ai-marketing-skills/yt-competitive-analysis

YouTube Competitive Analysis

Find what's actually working on YouTube. Analyzes any set of channels, identifies outlier videos (2x+ average views), and extracts packaging patterns from winners.

No manual spreadsheet work. No guessing. Data-driven competitive intel in minutes.

What It Does

1. Pulls recent videos from any YouTube channel(s)
2. Separates long-form from Shorts
3. Calculates per-channel averages
4. Flags outliers (videos performing 2x+ above the channel average)
5. Extracts title patterns from winners
6. Exports to console, JSON, or Google Sheets

Quick Start

# Set your YouTube API key
export YOUTUBE_API_KEY="your-key-here"

# Analyze specific channels
python3 analyze.py "$YOUTUBE_API_KEY" --channels "@AlexHormozi,@garyvee,@CodieSanchezCT"

# Use predefined channel sets
python3 analyze.py "$YOUTUBE_API_KEY" --set ai          # AI creator set
python3 analyze.py "$YOUTUBE_API_KEY" --set business    # Business creator set
python3 analyze.py "$YOUTUBE_API_KEY" --set both        # All channels

# Export to JSON for programmatic use
python3 analyze.py "$YOUTUBE_API_KEY" --set both --output json > results.json

# Custom lookback period
python3 analyze.py "$YOUTUBE_API_KEY" --channels "@mkbhd" --days 60

Setup

1. Get a YouTube Data API v3 key
2. Set it as an environment variable: export YOUTUBE_API_KEY="your-key"
3. Install dependencies: pip install -r requirements.txt

Output

Console (default)

================================================================================
  AI Creators — LAST 30 DAYS
================================================================================

📊 CHANNEL SUMMARY:
  Alex Hormozi             |  2,400,000 subs |  12 videos (3.0/wk) | L:  8 S:  4

🔥 LONG-FORM OUTLIERS (top 15):
  4.2x |  1,200,000 | [Alex Hormozi] How I'd Start a Business in 2025
       2025-01-15 | https://youtube.com/watch?v=...

📦 TOP TITLE PATTERNS:
   8x  business
   6x  money
   5x  started

JSON

Full structured data including all video metadata, scores, and multipliers.

Predefined Channel Sets

AI Creators: Jeff Su, Alex Finn, Riley Brown, Dan Martell, Matt Wolfe, Nate Herk, Grace Leung, Matt Berman

Business Creators: Alex Hormozi, Gary Vaynerchuk, Patrick Bet-David, Codie Sanchez, Leila Hormozi, Iman Gadzhi, My First Million

Edit the channel dictionaries in analyze.py to customize.

Interpreting Results

Metric	What It Means
Multiplier	How many times above channel average (2.0x = double normal)
Outlier threshold	2x average. Videos above this are worth studying.
Title patterns	Common words in outlier titles = proven formats
Cadence	Videos per week. Higher cadence may mean lower per-video averages.

Proven Packaging Formats

Based on outlier analysis, these title formats consistently overperform:

Long-form:

• "X, Clearly Explained" (definitive explainer)
• "X hours of Y in Z minutes" (condensed value)
• "The Laziest Way to X" (low-effort promise)
• "Give me X minutes and I'll Y" (time-boxed promise)
• "X INSANE Use Cases for Y" (listicle + power word)

Shorts:

• "2024 vs 2025 X" (year comparison)
• "Bad Good Great X" (tier ranking)
• "Stop doing X, do Y instead" (contrarian)

Weekly Automation

Run weekly to surface new outliers automatically:

# Cron: every Sunday at 8am
0 8 * * 0 YOUTUBE_API_KEY="your-key" python3 /path/to/analyze.py "$YOUTUBE_API_KEY" --set both --output json > /path/to/weekly-results.json

Requirements

• Python 3.8+
• YouTube Data API v3 key
• No external Python dependencies (uses only stdlib)

License

MIT

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