TL;DR

NPS is a -100 to +100 loyalty score: ask customers how likely they are to recommend you (0-10), then subtract the percentage of detractors from the percentage of promoters.

Key Points

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Respondents are bucketed by their 0-10 answer: promoters (9-10), passives (7-8), and detractors (0-6); passives count toward the total but not the score. [1][3]

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Formula: NPS = % promoters - % detractors, so the result always lands between -100 and +100. [1][3]

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The metric was introduced by Fred Reichheld at Bain & Company (with Satmetrix) in a 2003 Harvard Business Review article. [1]

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NPS is a relationship signal best read over time and against competitors, not a single absolute number; a score above 50 is generally considered strong but benchmarks vary widely by industry. [4]

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Pair NPS with operational support metrics like [[customer-satisfaction-score]], [[first-response-time]], and [[customer-effort-score]] for a fuller picture, since loyalty is shaped by far more than any one interaction. [2][4]

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It is a blunt instrument: binning answers into three groups discards information and a small sample lacks statistical validity, so treat it as a directional indicator. [2]

How NPS is calculated

NPS comes from one question: "How likely are you to recommend us to a friend or colleague?" rated 0-10. Promoters answer 9-10, passives 7-8, and detractors 0-6. You take the percentage of promoters and subtract the percentage of detractors; passives are ignored in the math but still count in the denominator. ^[1]^[3] For example, 60 promoters, 20 passives, and 20 detractors out of 100 responses gives an NPS of 40. Because it is a difference of two percentages, the result ranges from -100 (everyone is a detractor) to +100 (everyone is a promoter). The simplicity is the appeal: one number, easy to track across products, teams, and time. ^[3]

NPS vs. other support metrics

NPS measures overall loyalty and is usually run on a relational cadence (quarterly or annually); some teams favor it over per-interaction surveys because asking after every minor touchpoint annoys customers. ^[4] That makes it different from interaction-level signals: Customer Satisfaction Score (CSAT) gauges happiness with a specific Conversation, while Customer Effort Score (CES) measures how hard a task felt. For a support team, NPS works best alongside operational measures such as First Response Time (FRT), Resolution Time, and First Contact Resolution (FCR), because a recommendation reflects pricing, product, and brand on top of any one support exchange. ^[2]^[4]

Limits and pitfalls

NPS is well-liked by leadership because it correlates with growth and is cheap to collect, but it has real limits. Collapsing a 0-10 scale into three buckets throws away information, and a 9 reads identically to a 10. ^[2] Small samples are not statistically reliable, and the score says nothing about why people feel the way they do, so it needs follow-up questions or a Chat Transcript to surface root causes. ^[2] Treated as a hard target, it also invites gaming, where teams nudge the number rather than improve the experience. Read it as the signal, not the source, and pair it with behavioral data and metrics like Customer Retention. ^[2]^[4]

Sources & References

Net promoter score - Wikipedia ↗

Net Promoter Score: What a Customer-Relations Metric Can Tell You About Your User Experience - Nielsen Norman Group ↗

Measuring Your Net Promoter Score - Bain & Company ↗

Net Promoter Score (NPS): The Ultimate Guide - Qualtrics ↗

Last updated: June 25, 2026

Related Terms

Customer Satisfaction Score (CSAT)

Customer Satisfaction Score (CSAT) is a support metric that measures how happy a customer is with a specific interaction, product, or service, usually captured by a short post-interaction survey. It is expressed as the percentage of respondents who rate their experience as satisfied or very satisfied.

Customer Effort Score (CES)

Customer Effort Score (CES) is a single-question survey metric that measures how much effort a customer had to expend to get an issue resolved, a question answered, or a task completed. The premise is that lower-effort interactions drive higher loyalty and retention.

Customer Retention

Customer retention is a company's ability to keep its existing customers over a defined period by driving repeat purchases, renewals, or continued use rather than losing them to competitors. It is most often quantified as a customer retention rate, the inverse of churn.

First Response Time (FRT)

First Response Time (FRT) is the elapsed time between a customer's first message in a conversation and the first human reply from a support agent. It measures how quickly your team acknowledges an inbound request, not how long it takes to resolve it.

First Contact Resolution (FCR)

First Contact Resolution (FCR) is the percentage of customer issues fully resolved in a single interaction, with no transfer, callback, or follow-up needed. It measures how often a support team solves a problem the first time the customer reaches out.

Customer Support

Customer support is the set of services and people that help customers use a product effectively and resolve the specific problems they run into, covering everything from installation and troubleshooting to maintenance and upgrades. It is the reactive, product-focused subset of the broader discipline of [[customer-service]].

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