordLift automatically extracts the featured image (the main image of the entity) and the first lines of content of the entity page. For this reason, to take full advantage of this tool on a website, it is important to take care of the pages of the entities and to provide a useful definition in the first few lines, but which can also stimulate the user to go further and visit the entity‘s page. .
In the context of search, structured data are a predefined schema, helping search engines better understand and classify the information provided on a web page, thus making it more accessible to machines. That can also be used as an SEO marketing technique to improve your traffic.
What is structured data from a technical standpoint?
Structured data is data created using a predefined (fixed) schema and is typically organized in a tabular format. Think of a table where each cell contains a discrete value. The schema represents the blueprint of how the data is organized, the heading row of the table used to describe the value and the format of each column. The schema also imposes the constraints required to make the data consistent and computable
A relational database is an example of structured data: tables are linked using unique IDs and a query language like SQL is used to interact with the data.
Structured data is the best way for computers to interact with information. As opposed to semi-structured and unstructured data.
Semi-structured data is characterized by the lack of a rigid, formal structure. Typically, it contains tags or other types of markup to separate textual content from semantic elements. Semi-structured data is “self-describing” (tags are a good example, the schema is part of the data and the data evolves with the content but lacks consistency)
Unstructured data can be found in different forms: from web pages to emails, from blogs to social media posts, etc. 80% of the data we have is known to be unstructured. Regardless of the format used for storing the data, we are talking, in most cases, about textual documents made of sequences of words.
Structured data on the web
Structured data is a standardized format for providing information about a page and classifying that content on the page; for example, on a recipe page, what are the ingredients, the cooking time, the temperature, the calories, and so on.
Imagine a book supported in three different formats: ebook, paperback, and hardcover. Each has different weights, sizes and so on. So does Schema.org.
The Semantic Web movement, the creation of the Schema.org vocabulary and the importance that these technologies have on semantic search engines like Google, Bing, and Yandex have resulted in publishing online structured data on a previously unprecedented scale.
Structured Data Growth from the Common Web Crawl
Why structured data matter in SEO?
In the context of SEO, structured data are an effective tactic to pass critical information on a web page to search engines. In particular, in a recent update, Google clarified:
Content in structured data are eligible for display as rich results in search.
In short, the search engine is able to provide additional featured on the search results pages, that will enhance the visibility of your content. For instance, when asked about structured data, that is how the search engine might extract content from a web page, and place it into an answer box, called a featured snippet:
Example of a featured snippet coming from the WordLift blog, that with the help of structured data helps the search engine extract critical information. This sort of feature has a high click-through rate. It means that a large number of users finding it will land on your site thanks to a better real estate on Google’s pages.
A Knowledge Panel is a visualization that appears on top of search results (on mobile) or at the right side of them (on desktop) which provides authoritative information about any entity or concept. Structured data help trigger this feature, by enabling Google to pull critical data from your web pages, thus making your brand more visible on its search results.
Other rich elements triggered by structured data are event snippets, which can pull up critical information for an event directly on the search results, thus making your brand the most authoritative on that specific event. By creating an association in the mind of users between that event and your brand:
Example of an event snippet. With the WordLift team, an event page was created by using the mapping of our software to pass key information about the event, which was taken by the search engine as an authoritative source of information on that specific event.
From the technical standpoint, structured data are predefined (fixed) schema and are typically organized in a tabular format that helps machines understand how data are organized.
From the marketing standpoint Structured Data by leveraging on the Schema.org vocabulary, can help search engines better understand, interpret and process the information provided on the web page. Thus making it easier for the search engine (Google in particular) to show that data directly on its search results as a rich element.
Rich elements can be of various types. From featured snippets, knowledge panels, event snippets, top stories, Google news, People Also Ask, reviews and more. Those rich elements can become a key driver of qualified traffic and visibility toward your website.
Some Schema.org types are beneficial for most of the businesses out there. If you have a website you want to help search engines index its content in the most simple and effective way and to do that you can start from…well, the most important page: your homepage. Technical SEO experts like Cindy Krum describes schema markup (as well as XML feeds like the one that you can provide to feed Google Shopping via the Google Merchant Center) as your new sitemap. And it is true when crawling a website (whether you are Google or any other automated crawler you might think of), getting the right information about a website is a goldmine.
Let’s get started with our homepage. We want to let Google know from our homepage the following:
The organization behind the website (Publisher)
The logo of this organization
The URL of the organization
The contact information of the organization
The name of the website
The tagline of the website
The URL of the website
How to use the internal search engine of the website
The Sitelinks (the main links of the website)
We can do all of this by implementing the WebSite structured data type on the homepage of our website. A few more indications from Google on this front:
Add this markup only to the homepage, not to any other pages
very important and unfortunately on a lot of websites, you still find this markup on every single page. It should not happen: it is unnecessary.
Always add one SearchAction for the website, and optionally another if supporting app search (if you have a mobile app – this will help users searching from a mobile device to continue their journey on the mobile app).