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.
Structured data on the web uses Schema.org as a reference vocabulary and can be embedded in web pages using three formats:
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.
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.