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Commerce

Semantic Search

Retrieve by meaning, not only keyword match, so “waterproof shell for rainy hikes” finds the right gear without exact terms. Still show why a result matched and keep filters.

Interactive demo

Search by need, not keyword. Meaning chips appear with results.

Overview

How might we design semantic search so people can trust and act on AI output?

When to use

  • Essential for e-commerce platforms, content discovery applications, knowledge bases, and in-product feature search where users search by intent and meaning rather than exact keywords.

When to skip

  • Tiny catalogs where keyword search already returns complete, exact sets.
  • Legal or SKU lookup that must match exact identifiers, not “close enough.”
  • Offline or privacy-hard clients that cannot embed or call a retrieval index.

Rules

  • Semantic results with no keyword fallback when users search an exact ID.

  • Opaque ranking with no filters, sort, or “match explanation.”

  • Quietly ignoring part of a natural-language query (size, budget, brand).

  • Mixing ads into the semantic set without labeling sponsorship.

Evidence

ProductImplementation
Algolia NeuralSearch-style UXMeaning-aware retrieval with familiar facets and query understanding.
AmazonNatural-language browse and Rufus-assisted discovery over catalog search.
EtsyIntent-friendly product search across messy handmade titles.
Shopify storefront AI searchStore-scoped semantic product find with merchant filters.

FAQ

What is semantic search in product UX?

Semantic search finds items by meaning and intent rather than exact keyword overlap, so descriptive natural-language queries still return relevant products or documents.

Should semantic search replace keyword search?

Usually blend both. Keep exact SKU and quote-style matches reliable, and use semantic ranking for exploratory language. Users hate missing an exact product code.

How do citations relate to semantic search?

In research UIs, semantic retrieval often powers which passages are ranked; citations then show those sources on the answer. Search results pages may show snippets instead of claim-level cites.

What makes semantic search feel trustworthy?

Stable ranking, honest empty states, filters that still work, and visible query understanding (chips for detected attributes) so users can correct misread intent.