The term structured data is primarily a general term. Structured data – no matter in what context – is always present when it follows a certain pattern or format, that is, when it is organized according to a certain schema. The concept of schema is relevant in this case, I will come back to this later.
Since search engines are dealing with a virtually infinite qatar telegram data amount of information, the challenge lies in sorting and interpreting this data. Only when the information is sufficiently understood can it be used to best answer search queries. Structured data gives website owners the opportunity to help search engines understand and interpret their website and information.
The Schema.org Collaborative Project
In 2011, the most prominent search engines joined forces and launched the Schema.org initiative. Google, Yahoo, Bing (Microsoft) and Yandex have since joined this open source project. The goal is to ensure that the content of websites is uniformly labeled, so that search engines can interpret it more easily.
Schema.org represents in a sense an ontology, or an all-encompassing conceptual schema. All conceivable entities (things), actions and relations are catalogued here in the directory, which is accessible to everyone at www.schema.org . For example, if I sell books in my online shop, I can mark up the individual product pages so that search engines know: “This is about [Book]!”
The entity [Book] usually stands for concrete literary works with specific characteristics. I can bring these characteristics closer to the search engines in a second step. I fill in a more or less extensive mask of properties , where each property stands for a certain characteristic. For example, it is obvious to define the title of the book, the author, the number of pages, the language, the ISBN number and the price.
structured data book properties
Property of “Book” on Schema.org
A language is not complete without vocabulary alone
With schema.org, the major search engines have built a constantly growing dictionary. In order to create an understandable language from this, grammar is needed, rules that make the language logical. This is precisely supplemented by the following markup languages: JSON-LD, HTML Microdata and RDFa. Each grammar works differently, but they all offer me as a website manager the opportunity to make my website more understandable with the help of structured data. I will discuss the advantages and disadvantages of these different languages and what is the best choice at the moment in more detail later.
What use is structured data to me as a website manager?
Of course it is nice for search engines that they understand the information better, but what do I as a website manager gain from that? The answer to this is visually stronger results in search engines. These so-called rich results show, in addition to the title, description and URL, also other elements such as review stars, breadcrumbs and other striking elements.
Richer results Google structured data.
Google search for Most people are good with normal and rich results
Image 2 shows a screenshot of a Google search for De meest mensen deugen , the book by Rutger Bregman. A difference is immediately noticeable between the first and second result, namely the rating stars and the number of reviews. In addition, the first result shows a clear breadcrumb structure. The best example in this case is shown last at ako.nl, where the price and availability are also shown. For a user, this is of course valuable information, which in any case attracts more attention than the other results. Although this is speculation, it may well be that ako.nl has a better CTR than kiosk.decorrespondent.nl in this case, despite the latter having a better position.
Rich results
All these elements, so breadcrumbs, reviews, price and availability are fed by structured data. It happens that pages that are provided with structured data, do not get these rich results. On the other hand: pages that do not use structured data, certainly do not get these rich results.
