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We will discuss what exactly semantic search is, why it’s important for SEO, and how to optimize your content for semantic search.
History of SEO
Just a few years ago, optimizing for search engines meant loads of keywords and collecting as many backlinks as possible. SEO meant understanding how keywords drove the search engine results so we could get a higher ranking. The search for keywords in highly popular search phrase with little competition is not without risk. It is easy that in this quest you might find yourself trying to slip it in everywhere you can.
Done sparingly, this could give you a helpful edge, but it doesn’t take much before it's considered keyword stuffing. A ranking penalty isn’t the only downside of keyword stuffing, it puts your users off too. So optimizing the website with keywords, that rank well but have limited relevance to the content of your site, does little for user experience.
Today, search engines are AI-driven and have an understanding of the world and need to be fed with contextual information. Therefore we have to change our approach, because identifying keywords no longer leads to the desired result.
Now, you need to provide the meaning of the subject behind the keywords.
• Provide rich information that contextualizes those keywords
• Most importantly you need to understand the intent of the searcher.
For SEO all of these things are essential in an age of semantic search.
What is semantic search?
Semantic search refers to the ability of search engines to consider the intent and contextual meaning of search phrases. In this way the search engine can serve more relevant content to users on the web. The two factors that are addressed with semantic search:
• Searcher intent and query context. Search intent is the reason why someone performs a query. It tries to relates to what the user is trying to accomplish. Search intent could be to buy, learn, or verify something. If the intent of users is understood, the search results provided are more relevant to the searcher.
• The search engine must understand the semantics (what the words mean, not just what they are) of the text you provide on your website. The better the context of the search matches the context of the information on the webpage the higher it will be in the search engine result pages (SERPs).
What’s new? Structured data with Artificial Intelligence.
Search engines have difficulty interpreting the context of the strings of keywords. A lot of assumptions in this text are implicit. Computers cannot reason just on this strings of keywords.
An example of strings of keywords on an website, FB, Blog, etc., a human understands immediately:
• John Doe is on a sailboat in the Golf of Mexico
• There is only one sailboat in the Golf of Mexico
• There is a sailboat capsized in the Golf of Mexico
• John Doe is in danger
A search engine does not understand this immediately. We need to translate the strings of text to entity’s in structured data. In order to accomplice this we have to make use of the same Artificial Intelligence that is used by the search engines. The Artificial Intelligence that’s is used by the search engines on structured data is called: an inferencing engine. Datamachine Workbench is developed with this goal in mind.
• It supports users with the ‘translation’ of all your knowledge and facts of your organization to structured data. That is technically optimized for indexing and ranking.
• You can create content with people in mind and now you no longer have to think about search engines algorithm updates and identifying key words. You can zero-in on searcher intend and provide your audience with content that is relevant and of high-quality.
• Now you’re on the right track for the next generation SEO optimization with semantic search.
Would you like to know more about the inferencing engine? Contact us on our contact page or call us (+31) (0)20 716 52 74