Query Fan-Out Analysis

What Query Fan-Out Means

When a user types "best CFD brokers UK" into Google AI Overviews or ChatGPT search, the system does not treat it as a single question. It decomposes the query into a tree of sub-intents — anywhere from 8 to 40 specific questions that a fully satisfying answer must address. This decomposition process is called query fan-out.

Google's AI-powered search, Perplexity, and ChatGPT all use query fan-out internally before selecting which passages to retrieve. A page that addresses only the surface-level intent ("here are some brokers") will be outscored by a page that addresses the full fan-out tree ("here are brokers, here's how regulation works, here are the fees per instrument class, here's what leverage limits apply under ESMA"). The difference between the two is measurable topical coverage.

The Five Priority Levels (P1–P5)

Sub-intents in a fan-out tree are not equally important. They are classified into five priority levels based on how directly they relate to the central query intent:

• P1 — Core intent: The primary question the user is asking. A page that doesn't address P1 is irrelevant. Example for "best CFD brokers UK": "Which CFD brokers are regulated in the UK?"
• P2 — Required context: Information the user needs to evaluate the P1 answer. Example: "What does CFD regulation by the FCA mean for traders?" Without understanding regulation, broker rankings are meaningless.
• P3 — Expected depth: Sub-intents that sophisticated users expect to find. Example: "What is the maximum leverage available for CFD trading under ESMA rules?" Top-ranking pages address these; lower-ranking pages skip them.
• P4 — Differentiating detail: Sub-intents that separate expert content from generic content. Example: "How do margin requirements differ between CFD brokers for illiquid stocks?" Only pages with real depth address these.
• P5 — Peripheral coverage: Related questions at the edge of the topic scope. Example: "Can I trade CFDs through an ISA account?" Covers this topic for completeness but not the primary intent.

How to Perform Fan-Out Analysis Manually

Manual fan-out analysis uses five data sources to build a comprehensive sub-intent map for any target keyword:

1. Google's People Also Ask (PAA) — click "Show more" repeatedly on the SERP. Each question is a confirmed P1–P3 sub-intent that Google has validated as related to the query.
2. Autocomplete and related searches — the "Searches related to" section at the bottom of the SERP, plus autocomplete variations ("best CFD brokers UK reddit," "best CFD brokers UK for beginners").
3. Competitor H2/H3 headings — open the top 5 ranking pages. Every H2 and H3 heading represents a sub-intent that page's author identified as necessary for completeness.
4. Forum research — Reddit, Quora, and niche forums contain unfiltered questions actual users ask. These are often P4–P5 sub-intents that generic competitors miss.
5. Schema FAQ sections — existing FAQPage schema on competitor pages reveals which questions they've explicitly mapped to their content.

Mapping Fan-Out to Content Structure

Once the fan-out tree is built, map each sub-intent to a specific content block on the target page. The mapping follows this rule: P1 sub-intents get H2 sections with full coverage; P2 and P3 sub-intents get H3 subsections or callout boxes; P4 sub-intents are addressed within existing sections rather than given their own headings; P5 sub-intents belong in FAQ sections at the bottom of the page.

A content brief built from fan-out analysis specifies which sub-intents each section must address, preventing writers from producing topically shallow content that looks long but covers few actual sub-intents.

Fan-Out Gap Analysis vs. Competitors

Fan-out gap analysis compares which sub-intents your page covers against which sub-intents each competitor covers. The gap — sub-intents in competitor pages not in yours — directly predicts which topics to add to catch up or overtake a competitor in AI-powered search results.

Build a gap table: rows are all identified fan-out sub-intents, columns are your page and each competitor. Mark each cell with coverage level (0 = not covered, 1 = mentioned, 2 = fully addressed). Pages with the most 2s in the most cells win AI-era topical authority.

The last row — "margin closeout rules" — is a P3 sub-intent that no competitor covers. Adding it creates a differentiation gap that no current page can compete with. This is the most valuable output of fan-out analysis: identifying P3–P4 sub-intents where you can be the first comprehensive source.