Beginner’s Guide To Structured Data And Rich Snippets

Beginner’s Guide To Structured Data And Rich Snippets

structured data

Structured information has been a hot topic in SEO circles for many years, nonetheless several marketers still don’t have a transparent understanding of what it’s and the way it relates tooptimization. We hope this blog post helps shed some light on this topic.

In its most simple sense, structured data refers to any set of organized data or data that has been given structure.

For instance, “Mike called to confirm your 4pm business meeting on Wednesday at the restaurant” and “Don’tforget to meet Jane at her office for brunch, 11am this Friday,” are both examples of unstructured data. Labelling the details within these messages and arranging them according to categories such as date, time, people, and type of meeting translates to ‘organizing’ them into a more ‘structured’ presentation.

Structured data is useful in a lot of ways, such as in utilizing Open Graph markup for specifying Facebook titles and descriptions, or in using SQL or explore relational database.

In SEO, structured data refers to the implementation of a certain type of webpage markup so as to provide details around the content of a page. This strategy can improve a search engine’s understanding of that particular page’s content, thus increasing relevancy signals and enabling your website to take advantage of enhanced results in the SERPs (such as carousels, rich cards, rich snippets, knowledge boxes, and similar types).

Structured information as a markup must be systematically parsed and understood by humans and search engines. This has led to standardized implementations or formats and syntaxes, as well as the classification of relationships, concepts, and terms, or vocabularies that must be used to ensure correctness.

The three syntaxes search engines typically support are Microdata, Microformats, and JSON-LD. These syntaxes are commonly used with vocabularies such as Schema.org and Microformats.org. In SEO, the most commonly used structured data markup (although not the only one)is Schema.org.

How is structured data used in SEO?

Search engines like Google encourage sites to form use of structured information. They even incentivize its use by offering benefits to websites that correctly implement it. These benefits typically include search result advantages and enhancements, along with other content specific features like:

  • Rich search results or snippets, which can include images, styling, and similar visual enhancements to help you provide additional context for different types of content such as articles, products, videos, star ratings, product reviews, etc.
  • Rich cards, that are a variationon wealthy snippets, designed for mobile audiences
  • Enriched search results, which can include immersive or interactive features
  • Knowledge graphs, which contain information about brands or entities. Search engines like Google use structured data in order to populate their knowledge graph boxes with the appropriate information
  • Breadcrumbs in search results
  • Carousels, which are collectionsof several rich results, presented in carousel style
  • Rich results for accelerated mobile pages (AMP)
  • AdWords through structured  snipping extensions, which permit you to feature data in your ad copy thus folks will higher perceive your merchandise and services.

All of these search result enhancements require the use of structured data as a markup approach. Not only can these search result enhancements help propel your pages to higher rankings— but they can also help improve overall click-through rates, thus attracting more traffic to your site. This is possible because enhanced search results are generally more visually appealing. They also provide more useful information to searchers. Not only can enhanced click-through rates indirectly improve search rankings—they can likewise be considered as user behaviour signals.

Implementing structured data is one way to future-proof your SEO, as search engines continue to improve in favor of hyper-personalization and move towards better problem solving by attempting to answer queries directly.