Semantic Search: Why Search Intent Matters for SEO

Kyles Semantic Search Post
Sarah Kincius
September 23, 2022

In the world of SEO, what people search for online matters. To search engines today, though, that’s an understatement. Why?

Enter: semantic search.

Keep reading to learn more about semantic search, how long it’s been around, and why it still matters today for search engines and SEOs.

What Is Semantic Search?

Semantic search is all about, well, semantics—the study of words and their working.

Semantic search is the process a search engine takes to analyze and understand the meaning behind the text of a search. It does this by keeping both users and their queries in mind in order to organize SERP results.

Although keywords and phrases are the building blocks of a query, it’s how they work that’s of interest here.

For search engines like Google, the best way to interpret a search is by considering a searcher’s intent, the linguistic relationship between the keywords typed in, and the broader context of the query as a whole.

In terms of search intent, SEOs often identify four distinct types:

  • Informational Intent: queries that aim to help a user discover more information about a product, service, or phenomenon

  • Navigational Intent: queries that aim to help a user find a specific website or web page

  • Transactional Intent: queries that aim to help a user purchase products or services online

  • Commercial Intent: queries that aim to help a user learn more about products or services before making an online purchase

Understanding a user’s intent for their queries helps search engines queue up the right content—but search intent would be lost on engines if they didn’t have a strong grasp on linguistics.

Take a vague keyword phrase as an example. Let’s say you typed in “what’s a story of a building?” into a version of Google that struggled to learn English and all its conventions. Sure, this pseudo-Google might figure out your intent is informational in nature, but it would have a hard time knowing if you meant the floor of a building or if you just wanted to read random stories about random buildings.

The Google of today has a much easier time knowing what you mean. Utilizing data gathered all over the web, as well as the data you make permissible to use (including your search history and location), it identifies the “entities” or implications behind your search terms to create a more substantial query context.

All in all, semantic search is the pursuit of search engines reading your queries in a way that’s intuitive, conversational, and (most importantly) human.

So What’s the History of Semantic Search?

Believe it or not, semantic search has come a long way in a short amount of time.

Although other search engines use semantic search in some way, Google’s use has been the most significant, which is why we’re spotlighting them here.

Scroll through Google’s semantic search history below. We’re taking you all the way back to 2012…

Google’s Knowledge Graph (2012)

In the words of Google, the Knowledge Graph is a “database of billions of facts about persons, places, and things.” They created this massive online compendium to help users quickly resolve queries in the public domain (i.e., generally regarded as fact).

Let’s say you typed in a question like “what building does the queen of England live in?” into your Google search bar. Rather than project the top 10 royal websites answering your query, the Knowledge Graph would put a knowledge panel at the top or side of the SERP to answer your question outright.

Although this system isn’t directly related to semantic search, it shows Google’s commitment to understanding user intent and improving its automation accordingly.

Google’s Hummingbird Algorithm Update (2013)

The release of the Hummingbird algorithm is allegedly where semantic search really began for Google. The biggest goal of this update was to match users to more relevant search results by considering the intent of their queries more deeply.

The Hummingbird update integrated better NLP, or natural language processing, into Google searches to achieve this. This emphasis on conversational search practices meant stuffing exact-match keywords into content was no longer enough—web pages had to match the meaning or intent of keywords to make it to the SERP’s top spots.

Google’s RankBrain Algorithm Update (2015)

Like the Hummingbird update, the RankBrain algorithm was all about improving how Google understands the meaning and significance behind searched keywords and phrases.

Using machine learning, it improved upon Hummingbird’s algorithm by beginning to look beyond just search intent. RankBrain started to consider the context of a query, whether personal (i.e., search history) or environmental (i.e., searcher location).

RankBrain was also great for the 15% of queries that had never been seen or searched before. It could look at a brand new set of keywords, logically guess at related search terms, and then remember its successful searches for next time.

To this day, RankBrain is regarded as one of Google’s top 3 ranking factors.

Google’s BERT Algorithm Update (2019)

BERT, which stands for Bidirectional Encoder Representations from Transformers, is the latest and greatest semantic search update from Google. Like the two before it, its algorithm improved Google’s understanding of search intent and query context.

Unlike its predecessors, BERT has the best language processing capabilities. It analyzes a query’s words in relation to the other words present instead of reading and analyzing each keyword sequentially word for word. This feature is especially beneficial for getting results from more long-tail phrases and complex grammatical search terms.

The BERT update is now available in 70+ languages around the world.

Why Semantic Search Matters to SEO

So what are the semantics of semantic search? In other words, what does it mean for SEOs today?

As we’ve said, semantic search is all about the human doing the searching: the user. When considering search intent, query context, and keyword linguistics, search engines can create a better search experience that feels more natural, friendly, and real. As an SEO, it’s your job to do the same.

Semantic search is the future of SEOs as we know it. If you consider yourself one, make sure you’re:

  • Prioritizing user experience and search intent above all else by creating content and optimizations that speak clearly, cleanly, and humanly to users

  • Shifting your emphasis away from keywords and focusing more on interesting topics you can address in-depth with high-quality resources

  • Structuring your code and content logically to make it easier for users, engines, and crawlers to read (and rank) your site

  • Optimizing and refreshing your site’s pages to avoid errors that make them difficult for users and engines to navigate across desktop and mobile

Vetting external and internal links to improve your content’s authoritativeness to users and engines

Sarah Kincius

Sarah Kincius is a Naperville resident and student at Loyola University Chicago. She loves going to the Green Mill to read whatever’s etched on the bathroom stalls (and to listen to the music, of course). Sarah is currently teaching herself Italian from a book she found in Wisconsin.

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