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Glossary

NPS (Net Promoter Score)

Net Promoter Score (NPS) is a customer loyalty metric that measures how likely customers are to recommend your product or service to others. Customers rate their likelihood on a 0-10 scale and are classified as Promoters (9-10), Passives (7-8), or Detractors (0-6). NPS = % Promoters minus % Detractors.

How it works

NPS is calculated from a single survey question: "How likely are you to recommend [Company] to a friend or colleague?" on a 0-10 scale.

  • **Promoters (9-10)**: Loyal enthusiasts who actively refer others
  • **Passives (7-8)**: Satisfied but unenthusiastic; vulnerable to competitive offers
  • **Detractors (0-6)**: Unhappy customers who can damage your brand through negative word-of-mouth

**NPS = % Promoters - % Detractors** (score ranges from -100 to +100)

Unlike CSAT (which measures individual interaction satisfaction), NPS measures overall brand relationship and loyalty. A customer might rate a single support interaction 5/5 (high CSAT) but still be a Detractor on NPS because of product dissatisfaction. The two metrics complement each other.

Operational Review

In practice, nps (net promoter score) should be evaluated by what it changes in the support workflow. Ask whether it improves answer accuracy, reduces repeated agent work, clarifies handoff decisions, or makes reporting easier. If the answer is only "it sounds modern," the concept is not yet operational.

A concrete example is post-support nps survey: After resolving a support conversation, the customer receives an NPS survey a few days later. Analysis reveals that customers who received AI-resolved answers within 5 seconds have an NPS 15 points higher than those who waited 2+ hours for email responses, quantifying the AI support ROI in loyalty terms.

The simplest takeaway is: NPS measures overall brand loyalty on a -100 to +100 scale: Promoters (9-10) minus Detractors (0-6)

Why it matters

NPS is the most widely used loyalty metric in business, correlated with revenue growth and customer retention. Companies with high NPS grow 2-3x faster than competitors. For support teams, NPS reveals whether customer service is building or eroding brand loyalty, not just resolving individual tickets but shaping the overall customer relationship.

How Chatsy uses nps (net promoter score)

Chatsy helps improve NPS indirectly by ensuring every customer interaction is fast, accurate, and helpful. AI chatbots that resolve issues instantly and human agents who receive full context for complex issues create positive support experiences that move customers from Detractors to Passives and Passives to Promoters.

Real-world examples

Post-support NPS survey

After resolving a support conversation, the customer receives an NPS survey a few days later. Analysis reveals that customers who received AI-resolved answers within 5 seconds have an NPS 15 points higher than those who waited 2+ hours for email responses, quantifying the AI support ROI in loyalty terms.

Detractor recovery program

When a customer submits an NPS score of 0-6, the system automatically creates a priority ticket for the customer success team. A personal follow-up within 24 hours recovers 30% of Detractors, converting them to Passives or Promoters through direct attention to their concerns.

NPS-driven knowledge base improvements

NPS follow-up comments reveal that Detractors frequently mention "confusing billing" and "hard to cancel." The team creates clear billing FAQ articles and a simple cancellation flow in the AI chatbot. Six months later, billing-related Detractor comments drop by 60%.

Key takeaways

  • NPS measures overall brand loyalty on a -100 to +100 scale: Promoters (9-10) minus Detractors (0-6)

  • It is a relational metric (overall brand health) unlike CSAT which is transactional (per-interaction quality)

  • Companies with high NPS (50+) typically grow 2-3x faster than competitors

  • Support quality directly influences NPS: fast, accurate resolution moves Detractors toward Promoters

  • NPS follow-up comments are a goldmine for identifying systemic product and service issues

Frequently asked questions

What is a good NPS score?

NPS varies by industry. Generally: above 0 is acceptable, above 30 is good, above 50 is excellent, and above 70 is world-class. SaaS companies average 30-40. B2C companies average 20-30. Compare your NPS to industry benchmarks rather than absolute numbers.

How is NPS different from CSAT?

CSAT measures satisfaction with a specific interaction ("How was this support experience?"). NPS measures overall brand loyalty ("How likely are you to recommend us?"). A customer can have high CSAT (great support experience) but low NPS (unhappy with the product overall). Both metrics are valuable and complementary.

How often should I survey for NPS?

Most companies survey NPS quarterly or semi-annually to track trends. Avoid surveying the same customer more than once per quarter to prevent survey fatigue. Transactional NPS (sent after specific interactions) can be more frequent but should be distinguished from relationship NPS.

Can AI chatbots improve NPS?

Yes, indirectly. AI chatbots that resolve issues instantly, provide accurate information, and offer seamless human handoff create positive support experiences. Support quality is one of the top 3 drivers of NPS. Teams that deploy AI chatbots typically see NPS increases of 5-15 points within 6 months as support speed and consistency improve.

What does NPS stand for and how does it work?

NPS stands for Net Promoter Score. Customers answer one question on a 0-10 scale: "How likely are you to recommend us?" Scores 9-10 are Promoters, 7-8 Passives, and 0-6 Detractors. NPS is calculated as the percentage of Promoters minus the percentage of Detractors, giving a number between -100 and +100.

What does NPS mean in healthcare?

In healthcare, NPS is most often the same Net Promoter Score, applied to patient experience instead of customers. Note that "NPS" can also be used as an unrelated abbreviation in clinical contexts (for example, neuropsychiatric symptoms or numeric pain scale), so the meaning depends on the document.

Related terms

CSAT (Customer Satisfaction Score)

CSAT (Customer Satisfaction Score) is a metric that measures how satisfied customers are with a specific interaction, pr...

First Contact Resolution (FCR)

First Contact Resolution (FCR) is a customer support metric that measures the percentage of customer issues fully resolv...

Sentiment Analysis

Sentiment analysis is an NLP technique that identifies the emotional tone (positive, negative, neutral, or specific emot...

Average Handle Time (AHT)

Average Handle Time (AHT) is a customer support metric that measures the average total duration of a customer interactio...

Further reading

Measuring Customer SatisfactionChatbot Metrics To TrackSupport Automation Roi

Related Resources

Customer Support BlogSee Chatsy Features

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Conversational AIRetrieval-Augmented Generation (RAG)Vector SearchChatbotHuman HandoffCSAT (Customer Satisfaction Score)First Response Time (FRT)Ticket DeflectionNatural Language Processing (NLP)EmbeddingKnowledge BaseLive ChatSentiment AnalysisHybrid SearchLarge Language Model (LLM)AI HallucinationPrompt EngineeringAgentic AIAI AgentFine-TuningIntent ClassificationTokenContext WindowOmnichannel SupportSLA (Service Level Agreement)Average Handle Time (AHT)First Contact Resolution (FCR)WebhookSemantic Search

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