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Net Promoter Score (NPS) is a customer-feedback metric that summarizes how respondents rate their likelihood of recommending an organization, product, or service to a friend or colleague. On the standard 0–10 scale, respondents are grouped as promoters (9–10), passives (7–8), or detractors (0–6). NPS is the percentage of promoters minus the percentage of detractors, producing a score from −100 to +100. It describes the balance of those response groups; it does not explain why people answered as they did.
How NPS is calculated
Use the same set of valid survey respondents to calculate both percentages. Include every valid response—including passives—in the denominator:
NPS = percentage of promoters − percentage of detractors
Passives count toward the total number of respondents but are not added to either side of the subtraction. Bain & Company describes the measure as the percentage of promoters minus the percentage of detractors in its Net Promoter System methodology. Qualtrics documents the same calculation and scoring categories in its NPS question guide.
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Example
Suppose 100 valid respondents answer the question: 70 are promoters, 20 are passives, and 10 are detractors. Promoters make up 70% and detractors 10%, so the NPS is 70 − 10 = 60 points. It is not accurate to say that 60% of customers recommend the organization: NPS is a difference between two percentages, not the share who selected a particular response.
Score range
If every respondent is a detractor, NPS is −100. If every respondent is a promoter, it is +100. A score of zero means the promoter and detractor percentages are equal; it does not mean that no one is satisfied or that the organization has no promoters.
What the score tells you—and what it does not
A higher NPS means the surveyed group has a greater net share of promoters than detractors under the standard categories. Organizations can track defined groups—such as products, stores, service teams, customer segments, geographies, or functions—over time. That can help identify differences between groups or changes in a particular group, provided the survey and sample are reasonably comparable.
NPS alone does not tell you why respondents gave their ratings, whether they actually made a recommendation, or whether the organization will grow. It is not a complete measure of customer satisfaction or loyalty, and a relationship between a score and a business outcome does not by itself establish that one caused the other.
Is there a good NPS score?
There is no universal threshold that makes an NPS “good.” Interpretation depends on the audience, industry, survey method, response mix, and the comparison being made. A score that looks strong against one relevant peer group might not be meaningful against a different population or survey design.
When comparing scores, check whether the results are genuinely comparable:
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- Respondents: Who was invited, who replied, and how the sample was selected.
- Question and scale: Whether wording and the 0–10 scale stayed consistent.
- Timing and channel: Whether the surveys were sent at similar points in the customer experience and through similar channels.
- Audience: Whether the industry, customer segment, and relevant geography match.
- Response patterns: How many people responded and how promoters, passives, and detractors were distributed.
- Supporting evidence: Whether the score is accompanied by comments or other experience measures.
How to make an NPS result more useful
Choose respondents who can answer the question
A score can be misleading if the people surveyed do not represent the customers or experience being assessed. In B2B research, one contact may not represent an entire account: decision makers, influencers, and actual users can have different views. Bain’s measurement guidance discusses respondent selection, response bias, and the volatility that can arise from small or mixed samples.
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To understand what may be influencing ratings, pair NPS with an open-ended “Why?” prompt, targeted questions about experience drivers, or relevant operational data. Qualtrics recommends using driver questions and contextual data to interpret results. These additions can help investigate possible explanations, but a correlation between an experience measure and NPS does not prove causation.
Be cautious with small segments
Breaking results down by team, location, or customer type can expose differences hidden by an overall score. But each breakdown has fewer responses, which can make its result less stable. Treat small-segment changes as signals to investigate rather than definitive rankings, especially when the sample is mixed or response rates differ.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What critics say about NPS
NPS is widely used, but its value as a loyalty or market-research measure has been debated. Brendan Rocks’s 2016 paper, “Interval Estimation for the ‘Net Promoter Score’,” discusses statistical properties and published challenges to claims that NPS is superior to other loyalty measures. One concern is that converting an 11-point response scale into three categories can discard information. Nicholas I. Fisher and Raymond E. Kordupleski’s 2018 paper, “What is Wrong with Net Promoter Score,” presents a critical assessment of NPS as a high-level market-research metric.
These critiques do not establish that NPS is always useless, just as the metric’s use does not establish that it is always informative. Its usefulness depends on the question being asked, the quality of the survey, and whether decision-makers interpret the result alongside relevant evidence.
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