NPS Calculator

Total responses

total = detractors + passives + promoters

= 12 + 18 + 45

= 75 total responses

Sample size matters: NPS at n=75 has a ±23 margin of error at 95% confidence. Scores from fewer than 30 responses should be treated as directional only. Larger samples narrow the confidence interval and make movements statistically meaningful.

NPS statistical properties — Reichheld (2003); Satmetrix NPS methodology

Promoter %

promoterPct = promoters / total × 100

= 45 / 75 × 100

= 60.0% promoters (scores 9–10)

Promoters score 9–10 on "How likely are you to recommend?" They're your growth engine: on average, promoters make 4.2 referrals per year and have 14% higher lifetime value than passives (Bain & Co. research).

Promoter classification — Reichheld (2003), Harvard Business Review; Bain & Company NPS research

Passive %

passivePct = passives / total × 100

= 18 / 75 × 100

= 24.0% passives (scores 7–8)

Passives are satisfied but unenthusiastic — they dilute your score without contributing to it. They're vulnerable to competitive offers and represent your biggest conversion opportunity. One passive converted to a promoter adds 2 point to your NPS (since total increases by 1).

Detractor %

detractorPct = detractors / total × 100

= 12 / 75 × 100

= 16.0% detractors (scores 0–6)

Detractors actively harm your brand — Bain research shows they tell an average of 9–15 people about their negative experience. Resolving a detractor complaint has the highest ROI of any customer service action: a resolved complaint creates stronger loyalty than no complaint at all.

Detractor churn and word-of-mouth — Bain & Company, 'The Ultimate Question 2.0' (Reichheld & Markey)

NPS

NPS = % Promoters − % Detractors

= 60.0% − 16.0%

= +44 (Great)

Passives count toward the total (diluting both percentages) but don't appear in the score formula itself. A score of 44 means 60.0% of customers are active advocates minus 16.0% who may be spreading negative sentiment.

Net Promoter Score — Fred Reichheld, Bain & Company, Harvard Business Review (2003)

Statistical confidence interval

margin_of_error ≈ 196 / √n

= 196 / √75 = ±23 points

= NPS 44 ± 23 at 95% confidence

Your true NPS lies between 21 and 67 with 95% confidence. Changes of less than 46 points between surveys may be noise rather than signal. To halve the margin of error, quadruple your sample size.

Approximate 95% CI for NPS — based on standard error of proportional difference; Keiningham et al.

1 more promoter impact

ΔNPSpromoter = NPS(P+1, D, n+1) − NPS(P, D, n)

= 45 − 44

= +1 point per new promoter

Adding one promoter to your survey moves NPS by +1 points. This diminishes as n grows (law of large numbers). At n=75, each new promoter is worth 1 point; at n=1000 it would be worth less than 0.1 points.

Detractor-to-passive conversion impact

ΔNPS_convert = NPS(P, D−1, n) − NPS(P, D, n)

= 45 − 44

= +1 point per detractor converted to passive

Converting a detractor to a passive (not a promoter) yields 1 point — half the benefit of converting to a promoter (which would add ~2× as much). Detractor resolution is typically easier and faster than creating a new promoter from scratch.

Points to next tier (Excellent)

need NPS = 50 → gap = 50 − current

= 50 − 44 = 6 points

= Convert ≈ 3 detractors to passives to reach "Excellent"

"Excellent" starts at NPS 50. Converting 3 detractors to passives — through follow-up, service recovery, or product improvement — would move your score to the next classification tier.

NPS tiers — Bain & Company classification: <0 Needs Improvement, 0–29 Good, 30–49 Great, 50–69 Excellent, 70+ World Class

Overall Average industry benchmark

benchmarkDiff = yourNPS − Overall Average average

= 44 − 44

= +0 points vs Overall Average (44)

You beat the Overall Average industry average by 0 points. Maintain your lead by tracking which survey cohorts drive promoters and doubling down on what works.

Industry benchmarks — Satmetrix/Bain NPS Benchmarks 2024; Qualtrics XM Institute