Viral Pattern Analysis

Jenny describes a systematic approach to researching and analyzing viral content patterns through manual tracking and data analysis to understand what drives video performance.

Key Components:

• Daily Content Analysis:

  • Watch trending shorts every morning and night
  • Monitor trending page systematically
  • Allow algorithm to optimize feed for trending content discovery

• Data Collection System:

  • Manually label videos with specific attributes
    • Content type (family, malicious, wholesome)
    • Specific elements (mentions of YouTube, calls to subscribe)
    • Video components and techniques used
  • Track performance metrics for each attribute

• Performance Analysis:

  • Compare subscriber conversion rates across different content types
  • Analyze view counts relative to channel averages
  • Identify outlier videos that significantly outperform baseline
  • Track correlation between content elements and performance

• Insight Generation:

  • Create graphs and charts to visualize performance patterns
  • Identify which elements drive subscriber growth
  • Calculate true impact by considering both conversion rates and view counts
  • Use insights to optimize future content strategy

• Key Metrics Focus:

  • View versus swipe away percentage (targeting 80-85%)
  • Retention rates (aiming for 90-95%)
  • Subscriber conversion rates
  • Relative performance compared to channel average