Key Takeaways
- What is semantic search? It is a method of retrieving information by matching the meaning and intent of a query, rather than the exact words used.
- Semantic search’s strengths are query intent detection and overall discoverability.
- Keyword search remains valuable for precise terms such as product codes, stock keeping unit (SKU) numbers and brand names.
- Semantic search reduces failed searches caused by synonyms, misspellings and conversational phrasing.
- A hybrid approach, combining both methods, typically delivers the strongest results.
What Is Semantic Search?
Semantic search is an AI-powered search(external link) that can help superpower the way users search for content on your website. As opposed to traditional keyword search, semantic search interprets the meaning behind a query, so users find relevant content even when their wording differs from the content on your website.
In short, semantic search looks at what they are trying to find. If a visitor searches "help paying my power bill", semantic search recognises the intent and connects it to a page titled "Energy hardship assistance", even though the two share no keywords.
Intent Detection and Contextual Matching
Understanding what semantic search is also means understanding its two defining strengths:
- Intent detection: The system recognises synonyms and contextual relationships, even in long, conversational queries.
- Discovery: It surfaces documents that share the underlying concept, rather than only those with matching spelling.
A visitor searching "help paying my power bill" will find a page titled "Energy hardship assistance", because semantic search connects the two ideas. Search platforms, like Elasticsearch, can handle this process behind the scenes so you don’t need to worry about the technical side of things.
How Does Semantic Search Use AI?
Semantic search uses artificial intelligence (AI), specifically machine learning models trained on large amounts of text, to understand how words relate to each other and what people mean when they use them. This field is known as natural language processing (NLP)(external link), and it is what allows semantic search to interpret queries in context. With time these models should keep improving as they are refined with more data, so the understanding behind semantic search continues to get more accurate over time.
How Does Semantic Search Differ from Keyword Search?
The clearest way to answer "what is semantic search?" is to compare it with the method it builds on. Keyword search is likely the search type you have most familiarity with. While it has become the most common type of search found on most websites it does have its limitations.
How Does Keyword Search Work?
Keyword search, also called lexical search, typically relies on an algorithm called BM25 (Best Matching 25)(external link). It scores each document by counting how often the search terms appear, and by how rare those terms are across the whole collection. More matches generally means a higher ranking.
Think of it as the index at the back of a book. If the exact word is listed, you find it quickly. If it is not, you find nothing.
This produces both strengths and weaknesses:
- High precision: Keyword search delivers reliable exact matches for structured terminology, such as product codes, SKU numbers(external link) and exact brand names.
- Context blindness: It struggles with natural language and the wider context of a query, so highly relevant content is frequently missed.
- Synonyms and misspellings: It can struggle to recognise spelling variations or different words with the same meaning. A search for "trainers" may return nothing on a site that only uses "sneakers", and users often abandon the search. In the past, we have built custom functionality into our clients' websites so that they can manually add synonyms to their site search. While this has improved search performance, it is less efficient than semantic search.
What Semantic Search Does Instead
Instead of asking, "Which pages contain these words?", semantic search asks, "Which pages address this need?"
A search for "something comfortable for standing all day at work" illustrates the difference. A keyword system looks for those literal words. A semantic system infers that the user wants supportive footwear and returns relevant products, even if the word "shoes" never appears in the query.
Where keyword search matches spelling, semantic search matches sense. For organisations, this distinction can have a measurable effect on how many visitors find what they came for.
What Are the Benefits of Semantic Search?
From an analytical standpoint, the value of semantic search lies in improved relevance, reduced friction and richer data about user behaviour.
Benefits of Semantic Search
- Greater relevance: Results reflect user intent rather than literal wording.
- Fewer dead ends: Synonyms and misspellings no longer lead to empty results pages, which lowers abandonment.
- Natural language support: Users can search as they speak, which suits mobile and voice-based searching.
- Improved accessibility: Users who cannot find the "right" terminology still reach the right content, supporting a more inclusive experience.
- Stronger insight: Search data reveals the language and intent of your audience, informing content and service decisions.
- Better engagement: When people find answers quickly, they stay longer and are more likely to act.
Examples of Semantic Search
Practical examples show where semantic search can add the most value:
- Retail: A shopper searches for "waterproof jacket for tramping in winter" and receives insulated, weatherproof hiking jackets, even if the product pages never use the word "tramping".
- Government services: A resident searches "help paying my power bill" and is directed to energy hardship support.
- Transport: A commuter searches "why is my bus late?" and sees service alerts and delay notices.
- Internal knowledge bases: A staff member searches "how do I claim back travel costs" and reaches the expenses policy.
Why Hybrid Search Is Often the Best Choice
While there are many benefits to semantic search, it does not make keyword search obsolete. A user may know exactly what they are looking for and so their search term may match exactly with the keywords of a specific page. In this instance a page that is conceptually similar won’t be as relevant. Many modern platforms therefore are starting to combine both methods, using keyword precision for exact terms and semantic understanding for everything else.
Conclusion: Is Semantic Search Right for Your Website?
So, what is semantic search? It is search that prioritises meaning over matching words. It reduces user frustration, surfaces content that would otherwise remain hidden, and gives you clearer insight into what your audience needs.
If you are interested in upgrading your website's search and want to know more about how semantic search works, the team at Somar Digital can help get you started.
Get in touch with Somar Digital today to start the conversation.
