Semantic search is one of the latest concepts shaping the world of SEO, and it’s essential for companies putting together an organic content marketing plan.
Every search engine works towards improving the results it shows to its users. To achieve this, Google and other platforms have to gain a better understanding of how people conduct searches online. This allows every search engine to provide rich results for every search that’s performed.
Search semantics is a key concept that helps Google deliver better results, but it’s also crucial for websites looking to create content that ranks.
In this article, we’ll go over the definition of semantics in the context of search engine optimization (SEO). We’ll also explore how semantics relate to natural language processing (NLP), the searcher’s intent, the process of creating content, and your technical SEO efforts as a whole.
What is Semantic Search?
Before going any further, let’s answer one key question: what is semantic search?
Search engines are constantly looking to improve the results they generate after each search. The most basic aspect of this is delivering the most accurate results based on the user’s search.
However, determining the reason behind a search by its contextual meaning is difficult because languages can be ambiguous.
Semantic search is the practice of attempting to understand the search intent behind each query, beyond the keywords being used in a query. In short, semantic search seeks to determine the user intent by considering context and other variables.
Difference Between Lexical and Semantic Search
Google and other search engines have been veering from lexical queries and are focusing more on semantics. But what’s the difference between lexical and semantic search?
When lexical search queries are performed, only exact keywords and their variants are considered, not the meaning behind them.
Semantic queries, on the other hand, generate more relevant results because they consider the exact meaning behind the phrase. In other words, users see search results that are more closely related to the topic of the search rather than the exact terms in the search query.
How Semantic Search Works
Search engines understand that individual search terms can have several meanings. This is why semantic SEO has become a good strategy to prepare content for the searcher’s intent and send more traffic to a web page.
But how exactly do semantic queries work?
Google’s Knowledge Graph technology, which was introduced back in 2012, laid the foundation for the concept of modern semantics. In short, Knowledge Graphs allowed the search engine to transform “strings” of words into “things” or concepts.
Other major search engines quickly adopted the same concept, changing the way marketers conduct keyword research and design structured data schemes. Additionally, the introduction of voice search queries has fueled the need for improved latent semantic indexing in order to provide better search results.
Importance of Semantics
So, why is there so much focus on semantics? Google, as well as all other major search engines, knows that consumers are constantly looking for the best search experience. But, the exact terms that each user types into the search bar in order to find information varies drastically.
In this context, semantics attempt to breach this gap and help deliver the same content to users conducting the same search, even if the query terms in their search bars are different.
In the past decade, many websites have flooded the internet with low-quality content, using keyword stuffing, over-optimizing content, and exploiting every known ranking factor to get in the top 10 positions.
Semantic search engines like Google are finding ways to filter out this content from their search results. This results in a better search experience for users while driving content craters away from keywords and towards query intent. This results in SEO resources that deliver in terms of technical performance and enhance search results at the same time.
Frequently Asked Questions (FAQs) – Semantic Search
Have questions about semantic product search? Here are common questions about search intent, natural language search, and semantics.
What is Semantic Search in NLP?
Artificial intelligence and machine learning play a major role in voice-based searches. But, semantics also play a major part in this process as this allows NLP tools to determine the search intent based on search history, context, and other variables.
Is Google a Semantic Search Engine?
Yes, Google is a semantic search engine. But this hasn’t always been the same.
Until 2013, Google had difficulties understanding semantics. Before this, if you were to look for “biggest bird on the planet” you’d get the answer to this question. But, if you followed it up with “how big is it,” the results would show sites with these literal words on them.
Now, if you follow the same process, the second search you conduct would be related to the first. This is possible thanks to the advancements in semantics implemented by the search giant.
Where is Semantic Search Used?
Semantics are used in semantic search marketing or SEO. In short, semantics allow search platforms to improve user satisfaction and provide answers based on intent, rather than textual meaning.
Understanding semantic search is also important for marketers looking for the best-ranking keywords. Not only this, but it also gives marketing professionals a better understanding of the elements that each web crawler looks for when parsing a site. Which, in turn, results in a deeper understanding of this ranking factor.
Semantic search technology is in its early stages, and it’s already having a major impact on Google’s algorithm.
The more search platforms understand semantic search, the better results they’ll deliver to people searching for information. In addition to link building, your SEO strategy should also consider the semantic meaning of words and the way you leverage related concepts in your web pages.
Helpful Content: Web Crawling