Understanding How Semantic Search Works

how to improve your SEO strategy by understanding semantic search

Site owners and publishers must consider tweaking their SEO strategies as Google continues using semantic search. Semantic search considers the user intent and semantics to discover the most relevant and accurate SEO content for queries. It uses information that is extremely relevant to what the searcher is looking for but isn’t necessarily included in the text, making it much better than keyword matching.

Although a search engine can successfully find the right content using keyword matching alone, it can only satisfy simple user queries if semantic search is not involved. For instance, if someone types in “red toaster” in the search engine box, the search engine finds all the items with “toaster” in the titles or descriptions, as well as those that come in red colour. When the user adds synonyms like maroon for red, they will see more results for toasters, but things can get difficult because the user will have to add the synonyms themselves, and there will also be unnecessary toaster ovens in the results. Therefore, semantic search is important for more complex user queries.

Understanding how semantic search works and its components can help SEOs determine if it’s a good fit for their company and how to make the most of it by involving it in their SEO strategies.

The Elements of Semantic Search

The goal of semantic search is to find and display relevant information while taking into account the context, user intent, and conceptual meanings. It utilises machine learning and vector search to provide results relevant to the user’s query regardless of whether there are word matches. These components collaborate to provide the searcher with relevant content based on meaning. Context is one of the most important components of semantic search.


The context in which a search takes place is crucial in determining what a searcher is looking for. It can be as simple as the location where the searcher is because a British person searching for “football” may be looking for a different piece of content than a US resident who typed in the same word in Google’s search box.

It can also be much more complicated. Google uses the context of both personal and group variables, and the term used to describe the personal level influencing results is personalisation.

Personalisation involves the user’s previous searches, affinities, and past interactions to provide the most appropriate results for the current query. It works with all sorts of queries, but semantic search can take it a step further. A search engine on a mass scale may re-rank results based on how all searchers interact with thematically similar results, such as which ones are clicked on the most frequently or when results are more popular than others. Moreover, semantic search can use the context within the text.

User Intent

The goal of any search engine is to find the most relevant SEO content for the searcher. To do this, the search engine must determine what the user intends to do or achieve.

The search engine can deliver the most relevant results if it understands what the user is searching for and gets ahead of their intent. This may be all the more important with query categorisation, which involves categorising the query and restricting the list of results so that only relevant results appear. An example of this is customising the search of the price from lowest to highest.

Difference Between Keyword and Semantic Search

Keyword search engines employ natural language processing (NLP) to improve word-to-word matching by utilising synonyms and eliminating stop words, among other things. However, this process depends on matching words to words.

Semantic search can pull up results even when there is no matching text, but one can see that there are good matches. This is a huge difference between the two, which is how matching between records and query happens.

For example, keyword search involves matching on text, so “soap” will match “soapy” or “soap” due to the overlap in textual quality. What’s more, there are enough matching characters or letters that give signals to the search engine that a user may want the other result. In the same scenario, the search engine will also most likely match the query soap with the word “soup” instead of detergent, unless the search engine’s owner coded beforehand that soap and detergent are the same. Doing so will make the search engine treat the two words as the same.

To assist with information retrieval, keyword-based search engines may utilise alternatives, query word removal, synonyms or other forms of query relaxation and expansion.

NLU and NLP tools like normalisation, tokenisation, and typo tolerance also aid in information retrieval. While these can help provide better results, they may fall short when it comes to more concept matching and intelligent matching.

Semantic Search Matches on Concepts

The search engine may not be capable of telling whether records are relevant based on the number of characters two terms have because semantic search focuses on concepts. For example, “soup” versus “soap” versus “detergent”, or more complicated queries, like “laundry cleaner”, “remove stains clothes”, or “how do I get grass stains out of denim?” Users may even conduct image searches!

It’s like a customer asking an employee for help in finding the “toilet unclogged” aisle in the grocery store. If the employee only has a pure keyword-esque comprehension of the request, they would fail unless they know that the customer’s question explicitly means drain cleaners, toilet augers, or plungers.

A more in-depth description of what semantic search does is to claim that it adds greater intellect to the match on concepts rather than words through vector search. Semantic search, with this intelligence, can perform more like a human being assisting a searcher shopping for dresses or suits when searching for fancy clothing, even without results relating to casual jeans in the search results.

Position1SEO Can Help You Optimise Content for Semantic SEO

To be successful in today’s world, it is important to do research on your target audience’s user intent and create relevant and informative content that satisfies their queries. If that’s what you’re aiming for, Position1SEO can help! We are a UK-based SEO agency with years of experience in developing the best SEO strategies and helping businesses achieve their online marketing goals.

Our unique approach to SEO means that we can help you boost your rankings and site traffic, regardless of how many key phrases you choose to target. Plus, our team of experts are always on hand to help you write relevant and accurate content about your products and services. So why not give position1seo.co.uk a try today? You won’t be disappointed!

how to improve your SEO strategy by understanding semantic search min
Author: Jason Ferry
Jason Ferry is an SEO specialist based in the United Kingdom. Taking pride in his many years of experience in the search engine optimisation industry, he has honed his skills in various digital marketing processes. From keyword marketing, website auditing, and link building campaigns, to social media monitoring, he is well-versed in all of them. Jason Ferry’s excellent skills in SEO, combined with his vast experience, makes him one of the best professionals to work with in the industry today. Not only does he guarantee outstanding output for everyone he works with, but also values a deep relationship with them as well.

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