Retail & CX metrics glossary
NPS calculator: promoters, passives and detractors — your score, instantly.
NPS (Net Promoter Score) comes from a single question — "on a scale of 0 to 10, how likely are you to recommend us?" — and a simple subtraction: the percentage of promoters minus the percentage of detractors. A 9 or 10 makes a promoter; 7 or 8 is a passive (counted only in the total); 0 to 6 is a detractor. The result runs from −100 to +100.
Use the calculator below with the numbers from your latest survey and get the score instantly. Then keep reading for the score zones, the most common calculation mistakes, and the one limit no NPS ever escapes — it tells you whether customers would recommend you, never why. For the full guide to the metric (origins, relational vs transactional use, acting on the score), see our complete NPS guide.
NPS calculator
NPS = % promoters − % detractors
promoters = 9–10 answers on the recommendation question · passives = 7–8 answers — excluded from the subtraction, counted in the total · detractors = 0–6 answers
NPS calculator
A retail chain collects 530 survey responses in a month: 320 promoters, 130 passives and 80 detractors. NPS = ((320 − 80) ÷ 530) × 100 = 45. Note that the 130 passives add no points either way, but they do grow the denominator — which is why converting passives into promoters lifts the score twice: it adds to the numerator and improves the ratio.
What is a good NPS? The score zones
The common reading divides the −100 to +100 scale into four zones. Use them as a first reference — then compare against your own history and your industry:
| Excellence zone | 75 to 100 |
|---|---|
| Quality zone | 50 to 74 |
| Improvement zone | 0 to 49 |
| Critical zone | −100 to −1 |
Zones are a market convention, not a standard: averages vary widely by industry (telcos run far below specialty retail, for instance). The most honest comparison is against your own series, collected with the same method.
How to calculate NPS step by step
First, collect answers to the recommendation question on a 0–10 scale. Then classify: 9–10 promoters, 7–8 passives, 0–6 detractors. Divide promoters by total responses, do the same for detractors, and subtract the two percentages — the difference, in points, is your NPS. The calculator above runs exactly that.
Two method disciplines matter more than any benchmark: sample size and consistency. Scores computed on few responses swing violently — below ~100 responses per period, treat the number as directional. And changes in survey timing (right after purchase vs days later), channel or incentive move the score without the experience changing — only compare periods measured the same way.
The most common mistakes (in the math and in the reading)
The classic mistake is reading NPS as a percentage — it is a difference in points, and it can be negative. Another is dropping passives from the denominator, which inflates the score. And there is the reading error: the same 45 can come from 45% promoters and 0% detractors, or from 65% against 20% — very different operations behind the same number. Always look at the composition, not just the result.
Finally, beware score-chasing: coaching customers to "give us a 10" at the counter, filtering who receives the survey, or only surveying buyers distorts the thermometer. An inflated NPS doesn't improve the operation — it just hides the problem for another quarter.
The limit: NPS tells you whether they'd recommend you — never why
NPS is an excellent loyalty thermometer and a poor diagnostic. When the score drops, it doesn't say what caused the drop: price, queue, the seller's approach, a refused exchange? The answer isn't in the number — it lives in the interactions that happened in the store before the customer picked a score.
That is also why stores with a high NPS can convert poorly: the customer who bought and was well served recommends you — but the survey never hears the majority who walked out without buying. NPS measures the loyalty of those who stayed; it cannot see the sale that never happened.
NPS tells you if customers would recommend you. We show you why.
Cognifyze captures the in-person sales interaction — with consent, without identifying any individual shopper — and turns every conversation into the diagnosis the score can't give: what was asked, what was offered, where the experience got stuck. NPS points at the fever; the interaction shows the cause.
In measured deployments, making the interaction visible moved same-store conversion from 51.5% to 79.5% (+28pp, p<0.001), with 383% ROI and payback in 1.4 months.
Find out what's behind your score — book an executive diagnostic.
Related metrics and guides
NPS calculator — frequently asked questions
What is the NPS formula?
NPS = percentage of promoters (9–10) minus percentage of detractors (0–6), both computed over total responses. Passives (7–8) count in the total but add nothing either way. The result runs from −100 to +100 and is read in points, not as a percentage.
Can NPS be negative?
Yes — whenever detractors outnumber promoters. A negative NPS means your base holds more people inclined to speak against the brand than to recommend it, and it usually signals a structural experience problem rather than one bad month.
How many responses do I need for a reliable NPS?
As a practical rule, treat scores built on fewer than ~100 responses per period as directional: with small samples, two or three angry customers move the score by ten points. Aggregate small stores over longer windows before comparing units or paying bonuses on the number.
What is the difference between relational and transactional NPS?
Relational NPS asks about the brand as a whole, periodically (quarterly, twice a year). Transactional NPS asks right after a specific interaction — a purchase, an exchange, a service contact — and can be attributed to a store and a moment. Mature retailers run both, without mixing the series.
NPS or CSAT: which should I use?
Both, for different questions: CSAT measures satisfaction with a specific interaction and is the operational thermometer per store and shift; NPS measures willingness to recommend the brand and works as the relational gauge. What neither answers is what happened in the interaction that produced the score.