Google defines query fan-out in its own optimization guide:
A set of concurrent, related queries generated by the model to request more information and fetch additional relevant search results to address the user's query.
Last verified: September 2, 2026.
Google's worked example starts with "how to fix a lawn that's full of weeds" and fans out into things like best herbicides for lawns and removing weeds without chemicals. A local service request behaves the same way: one question about a failed water heater turns into several searches about the job, the market, the proof, and who is available. Google does not publish the exact hidden set for any given answer.
The panel data shows the practical consequence. Across the Cheers panel of 119 home-services organizations, 28 days ending September 2, 2026, aggregate only, the shape of the question changed the outcome more than anything an operator does on the page that week. Price and cost questions returned a 37.9% pooled appearance rate. Broad "best or top" prompts without a place name returned 28.9%. Question-shaped prompts, the how and what and should-I family, returned 26.4% appearance but the highest citation rate of any family at 27.3%. "Best near me" and named-place prompts came last at 22.8%.
Cheers panel, by prompt shape
Named is not the same as cited
Pooled citation rate by prompt shape, Cheers panel, 28 days ending September 2, 2026
Appearance 26.4%
Appearance 37.9%
Appearance 28.9%
Appearance 22.8%
Cheers panel, 28 days ending September 2, 2026: 119 home-services organizations, pooled citation rate by prompt shape. Citation means the organization or its site appeared as a source. Aggregate only.
| Prompt shape | Pooled citation rate |
|---|---|
| How, what, why, should I questions | 27.3% (Appearance 26.4%) |
| Price and cost questions | 23.8% (Appearance 37.9%) |
| Best or top lists, no place name | 23.2% (Appearance 28.9%) |
| Best near me or in a named place | 19.6% (Appearance 22.8%) |
That is the argument for writing pages that answer the whole buying decision instead of chasing one phrase. The cuts are in AI visibility statistics and the sampling rules in the methodology.
What Google confirms
Google says AI Mode and AI Overviews use core Search ranking and quality systems. Retrieval-augmented generation pulls current pages from the Search index. Query fan-out generates related searches. The system then shows supporting links for the response.
That means the technical foundation still matters. A useful page has to be crawlable, indexed, eligible for a Search snippet, and linked clearly from the rest of the site. Google says there is no special AI schema or extra technical requirement.
What local operators should do
Write for the buying decision, not an imagined list of subqueries. A strong location page should state the services that branch truly provides, the area it serves, current contact and booking details, hours or availability, qualifications, and local proof.
The location-page checklist covers that structure. Service pages should answer the parts of the job that change the buyer's choice, such as what is included, who performs the work, how estimates work, and what evidence supports the claim.
Do not produce a thin page for every city-service wording. Google names the tactic and the policy directly, and then explains why it fails on its own terms:
a high quantity of pages doesn't make a website higher quality or more relevant to users
Creating separate content for every search variation or fan-out query, primarily to manipulate rankings or generative AI responses, violates Google's scaled content abuse spam policy. The safer version of that instinct is building city pages without doorway risk.
Next step
Is AI recommending your business?
Find out how visible you are across ChatGPT, Gemini, Perplexity, and AI Overviews.
How I audit a result
I save the original prompt, AI Mode response, supporting links, market, and time checked. Then I compare the pages Google cited with the branch page and public business facts.
If a competitor page answers a real buyer concern more clearly, improve the useful content. If a source contains the wrong location or hours, correct the source. Do not claim to have reverse-engineered the hidden query tree from one response.
The AI engine source comparison explains why AI Mode should be tracked separately from ChatGPT, Perplexity, and Copilot. Does SEO Still Work? covers why the core Search work still matters. Use the AI Visibility Grader when you need a current baseline for your own business.
Sources
Every link below was opened and checked on September 2, 2026.
- Optimizing your website for generative AI features on Google Search. Google Search Central, last updated July 2026. Source of the query fan-out definition, the lawn-weeds example, the scaled content abuse warning, and the note that structured data is not required for generative AI search.
- AI features and your website. Google Search Central. Eligibility, indexing, internal-link, and Search Console guidance for AI surfaces.
- Scaled content abuse. Google Search Essentials spam policies. The policy Google names when it warns against a page per query variation.
- Cheers panel, 28 days ending September 2, 2026. 119 home-services organizations, pooled appearance and citation rates by prompt shape, aggregate only. Methodology.
Dylan Allen-Arnegard is the CEO and Co-Founder of Cheers. I help multi-location service brands get recommended by AI search and Google, with results tracked by location, employee, and competitor.