Do you know that you can use Semantic Search to improve your search accuracy by understanding the intent of the searcher through contextual meaning?

SEO Specialists tend to spend a lot of time trying to get Google and search engines on their side, to see the excellence in their content, its integrity, and organic strategies.

Moreover, they spend time treating Google and other search engines as a metaphorical friend that sometimes loses sight of the overarching picture.

Algorithms tend to solve a number of problems, however, having one that matches the conversational level of humans presents a huge challenge.

It is important to note that since the beginning of Google, it has been pushing search results into the realm of natural conversation.

And a huge component of its strategy has been categorized under the umbrella of semantic search and machine learning algorithms.

Thus, when it comes to showing up on Google, what exactly take to rank #1?

Many of the following elements tend to come back to the idea of a simple conversation.

How? Keep on reading.

Semantic Search

Semantic search is how search engines tend to use meaning and context to understand search queries and provide results that match intent.

Moreover, it is how search engines tend to understand human language.

This also means Google does not need an exact match keyword to deliver the results of what you are searching for.

So if you search for “I need guns – lots of guns” Google can tell you are looking for a certain result and shows the following:

In the same way, Google can serve the correct results if you misspell a keyword.

Consider the following example:

It is also the reason you see nearby restaurants when you search for “restaurants near me”.

Keep on reading as we learn more about semantic search’s working, the evolution of Google’s Algorithm, and how you can optimize your content for semantic search.

Let’s dive into its history first.

History of Semantic Search

To understand semantics, the Google Algorithm has evolved and it started with the Knowledge Graph which debuted in 2012.

Knowledge Graph, 2012

This is the database of people, places, and things or entities in Google and how they are connected.

There are about 500 billion entities.

It is important to note that Google describes the relationship between entities as “things, not strings”.

In simple words, when you enter a “string” into the search bar, Google understands that string as a “thing”.

It tends to have meaning and context. And Google understands that it shares a relationship with other “things”.

Moreover, Google tends to show information from Knowledge Graph through knowledge panels that tend to appear on the search engine results page, SERP.

Hummingbird, 2013

In 2013, Hummingbird prioritized natural language processing, NLP.

That is the ability of the machine to read, understand, and derive meaning from human language.

This update occurred are the time people began making searches with their voices.

Thus, it was important to keep up and provide them with accurate results.

Together with Knowledge Graph, Hummingbird improved on NLP which also laid the groundwork for semantic search.

Moreover, Google adopted NLP to better match pages to their meaning which allowed Google to understand more conversational searches.

RankBrain, 2015

This is a system that helps Google to understand the intent of the searches of the users.

It is built upon Hummingbird by helping Google understand search queries that contain words or phrases that it did not know.

Moreover, RankBrain is a machine-learning language.

This means that it continues to learn and analyze based on best-performing search results.

It is important to note that this is also a ranking factor.

However, there is no sure way to optimize for it.

The best you can do is to provide as much information about a page as possible and let Google do the rest.

BERT, 2019

BERT Is a language processing technique that Google implemented in 2019.

It stands for Bidirectional Encoder Representations from Transformers.

In simple terms, Google doubled down to understand conversational search.

Moreover, BERT also considers the full context of a keyword, including the words that come before and after it.

Consider the example below:

 

In this example, Google shows pre- and post-BERT examples of how it interprets the keyword “2019 brazil travelers to the USA need a visa”.

The word “to” in this keyword is especially important as it implies that a Brazilian traveling to the U.S.

In the past, Google’s algorithm did not understand the connection.

After BERT, it is better able to understand what the searcher means.

MUM, 2021

The Mulittaks Unified Model, the MUM, is a language processing framework that Google implemented in 2021.

According to Google, it is 1,000 times more powerful than BERT.

It is important to note that MUM understands images, videos, and audio files.

Moreover, it is also multilingual, so it can find information related to your search query even when the information is in a different language.

Working of Semantic Search

Google tends to use machine language to figure out what people are looking for depending on context and search intent.

Search intent is why a user is looking for something.

Are they comparing products? Trying to buy something?

Google with serve different results depending on the intent.

However, how does Google know how to do this?

Semantics.

In other words, the ability to understand the meaning of keywords and their relationship to other keywords.

This is what makes search results appear more accurate and more relevant to the searcher.

Consider an example where you search for “wedding anniversary”.

Google is able to make assumptions about the content you may want, so it will show related pages about wedding anniversary cards and gifts.

Moreover, the factors that influence the semantic search can vary for the same keyword, and a number of things also influence them, including:

• your location
• your search history
• current news and events
• trends

All of these factors provide context to semantic search. For instance, you search for the soccer player Cristiano Ronaldo.

