Move from dashboard charts to defensible statistical analysis
Analyze weighted estimates, significance, regression, experiments, reliability, factor structure, key drivers, and trends while exposing assumptions and calculation details.
Recommended test
Weighted proportion comparison
Comparing satisfaction between two regions with survey weights and unequal sample sizes.
Significance & intervals
Proportions, means, t-tests, chi-square, ANOVA, confidence intervals, and effect sizes.
Regression
Linear, logistic, and ordinal models with readable diagnostics and exportable specifications.
Survey design
Weights, strata, clusters, PSU, design effects, effective sample size, and weighted estimates.
Reliability & factors
Cronbach alpha, item-total diagnostics, exploratory factor analysis, and scale review.
Key drivers
Estimate which experience attributes are most strongly associated with NPS, CSAT, retention, or other outcomes.
Experimental analysis
Treatment-control comparisons, uplift, confidence intervals, assignment metadata, and predefined outcomes.
Identify the strongest improvement opportunity
Show the math and the data lineage
- View assumptions and model settings
- See included/excluded cases
- Trace weights and filters
- Export analysis-ready scripts
- Link narrative conclusions to supporting outputs