Metrics & Analytics

NPS (Net Promoter Score)

A customer loyalty metric based on a single question — 'How likely are you to recommend us?' — scored 0–10, that classifies respondents as Promoters, Passives, or Detractors.

What is NPS?

NPS (Net Promoter Score) was developed by Fred Reichheld at Bain & Company in 2003. It measures customer loyalty by asking one question:

*"On a scale of 0–10, how likely are you to recommend [product] to a friend or colleague?"*

How NPS is calculated

ScoreCategoryDefinition
9–10PromotersLoyal enthusiasts who will refer others
7–8PassivesSatisfied but unenthusiastic; vulnerable to competitors
0–6DetractorsUnhappy customers who may damage brand through negative WOM
**NPS = % Promoters − % Detractors**

Range: −100 to +100


NPS benchmarks (SaaS)

ScoreInterpretation
< 0Critical — more detractors than promoters
0–30Below average
30–50Good
50–70Excellent
> 70World-class (Apple, Netflix at their peaks)

NPS limitations for product decisions

NPS measures satisfaction, not behaviour. A user can give 9/10 NPS and still churn. Always pair NPS with:

  • Retention cohort data
  • Follow-up qualitative "why" question
  • Segmented analysis (by plan, cohort, or persona)

Frequently asked questions

When should you send the NPS survey?

In-product, after the user has experienced core value — not immediately after signup. For SaaS, trigger it at Day 30 or after the user completes 3–5 key actions. Annual email surveys produce less actionable data than in-product, event-triggered surveys.

Is NPS a reliable predictor of growth?

Weakly. Reichheld's original research showed correlation between NPS and revenue growth, but subsequent studies found the correlation is industry-specific and often overstated. Use NPS as one signal among many — not as your primary growth metric.

Apply NPS to your real product data

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