ds@mcpanalytics.aiA data scientist you can email your data and question to, and get a reliable response. Not AI slop.A data scientist you can email. Not AI slop.
Upload your survey CSV, pick the 0-10 score column, and get NPS with a real 95% confidence interval, the promoter/passive/detractor mix, and honest segment comparisons. Free.
Free analyses run on up to 10,000 rows. Larger files are randomly sampled to that size, so sign up to analyze your full dataset.
Scoring promoters, passives, and detractors...
Sent to . Inside: NPS with 95% confidence interval, score distribution, promoter/passive/detractor mix, segment comparison, R code, and AI insights.
Analyze another fileResponses are classified on the standard NPS scale: promoters score 9-10, passives 7-8, detractors 0-6. NPS = % promoters minus % detractors, stated as a point score from -100 to +100. The 95% confidence interval uses the classical multinomial variance formula Var(NPS) = (p_promoter + p_detractor - (p_promoter - p_detractor)^2) / n. With a segment column mapped, each segment gets its own NPS and interval, and the best and worst segments are compared with a two-proportion-style z-test — only when both have at least 30 responses.
Use it whenever you have raw answers to the 0-10 'how likely are you to recommend us' question and want the score, its real margin of error, and honest segment comparisons.
Not for 1-5 star ratings or CSAT scales (NPS is defined on 0-10 only), and not for tracking NPS over time — use a time-series or control-chart analysis for trend questions.
Built for: Product, CX, and marketing teams reading NPS surveys
Typical data source: A survey export with one 0-10 score per respondent, often with a plan/region/segment column
One 0-10 score per respondent, optionally with a segment. For example, a post-purchase survey:
Minimum 10 rows · Best with 100-50,000 responses and 2-8 segments
Standard-library analysis: Net Promoter Score from a 0-10 likelihood-to-recommend column. Promoter / passive / detractor shares, the NPS point score with a proper 95% confidence interval, the full 0-10 score distribution, and per-segment NPS with a statistically honest best-vs-worst comparison. Works on any survey export: map the 0-10 score column, optionally a segment column.
The raw 0-10 responses as a bar chart — the shape behind the single NPS number.
The promoter/passive/detractor composition, per segment when mapped — whether the score is dragged by detractors or starved of promoters.
Each segment's NPS with sample size, confidence interval, and a low-sample flag — the honest segment comparison.
The formulas: NPS definition, the multinomial variance behind the interval, and the rules that keep small samples from over-claiming.
Plain-English interpretation of what the numbers mean, what's significant, and what to do next.
What is our NPS, really?
Map your 0-10 score column. You get the NPS point score with a proper 95% confidence interval — so a +23 on 40 responses reads as the rough estimate it is, not a precise number.
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data: R analyses, interactive reports, AI insights, and PDF export.
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CympleData Scientist Send me your data and question, I’ll send you the analytics. ds@mcpanalytics.ai
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