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:

1. 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”
2. 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.

3. 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
4. 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?

Query Categories

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

Feature-Based Queries

Queries focused on specific app capabilities.

Timer Features

"meditation timer app"
"app with customizable meditation timers"
"best pomodoro timer for focus"

Use Case Queries

Queries about solving specific user problems.

Anxiety Relief

"apps to help with anxiety"
"stress relief meditation app"
"best app for panic attacks"

Comparison Queries

Direct competitive comparison requests.

Head-to-Head

"headspace vs calm"
"compare meditation apps"
"best alternative to [competitor]"

Data Frequency

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

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

What Gets Tracked

Direct Metrics

Mention Count

Total number of times your app is mentioned by name across all queries and platforms.

Tracked: Daily, weekly, monthly aggregates

Visibility Score

Percentage of relevant queries where your app appears.

Formula: (Queries mentioning your app / Total queries run) × 100

Citation Frequency

How often AI models cite your app store listing or reviews as sources.

Includes: App Store reviews, feature descriptions, screenshots

Ranking Position

Average position when your app is mentioned in lists.

Example: Mentioned 2nd in “top meditation apps” = position 2

Sentiment Metrics

Feature Attribution

Which features AI associates with your app.

Tracked: Most mentioned features, feature sentiment, competitive differentiation

Use Case Association

What problems AI thinks your app solves.

Example: “anxiety relief”, “sleep improvement”, “mindfulness training”

Sentiment Tone

Overall tone of AI mentions (positive, neutral, negative).

Analyzed: Language patterns, recommendation strength, comparison context

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

Data Retention

• Starter: 30 days of detailed data, 90 days of aggregates
• Pro: 180 days detailed, 365 days aggregates
• Studio: Unlimited retention

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

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

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

AI Platforms

Learn about each platform we track

Tracking Visibility

How to interpret your visibility data