What is semantic SEO?

Semantic SEO is what you do; semantic search is what the search engine does. It is not semantic HTML either, which is about using the right tags in the code, nor the semantic web of linked vocabularies, although it touches it. A store should care for a practical reason: the search engine no longer matches your product page to a query word by word, but by what the two mean, and a page written for a keyword can end up without saying what the shopper asks.

What Google documents

"Semantic SEO" is not a Google term: it appears neither in its guide to ranking systems⁠^{[1]Google Search Central. A guide to Google Search ranking systems} nor in its explanation of how Search works.⁠^{[2]Google. How Search works: ranking results} What those pages describe are the pieces it responds to.

The meaning of the query. Google explains that, to return relevant results, it first has to establish the intent behind the query, and that to do so it builds language models. Its synonym system finds relevant documents even if they don't contain the exact words: if you search "change laptop brightness" and the manufacturer wrote "adjust laptop brightness", its systems understand that the words and the intent are related.⁠^{[2]Google. How Search works: ranking results}

Relevance beyond the keyword. The most basic signal of relevance is still that the page contains the words in the search. But Google gives an example: someone searching "dogs" doesn't want a page with that word repeated hundreds of times, so its algorithms look at whether the page has other relevant content, such as pictures of dogs, videos or a list of breeds.⁠^{[2]Google. How Search works: ranking results}

Systems that understand concepts. Google's guide to ranking systems describes four that do this work:⁠^{[1]Google Search Central. A guide to Google Search ranking systems}

Things, not strings. With that motto Google introduced its Knowledge Graph in May 2012: a model of real things and their relationships, designed to understand which thing a search refers to and not just which words it contains.⁠^{[3]Google, The Keyword (Amit Singhal, May 16, 2012). Introducing the Knowledge Graph: things, not strings} Each of those things is an entity, and semantic SEO consists largely of making clear which entities your page talks about.

Markup. Google uses the structured data it finds to understand the content of the page and to gather information about the world, such as the people, books or companies that appear in the markup.⁠^{[4]Google Search Central. Introduction to structured data markup in Google Search} It is the most direct way to declare those entities instead of letting the search engine deduce them, and Google advises continuing to use it because it helps qualify for rich results.⁠^{[5]Google Search Central. Optimizing your website for generative AI features on Google Search}

What Google says you don't need

In its guide to appearing in Google's AI search, the company responds to several practices that tend to be sold under this label. You don't need to write in a special way: its systems understand synonyms and the general sense of what someone is searching for, so you don't have to worry about not having enough long-tail keywords or about having covered every variant of a search. Nor do you need to chop content into pieces, because its systems understand the nuances of several topics on the same page.⁠^{[5]Google Search Central. Optimizing your website for generative AI features on Google Search} And creating separate content for each variant of a query, especially to manipulate rankings, violates its policy against scaled content abuse.⁠^{[5]Google Search Central. Optimizing your website for generative AI features on Google Search}

In a store

A made-up example: the same coffee maker, written for a keyword and written for meaning.

The right-hand column doesn't repeat the keyword: it says what the product is, what it relates to and what data it has. A query like "six-cup coffee maker for a ceramic glass stove" can find it even if it doesn't share the order or form of the words, because the data is there. And links count: Google analyzes the relationships between pages from their links to understand the site's structure, and recommends structured data so it understands what each page is for.⁠^{[6]Google Search Central. Help Google understand your ecommerce website structure}

In code, the structured data part would look like this in JSON-LD, simplified and with made-up data:

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Stainless steel stovetop espresso maker, 6 cups, induction compatible",
  "gtin13": "8400000000000",
  "brand": { "@type": "Brand", "name": "Example Brand" },
  "material": "18/10 stainless steel",
  "additionalProperty": [
    { "@type": "PropertyValue", "name": "Capacity", "value": "6 cups" },
    {
      "@type": "PropertyValue",
      "name": "Heat source",
      "value": "Induction, gas, ceramic glass"
    }
  ]
}

Each property comes from the Schema.org vocabulary, and the GTIN identifies the product unambiguously: it is the entity declared, not deduced.

How to check it

1. Pick a product page and write down the five questions a shopper would ask. Mark which ones have the answer written on the page: the ones that don't are the work.
2. Open the Search Console performance report and look for queries that bring impressions to that page without containing the words in its title: that is meaning working in your favor.
3. Run the page through the Rich Results Test and see which structured data Google detects and which is missing.
4. Check the page's links: to its category, to related products and to guides. Google uses links between pages to understand the site's structure.⁠^{[6]Google Search Central. Help Google understand your ecommerce website structure}
5. Don't create pages for variants of the same search. Google doesn't ask for it and may treat it as scaled content abuse.⁠^{[5]Google Search Central. Optimizing your website for generative AI features on Google Search}

Related concept: semantic search

Semantic search is the search engine's ability to understand the meaning and intent of a query; semantic SEO is the work of making your content give it something to understand. Neither is much use without the other: the search engine can match "hiking" with trail, but it can't read a weight the page doesn't state. Search intent decides which query each page answers, and topical authority is what the industry hopes to earn when that work is done across a whole topic and not on an isolated page. Semantic enrichment is the same idea applied to product data.

To go further, the AI search reading path orders the rest of the terms.