What is Semantic Search? How Does it Improve Search Accuracy?
The introduction of semantic search has enhanced search accuracy like never before. A few years ago, Search Engine Optimization (SEO) strategists relied solely on keyword research to improve website rankings. Today, while keyword research still fulfills its own set of functions, understanding user intent through semantic search has become a key aspect that every content marketer swears by.
Do you want to learn more about this kind of search, how it works, and why it plays such an integral role in SEO today? Then dive in!
What is Semantic Search?
In simple terms, it is a data-searching technique that seeks to improve search accuracy and derive relevant results by focusing on two aspects—user intent and contextual meaning. It goes beyond just analyzing keywords and attempts to maximize the user’s chance of finding more personalized and accurate results. It uses Machine Learning (ML) techniques and deep learning models to find and deliver contextual data.
How Does Semantic Search Work
A semantic search works by drawing links between words and phrases that users enter on a search engine platform and interpreting this content in a more “human” way. For example, if you ask your friend “What is your favorite book” and follow it up with “Who is it written by?”, your friend would understand that “it” here refers to their favorite book. Similarly, semantic search attempts to understand user queries as a human would. It interprets a search query based on a variety of factors like user search history, location, number of keyword matches, spelling variations, etc.
Where is Semantic Search Used?
This search is most popularly used by search engines like Google to strengthen search query processing. It is used to understand content for data mining and contextual classification for Expertise-Authoritativeness-Trustworthiness (E-A-T) evaluation. Organizations also use it to improve knowledge management services and enhance market visibility. A few other modern applications include:
- Maintaining business directories
- Academic archiving
- Marketing campaigns
- News monitoring and research
- Editing suite platforms
How to Implement Semantic Search
Implementing semantic search effectively requires marketers to match their content with the search term using the right digital strategy. We have compiled six practical ways to help marketers implement semantic search across their digital content strategy:
- Enhance topical length and depth of content
- Optimize for keyword clusters
- Include related terms and synonyms
- Use structured data
- Explore content optimizer tools
- Build topic clusters on the website
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Semantic Search Features
Semantic search can be conducted efficiently when user intent, context, and conceptual meaning match the main user query and reflect relevant results. Even if there are no exact word matches, semantic search uses vector search and ML applications to deliver information that targets the user’s query.
Let’s take a closer look at the two most important elements of semantic search—context and user intent.
Context
It is important to correctly identify the context in which the user query is being made to understand what the user is trying to find. Search engines generally use context on both personal and group levels. The personal level involves the personalization of results based on the user’s previous searches or interactions. At a group level, this technique enables search engines to display results based on how other searchers react to similar queries.
User Intent
Learning about the user’s intent is the basis of semantic search and helps search engines figure out the exact information the user is looking for. Deep learning enhances this process by automatically generating additional features that accurately capture the intent of the query and the characteristics of the webpage.
How Does Semantic Search Impact SEO
In recent times, there have been significant changes in SEO techniques in the context of Google algorithms like Penguin and Panda. Amidst these changes, one thing that has remained pretty much
unchanged is the use of keyword targeting for SEO. But this would often result in keyword stuffing, which means over-utilizing keywords on a webpage.
Today, it has given rise to changes in Google’s algorithm, which now functions by understanding the intent and context of user queries and not just matching keywords. It has rebuilt its focus around creating quality content and, by default, made keyword stuffing obsolete. These are a few ways in which semantic search benefits SEO:
- Helps in ranking long-tail keywords
- Improves the Click-Through Rate (CTRs)
- Generates higher leads
- Drives more sales
ALSO READ: A Comprehensive Guide to Content Marketing in 2022 and Beyond
Semantic Search vs. Keyword Search
We have already seen how this search functions and optimizes search accuracy. But it is important to know how it is different from keyword search. The primary difference here lies in how the matching of the user query and records occurs. Keyword search functions by matching the word-to-word text of the query with records using synonyms, ignoring plurals, eliminating stop words, etc. They may also use Natural Language Processing (NLP) and Natural Language Understanding (NLU) tools to improve retrieval.
However, it matches queries with records based on similar concepts. It increases intelligence by matching queries with concepts rather than keywords. This is done using vector search. Using this intelligence optimizes results more humanly and enables users to find information that is more personalized and relevant to their search.
The principle of this search highlights looking beyond the keywords of a query and finding answers based on matching concepts, logic, and intent. If you want to learn more about semantic search and its functions, check out sales and marketing online courses at Emeritus and grow your prospects in the digital marketing industry.
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