TL;DR: Search that understands what a query actually means, not just the literal words used, powered by Google’s BERT and RankBrain systems.
In a nutshell
Semantic search lets Google rank a “running shoes for flat feet” page for someone typing “trainers for flat-footed runners”. It uses language models like BERT and entity data from the Knowledge Graph to match intent, not just keywords. For SEO, this means writing for topical depth, not keyword repetition. Example: covering related questions and synonyms naturally beats stuffing the exact phrase 20 times.
Quick answer: Semantic search is search that understands the meaning behind a query rather than just matching keywords. Modern Google relies heavily on semantic understanding: it knows that "running shoes for flat feet" and "trainers for flat-footed runners" mean basically the same thing, and ranks the same content for both.
What Is Semantic Search?
Semantic search refers to Google’s ability to understand the intent and contextual meaning behind a search query, not just the exact keywords used. Rather than matching words mechanically, Google tries to understand what the person actually wants.
It’s the difference between a very literal librarian who only finds books with the exact title you asked for, and a brilliant one who says, “I know what you’re after, here are three books that will actually help.” The shift is documented in the Google Search Central documentation.
How Semantic Search Works
- RankBrain: A machine learning system that interprets unfamiliar queries
- BERT: A language model that understands how words relate to each other in context
- Knowledge Graph: Google’s database of entities and relationships (people, places, concepts)
What Semantic Search Means for SEO
You no longer need to repeat the exact keyword dozens of times. Instead:
- Cover topics comprehensively, including related subtopics Google expects to see
- Use semantic keywords, related terms and synonyms
- Build search intent alignment, answer what users actually need
- Develop topical authority through interconnected content
Entity SEO and the Knowledge Graph
Google increasingly thinks in terms of entities (real-world things) rather than keywords. Establishing your brand as a trusted entity, through structured data, consistent mentions, and authoritative content, is a key part of modern SEO. The Schema.org vocabulary is the canonical reference for entity definitions.
Our SEO strategies always include topic cluster planning alongside keyword research to build topical authority properly. See also LSI keywords.
How Semantic Search Changed SEO
Pre-semantic search rewarded exact keyword matching: a page targeting "cheap flights" needed to use those exact words repeatedly to rank. Today that approach underperforms. Semantic search rewards:
- Topical depth: covering a topic comprehensively, including related concepts and questions.
- Entity inclusion: mentioning specific tools, people, places, products, and companies that signal real expertise.
- Natural language: writing for humans, not stuffing keywords. Google now understands synonyms and intent.
- User intent matching: answering what the user actually meant, even when the query is vague.
For broader fundamentals, the Moz Beginner’s Guide to SEO covers how this changed keyword strategy.
Frequently Asked Questions
How is semantic search different from regular search?
Regular keyword search matches the exact words in the query against the exact words on a page. Semantic search interprets the meaning of the query and matches it to content that addresses the same intent, even when the words are different. Modern Google has been semantic for years.
What is the BERT algorithm and how does it relate?
BERT (Bidirectional Encoder Representations from Transformers) is a Google algorithm rolled out in 2019 that improved Google’s semantic understanding, especially of long-tail and conversational queries. BERT is now baked into how Google interprets every search query.
How do I optimise for semantic search?
Stop targeting individual keywords in isolation. Plan content around topics and clusters of related questions. Include synonyms, related terms, and the kind of vocabulary actual experts use. Demonstrate depth rather than density.
Are LSI keywords part of semantic search?
Loosely, yes. The colloquial idea of "LSI keywords" (related terms that demonstrate topical relevance) overlaps with how semantic search rewards topical depth. Google itself does not use LSI as a specific signal, but the underlying principle (related vocabulary signals topical authority) is real.
Take this further
Semantic search rewards depth over keyword density. Most SEO programmes that move clients meaningfully are built around topical strategy, not keyword targeting.
Ready to apply this to your own site? Book a free discovery call, or explore our SEO strategy service.