diegosouzapw 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
/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:
- 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:
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:
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:
- Summary Report: Key findings with evidence
- Knowledge Update: New entries in
lessons_learned.yaml - Recommendations: Actions for next sessions
- Questions: Areas needing more data
Related Resources
- Skill:
tier4-growth/feedback-integration/(comment analysis) - Knowledge:
knowledge/lessons_learned.yaml - Knowledge:
knowledge/analytics_history/