> ## Documentation Index
> Fetch the complete documentation index at: https://docs.superlines.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Competitive Intelligence

> Use fan-out queries, citations, and competitor analysis to reverse-engineer what works and improve your AI search visibility.

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.

## The competitive intelligence loop

<Steps>
  <Step title="Track prompts in your market">
    Your tracked prompts generate responses across AI engines. Each response contains data about who gets mentioned and cited.
  </Step>

  <Step title="Analyze fan-out queries">
    See what web searches AI engines perform behind the scenes. This reveals the *real* queries that drive AI citations.
  </Step>

  <Step title="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.
  </Step>

  <Step title="Reverse-engineer winning content">
    Analyze the top-cited URLs to understand what makes them win — then create better content for those topics.
  </Step>

  <Step title="Monitor improvement">
    Track your visibility and citation changes over time as your content improves.
  </Step>
</Steps>

***

## Fan-out queries as competitive signals

[Fan-out queries](/metrics/citations#what-are-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.

### What fan-out queries reveal

| Insight                             | How to use it                                                        |
| ----------------------------------- | -------------------------------------------------------------------- |
| **Which searches drive AI answers** | Optimize your content for these specific queries                     |
| **Your domain's ranking per query** | Identify where you rank well vs. where you're invisible              |
| **Competitor rankings**             | See which competitors dominate the searches AI engines use           |
| **Content gaps**                    | Discover fan-out queries where no one in your space has good content |

### Reading fan-out query data

When you view fan-out query insights (via the dashboard or the `get_fanout_query_insights` [MCP tool](/mcp/tools#get_fanout_query_insights)), 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

<Tip>
  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.
</Tip>

***

<h2 id="competitive-gap-analysis">
  Competitive gap analysis
</h2>

The competitive gap analysis reveals where competitors consistently outperform you.

### 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

### Using the MCP server

The `get_competitive_gap` tool provides programmatic access to gap analysis:

```
"Show me prompts where my competitors lead and I have low visibility,
 and recommend which ones to prioritize for content creation."
```

This returns prompts ranked by gap size, with AI-powered recommendations for how to close each gap.

***

## Reverse-engineering competitor content

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

### 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.

### Step 2: Audit the winning content

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

| Analysis tool                                                       | What it reveals                                                   |
| ------------------------------------------------------------------- | ----------------------------------------------------------------- |
| **[`analyze_competitor_url`](/mcp/tools#analyze_competitor_url)**   | Comprehensive content analysis with recommendations for competing |
| **[`webpage_audit`](/mcp/tools#webpage_audit)**                     | Technical and content quality audit                               |
| **[`webpage_analyze_content`](/mcp/tools#webpage_analyze_content)** | Content structure, tone, and writing quality                      |
| **[`schema_optimizer`](/mcp/tools#schema_optimizer)**               | Schema.org markup that may be boosting their citations            |

### 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

***

## Content opportunity prioritization

Not all competitive gaps deserve equal investment. Prioritize based on:

| Factor                        | Higher priority                                              | Lower priority                |
| ----------------------------- | ------------------------------------------------------------ | ----------------------------- |
| **Prompt importance**         | Strategic prompts with high market relevance                 | Low-volume monitoring prompts |
| **Gap size**                  | Competitors have 80%+ visibility, you have \<20%             | Small visibility differences  |
| **Fan-out query opportunity** | You rank for none of the fan-out queries                     | You already rank for some     |
| **Content feasibility**       | Topic is in your expertise area                              | Requires new domain expertise |
| **Citation potential**        | Engines that cite sources (Perplexity, Copilot) are involved | Mostly offline models         |

<Info>
  Use `find_content_opportunities` via the [MCP server](/mcp/tools#find_content_opportunities) to get an automated prioritization of topics with high query volume and low brand visibility.
</Info>

***

## Automating competitive intelligence

For ongoing competitive monitoring, use [MCP automation workflows](/mcp/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](/mcp/workflows) page for ready-to-use workflow examples.

***

## From intelligence to action

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

```
Fan-out query analysis → Identify gaps → Audit competitor content
    → Create content brief → Produce content → Publish
        → Monitor in Superlines → Iterate
```

<CardGroup cols={2}>
  <Card title="MCP Workflows" icon="robot" href="/mcp/workflows">
    Automate the competitive intelligence pipeline with AI agents.
  </Card>

  <Card title="Citations & Fan-out Queries" icon="link" href="/metrics/citations">
    Deep-dive into how citations and fan-out queries work.
  </Card>
</CardGroup>