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Google have mastered artificial intelligence, advanced language processing, voice recognition, augmented reality and headless page-rendering software. They have some of the most advanced technology in the world, ranging from military robots and driverless cars to interactive global satellite maps and semantic internet archives.

Of course, not all of that tech gets used by their search engine algorithm for answering day to day search queries, but it could be if they felt it was worth the processing power. The point is, Google’s search engine algorithm is just about as clever as they feel it needs to be right now.

As a result, Google is very good at understanding content. It sees beyond ‘keywords’ and works out the content’s topical relevance, its meaning and even the context that the content was found in. It can assess the trustworthiness and accuracy of the content. It understands the intent behind content and only shows it to users with relevant needs.

However, despite all of this big picture stuff, sometimes Google can still struggle to pull out the smallest, most granular pieces of info. This is where structured data, microdata and Schema come into play.

What are structured data, microdata and Schema?

Structured data, as the name suggests, is any data that has been organised into a logical and defined format. For example, data in a table with rows and columns specifying different types of information could be described as structured data. The opposite would be scattered information without formatting – and this would be known as unstructured data.

When coding a website, unstructured data scattered in the page’s content can be given structure by adding special tags to label it up. Those tags are known as ‘microdata’. So for example, a product’s name, description and price can all be wrapped in microdata tags so that any crawlers, such as search engines, can know exactly what that content is.

Schema, which is a word you’ve probably heard a lot recently, is a specific library of microdata. It is the result of a collaboration between Google, Bing, Yandex, and Yahoo. These search engines use it to improve their search results and create richer experiences for their searchers.

Common examples are displaying prices and review ratings within the search results. This is only possible because of Schema markup.

schema markup examples

These enhanced elements on search results are known as rich snippets and are considered very effective at boosting click through rates from search results.

Schema predictions for 2020

1. Rich Results
More and more of the first page of results in Google is taken with what are known as ‘rich results’. These come in many forms, but are essentially any results that are not a traditional ‘blue link’.

They are designed to highlight key information from a page’s content as accurately as possible. Rich results are composed of rich snippets and new ‘rich cards’ –offering more image space and a carousel feature. All of this hinges on Schema data.

2. Ranking Factor
Google and most SEOs have repeatedly said that Schema is not, in itself, a ranking factor. However, with the meteoric rise of Rich Results and the increasing complexity of search engine results pages, this could feasibly change.

3. Voice Search
Voice search is nothing new, but it is still growing. Home assistants have made some big leaps in 2019, including the ability for single commands to trigger a series of events pulling data from various tools and platforms, allowing much more complex tasks to be carried out. Schema will likely continue to grow in importance as a mechanism for facilitating voice search technologies.

Is your website as transparent as it could be to Google? Are you ready to capitalise on the rise of voice search? Speak to our experts for help and advice.

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