Semantic Search: What Is It and How It Affects Your SEO

It is no secret that the internet has become a big place filled with content. Search engines have struggled to keep up, and in recent years they have begun hiring more people just for semantic search.

Semantic search is a process in which websites and web content are created in such a way that they can be easily understood by people. This allows for better search results and higher rankings.

Google, Bing, and other alternative search engines are working hard to cut down on spam, give the most relevant results, and customize the user experience. That is why semantic search is such an important aspect of search engines’ efforts to produce high-quality material that fits the intent of a searcher. 

Improving these qualities necessitates the development of ever-evolving algorithms. Using data such as a user’s location, prior searches, natural language features, and more, these more complicated algorithms are growing better at interpreting each search query’s purpose and contextual meaning.

On the one hand, semantic search aids in the delivery of more relevant and better search results. It adds a new degree of complexity to SEO, requiring new approaches to activities like as keyword research and content optimization.

However, if you want to optimize your site for semantic search, you must first learn what semantic search is and how it works. We’ll look at the following topics in detail in this guide:

How Does Semantic Search Work?

It’s the year 2020, and you’ve undoubtedly noticed that Google has improved its ability to comprehend and respond to your inquiries. It wasn’t always like this, but Google has made multiple modifications in recent years to better its comprehension of the purpose behind a query put into the search engine. 

Simply said, semantic search was intended to help people better comprehend search intent by looking at the context of a search query.

Semantic search improves comprehension of the meaning of search queries (remember, 15% of searches have never been done before), resulting in more relevant and tailored results.

To summarize, semantic search employs intent, query context, and word connections to create the most accurate search results.

An Example of Semantic Search

Let’s look up “kid who lives in a cupboard beneath the stairs” on Google.


Of course, Google understands that you’re referring to Harry Potter.

But how do you do it? Let’s take a closer look at what happens when you do this search.


Google has taken a search query and produced a result based on its understanding of the purpose and context around how these words are linked. 

However, semantic search is used to drive much more than just the answers to our inquiries.

Are you looking for a plumber? Google recognizes your location and offers results that are relevant to you. Are you looking for “restaurants near me”? Google recognizes your location and offers results that are relevant to you. Are you looking for “corona”? Google is aware of the situation. If you did a search a year ago, the results would have been about beer; today it’s about the virus. Are you looking for “Amazn”? Google is aware that you misspelled Amazon and consequently provides results.   

Find out what your audience is looking for right now.

With Webinomy’s keyword intent analysis, you can find out what people are looking for.

ADS illustration

What Is the Importance of Semantic Search?

But first, let’s take a look at why semantic search is so important for SEOs to grasp and include into their strategy.

Users don’t always search for the same terms or in the same manner that the material that best answers their inquiry does. In 2020, search will be significantly more conversational than it has ever been. Google, on the other hand, must offer relevant results, implying that it must change and adapt to this new manner of searching.

The Rise and Fall of Semantic Search

Semantic search isn’t a new concept.

Google created the Knowledge Graph in 2012 to provide a speedy response to searches directly on the SERPs.

However, you must be aware with the progress of semantic search over the last eight years to appreciate its intricacy and development in today’s environment.

Graph of Knowledge (2012)

The Google Knowledge Graph (launched in 2012) is a database of entities and their relationships. There are almost 500 billion of them.

Let’s take a look at a clip from Google’s reintroduction to the Knowledge Graph to see how they define it:

Google Search may sometimes display unique boxes with information on people, places, and objects. These are what we refer to as “knowledge panels.” They’re designed to help you learn more about a subject fast by revealing crucial data and to make it easy to go deeper into a subject. Our Knowledge Graph, which is like a big virtual encyclopedia of information, provides data for knowledge panels.

Sullivan, Danny

Even if you don’t know what it’s called, you’re probably acquainted with the knowledge panel. These are the items that display to the right of search results for persons or companies. Here’s an example of Apple’s knowledge panel:


These knowledge panels are powered by Google’s knowledge graph, which is a collection of facts, information, people, locations, and enterprises, as well as how they are related.

