A loyalty metric that asks users how likely they are to recommend a product to a friend or colleague on a 0–10 scale. Respondents are grouped as Detractors (0–6), Passives (7–8), and Promoters (9–10), and the final score is Promoters minus Detractors expressed as a percentage. NPS tracks long-term sentiment but doesn't explain the reasons behind it.
Common contexts
- Tracking NPS quarterly across a product line to detect sentiment trends before they show up in churn data
- Pairing an NPS survey with an open text follow-up to qualify the score with user language that guides design decisions
- Segmenting NPS responses by user cohort to identify whether Detractors are concentrated in a specific feature area or user type
Use when
Use NPS as a longitudinal tracking metric alongside behavioral data — it's most useful for detecting directional change over time and for benchmarking against industry scores, not for diagnosing specific UX problems.
Avoid when
Don't use NPS as your primary measure of UX quality — it measures willingness to recommend, which is influenced by customer support, pricing, and brand as much as product experience.
An NPS score without qualitative follow-up is nearly useless for design decisions — the number tells you something changed, but only the open responses tell you what to do about it.
Real-world examples
- Airbnb tracks NPS after every stay and reports that a 1-point NPS increase correlates with a 2.5% reduction in annual churn — making it the company's primary indicator of long-term retention health.
- Apple's consumer NPS consistently exceeds 70 (industry benchmark is 30), which the company uses to justify premium pricing and forecast demand for new product categories like AirPods.
- Slack's bottom-up enterprise growth — where individual user advocacy drives team and company-wide adoption — is tracked entirely through NPS, which the team treats as a leading indicator 6 months before renewal.