Definition
Semantic search is a way of searching that matches the meaning and intent behind a query instead of just the exact words typed.[1]
At a glance
- Matches meaning, not literal words: a search for laptop bag can find notebook case or carrying sleeve.[2]
- Powered by embeddings: software turns text into numbers that capture meaning, then finds the closest matches.[4]
- Forgiving of vague or messy queries: customers get good results even with typos, slang, or fuzzy wording.
- Often paired with keyword search: exact codes like SKU-2847-B still need literal matching.[3]
Why it matters for your business
Customers rarely type the exact words in your product titles or help docs. Semantic search bridges that gap, surfacing relevant products, articles, and answers from vague queries.[1] The payoff is fewer dead-end searches, higher conversion, better support self-service, and customers who find what they want faster.
How it works, plainly
A model converts every product or document into a list of numbers, called an embedding, that represents its meaning.[4] Your customer’s query is converted the same way. The system then returns items whose numbers sit closest, meaning closest in meaning, even if no shared words exist.[3]
Bottom line
Semantic search lets your site understand what people mean, not just what they type, so customers find the right product or answer even when their words do not match yours.
References
- What is Semantic Search? A Comprehensive Semantic Search Guide. Elastic www.elastic.co
- Semantic Search vs Keyword Search: Key Differences Explained. CelerData celerdata.com
- Semantic search vs. keyword search: when to use each. Redis redis.io
- Embeddings, Vector Databases, and Semantic Search. DEV Community dev.to
Comments
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