Google uses the knowledge graph to return facts and information about these billions of interconnected entities.

However, we propose utilizing Kalicube’s Knowledge Graph Explorer to explore the knowledge graph for yourself (either your brand or you as an individual). The following is an example of how Google knows you: 


Hummingbird is a little bird that flies about (2013)

In 2013, Google released the Hummingbird algorithm in an attempt to improve search results. 

Danny Sullivan explained this fresh version of the method as follows at the time:

Consider an automobile from the 1950s. It might have a fantastic engine, but it could also be one that lacks features such as fuel injection or is unable to run on unleaded petrol. When Google transitioned to Hummingbird, it was like taking out the old engine and replacing it with a new one. It also done so swiftly that no one was aware of the change.

Sullivan, Danny

The most notable difference with Hummingbird, though, was Google’s improved understanding of conversational search. 

The search engine improved its ability to answer inquiries like “What is the difference between A and B?”

Hummingbird marked the beginning of search engines becoming more intelligent. This transition was prompted in part by the shift to mobile, which required the algorithm to better distinguish various sorts of searches and give better results depending on the manner a user searched.

“They want to enter into a more ‘natural interaction’ between consumers and Google,” said Scott Huffman, a Google engineering director, to Forbes Magazine.

Seven years later, it’s hard to believe that Google struggled to answer inquiries in the not-too-distant past, but Hummingbird was a game changer that ushered in the modern era.

RankBrain is a search engine that ranks people based on (2016)

One of Google’s top three ranking criteria is RankBrain.

But what exactly is it, and why is it so crucial?

In a nutshell, it is a machine learning technique that Google employs to generate search results, and it was created to assist the search engine in comprehending the meaning of the words submitted by users. 

And back in 2016, when this was first announced, we wrote:

RankBrain uses artificial intelligence to insert words into numerical entities so that computers can interpret them better. For filtered results, any words or phrases new to RankBrain will be turned into words and phrases with comparable meanings. When it comes to fresh search queries, this improves Google’s accuracy and efficiency.

Courtney Capellan (Courtney Capellan)

This was all about Google being smarter and better at answering a searcher’s questions. It was the beginning of the requirement for SEOs to delve deeply into search intent. 


BERT, or Bidirectional Encoder Representations from Transformers, is the most recent semantic search enhancement you should be aware of.

But what exactly is BERT?

BERT, our new technique for Google Search to comprehend language better, is now available in over 70 languages across the globe. It was first released in October for US English. More information regarding BERT may be found below, as well as a complete list of languages in this thread….

December 9, 2019 — Google SearchLiaison (@searchliaison)

BERT, like the other upgrades we’ve discussed, is all about Google getting a better understanding of search queries. Anyone may train their own cutting-edge question-answering system using the technology that underpins it.

Danny Sullivan corroborated this information “It affects around 10% of inquiries in areas where BERT is active. The remaining 90% of people do not employ BERT to decipher queries “”Intended.”

BERT evaluates the whole context of a word by looking at the words that come before and after it, making it especially valuable for deciphering the purpose of search queries.

Have you noticed how important purpose is once again? 

Keep this notion in mind since we’ll be addressing it in further detail momentarily. 

What Does SEO Mean by Semantic Search?

So, what does semantic search imply in terms of SEO?

At its most basic level, it refers to a search engine that has improved its understanding of a user’s search query and the capacity to provide more relevant, tailored SERPs.

However, in terms of how SEOs should approach semantic search optimization, this means:

  • Topics, not keywords, should be considered. 

  • Understanding that high-volume keywords are no longer as important as they once were, and that long-tail, related keywords and high-quality content are more important than ever. 

  • Before developing content, it is critical to examine and comprehend search intent. It’s also necessary to arrange your content to match the query type and any SERP characteristics you’d want to win. 

