What is semantic search?
Semantic search describes a search engine’s attempt to yield the most accurate results possible for search queries by getting a deeper understanding of contextual meaning based on query context, search intent, and the relationship between words. Simply put, semantic search allows users to search with meaning. Consequently, it helps deliver the best-performing search results quickly.
Here’s an example
For a typical keyword search, a customer may write keywords like ‘sweater’ in the search bar to find a sweater. However, the semantic search will better serve queries like ‘warm clothing’ or ‘how can I keep my body warm in the winter?’.
How semantic search works
A semantic search engine applies user search intent and the meaning (or semantics) of words and phrases to find the right content. It goes beyond keyword matching by using information that might not be present immediately in the text (the keywords themselves) but is closely tied to what the searcher wants.
Difference between keyword search and semantic search
A keyword search retrieves all the documents from the database which have a specific search term present in the query. Unlike keyword search, the semantic search takes into account the meaning of the words according to their context. Let’s compare the two side by side.
Keyword search
- Synonyms could be neglected during the search.
- The user needs to carefully pick the keywords for search.
- The information retrieved depends on keywords and page ranking algorithms that can generate spam results.
Semantic search
- As it incorporates the meaning of words, semantic search technology comprehends synonyms well.
- The search query is automatically enriched by latent encoding.
- The information retrieved is independent of keywords and page rank algorithms that improve search accuracy, yielding exact results.
Gain momentum with us!
The Momentum scores for E‑Commerce Search display each product’s Momentum score on the vertical axis and Satisfaction score on the horizontal axis, based on G2’s algorithms. Products within the shaded area have a top 25% Momentum Grid® score.
G2’s E-Commerce Search Relationship Index
Discover the factors influencing product relationships. See the chart below for insights on ease of business, support quality, and recommendations from our customers.
- Ease of business
- Likely to recommend
- Quality of support
- Other factors
-
Ease of business: 1.75
-
Likely to recommend: 2.78
-
Quality of support: 2.79
-
Other factors: 1.67
-
Ease of business: 1.88
-
Likely to recommend: 2.9
-
Quality of support: 2.79
-
Other factors: 1.31
-
Ease of business: 1.78
-
Likely to recommend: 2.69
-
Quality of support: 2.7
-
Other factors: 1.63
-
Ease of business: 1.92
-
Likely to recommend: 2.64
-
Quality of support: 2.68
-
Other factors: 1.45
-
Ease of business: 1.75
-
Likely to recommend: 2.75
-
Quality of support: 2.77
-
Other factors: 0.96
Difference between lexical search and semantic search
Unlike semantic search, a lexical search engine looks for literal matches of the query words or variants of them, without understanding the overall meaning of the query.
Most searches on the web do not have a lexical intent. This is why we need semantic search, a method that takes our query and gives us back the result that matches our intent. For instance, when we search for ‘shoe store near me,’ we want the closest shoe store to our physical location, and not a shoe store named ‘Near Me’ or in a town named ‘Near Me.’
The technology behind semantic search
Semantic search applies user intent, context, and conceptual meanings to match a user query to the corresponding content. It uses vector search, artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to return results that aim to match a user’s query, even when there are no word matches.
AI and ML use trial-and-error patterns and data to improve a searcher’s experience, whereas NLP allows your search box to develop a deeper understanding of your products.
Why semantic search matters in e-commerce
The benefits of semantic search are no longer restricted to search engines like Google. It also offers a number of benefits to e-commerce websites.
Improve customer experience
About 68% of customers would not return to a website that provides a poor search experience. If customers can’t find the products they need, they’ll leave your site and find them elsewhere. Semantic search helps improve customer experience by delivering accurate results quickly.
Increase user satisfaction
Semantic search technologies boost user satisfaction by providing more interactive, dialogue-based, or conversational search results. For example, semantic search makes it simple to distinguish between searching for crane; the bird, and crane; the machinery used to lift heavy objects.
