Analytics & Retention

NPS (Net Promoter Score)

Also known asNet Promoter ScoreNPS Score

A user-satisfaction metric calculated from the question "How likely are you to recommend this app to a friend?" on a 0-10 scale. NPS = % Promoters − % Detractors.

Key takeaways

  1. 01NPS = % Promoters (rated 9-10) − % Detractors (rated 0-6). Range: -100 to +100.
  2. 02Mobile app NPS benchmarks: above 30 = good, above 50 = excellent, above 70 = world-class.
  3. 03Useful for tracking satisfaction trends; limited as a sole metric — doesn't predict revenue / retention reliably for all categories.

NPS (Net Promoter Score) is a user-satisfaction metric calculated from a single survey question: "On a scale of 0 to 10, how likely are you to recommend this app to a friend or colleague?" Users are classified by response: Promoters (9-10), Passives (7-8), Detractors (0-6). NPS = % Promoters − % Detractors. The score ranges from -100 (everyone is a Detractor) to +100 (everyone is a Promoter).

Mobile app NPS benchmarks (2026 anchors):

Compare to your own historical trend and category peers — cross-category comparisons mislead because category satisfaction patterns differ.

When NPS is useful

  • Tracking satisfaction trends over time — a rising NPS suggests improving product; falling suggests problems even before they show in churn.
  • Comparing across features / releases — does the new redesign lift NPS? Lower? Track around launches.
  • Identifying detractors — Detractor cohort retention curves usually drop hardest. NPS surveys identify them; targeted follow-up can recover some.
  • Benchmarking externally — NPS is a common metric across companies and industries, useful for board reporting and external comparison.

Limitations of NPS as a sole metric

  • Doesn't predict revenue reliably — high-NPS apps don't always grow faster than mid-NPS apps. Depends on category and business model.
  • Cultural bias — Japanese users rarely rate 9-10 even for great products; Americans rate 10s freely. NPS skews by geo / culture.
  • Survey-only signal — captures stated intent ("would recommend") not revealed behavior ("actually recommended"). Stated intent overstates actual referrals.
  • Sensitive to sample bias — NPS taken right after a great experience differs from NPS at random sample times.
  • Single dimension — masks underlying drivers. A 50 NPS could come from 70/30 Promoter/Detractor split or from a different mix; you need follow-up "why" questions.

Most mature mobile apps use NPS alongside other satisfaction metrics: feature-specific surveys, CSAT (customer satisfaction) for specific interactions, retention metrics as the ultimate satisfaction signal.

Quick answers

How is NPS calculated?

NPS = % Promoters − % Detractors. Promoters rate 9-10 on "How likely are you to recommend this app?" Detractors rate 0-6. Passives (7-8) don't count. Score ranges -100 to +100. Example: 60% Promoters, 10% Detractors, 30% Passives → NPS = 60 - 10 = 50.

What is a good NPS for a mobile app?

Above 30 = good. Above 50 = excellent. Above 70 = world-class (typically only the most loved consumer apps). Compare to your category and historical trend, not absolute benchmarks — satisfaction patterns differ by category. Track trends over time rather than focusing on absolute level.

Is NPS a useful metric for mobile apps?

Yes for tracking satisfaction trends, comparing across features / releases, identifying Detractor cohorts for targeted follow-up, and external benchmarking. Limited as sole metric — doesn't predict revenue / retention reliably for all categories, has cultural bias (some geos rate harshly), captures stated intent not actual behavior, masks underlying drivers without "why" follow-up questions. Use NPS alongside retention metrics and feature-specific surveys.

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