A Guide to Semantic Search SEO

By in
A Guide to Semantic Search SEO

Multiple changes have occurred with Google and other search engines in recent years. Rather than retaining a focus on keywords to derive the meaning of a search, Google especially has been looking at what is behind it.

The meaning and reason for the search being performed by the user have led to various new approaches. These have been aimed at better understanding what the user is looking to find out, a process known as semantic search SEO.

Finding the True Meaning Behind Words

The Knowledge Graph was started by Google in 2012. It was designed to absorb information from millions of public domain sources. This factual information is related largely to people, places, and things.

For the first time, Google could answer back with facts when asked about them. It could also better separate events from people and facts about them. Therefore, an actor like Harrison Ford gets information applied to his entry including that he’s an actor, is male, and has starred in several movies.

Information from movies was also absorbed, so if a child searches in Google, “Is Han Solo still alive?” it’s possible that the search giant can work out that Han Solo is a character from a few Star Wars movies and played by Harrison Ford. Google may even know whether in the Star Wars universe of movies and books the fictional Solo character is still alive or not.

Hummingbird

Hummingbird (2013) aimed to move away from keyword spamming, which fooled the search engine that the page was more related to the subjects because the keyword phrase was repeated so many times.

Instead, the Hummingbird update attempted to better identify the meaning behind the content on a page to determine if it related to the searched topic, or not. This placed a greater emphasis on the value of the content – what it was about – and less on keywords.

Related Articles:  5 Ways to Stay Up to Date with the Latest SEO Trends

A Giant Leap Forward with RankBrain and BERT

RankBrain

A few years ago, RankBrain began using machine learning to intelligently identify related pages.

Google became much better at figuring out what pages related to each other because they covered related subjects. Also, the search engine results pages (SERPs) were analyzed to see what results proved successful with searchers whereas others saw them bouncing back to the SERPs to try another search result.

By using this information, Google got smarter about how information related to the subject of the search, and how users interacted with it (including data from Google Analytics providing further insight on sites setup with it).

BERT

In 2019, BERT was released. This represented a further iteration in semantic search and is most evident in what we see today. Each advancement has been a building block to get this far. This is similar to how AI systems aren’t immediately intelligent but must be fed information that they can digest to become smarter.

Search results improved with BERT because Google could break down a search query using natural language processing to understand the relationships and entities inside it (people, places, and things). It could also do that with web content. Using a combination of AI and machine learning, it could dive deeper into the meaning behind the words. It could connect the dots in the same way that humans can.

Rather than relying on keywords specifically, Google could understand what someone was searching for even if the search wasn’t one it had seen before, or it hadn’t been asked that way before. Also, when a user followed up with a second search that built on the knowledge gleaned from the first one, Google could now follow their train of thought and provide an answer that was likelier to be what was really being asked.

Related Articles:  Seven Sneaky Ways to Monitor Your Competitors' Keywords

How Semantic Search Changes the Game for Content Creators and SEOs

Previously, SEOs and content creators needed to ensure that the targeted seed keywords were included in an article title. However, now SEOs are free to be more creative with titles to attract the reader, rather than the search engine. This is because Google can better grasp what the subject of the article is and the value it provides.

Whereas previously secondary headings known in HTML code as H2s would need to include related keywords, they too were free to become more descriptive. This has also allowed Google in a recent enhancement to provide new search results that rank the secondary heading and jump directly to it while highlighting the pertinent text in that section too. This wouldn’t have been possible without semantic search improving over the years.

Writing for the Searcher

For SEOs, marketers, and other professionals, content can be produced around subjects and not single keyword phrases. They can even target long-tail search queries – longer searches that are more specific – and not worry about receiving limited search traffic from them.

Google will invariably rank an article perhaps for the seed keyword phrase (or long-tail keyword phrase) and secondary headings too, but also there’s more to come. Later, as the article ages and respond to it, it often will rank the page for other search phrases that aren’t even included in the article. This is because through greater knowledge, Google “gets it.”

Google understands far more often how one article offers something more useful than another. This is even when the first article is shorter but more information dense. It also sometimes applies when a newer website with its article can outrank a previously entrenched site with high authority because the article is more on point…. And the search giant knows it. Even backlinks aren’t overriding that.

Related Articles:  8 Link Building Tactics that Actually Work

What This Means for Site Owners

Site owners can pay greater attention to the usefulness of their content, rather than backlinks or tricks to rank better.

This might mean that a cleaner structure, simpler words to make it easier to digest, and a shorter article are the right solution. Adding relevant images or videos embedded into an article can enhance them when they’re relevant to improve the usefulness of the article overall.

There has been a distinct move away from long-form content that’s overly wordy without increasing the value it provides for the extra 1,000+ words published. Searchers want concise information, especially if they’re using a mobile device. Also, they’re increasingly looking for precise answers on long-tail queries that are very specific. So, when Google cannot answer it in a snippet because it’s a complex topic, then content that gets to the heart of the query can win out.

Site owners that have always wanted quality to win over backlinks and keyword-stuffed content are seeing their dreams come true through semantic search. As Google and other search engines continue to improve how they process search queries and absorb content on the web, these sites are ranking more appropriately. Also, as the searcher responds better or worse to it, this form of crowdsourcing behavior further refines results

Semantic search should now encourage site owners to offer high-value content and trust that it will be rewarded in the end.