With the rise of conversational search queries and the importance of keywords in SEO, semantic search has become the answer.
New types of queries have emerged due to the wide range of devices used. From laptop, smartphone, tablet to desktop computer, our way to search for information has changed.
What is semantic search?
Moz has given a relevant definition which says that:
Semantic search uses artificial intelligence to understand the searcher’s intent and the meaning of the query and not parsing through keywords like a dictionary. When you search now, Google gives you results based solely on the text and the keywords that you put in that search. Essentially, Google gives you its best guess. When you use semantic search, Google will dive into the relationship between those words, how they work together, and attempt to understand what those words mean.
To recap, semantic search tends to understand the searcher’s intent and the real meaning of a query rather than just looking at each keywords separately. Google will dive into the real meaning of the words when they are placed together.
It is about intent and context. Google will not necessary display content with the exact search terms but content which might match with your expectations.
The Google Knowledge Graph
Semantic search is supported by the Knowledge Graph. In clear, it offers valuable information in the SERP to answer to the user’s queries. It is contextualised by the user’s intent. We have written an article about the Knowledge Graph that goes further.
What impact on your SEO?
Semantic search is based on conversational queries. And conversational queries do not only focus on one single keyword but on a whole range of variations of this keyword. To rank well, it is important to understand that because it is about catching the user’s intent and not only to focus on a few keywords. You have to create content around that embrace the keyword. People are looking for answers.
When researching your keywords, you will need to guess what the person actually means when he is looking for something. If the query is “italian food” what does it really mean ? It could be “ where is the nearest italian restaurant?” or “how to cook italian food” or even “best italian food”. And this list is absolutely not exhaustive.
The clue is to focus on the natural language users will use to look for something and to find the best keywords to suit these questions.
And with the Knowledge Graph answering directly to some questions, you will have to be even better than Google itself in your answers.