A Guide to Semantic Search Technology (+ Examples)

In the vast world of online shopping, finding the right products amidst countless options can be a daunting task. 

Thankfully, semantic search is transforming the way we navigate eCommerce platforms, making the search process more efficient and personalized.

Semantic search is a groundbreaking technology that goes beyond traditional keyword matching. 

It understands the meaning behind user queries, delivers tailored product recommendations, and enables a more intuitive shopping experience.

In this article, we’ll explore the impact of semantic search on eCommerce. 

We’ll uncover how it enhances product discovery, personalizes recommendations, and streamlines the online shopping journey for both consumers and retailers.

Get ready to dive into the world of semantic product search and discover how this game-changing technology is reshaping eCommerce, making it easier than ever to find that perfect product.

What is semantic search?

what-is-semantic-search

Semantic search is a type of AI-powered search that focuses on the meaning and context of your query, rather than just matching specific keywords.

When you search using traditional methods like lexical search, the search engine looks for web pages that have the exact words you entered. It’s like a simple word-matching game. 

But with semantic search, it goes a step further and tries to understand what you’re actually looking for.

For example, let’s say you want to find information about the tallest mountain in the world. In traditional search, you might type “tallest mountain in the world” and hope for the best. 

But with semantic product search, the search engine goes beyond those words. 

It recognizes that you’re interested in mountains and their heights, so it brings up relevant information about Mount Everest, which is actually the tallest mountain.

Semantic search uses things like natural language processing and artificial intelligence to understand your query in a more human-like way. 

It looks at the context, relationships between words, and the overall meaning of what you’re asking. 

This allows it to provide more accurate and helpful results.

Semantic Search Examples

Natural Language Question Answering

semantic-search

This type of semantic search is like talking to a smart search engine that understands your questions in a more human-like way. 

Instead of just matching specific words, it tries to grasp the meaning behind your question. 

So when you ask something like, “Who won the Grammy for album of the year in 2021?” it doesn’t just give you web pages containing those words—it actually figures out the answer and provides it to you directly.

Entity-based Semantic Search

semantic-search

Imagine you’re searching for something specific, like information about a famous person or a particular place. 

With entity-based semantic search, the semantic search engine recognizes and understands these entities. 

So if you search for “Paintings by Vincent van Gogh,” it knows you’re referring to the painter Van Gogh and presents you with a list of his popular paintings. 

It helps you find information related to specific people, locations, or objects you’re interested in.

Concept-based Semantic Search

semantic-search

Sometimes you might want search results that match the overall idea or concept you have in mind, rather than specific words or phrases. 

Concept-based semantic search does just that. 

For example, if you’re looking for healthy dessert recipes, instead of simply searching for the exact words, it understands that you’re interested in desserts that are good for your health. 

It then provides you with a variety of dessert recipes that meet those criteria, giving you options that align with your concept of “healthy desserts.”

How does semantic searching work?

semantic-search

Semantic searching plays a crucial role in enhancing the online shopping experience. 

Here’s how it works in eCommerce:

1. Understands Product Intent

Semantic search aims to understand the intent behind user queries related to products. 

For example, if a user searches for “comfortable running shoes,” semantic search recognizes the user’s desire for comfortable athletic footwear and displays relevant options from various brands.

2. Grasps Product Relationships

Semantic search goes beyond exact keyword matches and understands the relationships between products.

For instance, if a user searches for “smartphone accessories,” semantic search recognizes that this query is related to various types of accessories like cases, chargers, screen protectors, and provides a comprehensive range of relevant options.

3. Recognizes Product Attributes

Semantic search can recognize and process specific product attributes mentioned in a query. 

For example, if a user searches for “black leather purse,” semantic product search understands the desired color (black) and material (leather) to display relevant black leather purse options.

4. Personalizes Product Recommendations

Semantic search leverages user preferences and browsing history to provide personalized product recommendations

For instance, if a user frequently searches for organic skincare products, semantic product search learns this preference and suggests natural skincare brands, aligning with the user’s interests.

5. Improves Semantic Product Search Accuracy

Semantic search helps improve the accuracy of product searches by understanding and correcting spelling errors or typos related to product names. 

For example, if a user types “iphon” instead of “iPhone,” semantic product search recognizes the intended product and displays relevant iPhone options.

User Benefits of Semantic Search Technology

semantic-search

1. Typo Correction

Imagine you’re searching for a “MacBook Pro” laptop, but you accidentally type “MackBook Pro.” 

With semantic search, it recognizes the typo and understands your intention, displaying the correct “MacBook Pro” options.

2. Personalized Recommendations

Let’s say you frequently shop for home decor items. Semantic search learns your preferences and past purchases. 

When you search for “table lamps,” it will provide personalized recommendations based on your preferred styles, colors, or brands.

3. Trending Product Insights

If you’re interested in finding popular kitchen gadgets, you might search for “top-rated kitchen appliances.” 

Semantic product search uses AI to analyze search trends and user behavior, presenting insights into the latest popular appliances like air fryers, smart coffee makers, or instant pots.

4. Voice Search

Picture yourself using voice search to find a new pair of headphones. 

You say, “Find me wireless headphones with noise cancellation.” 

Semantic search processes your voice command, understands your requirements, and displays options for wireless headphones known for their noise-canceling capabilities.

How to Implement a Semantic Search Engine into Your Business

Implementing a semantic search engine into your business can revolutionize the search experience for your customers. 

With Doofinder, you have an easy solution that incorporates all the essential features mentioned in this article.

Doofinder provides advanced search capabilities such as natural language processing, personalized recommendations, and seamless integration with your existing systems. 

It empowers your eCommerce site to deliver accurate and relevant search results, enhancing user satisfaction and engagement.

To get started, take advantage of Doofinder’s 30-day free trial. Test out all the features and experience firsthand how they can benefit your website. 

If you need assistance in implementing Doofinder on your eCommerce site, request a free demo with one of our eCommerce search specialists. 

They will guide you through the process and help you maximize the potential of the tool.

Don’t miss out on the opportunity to elevate your search capabilities and provide your customers with an exceptional shopping experience. 

Try Doofinder today and discover the power of semantic search for your business.

FREE EBOOKS