# Spark POC Research Findings

## Project Goal
Recreate similar functionality to MonkIQ using Clockworks APIs from Apify platform.

## MonkIQ Analysis

### What is MonkIQ?
- **Target Market**: Global music analytics SaaS platform serving major record labels
- **Core Focus**: Music analytics tools trusted by world's top record labels
- **Team Structure**: 100% remote, small energetic team
- **Value Proposition**: Translating complex data into simple 'aha' moments, spotting growth opportunities, and maintaining strong relationships

### Functionality (Inferred)
Based on the limited information and context as a music analytics platform:
- Music performance tracking and analytics
- Data visualization for music industry professionals
- Growth opportunity identification
- Relationship management tools for labels and artists

## Clockworks APIs (Apify) Analysis

### Available TikTok Scrapers
1. **TikTok Scraper** (Main comprehensive scraper)
   - Profiles, hashtags, posts extraction
   - Music metadata extraction
   - Video metadata
   - User data (followers, hearts, shares)

2. **TikTok Sound Scraper**
   - Specific sound/music URL analysis
   - Extract videos using specific sounds
   - Music metadata including:
     - Name, author, album
     - Original sound detection
     - Music ID

3. **TikTok Profile Scraper**
   - User profile-specific data extraction

4. **TikTok Video Scraper**
   - Individual video data extraction

5. **TikTok Discover/Explore Scrapers**
   - Trending content discovery

### Music Data Extraction Capabilities
- **Music Metadata**: Name, author, album, ID, original sound status
- **Performance Metrics**: Likes, shares, views, hearts
- **Usage Analytics**: Videos using specific sounds
- **Creator Data**: Associated with music usage
- **Hashtag Analysis**: Music-related trending tags

### API Features
- **Export Formats**: HTML, JSON, CSV, Excel, XML
- **API Access**: Full programmatic control via Apify API
- **Scheduling**: Automated runs and monitoring
- **Integration**: Compatible with other tools

## POC Opportunity Assessment

### Potential MonkIQ Recreation Features
1. **Music Trend Analysis**
   - Track popular sounds/music on TikTok
   - Identify emerging musical trends
   - Monitor music performance metrics

2. **Artist/Label Analytics**
   - Track how music is being used across TikTok
   - Analyze engagement patterns
   - Monitor viral potential

3. **Competitive Intelligence**
   - Compare music performance
   - Identify successful music strategies
   - Track competitor music usage

4. **Growth Opportunity Identification**
   - Emerging sounds and trends
   - Underutilized music with viral potential
   - Cross-platform performance tracking

### Technical Implementation Approach
1. **Data Collection Layer**
   - Use Clockworks TikTok Sound Scraper for music-specific data
   - Use TikTok Scraper for comprehensive platform data
   - Implement scheduled data collection

2. **Analytics Engine**
   - Process extracted music metadata
   - Calculate performance metrics
   - Identify trending patterns

3. **Visualization Dashboard**
   - Simple, clear data presentation (following MonkIQ's "aha moments" philosophy)
   - Music performance charts
   - Trend identification

4. **Growth Opportunity Detection**
   - Algorithm to identify emerging music trends
   - Performance comparison tools
   - Actionable insights generation

## Next Steps for POC Development
1. Set up Apify account and test Clockworks APIs
2. Design minimal dashboard mockup
3. Implement basic data collection pipeline
4. Create simple analytics and visualization
5. Test with real TikTok music data

## Key Differentiators for POC
- Focus on TikTok-specific music analytics (vs broader platform coverage)
- Emphasis on actionable insights for labels/artists
- Simple, clear visualization approach
- Cost-effective alternative using public APIs