Semantic Search

Semantic search is search that tries to understand the meaning and intent behind a query, rather than simply matching the words typed. It uses context, relationships between concepts and language understanding to return results that answer what the person actually wants.

Written by Paul Hoda, SEO consultant since 2005. Last updated 8 November 2026.

How semantic search works

Early search engines mostly matched keywords: if your page contained the words in the query, it could rank. Semantic search looks deeper. It considers:

  • Intent: whether the person wants to learn, compare, buy or find a specific site. See search intent.
  • Context: location, language, previous queries in a session and the wording around each term.
  • Entities and relationships: recognising real-world people, places, brands and concepts, and how they connect.
  • Synonyms and variations: knowing that "sofa" and "couch" mean the same thing.

For example, a search for "how tall is the shard" is understood as a question about a London building, not about broken glass.

The Google developments behind it

Semantic search has grown through several milestones:

  • Knowledge Graph (2012): a database of entities and facts that helped Google understand "things, not strings". See Knowledge Graph.
  • Hummingbird (2013): a rewrite of Google’s core algorithm to better handle the meaning of whole queries, especially longer conversational ones.
  • RankBrain (2015): a machine learning system to help interpret unfamiliar queries.
  • BERT (October 2019): a language model that improved understanding of words in context, including small words like "for" and "to".

Today, AI systems using embeddings and language models take this further, matching queries to passages by meaning.

Why semantic search matters for SEO

Semantic search changed what good optimisation looks like. Repeating an exact phrase no longer guarantees relevance, and pages can rank for many queries they never mention word for word. Success depends on covering topics clearly and completely, which is the focus of semantic SEO.

How to optimise for semantic search

  1. Start with intent. Work out what the searcher is trying to achieve and shape the page around it.
  2. Cover the topic fully. Answer the main question and the natural follow-ups, using the related terms experts would use.
  3. Make entities clear. Name people, places, products and organisations explicitly, and link to related pages on your site.
  4. Use structured data. Schema markup states facts about your content in a machine-readable format.
  5. Build topic clusters. Connect a main guide with detailed supporting pages through internal links.
  6. Write naturally. Clear, well-organised language is easier for both people and machines to understand.

Common mistakes

  • Stuffing synonyms or "related keywords" into text in a way that reads unnaturally.
  • Creating separate thin pages for every minor keyword variation, when one strong page would cover them all.
  • Ignoring intent, such as writing a long guide when searchers clearly want a product page.

Key Takeaways

  • Semantic search interprets meaning and intent rather than just matching words.
  • The Knowledge Graph, Hummingbird, RankBrain and BERT all advanced Google’s semantic understanding.
  • Pages can rank for queries they never mention word for word.
  • Covering topics fully and making entities clear helps content perform.
  • Natural writing beats keyword or synonym stuffing.

Related Terms

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