Semantic Search
What is semantic search?
Let's first examine semantic search in more detail.
Search engines utilise semantic search as a method to try to decipher your search query's context and intent in order to provide you with results that are relevant to your search.
Semantic search, in other words, seeks to understand why you are searching for these specific terms and what you plan to do with the information you find.
Note that semantic search should not be confused with Latent Semantic Indexing (LSI), often known as semantically linked terms. Though LSIs can help by supplying context for your content (which subsequently aids in matching search intent), semantic search is much more than that.
If we're looking at semantic search holistically, here are the factors that guide how it works:
1. A user's search intent.
The phrase "search intent" describes the rationale behind a search (or, to put it another way, the reason you Google something). You most frequently wish to acquire, discover, or understand something.
For instance, since the goal is rather broad, if I search for "content marketing," Google returns results that are related to the definition of content marketing:
However, if I instead search "How do I get started with content marketing", Google does not provide definitions of content marketing, because my intent is different:
The key lesson here is that you must carefully consider search intent when selecting keywords and developing content. This is true for all content marketers and SEOs. Even if your material is highly ranked, if it doesn't fit user search intent, users will abandon the page, which is undoubtedly bad for conversions.
2. search keywords' semantic meaning.
The term "semantic search" was developed from semantics, which is the study of how words and phrases relate to one another and how they mean different things in different circumstances. Semantics in search relates to the relationship between a search query, words associated with it, and the information on website pages.
In order to present results that are relevant to the context, search engines need to be able to interpret the meaning of the search queries beyond a literal translation.
For instance, if you type in "wedding clothes," you might also find the phrases "wedding," "cake," "bride," and "dream." If you search for "dresses," similar terms like "lovely" and "knee-length" may come up.
The essential message: When selecting the keywords for your content, I suggest grouping related keywords together to form "keyword clusters." Because they guarantee that your material covers a wider area of the topic, these clusters immediately link to semantic search. A wider range also means more keyword ranks per page.
Other Semantic Search-Related Factors
These elements also have an impact on semantic search, even if the first two are the primary ones:
Featured snippets: Featured snippets are based on giving the searcher the most succinct and beneficial response.
Rich results: In the example in the following section, you'll see how these impact semantic search across material like photographs.
Voice search: Voice search inquiries tend to be highly straightforward and include natural language, lengthier phrases, and question words, which helps search engines digest the results.
The RankBrain algorithm, which is based on machine learning, aids Google in comprehending the first-instance set that satisfies the query as well as associated ideas, expressions, and synonyms.
Hummingbird: The goal of the Hummingbird algorithm update was to deliver better results for searches involving specific persons, conversational language, and voice searches.
Semantic Search Examples
Here are a few specific examples to help you understand how semantic search functions.
Because more people are searching for places to order rather than cook their own, even if I just type "pizza" into Google, I'll probably still receive local search results. However, because of the personalisation feature, if my search history is full of pizza recipes, my results for "pizza" will probably also be recipes.
In essence, semantic search influences all of the results a person sees. Therefore, a website will only appear as a result for a certain keyword if the material on the page corresponds to the context of the search. Results for "make a pizza" will include ingredients, preparation time, and other information, while those for "order a pizza" will include places, times, and other information.
It's fascinating to see that search results are impacted by recent news. Corona was a beer brand before the pandemic, but since COVID-19 spread, the majority of results from a search for "corona" are now related to the virus.
The other illustration is Jeff Bezos. You can get general information, a knowledge graph, and recent news by searching for his name.
How Google Uses Semantic Search?
Giving users the best search experience is Google's main goal. They employ semantic search in order to:
Determine low-quality content and exclude it.
learn more about users' search intentions. For instance, is the user trying to find a specific page to navigate to? Or are they want to learn more about a subject?
Create responses to the questions.
Determine what relevant data to pull from the Semantic Web
Instead of using keywords, think of websites and pages in terms of subjects.
Integrate Google technologies like Knowledge Graph, Hummingbird, RankBrain, and BERT where semantic search is important.
Format the data correctly so that it appears in the search results.
When the search purpose is unclear, connect with inquiries that have every meaning that could be feasible.
How to Use the Power of Semantic Search to Your Advantage
Simply said, your material won't appear in search results if it doesn't have a semantic relationship with the search query. This can be easily resolved by tailoring your material to the search phrase and using the appropriate method.
I advise you to try to accomplish the following in order to be on the right side of SEO when it comes to semantic search:
Focus on topics, not keywords.
Be sure to comprehend the user's search intent. Are they looking to buy? to navigate to a certain brand page? to educate?
Increase relevance by using links (both internal and external).
Schema markup is used.
Use semantic HTML elements such as "header," "footer," and "article."
