Semantic Search
Semantic search is retrieval based on conceptual similarity between queries and documents, typically using embeddings or semantic indexes.
Also known as: meaning-based-search · intent-aware-search
Why it matters
Marketing, product, and SEO teams phrase questions inconsistently. Semantic search lets analysts, composers, and users find the right knowledge without memorizing internal vocabulary or tag taxonomies.
How it works
Documents and queries map into a shared semantic space. Retrieval ranks by similarity scores; filters narrow by org, site, or content type. Hybrid systems blend semantic scores with keyword matches for robustness on proper nouns and SKUs.
Common mistakes
- Relying on semantics alone for exact SKU or error-code lookup.
- Poor chunking that splits tables and lists across vectors.
- Ignoring access control, semantic search must respect tenancy.
- Assuming semantic search replaces structured analytics queries.
Best practices
- Use hybrid retrieval for product names and technical codes.
- Attach metadata filters, site, doc type, freshness.
- Evaluate retrieval with real user questions weekly.
- Keep corpora small and authoritative vs dumping everything.
Learn Domains perspective
Your team tags knowledge inconsistently. "ICP," "ideal customer," "target buyer." Semantic search in the AI Analyst and Content Operations still retrieves the right passage when you ask or draft against a topic.
FAQ
- Is semantic search the same as vector search?
- Vector search is the common implementation; semantic search is the intent, meaning-based retrieval.
- Does Learn Domains semantic-search the public web?
- No, it searches your org Knowledge Base and URL Library, plus structured integration data.
- Can semantic search browse my GSC tables?
- Analytics use structured queries; semantic search targets unstructured knowledge chunks.
Next steps
- 1Add FAQ content to the Knowledge Base.
- 2Ask the analyst a paraphrased product question.
- 3Tune chunk sources if retrieval misses.
Knowledge graph
Parent terms
Related concepts
vector-search · llm-optimization · ai-growth-analyst