🎯 Satisfaction Analysis
What makes a session great? Regression analysis, interaction effects, and sweet spots.
Generated August 12, 2026 · 137 sessions · avg 8.68/10
💡 Recommendations
📊 What Predicts Satisfaction?
Stepwise regression adds components by marginal R² contribution. Higher bars = more unique predictive power after accounting for other components.
Note: Only components with ΔR² ≥ 0.005 are shown. Correlation (r) shows raw relationship; ΔR² shows unique explanatory power after accounting for other predictors.
🎯 Sweet Spots
Optimal ranges for each DNA component that maximize satisfaction. Based on sliding window analysis across all sessions.
Productivity
Ambition
Depth
Growth
Variety
Flow
Consistency
🏆 Top 20% vs Bottom 20%
DNA profile comparison between the 27 highest-satisfaction sessions (avg 9.04/10) and 27 lowest (avg 7.96/10).
🔀 Interaction Effects
How pairs of DNA components interact to affect satisfaction. Synergy means both high is better than expected; antagonism means they work against each other.
📈 How Satisfaction Drivers Change Over Time
Sessions split into three phases. Satisfaction drivers shift as the practice matures.