What does "semantic search" mean?

Semantic search is a search approach that interprets the meaning and intent behind a query rather than scanning for exact word matches. A shopper who types "warm jacket for hiking" can reach a product titled "thermal trail shell" because semantic search reads what the person means, not just the words they typed.

It is the opposite of traditional keyword search, which only returns results when the shopper's words appear in your product titles, descriptions, or tags.

How does semantic search work?

Semantic search converts text into numerical representations called embeddings that capture meaning, then finds results whose embeddings are closest to the query's. Because similarity is measured by meaning, synonyms, paraphrases, and descriptive phrases all map to the right products without anyone hand-writing synonym rules.

In practice that means:

• "running shoes for flat feet" can surface stability shoes even if "flat feet"

never appears in a title.

• Misspellings and alternate phrasings still resolve to the right items.
• New phrasings work without a merchandiser adding a rule for each one.

Why does semantic search matter?

When search only matches keywords, every query a shopper phrases in their own words risks a dead-end "no results" page - and most shoppers who hit one simply leave. Semantic search closes that gap, which is why it tends to move the metrics that matter: a lower zero-result rate and a higher conversion rate on search sessions.

It also reduces ongoing work. Teams running keyword search spend time writing synonym lists and pinning fixes for queries the engine gets wrong; meaning-based matching removes much of that maintenance.

For stores using Nobi, semantic matching is the default: a shopper's natural-language query is matched against the live catalog, so descriptive searches resolve without manual synonym upkeep.

Frequently asked questions

What is the difference between semantic search and keyword search? Keyword search matches literal words against your catalog, so it fails when shoppers describe a product differently than you labeled it. Semantic search interprets meaning and intent, so descriptive and long-tail queries still return relevant results.

Does semantic search replace filters and facets? No. Semantic search handles how shoppers describe what they want; filters let them narrow by attributes like size, color, and price. The two work together.

How do you measure whether semantic search is working? Watch the zero-result rate (it should fall) and the search-to-cart or conversion rate on search sessions (it should rise).