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Everybody’s Talking About Query Fan-Out — How Do You Use It As Business Intel?
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Everybody’s Talking About Query Fan-Out — How Do You Use It As Business Intel?

Discover what query fan-out is in AI search and how to use the query fan-out technique to generate richer, more authoritative local content.

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I struggle to remember the last time I regularly (and patiently) typed queries into Google and scrolled through a sea of blue links for a good enough answer.

Search agents like ChatGPT, GI struggle to remember the last time I regularly (and patiently) typed queries into Google and scrolled through a sea of blue links for a good enough answer.

Search agents like ChatGPT, Gemini, and Claude have very quickly added a conversational layer to local search — one that delivers detail, context, and follow-up within seconds. While I still sanity-check AI answers with my own research, and while Google still has its place in my search toolbox — particularly for highly branded local searches — it's rarely now the starting point in my search journey.

And we know I’m not alone. More than half of consumers turn directly to AI systems for answers. Marketing teams and businesses are unsure, even frustrated — they’re targeting the right local keywords on paper; their technical SEO is solid; they’re publishing content frequently. But they still can’t move the needle. 

Location marketers, in particular, are asking us the same questions about this new AI search reality: How is my brand showing up? Why are our competitors being recommended instead of us? Can we influence that outcome — and how?

Like we say in search: “It depends,” but a likely answer is thin content and a lack of brand authority — and the solution is query fan-out.

What Is Query Fan-Out in AI Search?

Query fan-out has become a saturated conversation. So, let’s just go through the basics before talking about it in relation to local marketing specifically. 

What is query fan-out in AI search, and why is everyone in search suddenly talking about it? Query fan-out is the process in which: 

  1. A query is broken down into smaller, more digestible parts.
  2. That query is analyzed for semantic intent.
  3. The system searches for multiple sub-queries across its index or the live web. 
  4. The AI then analyzes the top results for each sub-query and extracts the data it needs to address the original query.
  5. The AI aggregates this data and delivers the cited facts in a single natural language response.

Let’s look at a query fan-out of a query related to query fan-out. Just for fun.

Original Query: "What is query fan-out technique?"
1. Query is broken down into smaller, more digestible parts
  • Query fan-out meaning
  • How query fan-out works
  • Query fan-out examples
  • Tools for query fan-out
2. Query is analyzed for semantic intent and expected answer type
Query is informational with technical content aimed at marketers/SEO professionals.
3. The AI system searches for multiple subqueries across index or live web
  • Why is query fan-out important for marketers?
  • What does query fan-out mean in SEO?
  • What are the benefits of using query fan-out?
  • Are there tools that help with query fan-out analysis?
  • Can query fan-out improve search visibility?
  • What's the difference between query fan-out and traditional keyword research?
4. The AI analyzes the top results for each subquery, extracting the data it needs
Top results are typically based on relevance, freshness, authority, and context.
5. The AI aggregates this data and delivers the cited facts into a single response
"The query fan-out technique is an approach used in SEO and AI-driven search to expand a single user query into multiple related sub-queries, allowing search systems to understand intent more comprehensively. Rather than treating a query as a single, isolated question, the system breaks it down into smaller components—covering definitions, examples, benefits, comparisons, and tools—so it can find the most relevant content across the web.

For marketers, query fan-out helps identify gaps in content and knowledge coverage, ensuring that a brand can appear in AI-generated answers for all related questions. By addressing these micro-queries, businesses improve visibility, relevance, and authority in AI search results." – Example AI-generated response

Maybe everyone is suddenly talking about query fan-out because it’s one reason people think SEO is dead. Because SEOs are asked to no longer expected to optimize for keywords. They’re expected to optimize for relevant “chunks” or passages from their pages to be pulled and surfaced by AI tools like ChatGPT, Gemini, Perplexity, and the like. 

The good SEOs will react to this by saying “We’ve been optimizing for long-tail keywords and E-E-A-T content and information gain through comprehensive content for years.” That’s because GEO is just good SEO with higher stakes.

There are many, many technical articles out there explaining how query fan-out works in far greater detail than this. My intention is to give you an actionable way to use query fan-out to boost your locations’ visibility — whether you’re an enterprise, franchise, or smaller business with multiple locations. 

What Does Query Fan-Out Mean for Multi-Location Brands?

We can quite confidently say that AI search is evolving to deliver a richer search experience that recognizes, respects, and satisfies consumer intent better than ever. AI responses now influence every stage of the funnel — awareness, decision-making, and conversion — often condensed into a single interface. And query fan-out is the vessel that enables this richer search experience.

Here’s the challenge for many multi-location brands: Your content may be thin, stale, or missing the structure and specificity AI models need — especially for location-specific content. And if your content doesn’t fully answer the questions and intent local customers have, AI is likely going to pull from competitors to fill those knowledge gaps.

In practical terms, this means that the $750 billion expected to flow through AI-driven search by 2028 may not pass through your business unless you optimize your locations for AI visibility and performance. And this is where query fan-out comes in.

