It makes sense that search engine result snippets need to contain as much accurate information as possible to help users find results that are relevant to their search. By using rich snippets you can label your data to help search engines further understand and categorize your content.

What are Rich Snippets?

If you were to write an online review for a restaurant, for example, and then fill in the business details and give it a star rating in standard HTML, to the human eye it may be very easy to read but to Google this may just seem like strings of text with no real meaning. But by using structured mark up such as Microdata or Microformats to label each field then Google and other search engines can more easily identify exactly what the content is.

Looking at these Google search results below, you can see which websites have micro-formatted their data against others that have not.

You can check if Google has correctly parsed your structured mark up data here with the use of Googles “Rich Snippet Testing Tool” (still currently in Beta).

So what is Schema.org?

On June 2nd 2011 Schema.org announced they were collaborating with the three major search engines Google, Bing and Yahoo to create a standard set of schemas for mark up data on web pages with the main focus being to simplify the mark up requirements for content creators across the web. The site aims to be the “one-stop resource” for webmasters and developers needing to add mark up to their web pages. So now, in addition to the categories that were already supported, there are over one hundred other categories including movies, music, places and much more.

The example provided below is taken from the Schema.org website. The first shows how standard HTML would look to a search engine when reading a product review:

Now see how to mark up your page using the schemas provided on Schema.org:

View the entire “type” hierarchy from schema.org here.

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Hayley

Search Analyst at Silkstream
SEO, blogger and Google geek. Committed to helping small business thrive during economic austerity.