The four parts are distinct. Experience asks whether the author has actually done the thing, which is why a review written by someone who used the product reads differently from one assembled from spec sheets. Expertise asks whether they have relevant knowledge or credentials. Authoritativeness asks whether others in the field recognise the source. Trustworthiness is the one the others feed into, and Google describes it as the most important: is this page accurate, honest, and safe to act on?
E-E-A-T is not a score in the algorithm. It is a description of what human raters look for, used to evaluate whether Google's ranking systems are surfacing good results. That distinction matters because it means there is no tag to add. The signals are ordinary and mostly unglamorous: named authors with real backgrounds, visible contact details and a physical address, clear pricing and policies, dated content, accurate claims, and honest corrections when something turns out to be wrong.
For a small business the practical version is simple. Say who you are, show that you do the work, state your facts plainly and keep them current. That is also what makes a site useful as a knowledge source: Clerkzo builds its AI chat widget from a crawl of your site, and a site that demonstrates real experience and states its details clearly produces a widget that answers visitors accurately instead of vaguely.
Related terms
Browse all 142 terms- Search IndexingSearch indexing is the process by which a search engine analyses a page it has crawled, works out what it is about, and stores it in a database so it can be retrieved and ranked for relevant queries.
- Large language model (LLM)A large language model (LLM) is an AI system trained on very large amounts of text to predict the next piece of language in a sequence. That single capability lets it answer questions, summarise documents, write code and hold a conversation.
- EmbeddingsEmbeddings are lists of numbers that represent the meaning of a piece of content, such as a sentence or a paragraph. Items with similar meaning end up with similar numbers, which lets software compare meaning mathematically instead of matching exact words.
- Vector databaseA vector database is a store designed to hold embeddings and retrieve the entries most similar to a given query vector. It answers "what is closest in meaning to this?" rather than "which row exactly matches this value?"