1. Scope
Calculates NPS from promoter (9–10), passive (7–8), and detractor (0–6) counts and provides benchmark context. It is not a customer-satisfaction model and does not causally link NPS to revenue.
2. Inputs and outputs
Inputs
- promoters number
- passives number
- detractors number
Outputs
- nps
(promoters − detractors) / total × 100.
- sampleSize
Sum of all three groups.
- distribution
Percentage of each bucket.
Engine source: src/lib/net-promoter-score-calculator/engine.ts
3. Formula / scoring logic
total = promoters + passives + detractors
nps = ((promoters - detractors) / total) * 100 4. Assumptions
- Respondents are a random sample of customers. Survey-response bias (happy/angry customers respond more) is not corrected.
- The 0–6 / 7–8 / 9–10 buckets are the Reichheld-standard definitions.
5. Data sources
6. Known limitations
- NPS-to-growth correlation is disputed in the academic literature. See Keiningham et al. (2007) "A Longitudinal Examination of Net Promoter and Firm Revenue Growth" — Journal of Marketing — for a methodologically critical view.
- Small samples (< ~200) produce unstable NPS. Use confidence intervals, not point estimates.
- Cross-industry benchmarks are noisy; within-vertical peer comparisons are more informative.
7. Reproducibility
Input
promoters = 60, passives = 25, detractors = 15.
Expected output
total = 100, nps = 45, distribution = 60% / 25% / 15%.
8. Change log
- 2026-04-24 methodology page first published.
Worked example
Run live against the same engine this site ships
(/engines/net-promoter-score-calculator.js).
The inputs and outputs below are recomputed on every build and
independently re-verified in CI — they are never hand-authored.
Input
- tool
- net_promoter_score_calculator
- promoters
- 120
- passives
- 45
- detractors
- 35
- industry
- saas
Output
- totalResponses
- 200
- npsScore
- 42.5
- promoterPercent
- 60
- passivePercent
- 22.5
- detractorPercent
- 17.5
- classification
- Good
- benchmarkComparison.industry
- saas
- benchmarkComparison.industryLabel
- SaaS
- benchmarkComparison.benchmarkScore
- 41
- benchmarkComparison.delta
- 1.5
- benchmarkComparison.comparison
- Near benchmark
- trendGuidance
- Push from Good to Excellent by converting passives with onboarding and support improvements.
Frequently asked questions
- What does the Net Promoter Score (NPS) Calculator calculate?
- Calculates NPS from promoter (9–10), passive (7–8), and detractor (0–6) counts and provides benchmark context. It is not a customer-satisfaction model and does not causally link NPS to revenue.
- What inputs does the Net Promoter Score (NPS) Calculator need?
- It takes 3 inputs: promoters, passives, detractors. Outputs returned: nps, sampleSize, distribution.
- What formula does the Net Promoter Score (NPS) Calculator use?
- The exact computation is: total = promoters + passives + detractors; nps = ((promoters - detractors) / total) * 100
- Can I verify the Net Promoter Score (NPS) Calculator with a worked example?
- Yes. With promoters = 60, passives = 25, detractors = 15. the tool returns total = 100, nps = 45, distribution = 60% / 25% / 15%.
- Where does the Net Promoter Score (NPS) Calculator get its benchmark data?
- Reference data is sourced from: Reichheld, The One Number You Need to Grow, Harvard Business Review, 2003 (as of 2003).
- What can the Net Promoter Score (NPS) Calculator not tell me?
- Known limitations: NPS-to-growth correlation is disputed in the academic literature. See Keiningham et al. (2007) "A Longitudinal Examination of Net Promoter and Firm Revenue Growth" — Journal of Marketing — for a methodologically critical view. Small samples (< ~200) produce unstable NPS. Use confidence intervals, not point estimates. Cross-industry benchmarks are noisy; within-vertical peer comparisons are more informative.