  • It’s critical to have structured data. 

  • You should be considering how to create a Knowledge Graph entity.

In many respects, optimizing for semantic search is what we should now consider best-practice SEO, but the need to develop content and optimize for people, not search engines, should stand out.

Consider how your consumers look for your goods and services, as well as their search intent. Then make this your main priority. 

How to Make Your Content Semantic Search Friendly

Do you want to improve your site’s organic exposure by optimizing your content for semantic search? Here are seven things you should think about:

1. Consider topics rather than keywords.

It’s time to move away from optimizing for particular keywords and instead focus on concepts.

Is keyword research as we know it a thing of the past? Of course not; things have only become more difficult. 

Google recognizes that terms like “home renovation loans,” “home improvement loans,” and “home renovation loans” all refer to the same thing. Because the aim is the same for all of the queries, the material delivered should be almost identical.

It will at the very least be the same page on the same site for all of these inquiries. 

In the past, you may have generated different pages to target single, plural, and other permutations of a term. However, it would be advantageous if you were not doing so in today’s environment. It would be ideal if you never had in the first place, but as Google’s knowledge of semantics has improved, this has become increasingly more critical.

For example, getting your website to the top of the SERPs for “home improvement loans” with a search volume of 27.1k (according to the SEMrush Keyword Overview Tool) is no longer your aim.

At the very least, it isn’t the main aim.


You may cover the whole subject and have your website appear for a variety of long-tail inquiries. We can see that the near variants add up to a substantially greater search traffic for your page – 65.5k searches, vs 27.1k for the single term.

Then there are the 3.8k searches that are prompted by inquiries. We can locate both of them by using the tool and inputting our primary keyword.


Take the effort to learn how keywords go together to make subjects, then optimize for them. You’ll reap the benefits.

2. Recognize and cater to search intent

Every Google search query is basically a question that represents the purpose of your target audience.

When you’re attempting to get inside your consumers’ thoughts, understanding it might be a difficult task. However, if you can develop content that fulfills this aim, ranking at the top of the SERPs will be much simpler.

And we can see this by looking at how search intent is generally divided into three categories:

  • Educating yourself (informational)

  • Purchasing an item (transactional)

  • Looking for something (navigational)

These informative, transactional, and navigational intentions are matched with the appropriate informational, transactional, and navigational keywords.

For example, if I want to compare cellphones, the search engine will not suggest that I purchase any right away. It recognizes that I’m at the top of the funnel, gathering information rather than seeking to make a purchase.


This implies you’ll need to create multiple types of content to meet different goals. While you may believe that writing new content for the same or comparable keywords is a waste of time, it isn’t always the case. Our keyword cannibalization tutorial will show you that the problem arises when you duplicate purpose rather than the term itself. 

Take your time analyzing the SERPs to learn about the various intentions for the subjects you’re interested in. 

Find out what your audience is looking for right now.

With Webinomy’s keyword intent analysis, you can find out what people are looking for.

ADS illustration

3. Make use of semantic HTML.

Using semantic HTML as a starting point for optimizing for the semantic web is an excellent place to start.

Have you never heard of this before?

This is how explains it:

Semantic markup is the use of a markup language like HTML to transmit information about the meaning of each element in a document via the right selection of markup components, while keeping the markup and the visual display of the elements included in the document completely separate.

To some degree, this entails reconsidering how we write our programs.

HTML components like span and div are probably recognizable to you. These aren’t semantic in any way. They don’t say what’s inside.

Look at a semantic tag like header>, footer>, or article>, for example.

These provide a clear picture of what is included in these components. Our tutorial will teach you more about semantic HTML so you can start marking up your code in this manner.

4. Content Optimization for the Featured Snippet

The Featured Snippet, or position zero, is based on semantic search and is one of the most sought-after SERP features.

To get the coveted featured snippet, you must demonstrate to Google that the response your web page delivers to a searcher’s issue is the most straightforward and useful on the internet. It’s an audacious assertion to make. But that’s where you should aim if you want to win the featured snippet.


