How it works

We will discuss what exactly semantic search is, why it’s important for SEO, and how to optimize your content for semantic search with the Datamachine Workbench.

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.

seo_volume_graphic_EN

Age of semantic search

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:

  1. Searcher intent and query context (Hummingbird and RankBrain).
    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.
  2. 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 the CEO of ACME
  • 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

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.

  1. 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.
  2. 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. 
  3. 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.

How does the Datamachine Workbench work in five easy steps

When you realize that 93% of online experiences begin with a search engine (Forbes). Content and search engine findability go hand-in-hand. Without one, your efforts on the other are seriously diminished. Your keyword research won't do much good unless you then use those keywords in your content, or if the keywords you use are not relevant in relation to the context of your content. And creating content without knowing what your audience is looking for will leave you without any significant traffic. Beyond that, relevant high quality content is what creates customer engagement.

Step one

Identify all the explicit and implicit knowledge and information on your website, social media, blogs, reviews, movies, etc.

Step two

Feed the information into the Workbench. The AI will help you to get the information in the right form in the database. The information in the database will be transformed to a format that is readable by the search engines.

Step three

For every website page you will decide which information will be shown. The Workbench will make shure the information presented is consistent.

Step four

Every time a page is served, the Datamachine API will dynamically insert the information into the webpage. So every change will be instantaneously visible.

Datamachine_Platform