{"id":118775,"date":"2020-06-25T19:27:28","date_gmt":"2020-06-25T11:27:28","guid":{"rendered":"https:\/\/seo-hacker.com\/?p=18775"},"modified":"2021-05-11T05:48:47","modified_gmt":"2021-05-11T05:48:47","slug":"semantic-search-seo","status":"publish","type":"post","link":"https:\/\/seo-hacker.com\/semantic-search-seo\/","title":{"rendered":"Understanding Semantic Search to Boost Your SEO"},"content":{"rendered":"

\"Semantic<\/a><\/p>\n

Before 2013, SEO was virtually a straightforward endeavor. You had to incorporate the exact keywords inside your content and the important places such as title tag, H1, meta description, then build a high number of relevant quality links to those pages to ensure ranking on the first page. However, the same could not be said today. Search engines evolved in how they understand searches and queries to the point that the same strategies we used almost a decade ago are not enough now.<\/span><\/p>\n

Today, a deep understanding of the meaning behind the keywords, content that effectively answers the context of the keywords, and the intent behind it is what succeeds in the search results. All of these were brought about by the age of semantic search. Let\u2019s dive deeper.<\/span><\/p>\n

<\/p>\n

What is Semantic Search?<\/span><\/strong><\/h2>\n

Semantic search, simple enough, is the search engine\u2019s way to have a deeper understanding of a user\u2019s queries by analyzing and connecting the meaning and relationship between the words and their context. This in turn enables search engines to find the best possible relevant pages to display even if the user\u2019s query wasn\u2019t straightforward. Here\u2019s an example:<\/span><\/p>\n

\"quick<\/p>\n

This specific search is pertaining to the well-known phrase \u201c<\/span>The quick brown fox jumps over the lazy dog<\/span><\/em>\u201d. Google\u00a0<\/span>understands<\/span><\/strong>\u00a0the context between the words used in the query and effectively answers it by knowing the relationship between the animal (quick brown fox) that jumped over the dog. Now, if semantic search was nonexistent, Google might have shown me results that showed\u00a0<\/span>random<\/span><\/strong>\u00a0animals jumping over dogs.\u00a0<\/span><\/p>\n

This just goes to show how far search engines have come to understanding the queries made by users. However, much like other machines, search engines are also limited to their own knowledge. Here\u2019s another example:<\/span><\/p>\n

\"chris<\/p>\n

Now, most of us know that the wizard in the Avengers is Doctor Strange, played by Benedict Cumberbatch. But when I searched for it, the answer Google gave me is Chris Evans, the actor that played Captain America. This isn\u2019t the correct answer, far from it. But this is what happens when I change a word in my query:<\/span><\/p>\n

\"sorcerer<\/p>\n

The search result actually shows the correct answer – Benedict Cumberbatch being the actor that played Doctor Strange. The snippet isn\u2019t as accurate as we\u2019d like but it still does answer the question. So, if you focus on the query I made, I changed the word \u201c<\/span>wizard<\/span><\/strong>\u201d to \u201c<\/span>sorcerer<\/span><\/strong>\u201d and Google actually gave me a fairly accurate answer. Why did this happen? The reason behind this is easier to infer than you might think.\u00a0<\/span><\/p>\n

Through the use of Knowledge graphs, introduced back in 2012, Google has an extensive database of public information and the entities contained inside them such as the people involved, their birthdays, parents, etc. Now, through the knowledge graphs that Google has, they use what\u2019s contained inside it to better understand queries. The inference we can make is that in Google\u2019s database, Doctor Strange (and the actor that plays the role) is known as a\u00a0<\/span>sorcerer<\/span><\/strong><\/span>\u00a0and not a\u00a0wizard<\/span><\/strong>. This, possibly, could be the correct answer to why Google was able to give me a more accurate answer than the one I previously searched for.\u00a0<\/span><\/p>\n

To summarize, Google uses the following to better understand a user\u2019s query:<\/span><\/p>\n