This guide explains the difference between semantic search vs keyword search.
As you’ll discover below, keyword search and semantic search have separate purposes for search engines and the end user. And knowing the difference between semantic search and keyword search for SEO will help you understand how they are beneficial for different applications.
There’s also a section with additional resources that explain more about the fundamentals of semantic search and keywords to help you create the most effective search engine optimization strategy.
Table of Contents
What Is the Difference Between Semantic Search and Keyword Search?
The main difference between semantic search and keyword search is that semantic search focuses on the context and intent behind a search term while a keyword search only matches search records based on the keywords used in the search.
Semantic Search vs Keyword Search
This comparison table shows the difference between semantic search and keyword search. After this table, we’ll look into both types of searches in more detail.
|Parameter||Semantic Search||Keyword Search|
|Definition||A data-searching method that denotes the meaning of a search query.||A data-searching method that uses lexical search to find literal matches of the query words.|
|Primary Purpose||To generate accurate search results based on the meaning and intent of the search query.||To deliver search records that specifically match the words used in the query.|
Improved search results, Better snippets of information, and Positive user experience
Fast and efficient, good for finding specific information, and eliminates guesswork for the algorithm
What Is Semantic Search?
Semantic search is a data-searching method that denotes the meaning of a search query by focusing on the context and intent behind the search. A semantic search goes beyond just matching documents on the web that contain the same keywords in a search query.
Semantic Search Details
The primary purpose of semantic search is to generate accurate search results based on the meaning and intent of the search query. This leads to improved search results, better snippets of information, and a positive user experience.
Google is a prime example of a semantic search engine. It uses a set of semantic algorithms to search through its index database and return the most relevant results to its users based on the contextual meaning of a search query. With a semantic search engine like Google, you cannot easily manipulate the rankings of a web page by just stuffing the content with more exact match keywords.
Improved Search Results
Semantic search provides better search results for the user because the listings are based on the meaning and intent behind the searcher. Through concept matching and natural language processing, a semantic search engine can deliver more accurate results that meet the contextual meaning of the user.
Better Snippets of Information
In semantic search, the search results return better snippets of information that provide users with a better glimpse of a web page’s content before clicking on a URL. This allows a semantic search engine to extract captions of information that more accurately depict what the user is searching for even if the content doesn’t include the same exact search keywords.
Positive User Experience
As a result of improved search results and better snippets of information, semantic search provides a more positive user experience because it promotes the most semantically relevant results to the top of the list. This means that users can find what they are looking for more quickly and easily on the search engine.
What Is Keyword Search?
Keyword search is a data-searching method that uses lexical search to find literal matches of the query words in search records. If a match is made, then the record will be displayed in the search results.
Adobe Bridge is a prime example of a keyword search engine. It uses lexical search to find and retrieve images, photos, and videos from a database that has been tagged with metadata that includes specific words and phrases that describe the visual content. With a keyword search engine like Bridge, you can easily make any type of content appear in the search results by adding an exact match keyword (or close) variant to the metadata if it’s not applicable.
Keyword Search Details
The primary purpose of a keyword search is to deliver search records that specifically match the words used in the query. Also known as a lexical search, a keyword search engine looks for literal matches (or close variants) of the query words typed by the user without making any effort to understand what the query actually means.
Fast and Efficient
Keyword search allows you to find exact matches for a search query in a large database, which makes this process a very efficient way to search for information. Unlike a semantic search engine that must extract the meaning and intent behind the query, a keyword search engine doesn’t have to use extra computing power to find matching records in the database.
Good for Finding Specific Information
Keyword searches are also good for finding specific names, dates, and other information that is not likely to change. When content includes specific details or is tagged in the metadata with it, those records can be found quickly and easily with a keyword search engine.
Eliminates Guesswork for the Algorithm
Because a keyword search doesn’t need to interpret the contextual meaning of a search query, there is no guesswork that has to be performed by the algorithm. If a document or record doesn’t include the exact match keyword (or close variant), then the content will not be returned to the searcher.
Which Is Better Semantic Search or Keyword Search?
Semantic search is better than keyword search for a public search engine because semantic search is optimized to return more relevant results for the query. Semantic search focuses on extracting the meaning of the query rather than matching the exact words or phrases as a keyword search does.
Additionally, a search engine that only uses a keyword search algorithm can easily be manipulated by keyword stuffing, which is the repeated use of a word or phrase to make it rank higher in the search results.
A semantic search engine like Google, on the other hand, can interpret multiple meanings of a word or phrase regardless if those terms appear on a document in the search database, which provides more relevant results by identifying related concepts that may not be explicitly mentioned in the query or in the content.
Learn More About Semantic Search and Keywords
- Semantic Keyword Research Explained
- Why Are Semantic Keywords Important for SEO?
- How to Find Semantic Keywords
- How to Use Semantic SEO
- Best Semantic SEO Tools
- Best Free LSI Keyword Generators & Research Tools
- Best Keyword Research Tools for SEO
- Free Keyword Research Tools
- Keyword Opportunities
Summary for Semantic Search vs Keyword Search
We hope you enjoyed this guide on semantic search vs keyword search.
As you have discovered, the main difference between semantic search and keyword search is that semantic search focuses on the context and intent behind a search term while a keyword search only matches search records based on the keywords used in the search. Both keyword search and semantic search engines play an important role in various use cases, making each type beneficial for different applications.
The Editorial Staff at SEO Chatter is a team of search engine optimization and digital marketing experts led by Stephen Hockman with more than 15 years of experience in search engine marketing. We publish guides on the fundamentals of SEO for beginner marketers.