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Fan-out queries and citation data together form a powerful competitive intelligence system. They tell you exactly what content AI engines use when answering questions about your market — and where your competitors are winning.

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The competitive intelligence loop

1

Track prompts in your market

Your tracked prompts generate responses across AI engines. Each response contains data about who gets mentioned and cited.
2

Analyze fan-out queries

See what web searches AI engines perform behind the scenes. This reveals the real queries that drive AI citations.
3

Compare your position vs. competitors

For each fan-out query, see where your domain ranks relative to competitors. Identify where you’re strong and where you’re weak.
4

Reverse-engineer winning content

Analyze the top-cited URLs to understand what makes them win — then create better content for those topics.
5

Monitor improvement

Track your visibility and citation changes over time as your content improves.

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Fan-out queries as competitive signals

Fan-out queries are the web searches AI engines perform when answering a user’s question. They’re the bridge between AI prompts and traditional web content.

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What fan-out queries reveal

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Reading fan-out query data

When you view fan-out query insights (via the dashboard or the get_fanout_query_insights MCP tool), you see:
  • The fan-out query text — the actual search the AI engine performed
  • Your domain’s position — where your site appears in search results for that query
  • Competitor positions — where competitors rank
  • Citation impact — whether this query led to your domain being cited in the AI response
Focus on fan-out queries where competitors rank in the top positions but you’re absent or low. These are your highest-impact content opportunities.

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Competitive gap analysis

The competitive gap analysis reveals where competitors consistently outperform you.

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Using the dashboard

The Competitive Gap view shows prompts where:
  • Competitors have high visibility but you don’t
  • Competitors are cited but your domain isn’t
  • Competitor sentiment is more positive than yours

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Using the MCP server

The get_competitive_gap tool provides programmatic access to gap analysis:
This returns prompts ranked by gap size, with AI-powered recommendations for how to close each gap.

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Reverse-engineering competitor content

Once you’ve identified where competitors win, dig into why they win:

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Step 1: Find the winning URLs

Use Top Cited URL per Prompt (dashboard or get_top_cited_url_per_prompt via MCP) to see which specific URLs get cited most for each prompt.

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Step 2: Audit the winning content

For each top-cited URL, analyze what makes it successful:

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Step 3: Create a content brief

From your analysis, identify:
  • Content structure — how is the winning page organized?
  • Key topics covered — what specific questions does it answer?
  • Fan-out query alignment — does it rank for the fan-out queries AI engines use?
  • Technical advantages — better Schema.org markup, faster page load, clearer structure?
  • What’s missing — gaps you can fill to create an even better resource

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Content opportunity prioritization

Not all competitive gaps deserve equal investment. Prioritize based on:
Use find_content_opportunities via the MCP server to get an automated prioritization of topics with high query volume and low brand visibility.

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Automating competitive intelligence

For ongoing competitive monitoring, use MCP automation workflows:
  1. Weekly gap scan — automatically identify new prompts where competitors have gained ground
  2. Content audit pipeline — when a new competitor URL starts getting cited, automatically analyze it
  3. Strategic action plans — generate prioritized recommendations using generate_strategic_action_plan
See the MCP Automation Workflows page for ready-to-use workflow examples.

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From intelligence to action

The end-to-end flow from competitive intelligence to improved visibility:

MCP Workflows

Automate the competitive intelligence pipeline with AI agents.

Citations & Fan-out Queries

Deep-dive into how citations and fan-out queries work.