Metrics & KPIs

NPS (Net Promoter Score)

NPS measures customer loyalty and likelihood to recommend, calculated from a 0-10 survey question grouped into Promoters, Passives, Detractors.

What Is Net Promoter Score?

Net Promoter Score (NPS) is a customer experience metric that measures customer loyalty and likelihood to recommend a company, product, or service. It is calculated from a single survey question, "How likely are you to recommend us to a friend or colleague?", answered on a 0-10 scale.

NPS is the most widely used loyalty metric in B2B and consumer businesses because it correlates strongly with revenue growth, retention, and word-of-mouth referrals.

How to Calculate NPS

Survey responses are categorized into three groups based on the 0-10 score:

  • Promoters (9-10): Loyal customers likely to recommend
  • Passives (7-8): Satisfied but not enthusiastic; vulnerable to competitive offers
  • Detractors (0-6): Unhappy customers who can damage brand through negative word-of-mouth

NPS = % Promoters − % Detractors

The result is a number between -100 and +100. Example: 100 responses, 60 Promoters, 25 Passives, 15 Detractors. NPS = 60% − 15% = +45.

NPS Benchmarks by Industry

Industry Average NPS Top-Quartile NPS
BPO / Contact Centers +25 +50+
SaaS / B2B Tech +30 +60+
Financial Services +20 +45+
Healthcare +15 +40+
Telecom -5 +30+
Insurance +10 +35+

A positive NPS indicates more Promoters than Detractors. Above +50 is generally considered excellent. Below 0 means more Detractors than Promoters and signals systemic CX issues.

NPS vs CSAT vs CES

NPS measures loyalty (likelihood to recommend, relationship-level). CSAT measures satisfaction with a specific interaction. CES measures effort required to get an issue resolved. Each answers a different question, and high-performing contact centers track all three. NPS shifts slowly; CSAT shifts fast and is more diagnostic for individual interactions.

How AI QA Correlates to NPS

NPS is a relationship metric driven by hundreds of micro-interactions over time. AI-powered call analysis can identify which specific call behaviors correlate with NPS movement: average handle time, first call resolution, agent tone, dead air, and resolution clarity. By auditing 100% of calls (instead of 2-5% sampling), AI QA surfaces the behavioral patterns that drive Promoters vs Detractors at the customer-segment level. Contact centers using automated call scoring can run NPS-correlated coaching: rather than coaching every agent on the same checklist, focus coaching on the specific behaviors most associated with NPS movement in that operation.

See the conversations behind your NPS

Gistly scores every call, chat and email, so this metric comes from your whole conversation volume rather than a sample.

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Frequently Asked Questions

What is a good NPS score?

NPS varies widely by industry. For BPOs and contact centers, +25 is average, +40 is good, +50+ is top-quartile. SaaS averages higher (+30 to +60). Telecom and insurance trend lower. Compare against your industry benchmark, not absolute numbers.

Should NPS be measured per-interaction or at the relationship level?

NPS is a relationship metric, it should be measured periodically (quarterly or after key milestones), not after every interaction. For interaction-level satisfaction, use CSAT instead.

How is NPS different from CSAT?

NPS measures overall loyalty and likelihood to recommend on a 0-10 scale. CSAT measures satisfaction with a specific interaction on a 1-5 or 1-10 scale. NPS is relationship-level and changes slowly; CSAT is interaction-level and changes call-by-call.

Can AI predict NPS?

Indirectly. AI cannot predict whether a customer will recommend you, but it can identify the call behaviors and outcomes that historically correlate with NPS in your operation, and flag interactions that have those characteristics for follow-up.


Related Reading


Last updated: April 2026

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