Your reputation: EEAT

Google EEAT — Experience, Expertise, Authoritativeness, and Trustworthiness

E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is the framework Google uses in its quality rater guidelines to assess content and sources. Although not a direct ranking formula, it shapes how Google (and, by extension, content that feeds AI systems) evaluates credibility.

• Experience — First-hand, real-world experience with the topic (e.g. actually using a product, doing the job, running the business). Google added "Experience" to E-A-T in 2022 to stress that practical experience matters.
• Expertise — Demonstrable knowledge: credentials, track record, or clear depth of understanding in the content.
• Authoritativeness — You (or your brand) are recognized as a go-to source: citations, links, and mentions from other experts and reputable sites.
• Trustworthiness — Transparency, accuracy, secure site (HTTPS), clear about who you are and what you offer; no deceptive or low-quality signals.

For AI search and GEO, the same signals matter: AI systems tend to favor sources that look credible, citeable, and consistent with what the rest of the web says about you. Building E-E-A-T on your site (author bios, clear sourcing, original research, consistent identity) and off your site (press, reviews, expert mentions) supports both Google and LLM retrieval. In 2025 and beyond, as multiple guides note, Google is emphasising E-E-A-T to surface content from real experts — and AI overviews often rely on similar quality signals.

On-page E-E-A-T checklist

• Author byline — Every key article or pillar page has an author name (and ideally a link to a bio). Use a real name or a consistent "By [Team name]."
• Author or team bio — At least 1–2 sentences: who they are, why they’re qualified (role, experience, credentials). Place it at the end of the article or on a dedicated author/team page.
• Link to 1–2 external sources per article where you make a factual or statistical claim. Use reputable sources (studies, official docs, established publications). This signals trustworthiness and helps AI verify context.
• About / team page — A clear "About us" and/or "Our team" page with company story, key people, and contact. Keep it accurate and up to date.
• HTTPS and clear site identity — Secure site; footer or header that states who owns the site and (if relevant) what they sell or offer. No deceptive or vague "we are the best" without substance.

Wikipedia, Quora, and Reddit as external sources of information about you

AI tools don’t rely only on your website. They also use external sources to validate and contextualise your brand. Three that matter:

Wikipedia

If your company or key people have a Wikipedia page that meets Wikipedia’s notability and sourcing rules, it can act as a high-authority summary that AI systems frequently cite. A well-sourced, neutral Wikipedia article gives the model a "canonical" description of who you are. You can’t control the content directly (Wikipedia’s policies forbid promotional editing), but you can ensure that what’s said about you elsewhere is accurate and well-referenced so that Wikipedia (and AI) can align with it.

Quora and Reddit: step-by-step

Quora and Reddit (and similar Q&A and community sites) are often used in RAG and training data because they reflect real questions and real answers. When users ask "What’s the best X?" or "Has anyone used Y?", AI may pull from these platforms. So:

• Participate authentically — Answer questions where your product or expertise is relevant; be helpful and honest (including when your product isn’t the right fit). Authenticity builds trust; astroturfing is detectable and backfires.
• Consistency — Use the same identity and key facts (company name, product name, value proposition) so that when AI aggregates mentions, it sees a coherent picture.

Action plan:

1. List 5 Quora or Reddit questions (or both) that your target audience actually asks — e.g. "What’s the best [your category] for [use case]?", "Has anyone tried [competitor] vs [your product]?", "How do I [task]?" Use search on Quora/Reddit and your support or sales team’s FAQs.
2. Answer 1 question per week — Write a genuine, useful answer. If your product fits, say so clearly and say why; if it doesn’t fit the question, don’t force it. Link to a relevant piece on your site (e.g. a guide or product page) where it adds value, not as spam.
3. Use the same key facts — Company name, product name, one-sentence value prop. So when AI aggregates mentions, it sees a coherent picture.

As we’ve covered in how LLMs decide what to recommend, answer engines lean on places where people speak freely; being present there in a genuine way supports both reputation and retrieval.

Wikipedia: when and how

• Check notability — Wikipedia has strict rules: articles require independent, reliable sources (news, books, established publications). If your company or key people don’t yet have enough coverage, focus on earning that coverage (press, research, speaking) rather than creating a Wikipedia page yourself (which can be removed).
• If you already have a page — Ensure that third-party references (cited in the article) are accurate and that your official site and other profiles (LinkedIn, Crunchbase) are consistent with what’s stated. You can’t edit the article for promotion, but you can correct factual errors via Wikipedia’s processes.
• If you don’t qualify yet — Invest in the on-page and Quora/Reddit actions above; over time, more citations and mentions elsewhere can support future notability.

Summary

Your reputation for AI visibility is built on-site (E-E-A-T, clear content, structure) and off-site (Wikipedia when applicable, Quora/Reddit and other trusted communities). Together they signal experience, expertise, authority, and trust — and make it more likely that AI will recommend you.

In the final module we go further: ultra-fast tactics, the importance of content structure over structured content alone, and how to keep optimising as the landscape evolves.