--- name: Analytics Learning tier: 4 load_policy: conditional description: Process YouTube analytics to extract actionable insights version: 1.0.0 parent_skill: growth-learning --- # Analytics Learning Skill > **Data-Driven Improvement** This skill processes YouTube Studio analytics to understand what works and improve future sessions. --- ## Purpose Extract actionable insights from performance data and update the knowledge base. --- ## Command ```bash /learn-analytics session-name ``` --- ## Input Data User provides from YouTube Studio: | Metric | Description | |--------|-------------| | Views | Total view count | | Watch Time | Total hours watched | | Average View Duration | Mean watch time | | Retention % | % of video watched | | Likes / Dislikes | Engagement signals | | Comments | Comment count | | Shares | Social shares | | Subscribers Gained | New subscriptions | | Impressions | How often shown | | CTR | Click-through rate | --- ## Analysis Process ### 1. Benchmark Comparison Compare session metrics to portfolio averages: | Metric | This Session | Average | Verdict | |--------|--------------|---------|---------| | Retention | 48% | 42% | Above average | | Like Ratio | 6.2% | 5.8% | Slightly above | | Comments | 24 | 18 | Above average | ### 2. Pattern Identification Correlate session attributes with performance: | Attribute | Correlation | |-----------|-------------| | Topic: Healing | +15% retention | | Duration: 25 min | Optimal | | Voice: Neural2-H | Consistent | | Binaural: Theta | +8% engagement | ### 3. Insight Extraction Generate specific, actionable findings: ```yaml - finding: "Healing topics achieve higher retention" evidence: "62% vs 45% average across 5 sessions" action: "Prioritize healing themes" confidence: high timestamp: "2025-01-15" ``` ### 4. Knowledge Update Store in `knowledge/lessons_learned.yaml`: ```yaml lessons: - id: "LESSON-2025-001" category: "content" finding: "Healing topics achieve higher retention" evidence: "62% vs 45% average across 5 sessions" action: "Prioritize healing themes" confidence: high sessions_analyzed: - "inner-child-healing" - "heart-chakra-restore" - "grief-release-theta" date_discovered: "2025-01-15" date_validated: null ``` --- ## Retention Analysis ### Retention Curve Patterns | Pattern | Meaning | Action | |---------|---------|--------| | Steep initial drop | Poor hook/intro | Improve pre-talk | | Drop at 5-7 min | Induction too slow | Tighten pacing | | Steady through journey | Good engagement | Maintain approach | | Drop at integration | Exit feels abrupt | Smooth emergence | ### Target Retention by Section | Section | Target Retention | |---------|------------------| | Pre-Talk (0-3 min) | 90%+ | | Induction (3-8 min) | 75%+ | | Journey (8-22 min) | 55%+ | | Integration (22-28 min) | 45%+ | | Close (28-30 min) | 40%+ | --- ## Engagement Analysis ### Like Ratio Interpretation | Like Ratio | Interpretation | |------------|----------------| | >10% | Exceptional resonance | | 6-10% | Strong positive response | | 4-6% | Normal engagement | | <4% | Review content quality | ### Comment Analysis Signals | Signal | Meaning | |--------|---------| | Emotional sharing | Deep impact | | Questions | Interest but confusion | | Requests | Unmet needs | | Criticism | Quality issues | --- ## Session Attribute Tracking For each session, track: ```yaml session_attributes: topic: "healing" sub_topic: "inner_child" duration: 25 depth_level: "Layer2" voice_id: "en-US-Neural2-H" binaural_target: "theta" archetypes: - "Guide" - "Healer" imagery_style: "eden_garden" metrics: views: 1250 watch_time_hours: 312 avg_view_duration: "14:58" retention_percent: 48 likes: 78 dislikes: 2 comments: 24 shares: 12 subs_gained: 15 impressions: 8500 ctr: 14.7 ``` --- ## Confidence Levels | Level | Definition | |-------|------------| | `high` | 5+ sessions, consistent pattern | | `medium` | 3-4 sessions, emerging pattern | | `low` | 1-2 sessions, hypothesis only | --- ## Output After analysis: 1. **Summary Report**: Key findings with evidence 2. **Knowledge Update**: New entries in `lessons_learned.yaml` 3. **Recommendations**: Actions for next sessions 4. **Questions**: Areas needing more data --- ## Related Resources - **Skill**: `tier4-growth/feedback-integration/` (comment analysis) - **Knowledge**: `knowledge/lessons_learned.yaml` - **Knowledge**: `knowledge/analytics_history/`