Understanding — and operationalizing — query fan-out is critical for showing stakeholders not just where your brand appears (or doesn’t appear) in AI search, but why. By expanding a single prompt (or query) into dozens of connected microquestions, brands can understand how to increase their coverage, authority, and relevance across AI responses. 

GEO Studio, the first generative optimization tool built for multi-location brands, helps marketers identify where AI visibility is slipping to competitors and where authority gains can be made. The platform supports creating expert-led content that directly answers the prompts your potential customers are asking — and measures the results through:

  • Higher AI Mention Rate: Your business is referenced more frequently within AI responses.
  • Higher AI Citation Rate: Your content is cited as a source inside AI answers.
  • Higher AI Share of Voice (SoV): Your visibility outpaces competitors across AI-generated responses.

You can find more detailed information about these key terms in AI search in our article, and you can find out more about this kind of workflow and GEO reporting by requesting a demo from our team.

Maximizing your performance in these metrics over time reduces potential customers’ reliance on local competitors for information, products, or services. You’re ranking as an authority customers turn to, wherever they search. 

This is what query fan-out might look like if we now applied it to a multi-location pizza brand wondering how to fix its thin content.

Original Query: "What are the best Italian restaurants in London?"
1. Query is broken down into smaller, more digestible parts
  • Best Italian restaurants by neighborhood
  • Best Italian restaurants for pizza
  • Best Italian restaurants for pasta
  • Best Italian restaurants based on reviews
  • Best Italian restaurants with Michelin stars
  • Italian restaurants for delivery or takeout
2. Query is analyzed for semantic intent and expected answer type
Query is informational with local, experiential content aimed at consumers. Answer type likely to be ranked lists, recommendations, or curated guides.
3. The AI system searches for multiple subqueries across index or live web
  • Best Italian restaurants in Soho London
  • Best pasta restaurants London reviews
  • Top-rated pizza restaurants London
  • Italian restaurants London for vegetarian options
  • Italian restaurants with delivery option London
  • Italian restaurants near Oxford Street London
4. The AI analyzes the top results for each subquery, extracting the data it needs
Top results are typically based on relevance and location information, reviews, freshness, authority, and context.
5. The AI aggregates this data and delivers the cited facts into a single response
"The best Italian restaurants in London in 2026 include: Osteria Francescana-inspired eatery XYZ in Soho, known for its fresh pasta and Michelin-quality service; Pizzeria ABC in Covent Garden, celebrated for its wood-fired pizzas and vegan options; Ristorante LMN in Mayfair, offering fine dining with top-rated wine pairings; and Trattoria OPQ in Shoreditch, popular for authentic regional dishes and casual dining."

Here’s How to Use Query Fan-Out for Your Strategy

Tools that enable you to see your most relevant queries “fanned-out” will help you build authoritative topic clusters and comprehensive content hubs around your locations. And don’t forget content authority compounds. AI models tend to cite brands that cover a topic holistically, from the main pillar topic “best Italian restaurants in London” to the fan-out subtopics “best-rated Italian restaurant for vegetarians in London.” 

I would focus on asking yourself the following questions when finding and addressing content gaps:

  • Is my content answering the prompt?
  • Is my content full of expert, authoritative, and unique location-specific insights?
  • Is my content coherently structured with headings, paragraphs, metadata, schema, tables, listicles, FAQs?
  • Am I making sure my content stays fresh? 
  • Am I monitoring content performance with the right KPIs?

This is how we are telling our multi-location clients to do it in GEO Studio, step by step as follows:

  1. Identify content gaps and prompt opportunities. See where your brand or location is being mentioned and cited — and where it’s not in the Prompt Center.
  2. Prioritize content creation. Focus on prompts with the highest value and volume. 
  3. Publish expert-led content. Ensure each piece demonstrates E-E-A-T, delivers information gain, and fully answers the prompt. You can do this directly in the Action Center.
  4. Track query fan-out. Identify connected prompts that stem from your main prompt to expand your authority across related topics and local intents.
  5. Repeat step 3.
  6. Monitor your AI visibility over time. Check the Olympus dashboard for your Mention Rate, Citation Rate, and Share of Voice over time.

This ensures you use intel from query fan-out to build your brand authority deliberately, reinforce it everywhere, and ensure it will be chosen over local competitors.

Stay Locally Relevant with GEO Studio

AI visibility will fluctuate, just like traditional visibility did before. But what keeps you ahead (and enjoying a slice of that $750 billion search revenue) is optimizing thin content, prioritizing helpfulness, and encouraging engagement. “Thick” location-specific content that answers real customer questions across every relevant angle is what earns human trust — and AI citations. That’s fully in your control.

With GEO Studio’s Prompt Center, multi-location brands can turn query fan-out into business intelligence — identifying gaps, building authority, and measuring impact through Mention Rate, Citation Rate, and Share of Voice. This stops location marketers guessing: “How is my brand showing up? Why are my competitors being recommended instead of us? Can we influence that outcome — and how?” So they can focus on winning in the new search reality.

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