Gemini SEO: How to Get Cited in Google Gemini

Where does Gemini get the web pages it cites?

Gemini gets cited web pages from the Google Search index. Google calls this grounding: content from the Search index is supplied to the Gemini model at prompt time to improve factuality and relevance, and the answer links the pages it drew on.

Gemini is Google’s AI assistant, available as the Gemini app on the web and on phones; Google’s documentation calls the app and its surfaces Gemini Apps. They run on Gemini models, the family of large language models Google also offers to developers. Google’s crawler documentation defines grounding as “providing content from the Google Search index to the model at prompt time to improve factuality and relevancy.” A grounded answer is one built on pages retrieved for the question, not only on what the model learned in training.

Google’s developer documentation for the Gemini API describes the same process in four stages:

1. Read the promptThe model analyses the question.
2. Decide on a searchIt "determines if a Google Search can improve the answer".
3. SearchIt generates one or more search queries and runs them against Google Search.
4. Answer with sourcesIt writes the response from the results and attaches citations to the source pages.

The model reads the prompt, decides whether a Google Search would improve the answer, runs one or more searches, then writes a grounded answer with its sources linked.

What does the Google-Extended token control in Gemini?

Google-Extended controls whether Google uses a site's crawled content to train future Gemini models and to ground answers in Gemini Apps and Vertex AI. It does not change inclusion or ranking in Google Search, including AI Overviews and AI Mode.

Google describes Google-Extended as “a standalone product token that web publishers can use to manage whether content Google crawls from their sites may be used for training future generations of Gemini models.” It is not a crawler: “Google-Extended doesn’t have a separate HTTP request user agent string. Crawling is done with existing Google user agent strings; the robots.txt user-agent token is used in a control capacity.”

Its scope has two parts, and most guides mention only the first. The token governs use of content for training the Gemini models that power Gemini Apps and the Vertex AI API for Gemini, and for grounding in Gemini Apps and in Grounding with Google Search on Vertex AI. Vertex AI is Google Cloud’s platform for building applications on Gemini models. What the token leaves alone is stated just as clearly: “Google-Extended does not impact a site’s inclusion in Google Search nor is it used as a ranking signal in Google Search.”

The matrix shows the trade-off in one row: disallowing Google-Extended keeps a site fully eligible in Google Search but removes its content from Gemini Apps grounding, which is where Gemini citations come from. The full list of Google-Extended and other AI tokens, with their operators and purposes, is in the AI crawlers directory.

How do you get a site cited in Gemini answers?

Get cited in Gemini in 5 steps: verify target pages are in Google's Search index, decide Google-Extended with grounding in mind, phrase answers to likely searches, align brand facts across trusted profiles, and inspect Gemini's Sources panel for target prompts.

Verify each target page is in Google’s Search index

Grounding draws on the Google Search index, so a page Google has not indexed cannot be a Gemini source. Run URL Inspection in Search Console on each page you want cited and fix anything that keeps it out: a noindex tag, a robots.txt rule blocking Googlebot, a canonical pointing elsewhere, or a page with no internal links. The same work makes the page eligible for Google’s other AI features.

Decide the Google-Extended setting with grounding in mind

Many sites added User-agent: Google-Extended with Disallow: / to opt out of model training. That choice also removes their content from grounding in Gemini Apps. If being cited in Gemini matters, leave Google-Extended allowed; if keeping content out of Gemini matters more, disallow it knowing that Search, AI Overviews and AI Mode are unaffected. Make the decision once, write down why, and review it when Google updates the token’s scope.

Phrase answers to the searches Gemini runs

Gemini writes its own search queries from the user’s prompt rather than searching the prompt word for word. As an illustration, a prompt asking Gemini to “help me choose running shoes for flat feet and a half marathon” could lead to plain searches such as “running shoes for flat feet” and “half marathon training shoes”. A page that answers each plain search in its opening sentences, naming the product type and who it suits, gives Gemini a passage it can use as it stands. The Gemini API lists the queries its model ran, which makes it a practical way to see how a Gemini model breaks down a prompt in your market.

Align brand facts across the site and trusted profiles

Gemini answers about a business are built from every page the searches return, including profiles and directories. Keep four facts identical everywhere:

• Name: one spelling of the brand name.
• Category: the same plain description of what the business does.
• Location: the same city, region or service area.
• Founder or lead: the same named person, linked to one profile.

Correct outdated versions at their source; Gemini has no way to know which of two conflicting descriptions is current.

Inspect Gemini’s Sources panel for target prompts

Build a list of 20 to 50 prompts your buyers would ask, run each one in Gemini, open the Sources panel and record which pages are linked. Repeat the same prompts monthly under the same conditions. The list of cited domains shows who holds each answer today, and the changes between runs show whether your fixes are working.

How does Gemini show the sources behind an answer?

Gemini shows sources through a Sources button at the end of a response or in-line links, which open a side panel of pages. Google states that not every response includes sources; a response without the Sources button provided no links.

Google’s Gemini Apps Help puts it this way: “When sources are available, you can find the Sources button at the bottom of the response or in-line throughout the response.” Selecting it opens a panel on the right that lists the linked pages. The same page adds: “Not all responses include related links or sources. If you don’t have the Sources button below a response, Gemini Apps didn’t provide any links for that particular response.”

That second statement matters for tracking. A prompt whose answer has no Sources button is not a lost citation; it is a response Gemini answered without links. Record those prompts separately, so a monthly count of cited pages is not diluted by answers that could not have cited anyone.

How are Gemini, AI Overviews and AI Mode related?

Gemini is Google's standalone AI assistant, while AI Overviews and AI Mode are features inside Google Search. All three draw on the Google Search index, but only Gemini Apps grounding responds to the Google-Extended token.

The table shows one shared foundation and one fork. Work that earns Google AI Overviews citations — indexing, snippet eligibility, answer-first passages — also serves Gemini, because both draw on the same index. Google AI Mode adds query fan-out on top of the same eligibility rules. The fork is Google-Extended, which reaches only Gemini.

Does Search Console report Gemini citations?

No. Search Console's Generative AI performance report covers AI Overviews and AI Mode, not Gemini Apps. Gemini visibility is measured by running a fixed prompt set in Gemini and recording which pages appear in its Sources panel.

The report counts impressions of links to a site in Google Search’s generative AI features, and Gemini Apps sit outside Google Search. Until Google adds a Gemini report, the prompt log from the fifth step above is the measurement: the same prompts, run on a schedule, with every linked page recorded.

Google documents the controls. Whether markup changes what Gemini cites is untested — one planned experiment addresses it.

What will Bikash Roy test about Gemini citations?

Bikash Roy's planned Exp 05 tests whether structured data changes citation rates in Gemini and AI Overviews. Article and FAQ markup goes on half of a matched page set, and citations are compared for 8 weeks.

• PlannedExp 05

  Does structured data change citation rate?

  Article and FAQ markup added to half of a matched page set; citations compared across 8 weeks.

  Status: planned · Engines: AI Overviews, Gemini · Duration: 8 weeks

No result exists yet. Gemini is also one of the 6 engines in Exp 01, the running test of whether a new domain earns any AI citations within 90 days. Both are described with their methods on the GEO experiments page.