Query Fan-Out: How AI Actually Researches Your Brand

Written by Mackenzie

We’ve all been there

You find that one golden keyword with massive search volume, you throw all your content and PR budget at it, and you assume that if you rank for it, you win. Right?

Well, not anymore.

When a user asks a Large Language Model (LLM) like ChatGPT or Gemini a complex question, the AI doesn’t just run a single, linear search. Instead, it actively researches the topic by expanding the original prompt into multiple, highly related searches to pull together a comprehensive answer.

We call these additional backend searches query fan-outs.

Still clinging to traditional search volume? You might want to read GEO vs SEO: The New Role AI Plays in Search first.

What the Hell is a Query Fan-Out?

How AI actually does its homework

In simple terms, the process looks like this:

One user prompt → Multiple related backend searches → One neat AI-generated answer

Let’s say a user prompts an AI with: “What are the best family holidays?” The AI won’t just look for pages lazily stuffed with that exact phrase. It will instantly expand the prompt into a fan-out of related queries, such as:

Best destinations for family holidays
Family holiday resorts with kids’ clubs
Cheapest family holidays in Europe
Family holidays with waterparks

A visual way to mimic the exploding of a keyword

Each of these searches explores a totally different angle of the user’s underlying intent. The AI gathers information from multiple sources across these fan-outs, cross-checks the facts, and synthesises them into one neat response.

"When a user asks an LLM a question, it doesn't just pull the first answer it finds. It acts like a hyper-caffeinated researcher, opening ten tabs at once to cross-reference the data. If your brand’s content is only visible for one of those ten searches, you aren't making it into the final generative answer."

Mackenzie Brook, Head of Content at Flaunt Digital

Six Ways AI Models Expand a Query

When AI systems expand prompts, they generally fall into one of six core patterns:

Want to see exactly which of these fan-out queries your brand is actually winning?

See how we track it with our tool, LLMLens

Why You Need to Stop Obsessing Over Single Keywords

Here is a hard truth for your next reporting meeting: Visibility in AI-generated responses is absolutely not determined by ranking for a single keyword.

Query fan-outs behave a lot like traditional long-tail keyword research, but they operate around conversational, human prompts. This means your search strategy has to fundamentally shift from targeting isolated keywords to building deep, interconnected topic coverage.

This is exactly why your Digital PR campaigns cannot just link to a generic homepage anymore. Read: How to Influence the Environment LLMs Learn From.

Pages that cover a topic in extreme depth and answer several related questions are significantly more likely to be retrieved across these fan-out searches. This is what builds true topical authority.

"We have to stop treating keyword lists like a checklist. When you build an ecosystem of content that naturally answers the six stages of a query fan-out, you're boxing out the competition entirely. You become a logical source the AI can cite."

Mackenzie Brook, Head of Content at Flaunt Digital

When you stop writing for outdated algorithms and start answering real human questions, you give the AI the interconnected ecosystem it needs to confidently recommend your brand.

Every. Single. Time.

This post is just one part of our deep dive into the new era of discovery. If you’re ready to stop relying on outdated keyword lists and want to see how to actually win in generative search, check out the rest of our AI & LLM Series over on the Flaunt Digital Blog.

Or, if you’re tired of reading and just want to know exactly what the AI thinks of your brand right now: drop us a line and let’s run your site through LLMLens.

Flaunts Premium Intelligence Suite: Discover our tools here.

Mackenzie Brook

Head of Content