When writing this article, before the FIFA World Cup, the results for Ronaldo were mostly about his career.

However, after World Cup, you can see his latest stats, achievements, and game highlights.

Optimizing your Content for Semantic Search

To optimize your content for semantic search, you will need to put the user first.

The following are a few ways to do that:

• better understand the search intent of the user
• focus on topics rather than keywords
• use the structured data to enhance search results
• connect related content with internal links
• use semantic HTML

In short, you will need to optimize your content for semantic search which means creating content that does not match keywords.

However, it also reflects the way users write and speak.

The following are the five ways you can do that:

1# Understand and Optimize for Search Intent

Search Intent refers to the main goal of the user when they type something into Google.

This ties into semantic search as Google tries to close the gap between what the user is typing and what they actually want to know.

To work with algorithms, SEOs will need to prioritize user intent in their strategy.

So when you create content, your goal should be to match what the user is looking for and also anticipate their follow-up questions.

For instance, if someone searches for ‘restaurants near me”, then they are also looking for dine-in and takeaway services.

Keywords can fall under four search intent categories:

• informational, i.e. they want to learn about a topic
• navigational, i.e. they are looking for something specific
• commercial, i.e. they are investigating products, services, or brands
• transactions, i.e. they intend to make a purchase

It is important to note that understanding the category of intent can help you shape your content.

Moreover, you can use keyword intent using various Semrush tools.

A good way to approach this is to create content pillars.

You will need to begin with a broad topic, then come up with content that addresses more specific subtopics.

Make sure to link these pieces of content together so Google can tell they are related and better understand their relationship.

Moreover, this will help you create content that meets and anticipates the needs of your user, which is also great for optimizing the semantic search.

Learn more about Content Writing here.

2# Focus on Topics, not Keywords

As Google is now attempting to process information like a human will, it is important to focus on border topics rather than specific keywords.

This is because people search more conversationally today.

And Google does its best to match these queries with what it thinks is the best answer.

Moreover, standard keyword research is important, however, creating quality content is more than just including keywords at certain times.

If you cover one topic exhaustively, chances are that your page will rank for a variety of related long-tail keywords, i.e. more specific keywords that have lower search volume but high click-through rate.

Also, you can find semantically related keywords with the SEO content template in Semrush.

It tends to analyze content from the top competitors, then gives you a list of relevant keywords that appear on their pages.

It is important that you take time to understand how keywords fit together to form topics, while the goal is to understand user intent rather than matching a specific keyword.

Keep in mind that the goal is not to rank for every single sub-topic.

It is actually about finding sub-topics all your competitors are covering in their articles.

3# Use Structured Data

Structured data is an organized set of data that helps search engines understand your content.

Moreover, this data markup also increases your chances of triggering rich snippets, search results that display extra information like ratings or reviews like the following:

Markup, i.e. how you write the code is important as it will help Google to understand how to categorize your content.

And this is how Google gets the data to rich snippets.

The following is how you can make the most of structured data or schema, i.e. the standardized way of creating structured data:

• visit schema.org to browse a wide range of schema markup templates that are understood by all major search engines
• use Google’s structured markup helper to assist in marking up your content
• Merkle’s Schema Markup Generator is another great option
• use Google’s Rich Results Test to check that your markup is correct

You can also use the Site Audit Tool of Semrush to see how structured data markup has been implemented on your site.

4# Build Links that Shows Relevance

It is important to note that both internal links and backlinks show topical relevance and help Google Understand your content better.

It can take time and patience to secure external links.

Moreover, executing the right internal link-building strategy takes far less effort on the other hand, as you have the power to make changes on your own.

Internal links can be just as important as backlinks from other sites.

Let’s consider the example of content pillars again.

Your main pillar should link to related sub-topics. Those sub-topics may also have another layer of topics like the following:

 

Adding internal links to these pages will show Google that your pages are related.

In ideal cases, if you comprehensively cover a broad topic, your site will have the answer to the questions of users, when they make a related semantic search.

5# Use Semantic HTML

Semantic HTML consists of elements that clearly describe the meaning to search engines.

For instance, you can write text in HTML that looks like a heading on your page.

However, unless you tag it with a specific heading HTML code, Google may not know it is actually a heading.

Moreover, non-semantic HTML uses unspecified <div> and <span> tags to create content.

But on the semantic HTML, there are clearly defined tags that organize the content in a way that communicates their meaning to Google.

Also, semantic HTML stages include <header>, <footer>, or <article>.

Header tags show a header, footer tags show a footer, and so on.