Pro Tool

See what AI actually searches for
when researching your category

ChatGPT, Claude, Perplexity, and Gemini don't answer from memory. They fire background queries before every recommendation. The Fan-Out Query Analyzer reveals exactly what those queries are.

Start analyzing freeSee all tools

Example output

What AI searches for when asked: “best CRM for small business”

Fan-Out Queries
ChatGPTClaudePerplexityGemini
100%

top-rated CRM software small business 2025

100%

CRM pricing comparison HubSpot vs Salesforce

100%

CRM ease of use reviews G2 Capterra

75%

CRM free tier features comparison

25%

small business CRM integrations Zapier Gmail

Colored dots indicate which models fire each query. 100% consensus means all four models search for this query before answering.

How it works

From topic to optimization in four steps

1

Enter a topic or keyword

Type any query your potential customer might ask an AI, a category, a problem, or a comparison. The analyzer processes it exactly as ChatGPT, Claude, Perplexity, and Gemini would receive it.

2

Watch the fan-out queries surface

AI models don't answer from memory alone. They fire multiple background sub-queries to gather current, specific information before composing a response. The analyzer reveals every one of those hidden searches.

3

See model-level divergence

ChatGPT, Claude, Perplexity, and Gemini don't always search for the same things. The analyzer shows you where they agree (high consensus) and where they diverge, so you can prioritize the queries that matter most.

4

Optimize content for each query

Each fan-out query is a content opportunity. If your site doesn't directly answer that sub-query, AI models will find a competitor that does. Use the results to build targeted pages, FAQs, and comparison content.

Why fan-out analysis matters

The gap between SEO and AI visibility

AI doesn't search the way humans do

When a user asks ChatGPT to recommend a product, ChatGPT doesn't surface your homepage. It runs a series of background searches, for pricing data, review aggregates, comparison content, and specific feature specs. If your site doesn't answer those sub-queries explicitly, you won't appear in the recommendation.

Fan-out queries are invisible to standard SEO tools

Google Search Console shows you what people search. It doesn't show you what AI models search on their behalf. Fan-out queries are a fundamentally different signal, and they're the ones that actually determine whether you get cited in AI responses.

Consensus queries carry the most weight

When ChatGPT, Claude, Perplexity, and Gemini all fire the same background query, that's a signal it's load-bearing for your category. The analyzer scores each query by cross-model consensus, so you know where to focus first.

Turn gaps into content before competitors do

Most businesses have no idea what AI models are searching for when evaluating their category. Identifying these gaps early, and publishing the content that answers them, is the fastest path to consistent AI citation.

What you get

Everything in the Pro analyzer

Full fan-out query list

Every background query ChatGPT, Claude, Perplexity, and Gemini fire for your topic.

Consensus scoring

Each query scored by how many models run it, prioritize high-consensus gaps first.

Model-level breakdown

See exactly which queries each model runs and where they diverge.

Query history

Track how fan-out patterns change over time as AI models are updated.

Copy-all export

Export the full query list to use in your content planning or keyword tools.

Example query pills

Start instantly with pre-loaded topic examples across common B2B categories.

Common questions

Fan-out queries explained

What is a fan-out query?

When an AI model receives a question, it doesn't answer from its training data alone. It fires multiple background searches, called fan-out queries, to gather specific, current information. These are the real queries that determine what content AI models surface and which businesses they recommend.

Which AI models does the analyzer cover?

The Fan-Out Query Analyzer covers ChatGPT (GPT-4o via OpenAI Responses API), Claude, Perplexity, and Gemini. It shows both where models agree on their fan-out behavior and where they diverge.

How is this different from keyword research?

Traditional keyword research shows what humans type into Google. Fan-out query analysis shows what AI models search for when constructing responses. These are often completely different query sets, specific, comparison-focused, and structured around how AI evaluates vendors rather than how humans discover them.

How often do fan-out queries change?

Fan-out behavior shifts as AI models are updated and as new content enters their knowledge base. Faro lets Pro and Agency users run the analyzer as often as needed and tracks changes in fan-out patterns over time.

How do I use fan-out queries to improve AI citations?

Each fan-out query surfaces a content gap on your site. If ChatGPT searches for a specific comparison when someone asks about your category, and your site doesn't address that comparison, ChatGPT will find a competitor that does. Publish content that directly answers each fan-out query to move into contention for AI citations.

Is this tool available on the free plan?

The Fan-Out Query Analyzer is a Pro feature. You can explore Faro's free AI Readiness Scan without signing up, and upgrade to Pro to unlock the full analyzer with query history and cross-model comparison.

Related tools

AI Readiness Scan

Score your site across 30+ AI visibility checks.

Vertical AI Leaderboard

Pro

See where brands rank in AI responses by category.

OKF Generator

Build the machine-readable knowledge bundle AI agents need.

Find out what AI is searching
for in your category

Run your first fan-out analysis. Upgrade to Pro to unlock query history, model comparison, and the full Faro toolkit.

Get started freeSee Pro pricing