Semantic search

1. Semantic Search

SEO specialists spend a lot of time and effort trying to get Google on their side — to see the brilliance of their content, the ingenuity of the meta elements and the genius of the organic strategies. We spend so much time treating Google as a “friend” that we sometimes lose sight of the big picture: Google’s results are derived from an algorithm that seeks conversation.

The entire realm of computer science is based on the use of algorithms to solve the many problems that are produced by the sheer volume of the information processed when it comes to producing the required results. However, to create an algorithm that tries to imitate the level of complexity of a human conversation is a challenge of unprecedented magnitude. Artificial intelligence has always been the objective of computer engineering of the top Mountain View companies. The advancements in teaching machines how to think like people have been nothing short of impressive:

  • Appearing in local stores as pseudo-employees
  • Cars that no longer require a driver

and many more. The predictions for the future speak of even further advancements for meaningful and fruitful interactions with our smartphones and personal data assistants. And search engines are the field of implementing these advancements on artificial intelligence.

2. What is semantic search?

The word “semantic” denotes the meaning or the essence of a word. Essentially it tries to link a word with a logic, a notion, a feeling or whatever a person tries to express when using that word. Human beings, contrary to what many may believe, do not do this automatically. It is a process that one learns in school and as they grow up accumulating knowledge through experience.

A semantic search takes advantage of the lessons learned by the human process and tries to improve on the accuracy of an enquiry by understanding its intention through its contextual meaning. In a similar manner to the inner workings of the human brain, such a search takes into account concept matching, synonyms and natural language algorithms to provide more interactive results through the transformation of the structured and unstructured data it receives, into an intuitive and responsive database.

The process brings about an enhanced understanding of searcher intents, the ability to extract answers and delivers more personalized results. Google’s Knowledge Graph is a good example of what semantic search can do.

3. SEO semantic search strategies:

a) Value. Google is looking to AI and how it envisions a conversation as the next evolution of search technology. It needs a source of good information for all of its conversations, a reference point, an expert friend, and so on. This translates to a prioritization of the most important questions to be asked when you set your targets:

– What are the keywords you want to rank for?
– Who is your audience?
– How can you become better?
– Who is interacting with your content?
– How are users interacting with your content?
– Do you get conversions?

The responses to these questions provide the value for the search. Wrong responses provide wrong results.

b) Content that answers your customer’s questions. Create targeted non-brand related content, which should not interfere with your acquisition-focus online. The idea is to create content referring to the essence of what you sell, which interests users and fills gaps in organic visibility. The objectives are:

– to become a valuable source of information for your customers
– to build your semantic authority in the “eyes” of search engines
– to become search engines’ “go-to” guru on a topic via building robust, informational content using mixed media (images, graphics, and videos).

c) Structure sentences clearly and providing answers. SEO writing is no different than natural language writing. Your content should use natural spoken language. In simple terms: your content should make sense. With Hummingbird’s improvement on precision and semantic search, RankBrain’s machine learning ranking factor incorporated in 2015 and the growing popularity of voice searches, natural language is not just necessary. It’s a must.

When you create content it is important to write in terms of tangible subjects, which means more noun-focused sentences. Simple, topic focused sentences provide engines with more information. Try to structure your sentences in the format of Subject Predicate Object (SPO). This will make your content easily understandable to your users, while search engines will be able to better parse the information. The key here is to sound natural, construct your sentences with purpose and write content that directly answers a question.

One thing you should pay special attention is that while all responses are answers not all answers are responses. A generic answer is not a response. A vague answer is not a response. An answer that your user can find anywhere else is not a response. A detailed, focused to the topic at hand answer with some unique information is the response your user is looking for. And it will be the answer that will move you closer to the objective of providing value to your content.

d) Structure your data to help bots parse content. Structured data markup explains information that is already on web pages, adding clarity and increasing the confidence to search engines. Using structured markup not only enables search engines to better grasp the content, but it can also be used to signal a desire for enriched search results. These snippets provide users with additional information about the contents of the page and can improve click-through rates (CTR) from organic search.

e) Leverage internal linking. Internal linking has long been a method of indicating relevance, supporting the user experience as they navigate throughout your site. Remember to use internal linking sparingly and only when it is in the best interest of the user.

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