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

# Data Collection

> Deep dive into how GenTrackr collects and analyzes AI visibility data

## Collection Process

GenTrackr runs automated queries across AI platforms to track your app's visibility. Here's exactly how it works:

<Steps>
  <Step title="Query Generation">
    We generate relevant queries based on:

    * Your app's category and features
    * Common user search patterns
    * Competitor landscape
    * Trending topics in your niche

    **Example queries for a meditation app**:

    * "best meditation app for beginners"
    * "apps to reduce anxiety"
    * "compare headspace vs calm"
    * "meditation timer app recommendations"
  </Step>

  <Step title="Automated Execution">
    Our system submits these queries to each AI platform daily:

    * **ChatGPT**: Web version with GPT-4
    * **Claude**: Claude.ai interface
    * **Perplexity**: Perplexity.ai search
    * **Gemini**: Google Gemini interface

    All interactions simulate real user behavior to capture authentic responses.
  </Step>

  <Step title="Response Capture">
    We record complete AI responses including:

    * Full text content
    * App mentions (direct and indirect)
    * Source citations
    * Context and recommendations
    * Timestamp and platform metadata
  </Step>

  <Step title="Data Analysis">
    Each response is analyzed for:

    * **Mention Detection**: Is your app mentioned?
    * **Sentiment Analysis**: How is it described?
    * **Ranking Position**: Order in recommendations
    * **Feature Highlights**: Which features are mentioned?
    * **Competitive Context**: Who else is mentioned?
  </Step>
</Steps>

## Query Categories

We organize queries into strategic categories to provide comprehensive visibility insights:

### Feature-Based Queries

Queries focused on specific app capabilities.

<CodeGroup>
  ```text Timer Features theme={null}
  "meditation timer app"
  "app with customizable meditation timers"
  "best pomodoro timer for focus"
  ```

  ```text Social Features theme={null}
  "meditation app with community"
  "apps to meditate with friends"
  "social wellness apps"
  ```
</CodeGroup>

### Use Case Queries

Queries about solving specific user problems.

<CodeGroup>
  ```text Anxiety Relief theme={null}
  "apps to help with anxiety"
  "stress relief meditation app"
  "best app for panic attacks"
  ```

  ```text Sleep Improvement theme={null}
  "meditation app for sleep"
  "bedtime relaxation apps"
  "insomnia help apps"
  ```
</CodeGroup>

### Comparison Queries

Direct competitive comparison requests.

<CodeGroup>
  ```text Head-to-Head theme={null}
  "headspace vs calm"
  "compare meditation apps"
  "best alternative to [competitor]"
  ```

  ```text Category Leaders theme={null}
  "top 5 meditation apps"
  "most popular wellness apps"
  "highest rated mindfulness apps"
  ```
</CodeGroup>

## Data Frequency

<Note>
  **Query Volume by Plan**

  * **Starter**: 500 queries/day across all platforms
  * **Pro**: 2,000 queries/day with advanced categories
  * **Studio**: 5,000+ queries/day with custom query sets
</Note>

| Activity          | Frequency |
| ----------------- | --------- |
| Query execution   | Daily     |
| Data updates      | Real-time |
| Trend calculation | Hourly    |
| Competitor sync   | Daily     |
| Report generation | Weekly    |

## What Gets Tracked

### Direct Metrics

<AccordionGroup>
  <Accordion title="Mention Count" icon="hashtag">
    Total number of times your app is mentioned by name across all queries and platforms.

    **Tracked**: Daily, weekly, monthly aggregates
  </Accordion>

  <Accordion title="Visibility Score" icon="eye">
    Percentage of relevant queries where your app appears.

    **Formula**: (Queries mentioning your app / Total queries run) × 100
  </Accordion>

  <Accordion title="Citation Frequency" icon="quote-left">
    How often AI models cite your app store listing or reviews as sources.

    **Includes**: App Store reviews, feature descriptions, screenshots
  </Accordion>

  <Accordion title="Ranking Position" icon="ranking-star">
    Average position when your app is mentioned in lists.

    **Example**: Mentioned 2nd in "top meditation apps" = position 2
  </Accordion>
</AccordionGroup>

### Sentiment Metrics

<AccordionGroup>
  <Accordion title="Feature Attribution" icon="list-check">
    Which features AI associates with your app.

    **Tracked**: Most mentioned features, feature sentiment, competitive differentiation
  </Accordion>

  <Accordion title="Use Case Association" icon="bullseye">
    What problems AI thinks your app solves.

    **Example**: "anxiety relief", "sleep improvement", "mindfulness training"
  </Accordion>

  <Accordion title="Sentiment Tone" icon="face-smile">
    Overall tone of AI mentions (positive, neutral, negative).

    **Analyzed**: Language patterns, recommendation strength, comparison context
  </Accordion>
</AccordionGroup>

### Competitive Metrics

* Apps frequently mentioned alongside yours
* Queries where competitors appear but you don't
* Competitive win rate (you vs specific competitors)
* Share of voice in your category

## Data Storage & History

<Info>
  **Data Retention**

  * **Starter**: 30 days of detailed data, 90 days of aggregates
  * **Pro**: 180 days detailed, 365 days aggregates
  * **Studio**: Unlimited retention
</Info>

All data is:

* Encrypted at rest and in transit
* Backed up daily
* Accessible via dashboard and API
* Exportable to CSV/JSON

## Quality Assurance

We ensure data accuracy through:

### Automated Validation

* Response completeness checks
* Duplicate detection
* Error handling and retries
* Platform availability monitoring

### Manual Auditing

* Weekly spot checks of query results
* Monthly quality reviews
* User-reported issue investigation
* Continuous algorithm improvement

## Privacy & Ethics

<Warning>
  **Important: Public Data Only**

  GenTrackr only collects publicly available AI responses. We never:

  * Access user accounts or private data
  * Track individual users
  * Collect personal information
  * Store user queries to AI platforms
</Warning>

Our data collection complies with:

* All platform terms of service
* GDPR and international privacy laws
* Ethical web scraping practices
* Industry data collection standards

## Next Steps

<CardGroup cols={2}>
  <Card title="AI Platforms" icon="robot" href="/essentials/ai-platforms">
    Learn about each platform we track
  </Card>

  <Card title="Tracking Visibility" icon="chart-line" href="/essentials/tracking-visibility">
    How to interpret your visibility data
  </Card>
</CardGroup>