But how can you improve your chances of getting this job?

  • Examine the most commonly asked queries in your niche to see which ones cause the Featured Snippet to appear. With our Term Overview Tool, you can observe the SERP elements that are activated while evaluating a keyword.

  • Examine the article’s structure that is now ranked in the snippet. Look for bulleted lists, tables, images, and heading depth in your material and attempt to mimic it.

  • Make material that directly addresses the question and arranges your phrases such that they flow naturally. 

5. Recognize and Apply Structured Data

Structured markup helps a search engine comprehend the context of your content and sift through specific entity properties to present the user with better relevant search results when it crawls your site.

Structured markup also improves your chances of triggering rich snippets.


You may use this markup to create entities, actions, and relationships, as well as to assist search engines better comprehend your content, by reading our guide to schema and structured data.

In addition, as stated in the guide:

These markups are becoming more useful in efficient Internet communication as Google strives to construct a more semantic web.

But what can you do to mark up your material with structured data? 

6. Establish yourself as a Knowledge Graph Entity

People think in various ways, thus they seek in different ways. That is why semantic search is based on a network of entities (people, places, objects, ideas, concepts, and so on) and their relationships. 

This is why it’s advantageous to become a Knowledge Graph entity, which you can learn how to achieve in Jason Barnard’s #SEOisAEO episode “How to Get Entities and Their Attributes in the Knowledge Graph.” 


Assume you’ve successfully converted your brand website or blog into a Knowledge Graph item. In that scenario, you’ll earn a spot in SERP features like Knowledge Panels and Knowledge Cards, with with all the exposure, authority, and trust that comes with it.

It may, however, cost you some organic traffic since searchers may be able to discover all they need to know about your firm directly from the SERPs page.

However, consider beyond your company’s organic traffic. Consider the benefits of being at the top of a SERP in terms of visibility and authority.

7. Create Relevance-Demonstrating Links

Internal and external links may both exhibit subject relevance and aid Google’s understanding of your material. 

While it’s tempting to imagine that the links you acquire might come from anyplace as long as they’re authoritative and editorial, you’ll notice a bigger effect when they’re all related to the same issue.


Because these connections aid Google’s understanding of your content. Consider and design a good link-building strategy that focuses on connections that establish you as an authority in your sector, and you will reap the rewards.

Internal linkages, on the other hand, should not be overlooked. They’re equally as crucial as backlinks when it comes to proving a thematic relationship between two sites. 

Putting Together a Semantic Search Strategy

Semantic features are being added to search engines to improve their capacity to grasp user intent.

This isn’t about to change anytime soon.

On the one hand, keeping up with ever-changing algorithms necessitates ongoing optimization work. On the other hand, it makes consumers’ lives easier. You can better address the questions consumers are looking for by ensuring that your content strategy involves generating material that covers all sorts of intent. 

Find out what your audience is looking for right now.

With Webinomy’s keyword intent analysis, you can find out what people are looking for.

ADS illustration

Semantic Search is the process of using natural language processing to identify content that is relevant to a given search query. This can be used in many different ways, but one of the most common uses for Semantic Search is in recruiting. Reference: semantic search in recruiting.

Frequently Asked Questions

What is semantic SEO search?

A: Semantic SEO is a technique that uses semantics as the source of ranking for search results. It also makes use of metadata and other data from within web pages to help rank those peoples content higher in searches, just like how Google does it now.

What is semantic search and why is it important?

A: Semantic search allows a user to understand what the meaning behind a word is. This will allow for better understanding when using terms in speech and writing. It becomes much easier to add new words to an already existing language, as there is no need for lengthy research into how it should be used or if it fits any rules that have been set out before hand.

Why is semantic SEO important?

A: Semantic SEO is important because it makes your content more readable by presenting information in a way thats already familiar to the internet, rather than trying to teach it something new.

Related Tags

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