Getting Cited by Gemini: What You Can Influence

"Gemini" covers more than one product, and Google gives each a different control. Treat them separately or your diagnosis will be wrong.

• The Gemini app (Gemini Apps). Google documents the Google-Extended token as the control for training and for grounding in Gemini Apps and Vertex AI.
• The Gemini API with Grounding with Google Search. A developer turns this on. Google's API docs say the model automatically generates one or multiple search queries and runs them.
• AI Overviews and AI Mode. These run inside Google Search. They are governed by Googlebot rules and Search Console, not by Google-Extended. Google says they "may use different models and techniques" and can return different links.

It helps to think in four stages. Parametric knowledge is what the model learned in training. Access is whether Google's crawlers may fetch your page. Retrieval is whether your page is pulled in for a given question. Generation is which retrieved pages get cited. You influence access directly, retrieval partly, and the other two barely or not at all.

If your real target is the search results page, read getting cited in AI Overviews instead. This page focuses on the Gemini app and the grounding paths around it.

Grounding with Google Search draws on Google's index. If your page isn't in it, Gemini has nothing of yours to retrieve.

Google states that to appear as a supporting link in AI Overviews or AI Mode, a page must be "indexed and eligible to be shown in Google Search with a snippet." It adds that there are no additional technical requirements and no special optimizations. Google also says indexing and serving aren't guaranteed.

Otterly's 2026 experiment shows the stakes. Google deindexed both of its AI-generated test sites with no manual action in Search Console. Afterward, Gemini, AI Overviews and AI Mode almost never cited them. Microsoft Copilot, which grounds on Bing, kept citing them. It's one pair of sites on a low-stakes topic, but it fits the mechanism Google documents.

What to check:

• Search Console shows your key pages as indexed.
• No noindex, nosnippet or max-snippet:0 on pages you want quoted. Google documents these, plus data-nosnippet, as the controls that keep content out of its AI features.
• data-nosnippet hasn't been inherited from a template, for example one meant to hide a cookie banner.
• The Search Console generative AI control hasn't excluded your property. Inclusion is the default, but child properties inherit the parent's setting. That control covers AI Overviews, AI Mode and Discover, not the Gemini app.

Google-Extended is a robots.txt token, not a separate crawler you'll see in logs. Google says it controls whether your content is used for training and grounding in Gemini Apps and Vertex AI. Google also says it "does not impact a site's inclusion in Google Search nor is it used as a ranking signal."

That gives you two independent switches:

• Googlebot governs Google Search, including AI Overviews and AI Mode. No robots.txt token blocks those two features on their own.
• Google-Extended governs Gemini Apps grounding and training.

The common failure is a blanket "block AI bots" rule copied from a forum. It quietly removes you from Gemini Apps grounding while Search looks fine. Look for lines like these:

User-agent: Google-Extended
Disallow: /

If you want Gemini Apps to be able to ground on your pages, remove that rule. Allowing the token buys eligibility, nothing more. It doesn't guarantee retrieval or a citation.

The robots.txt Checker for AI Crawlers resolves each token, so you can see what your file actually says about Google-Extended, GPTBot, OAI-SearchBot and the rest. Other engines use different tokens, which the ChatGPT and Perplexity pages cover.

Once access is open, the one on-page step with any positive experimental signal is plain: state the fact. A price, a number or a one-line definition on a fetchable page gives the engine a sentence it can quote.

Google renders JavaScript, so client-side content is less of a risk for Google's surfaces than for ChatGPT or Perplexity crawlers. Most of those don't execute JavaScript, according to Vercel's crawler study. Server-rendering your key facts covers both.

In practice:

• Put pricing, plan limits, locations and what you do in the HTML, in plain sentences.
• Keep each fact consistent across your pricing page, about page and footer. Contradictions on your own site give any engine two answers to choose from.
• Don't hide key facts behind tabs or "load more" buttons that require interaction.

Say you run a dental clinic in Austin (a hypothetical). "New-patient cleanings are $120" in visible text is quotable. A price that only appears inside a booking widget may not be.

When Gemini already cites other sites for your category, being named on those pages is associated with appearing in the answer. See how third-party mentions show up in AI answers. That's an association, not a promised effect.

Some of Gemini's behavior sits entirely with Google. Knowing which parts means you stop paying for fixes that can't work.

• The queries. Gemini generates its own search queries from the user's prompt, and Google Search can fan out across subtopics. You never see these queries. A tracker that tests your chosen prompts measures a proxy.
• Whether it searches at all. Retrieval happens per question. An answer may come from trained knowledge with no live search.
• Model routing. As of October 2026, Gemini's release notes list gemini-3.6-flash as selectable in the app since 2026-07-21. Google doesn't state which model free users get by default. Different models can give different answers.
• Parametric knowledge. What the model learned in training is frozen at its cutoff. Nothing you publish this quarter changes it.
• Citation choice. Among retrieved pages, topical relevance and position in the context drive citation, according to the 252,000-trial factorial study. Position isn't something a publisher can set. Being retrieved also isn't the same as being cited, as the guide to cited vs retrieved sources explains.

A lot of GEO advice targets Gemini with tactics Google itself contradicts.

• Schema markup. Google says structured data isn't required for generative AI search. Ahrefs' matched-control study found AI Overviews citations fell 4.6% after pages added schema. Existing markup does no harm. It just isn't a lever for AI answers.
• llms.txt. Google's AI optimization guide says Google Search ignores AI text files, and that adding one will neither harm nor help.
• E-E-A-T scores. Google says E-E-A-T isn't a specific ranking factor. There's no score to improve.
• "AI-friendly" rewriting or chunking. Google says you don't need to write in a special way for generative AI search, and that there's no ideal page length.
• Scaled AI content. Google's spam policy names mass-generated pages without added value. Otterly's test sites were removed from Google within weeks.
• Hidden or injected instructions. Prompt injection aimed at AI agents exists, and research shows it can sway some models. It's manipulation, it breaks policy, and it puts your index presence at risk. Don't do it.

Work through the gates in order. A failure early on makes everything after it irrelevant.

1. Confirm your key pages are indexed in Search Console, with no noindex or snippet restrictions.
2. Read your robots.txt for Google-Extended and Googlebot rules, and make sure each one matches your intent.
3. Check that pricing and core facts appear as plain text in the page HTML.
4. Ask Gemini a few buyer questions and compare its claims with your own pages. The guide on checking whether AI quotes your site accurately covers how.

For a quick snapshot, the free checker on this site scores up to three buyer questions. It's a single reading, not ongoing tracking, so re-check after any change you ship.