Semantic SEO: What It Is, How Google Uses It, and How to Do It

• 2012, the Knowledge Graph. Google announced a model of real-world entities and their relationships, which it summed up as things, not strings.
• 2019, BERT. Google said its BERT language model would help Search better understand one in 10 searches in English in the US, particularly longer, conversational queries.
• 2024 onward, AI Overviews and AI Mode. Google's AI features break a question into several related searches and write one answer, drawing on pages that match each sub-question.

Each step moved search further from matching words and closer to matching meaning. A page that repeats a phrase but does not actually answer the question behind it has been losing ground for years.

Entities

An entity is a distinct thing search systems recognize: your company, a product, a person, a place. Consistent facts about your entities across your site and other sources, such as names, what you do, where you operate and who runs the company, help systems describe you correctly. Inconsistent facts are a common source of wrong AI answers.

Topics

A searcher asking "best payroll software for restaurants" implicitly wants to know about tip handling, shift workers, pricing and integrations with point-of-sale systems. A page that covers those related needs matches the meaning of the query better than one that repeats the phrase.

Relationships

How your pages connect matters too. A clear structure, where a main page links to supporting pages on each subtopic and they link back, tells search systems which page is the main answer and how the pieces fit together.

• Start from questions, not keywords. List what buyers actually ask around a topic, including the follow-ups.
• Map the sub-questions. For each main question, note the narrower questions an expert answer would cover. These are also the searches AI features are likely to fan out to.
• Assign one main page per topic. Avoid several pages competing for the same intent. Supporting pages go deeper on sub-questions and link back to the main one.
• Make entity facts consistent. Your name, description, services, locations and leadership should match on your site, your profiles and major directories.
• Use structured data accurately. Organization, product and article markup help describe entities, as long as they match what is on the page.
• Write for the decision. Cover what a reader needs to choose, with specifics, rather than every loosely related term a tool suggests.

AI search raises the stakes. When Google runs many sub-searches for one question, pages that cover a topic's sub-questions well have more chances to be retrieved. When ChatGPT or Gemini describes your brand, it relies on consistent facts across the sources it reads. Our data shows how much comes from outside your own site: in our analysis of 2,311 ChatGPT citations, about half pointed to third-party pages, so entity consistency beyond your site is part of the job.

If you want this run as part of a program that covers rankings and AI answers together, see our AI SEO work, or start with our guide to AI search engine optimization.

What is the difference between semantic SEO and keyword SEO?

Keyword SEO targets specific phrases. Semantic SEO targets the meaning behind them: the entities, questions and related concepts a searcher expects a complete answer to cover. Keywords still matter, but as signals of intent rather than strings to repeat.

Is semantic SEO the same as entity SEO?

Entity SEO is part of it. It focuses on making sure search systems recognize your brand, products and people as distinct entities with consistent facts. Semantic SEO is broader and includes topic coverage and how pages relate to each other.

Does semantic SEO help with AI search?

Yes, indirectly. AI search features retrieve pages that match the meaning of the sub-questions they run, and they describe brands based on consistent facts across sources. Clear topical coverage and consistent entity information help on both counts.

Do I need schema markup for semantic SEO?

It helps describe entities clearly, especially your organization, products and authors, but it is not required. Google says there is no special markup needed for its AI features. Accurate, consistent content matters more.

How do I find the topics a page should cover?

Look at the questions people ask around the main query, the subtopics competing pages cover, and the sub-questions an AI answer on the topic addresses. Cover what a reader needs to decide, not every loosely related term.

• Google: Introducing the Knowledge Graph, things not strings (2012)
• Google: Understanding searches better than ever before, BERT (2019)
• Google Search Central: AI features and your website

Every High Salience engagement starts with the Category Salience Brief: your commercial questions run across Google and the AI surfaces, competitors side by side, and a ranked list of what to fix first.