Introduction

Semantic search is a search technique where a search query aims to determine the intent and contextual meaning of the words a person is using for search instead of simply matching keywords to pages.

Semantic search improves search accuracy by understanding a searcher’s intent through contextual meaning. 

Using contextual meaning, synonyms, and natural language processing, semantic search provides more interactive search results by transforming structured and unstructured data into an intuitive and responsive database. 

Semantic search is about an enhanced understanding of user intent, the ability to extract answers, and delivers more accurate and relevant results.

Once we type in a keyword, we’re now searching for the meaning of that keyword. Also, in addition, we’re searching for the words related to that keyword. 

In Google, the words related to “landlord” are like “apartment” and “housing”. 

Basis of Semantic Search

The two main factors that form the basis of  semantic search are:

• Search Intent of user –  Search intent defines the purpose of performing a query on a search engine. It is related to what a user is trying to achieve. Search intent could be to buy, learn, or find something. By understanding  the intent of users, search engines can provide more relevant and accurate  results.

• Semantic meaning of search query – Semantics is about meaning and relationships between words. In search, semantics connects the relationships between a search query, the words and phrases related to it, and content on webpages. By using semantics, search engines can display results that are more closely related to the context of the search query.

Need of Semantic Search

From an engine’s perspective, semantic search is about more data, less spam, a deeper understanding of user intent, and more natural language search.

Understanding all of these about the search queries maximizes the possibility of users getting the best search experience possible.

Semantic Search has the main goal: making it easy for your users to find what they’re looking for. 

So If they make a typo on the search bar, the item they requested still shows up. If they look up “blue”, all blue items will show up.

They shouldn’t get stressed while searching for an item. It should be seamless. 

Importance of Semantic Search for Businesses

Understanding Semantic Search is essential in order to get a maximum amount of traffic and conversions. 

Giving importance to the digital experience you provide to your users garners trust. They remember the ease you provided to shop on your site and think about coming back. 

Therefore driving traffic to your site is only part of the picture. The more important task is to make your digital presence as seamless and attractive as possible.

One way to build this trust, specifically for businesses with generally larger product catalogs, is by creating smart search (semantic search) on the platform itself. 

So the more relevant and understanding user searches are, the better your conversion rates will be. 

Benefits

Semantic search will help people find what they want much faster than ever before. The process relies on the power of search engines to interpret and understand complex data. 

It can also increase your site’s visibility on search engine results pages. Additionally, it enhances content quality, helps you leverage keywords, and improves your SEO efforts. 

When you use semantic search, a machine does the heavy lifting, searching for phrases and words that would best describe your website. Your product descriptions, product descriptions with customer reviews, email subject lines, and other types of textual content are transformed and given a richer meaning.

Since semantic search takes into consideration user intent and user data. The best result pages aren’t the ones that just contain lots of matching keywords, a well-crafted title tag, etc, but the one that aligns with the user’s intent. 

If we search for “lawn mower parts”. Google will realize that most users weren’t just looking for some hard-to-find part for their lawnmower. Instead, they want to get their lawnmower repaired, preferably by a professional who knows what part to order and how to order it.

Based on the aggregate data of millions of searches, Google’s machine-learning algorithm has learned to interpret what users really want. Search engines gather enormous amounts of data for every query.

As semantic search will evolve, we can think of even more accurate and relevant search results.

Semantic Search in Google

In 2012, Google brought Knowledge Graph which was the first step in developing the importance of entities and context over strings of keywords. 

Later in 2013, Google’s Hummingbird update is actually the beginning of the semantic search era.

Hummingbird makes sure that pages matching the meaning perform better on SERP, rather than pages matching just some keywords. This implies that pages that match searcher context and intent well will rank better than pages that repeat only keywords.

In 2015, Google launched RankBrain, a machine learning system that’s a ranking factor as well as a smart query analysis based on Artificial Intelligence.

RankBrain, like Hummingbird, tries to get user intent behind queries. The key difference between them is that RankBrain is based on machine learning.

RankBrain learns, analyzes the best-performing search results, and looks for similarities between the pages that users find relevant.

Therefore, RankBrain may find a page to be a “great response” to a query even if it doesn’t have exact keywords from the query.

Needs to be Done

So what needs to be done about it?

Just follow the below-mentioned points :

1. Don’t worry about exact keywords. Keywords still matter, but don’t worry too much about them and stop stuffing your content with keywords. As long as you have focused content you are fine.

2. Create high quality content with a clear focus. Since search engines now are made to identify the meaning of your content, every piece of content that you create should be focused around a single topic with clear meaning.

3. Use structured data markup. Data markup will help in improving your page SEO in the era of semantic search.

4. Focus on long tail keywords. Long tail keywords are still useful. Make sure to optimize your content for the long tail keywords.

Conclusion

Semantic search is often associated with big data and structured data retrieval. It is important to note that semantic search is in some ways more advanced than traditional search methods. 

As Google and other search engines collect more and more information, traditional search becomes increasingly complex.

In fact, by 2020, big data is projected to make up 98% of the world’s digital information, while semantic search will generate 80% of search results. 

The basic premise of semantic search is providing relevant results to users. It is a logical patterned approach that can be applied to any facet of the business, such as an online customer shopping cart, where you can search your website for a specific product or lead you into a discussion of the various benefits, costs, and purchasing options. 

So strive to give your user the best experience possible because SEO is basically user experience.

The better the user’s experience, the better will be your website performance in the search engines. This is very much true in the age of semantic search.