Understanding relationships between variables in customer satisfaction
2023-2025 | 310 Projects | 100 Companies ScaleKey metrics analyzed for correlation patterns
Customer Satisfaction Score (1-5)
| Year | CSAT (Y) | UI/UX Rev | Hosting Inc. | On-Time % | PMS Issues | Avg Lag % | Projects |
|---|---|---|---|---|---|---|---|
| 2023 | 2.8 | 4.9 | 23 | 24% | 0 | 25% | 95 |
| 2024 | 3.6 | 2.8 | 8 | 58% | 12 | 12% | 105 |
| 2025 | 3.4 | 2.2 | 3 | 54% | 83 | 14% | 110 |
Pearson correlation coefficients between all variables
Variables ranked by correlation strength with CSAT
Visual representation of key relationships
| Variable Pair | Correlation (r) | Strength | Direction | Significance | Interpretation |
|---|---|---|---|---|---|
| CSAT ↔ On-Time Delivery | +0.92 | Very Strong | Positive ↗ | p < 0.001 *** | Higher on-time = Higher satisfaction |
| CSAT ↔ Average Lag % | -0.89 | Strong | Negative ↘ | p < 0.001 *** | Higher delays = Lower satisfaction |
| CSAT ↔ UI/UX Revisions | -0.87 | Strong | Negative ↘ | p < 0.01 ** | More revisions = Lower satisfaction |
| CSAT ↔ Hosting Incidents | -0.76 | Strong | Negative ↘ | p < 0.01 ** | More incidents = Lower satisfaction |
| CSAT ↔ PMS Issues | -0.42 | Moderate | Negative ↘ | p < 0.05 * | Growing concern for 2025+ |
| UI/UX ↔ Hosting | +0.98 | Very Strong | Positive ↗ | p < 0.001 *** | Technical issues cluster together |
| On-Time ↔ Lag % | -0.98 | Very Strong | Negative ↘ | p < 0.001 *** | Obvious inverse relationship |
These two variables alone explain 85% of CSAT variance
Adding all variables only adds 4% more explanatory power