Enhance business intelligence
A semantic model provides structured data for business intelligence. For example, e-commerce stores can use semantic metadata to enrich their content pillars. Semantic search broadens the search area and makes it easier to ‘extract out’ information from unstructured content, which is almost impossible with keyword search.
Develop strong customer relationships
In semantic search techniques, your website search engine no longer depends on recognizing keywords and returning exact word matches. Instead, semantic search helps companies grow customer relationships that matter by conversing in the customer’s manner of speech.
Deliver personalized results
Implementing semantic search also helps personalize the customer experience. For instance, if someone has shown interest in men’s clothing and searches for generic terms like ‘running shoes’ or ‘active wear’, a semantic search engine will return relevant results based on search history and intent.
Get started with Luigi’s Box
Book a demo call to see how Luigi’s Box semantic search can help improve user satisfaction, simplify customer journey, and yield better conversions.
How to implement semantic search
Integrating Luigi’s Box is easy. All you have to do is insert a script we generate with GTM, send us product feeds, and let our integration team launch your search.
If you run your e-commerce store on one of our supported platforms, we can set up data connectors, so there’s no development cost on your side.
Learn MoreWe integrate with any platform
Luigi’s Box can be used with any e-commerce platform, especially Shopify.
Our AI Search & Discovery Shopify app offers a free plan and a 30-day free trial. It helps you personalize your website content to customers’ intent to achieve better search results relevance, thereby reducing wasteful shopping time.
Try for FreeLuigi’s Box Search overview
Schedule a demo call
Take Luigi’s Box on a test drive with a free demo call. Book a call today and see our semantic search tool live in action.
Book a Demo CallFrequently asked questions
What is semantic search?
A semantic search engine tries to understand the intent of the user and the contextual meaning of a query to deliver results that match what users are looking for.
Semantic search technology knows the different ways a concept can be expressed and in what context a term is used. It uses this knowledge to help you find more relevant content faster.
Where is semantic search used?
People use different ways, languages, and tones to look for a product or content. Moreover, search queries can be ambiguous in nature. Semantic search is used to understand the relationships between words. It works by drawing links between words and phrases.
This way, it is able to interpret digital content in a more ‘human’ language. When that’s achieved, it can offer the searcher more personalized and accurate search results. Today, many industries are using semantic search, such as e-commerce, entertainment, streaming media, and more.
What are the best providers of semantic search?
Some of the most popular semantic search providers include:
1. Luigi’s Box
Luigi’s Box leverages semantic search to improve customers’ shopping experience. It tracks their intent and offers them relevant search results based on previous interactions. The Search feature expects the user to make mistakes, typos, and use incorrect or slang terms or various synonyms that are not even grammatically correct during the search.
2. Algolia
Algolia Search offers a number of features for e-commerce businesses, such as search autocomplete, typo tolerance, synonyms management, filters, and facets, to help customers quickly find relevant products on your site. Algolia’s search engine is language-agnostic. It supports alphabet-based and symbol-based languages (such as Chinese, Japanese, or Korean).
3. AddSearch Site Search
AddSearch Site Search allows you to create quick search results with the ability to customize result fields and boost search availability. The user dashboard lets you control all your inventory search. You can also create smart searches. The platform also provides a search relevancy toolkit, which includes pinned results, promotions, and synonyms.
Why is semantic search important?
E-commerce site search engines are continuously striving to satisfy the searcher with the most precise results. This is where semantic search can help. It matches the searcher’s intent with the contextual meaning of content to offer the most accurate and relevant results.
Semantic search makes it possible for search engines to distinguish between different things, such as people and places. It allows you to interpret search intent by looking at factors like user location, search history, and spelling variations.
For example, suppose a user searches for the term ‘cancer’. A keyword or lexical search will fetch all documents in which cancer is mentioned as the disease as well as the species (such as Cancer borealis or Cancer pagurus). However, in a semantic search, the user chooses the search space as whether it is to be searched as a disease or a species.