This post explains what semantic search is, why it’s good for SEO, and how you can use this strategy to better appeal to search engines and improve your search visibility.
What is Semantic Search?
Semantic search refers to the ability of search engines to consider the intent and contextual meaning of search phrases when serving content to users on the web.
At one time, search engines could only analyze the exact phrasing of a search term when matching results with a search query. Now, search algorithms are more sophisticated and incorporate semantic search principles when ranking content.
Semantic Search Principles
The two primary factors that guide semantic search are:
- The search intent of the user. Search intent is the reason why someone performs a query on a search engine. It relates to what the user is trying to accomplish. Search intent could be to learn, find, or buy something. By considering the intent of users, search engines can provide more relevant results (e.g., an answer to a question, a product page, a brand’s website, etc.).
- The semantic meaning of search terms. Semantics is the study of meaning and relationships between words. In search, semantics relates to the relationships between a search query, the words and phrases related to it, and content on webpages. By considering semantics (what the words mean, not just what they are), search engines can display results that are more closely related to the context of the search query.
The History (and Importance) of Semantic Search
To understand the history of semantic search, you need to understand the history of search.
When search engines first started, keywords were the main ranking factor. Usually, a page that repeated the target search term the most times would get top placement on search engine results pages (SERPs).
This system wasn’t great for users or search engines.
This system was easy to manipulate, and resulted in low-quality content that was written for search crawlers instead of users.
For example, to rank for the phrase “content marketing,” a marketer could create a piece of SEO content that simply repeated the phrase over and over. This strategy is called keyword stuffing, and it resulted in a poor user experience and low-quality results.
The old search system also made it difficult for users to find relevant information because search engines couldn’t properly decipher the context and meaning of search queries. They could only analyze and produce exact match results.
For example, a search for “How do I start content marketing” might return results for “How do I start content writing” or something even more irrelevant.
Semantic search benefits both users and search engines, as it resolved these problems.
- It made it more difficult to use black hat SEO to manipulate search results, and it cut down on spam and low-quality content.
- It made search more intuitive, which helps users find results that more closely match what they are looking for.
Other Factors Related to Semantic Search
As search engines continue to refine their algorithms, improve their results, and provide better experiences for users, there are three other factors to consider:
- Featured snippets and rich results
- Hummingbird & RankBrain
- Voice search
Featured Snippets and Rich Results
In 2012, Google introduced Knowledge Graph to help users “discover new information quickly and easily.”
Knowledge Graph leverages semantic search to decipher meaning, which helps users find the information they want as fast as possible. It was also the beginning of Google’s shift towards providing more answers directly on SERPs. Google now displays content from webpages as Knowledge Graph results, rich results, and featured snippets to surface answers faster and more prominently.
Example Knowledge Graph Search Result
Example Rich Search Result
Example Featured Snippet Search Result
Hummingbird and RankBrain
Google is constantly refining its search algorithms to provide a better and better experience for users. Releasing updates and adding ranking factors to its algorithms help make search results even more accurate.
In 2013, Google released the Hummingbird update which placed greater emphasis on natural language queries and the principles of semantic search.
Then in 2015, they launched RankBrain, which started using artificial intelligence to learn and analyze the best-performing search results. Together, Hummingbird and RankBrain moved search further into prioritizing user intent and semantics as ranking factors.
Another factor impacting semantic search is the rise of voice search. As more and more people speak their search queries to virtual assistants like Alexa and Siri, search engines are evolving to recognize the semantic, conversational nature of their searches Click & Tweet! .
Voice searches tend to use more natural language, longer phrases, and more questions. Search engines are relying more on semantic search principles to provide relevant results for these types of searches.
Semantic Search Tutorial: 5 Ways to Optimize Your Content for Semantic SEO
Semantic search is an important ranking factor that is only going to get more influential. As you develop and execute your SEO strategy, use the following best practices to optimize your content for semantic SEO:
- Think about topics, not just keywords
- Match content to search intent
- Include related keywords in your content
- Optimize your content for featured snippets
- Include structured data in your content
Think about topics, not just keywords.
Semantic search has made topics, not just individual keywords, very important. Search engines strive to serve the most valuable and relevant results to users, so content must be more comprehensive and informative than ever before.
In that way, semantic search benefits readers greatly because it has resulted in highly targeted, useful content.
Instead of creating short, shallow pages of content for every variation of a broad search term, consider creating one comprehensive evergreen guide that covers the entire topic. Then use keyword optimization best practices to ensure your content is fully optimized for both search engines and readers.
Match content to search intent.
As you develop content ideas for the SEO keywords you want to target, think about why a user would search for that phrase. Consider what type of keyword it is and what type of search intent it represents.
- Informational keywords: The user is trying to learn something, so they use “know” keywords to look for information and get answers to their questions.
- Navigational keywords: The user is trying to navigate to a specific site or find a specific item, so they use “go” keywords to find the website for a familiar brand or thing.
- Transactional keywords: The user is trying to make a purchase, so they use “do” keywords to find a product to purchase or a page to make a transaction.
Include related keywords in your content.
Serve the “semantics” part of semantic search by adding related or LSI keywords to your content.Serve the “semantics” part of semantic search by adding related or LSI keywords to your content Click To Tweet
LSI keywords, or Latent Semantic Indexing keywords, are phrases that are closely related to your target keyword. They give context to your content and help search engines better understand what your content is about and how it serves audiences. To create content that is optimized for semantic search, find related keywords and use them a few times throughout your content.
Read more: How to Find LSI Keywords: 5 Easy Strategies
Optimize your content for featured snippets.
Search engines like to display rich results that give users the information they want directly on SERPs.
To increase your search visibility, optimize your content for answer boxes and paragraph, list, and table featured snippets Click & Tweet! . Clearly answer questions in your content, target long-tail keywords, and use formatting to make your information an attractive option for featured snippets.
Include structured data in your content.
Another way to help search engines understand the meaning and relevance of your content is through structured data.
Structured data or schema markup is a form of microdata that adds additional context to copy on a webpage. It uses a set of standard data structures that categorize content for search engines. For example, the structured data for a book might tell search engines that “Epic Content Marketing” is the book title, and Joe Pulizzi is the author. This extra information helps search engines rank content, and identify information that can be displayed in rich search results.
Want to learn more about semantic and how it affects your SEO strategy? Read this interview with Andy Crestodina, Co-founder and CMO at Orbit Media: Semantic SEO: How to Change Your Game to Win in Search
Build a Strong Semantic Search Strategy
To be competitive in search, your SEO strategy should account for semantic search.