Net Promoter Score (NPS) as a metric
Net Promoter Score (NPS) is a survey metric derived from one question — how likely you are to recommend, on a 0–10 scale. Respondents are bucketed into promoters (9–10), passives (7–8), and detractors (0–6), and NPS is the percentage of promoters minus the percentage of detractors, yielding a number from −100 to +100. It is simple and widely used, but the bucketing discards detail and ignores who answered.
What this means
NPS comes from the question 'how likely are you to recommend us', answered 0 to 10. Responses split into three groups: promoters (9–10), passives (7–8), and detractors (0–6). NPS = %promoters − %detractors. Passives count toward the base but not the score, so the result ranges from −100 (all detractors) to +100 (all promoters).
What the single number hides
Collapsing an 11-point scale into a single net figure loses information: a score built from many 9s and many 0s can equal one built mostly from 7s and 8s, despite very different customer bases. NPS also says nothing about why people answered as they did — the follow-up verbatim is where the insight is — and it is sensitive to sampling and timing, since who you survey and when (right after a great or poor experience) shifts the result. Treat NPS as a directional pulse, paired with its distribution and open-ended comments.
- Promoters 9–10, passives 7–8, detractors 0–6
- NPS = %promoters − %detractors (−100 to +100)
- Same score, different distributions; verbatim adds the why
How it appears in analytics and logs
An NPS value summarizes recommend sentiment on a −100 to +100 scale. Identical scores can come from very different distributions, and survey timing and who responded can move it as much as real sentiment.
Diagnostic use case
Use NPS as a single comparable loyalty indicator over time, while reading the promoter/passive/detractor distribution and verbatim comments behind it.
What WebmasterID can help detect
WebmasterID can record a first-party survey-response event (the bucket, not free-text PII), so an on-site NPS pulse ties to behavior without third-party cookies or fingerprinting.
Common mistakes
- Reading the NPS number without the response distribution.
- Ignoring sampling and survey timing effects.
- Treating a small NPS change as significant without enough responses.
Privacy and accuracy notes
NPS is computed from aggregated survey responses; the score itself carries no personal identifiers. Survey responses should be handled without exposing individuals. This is educational, not legal advice.
Related pages
- Customer satisfaction score (CSAT)
Customer satisfaction score (CSAT) measures how satisfied respondents are with a specific interaction, product, or experience, usually from a short rating scale. It is commonly the percentage of responses at or above a 'satisfied' threshold (for example the top two boxes of a five-point scale). CSAT is moment-specific and threshold-dependent, so the same data can yield different CSAT values under different scoring rules.
- Customer effort score (CES)
Customer effort score (CES) measures how much effort a customer had to expend to complete a task — resolving an issue, making a purchase, finding an answer. It is captured by an agree/disagree statement about ease, scored on a scale, and lower effort is treated as better. CES targets friction specifically, which makes it different from satisfaction (CSAT) or recommendation likelihood (NPS).
- Engagement rate and engaged sessions
Engagement rate is the percentage of sessions that were 'engaged'. In GA4 an engaged session is one that lasted longer than a threshold (10 seconds by default), had a key event/conversion, or had at least two pageviews. Engagement rate is the inverse of GA4 bounce rate, and its threshold is configurable — so the number depends on a setting most people never check.
- Events documentation
Record survey-bucket events first-party.
Sources and verification notes
Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.