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KPI Library

Net Promoter Score

Definition

Section titled “Definition”

Net Promoter Score (NPS) measures customer loyalty by gauging how likely customers are to recommend your product, service, or brand to others. It’s based on a single-question survey: “How likely are you to recommend our [product/service] to a friend or colleague?”

Business Context

Section titled “Business Context”

Net Promoter Score (NPS) is a key indicator of customer sentiment, loyalty, and word-of-mouth potential, reflecting how likely users are to recommend your product or service to others.

Customers respond on a scale of 0 to 10, and their responses categorize them into:

  • Promoters (9–10): Loyal enthusiasts likely to recommend your brand and drive growth.
  • Passives (7–8): Satisfied but unenthusiastic customers who are less likely to actively promote your brand.
  • Detractors (0–6): Unhappy customers who may discourage others from using your product or service.

Its interpretation varies based on where you deploy it:

  • In B2B SaaS, NPS helps spot renewal risks and customer champions
  • In consumer apps, it reflects brand love and social sharing propensity
  • In services and support, it gauges experience quality and resolution satisfaction

A rising NPS indicates positive experiences and product fit, while a low score highlights frustrations or loyalty erosion.

By segmenting by user role, plan, or lifecycle stage, you can uncover persona-specific pain points or evangelist signals.

Net Promoter Score informs:

  • Strategic decisions, like retention roadmap, loyalty campaigns, or advocacy programs
  • Tactical actions, such as launching save plays for Detractors or amplifying Promoter feedback
  • Operational improvements, including support training and customer comms updates
  • Cross-functional alignment, rallying product, CS, marketing, and UX around voice-of-customer insights

Key Drivers

Section titled “Key Drivers”

These are the main factors that directly impact the metric. Understanding these lets you know what levers you can pull to improve the outcome

  • Product Performance and Reliability: Bugs and crashes tank NPS. Smooth, fast experiences raise it.
  • Onboarding and Early Wins: Customers who succeed early are more likely to become promoters.
  • Support and Relationship Quality: Customers who feel heard — especially after something went wrong — tend to rate higher.

Improvement Tactics & Quick Wins

Section titled “Improvement Tactics & Quick Wins”

Actionable ideas to optimize this KPI, from fast, low-effort wins to strategic initiatives that drive measurable impact.

  • If NPS is low, dig into detractor feedback themes and prioritize the top 2 fixable issues.
  • Add “You said, we did” messages to close the loop with customers who gave feedback.
  • Run a test timing NPS prompts after major wins or milestones — not randomly.
  • Refine survey microcopy to clarify the ask (“How likely are you to recommend [Product] to a peer like you?”).
  • Partner with CX and product to segment NPS by role, account size, and lifecycle stage for targeted follow-up.
Section titled “Related Activities”

Activities commonly tied to improving or operationalizing this KPI.

ActivityDescription
Customer AdvocacyCustomer Advocacy is a strategic process focused on building strong relationships with satisfied customers to amplify their positive experiences, strengthen loyalty, and inspire them to share their success stories. It helps teams translate strategy into repeatable execution. Relevant KPIs include Customer Loyalty and Customer Referral Rate.
Retention StrategiesRetention Strategies involves systematic initiatives and processes aimed at maximizing customer lifetime value by proactively engaging and supporting existing users. It helps teams translate strategy into repeatable execution. Relevant KPIs include Customer Churn Rate and Customer Lifetime Value.
NPS Survey DesignNPS Survey Design involves more than simply creating a questionnaire. It gives teams a clear plan for where to focus, how to sequence work, and what to measure. Relevant KPIs include Net Promoter Score.
Feedback Loop ImplementationFeedback Loop Implementation involves systematically collecting, analyzing, and applying feedback from customers and internal teams to drive continuous improvement throughout the go-to-market strategy. It helps teams translate strategy into repeatable execution. Relevant KPIs include Net Promoter Score.

Required Datapoints

  • Survey Responses: Scores collected from customers (0 to 10).
  • Total Respondents: The total number of customers surveyed.
  • Promoters: (Number of Promoters / Total Respondents) × 100
  • **Detractors: **(Number of Detractors / Total Respondents) × 100

Example

A subscription service collects NPS responses from 1,000 customers:

  • Promoters: 600 (60%)
  • Passives: 250 (25%)
  • Detractors: 150 (15%)
  • NPS = 60% – 15% = 45

Formula

Section titled “Formula”
Net Promoter Score=(% of Promoters−% of Detractors)\mathrm{Net\ Promoter\ Score} = \left( \mathrm{\% \ of\ Promoters} - \mathrm{\% \ of\ Detractors} \right)

Positive & Negative Influences

Section titled “Positive & Negative Influences”

Negative Influences

  • Product Performance and Reliability: Frequent bugs and crashes lead to customer frustration, reducing their likelihood to recommend the product, thus lowering NPS.
  • Support and Relationship Quality: Poor customer support experiences, where customers feel unheard or unresolved, negatively impact their perception and decrease NPS.
  • Onboarding and Early Wins: A lack of clear guidance or early success can lead to customer dissatisfaction, reducing their likelihood to recommend the product, thus lowering NPS.
  • Pricing Perception: If customers perceive the product as overpriced relative to its value, they are less likely to recommend it, negatively impacting NPS.
  • Competitor Comparison: If customers find competitors offering better value or features, they may rate the product lower, decreasing NPS.

Positive Influences

  • Product Performance and Reliability: A smooth, fast, and reliable product experience enhances customer satisfaction, increasing their likelihood to recommend the product, thus raising NPS.
  • Onboarding and Early Wins: Effective onboarding that leads to early customer success increases satisfaction and the likelihood of recommendation, boosting NPS.
  • Support and Relationship Quality: High-quality customer support, where customers feel valued and heard, positively influences their perception and increases NPS.
  • Brand Reputation: A strong, positive brand reputation can enhance customer pride in association, increasing their likelihood to recommend the product, thus raising NPS.
  • Customer Engagement: Active engagement with customers through personalized communication and community building can enhance loyalty and increase NPS.

Funnel Stage & Type

Section titled “Funnel Stage & Type”

AAARRR Funnel Stage

This KPI is associated with the following stages in the AAARRR (Pirate Metrics) funnel:

Type

This KPI is classified as a leading Indicator. It signals likely future performance and is used to predict outcomes before they fully materialize.

Ownership

Section titled “Ownership”

Primary Owner

This role is directly accountable for the KPI and is expected to drive progress and decisions around it.

Stakeholders

These roles should stay informed on changes in the KPI because it influences adjacent planning, coordination, or outcomes.

Supporting Leading & Lagging Metrics

Section titled “Supporting Leading & Lagging Metrics”

Leading

These leading indicators influence or contextualize this KPI and help create a multi-signal early warning system, improving confidence and enabling better root-cause analysis.

  • Customer Satisfaction Score: High CSAT scores typically forecast strong NPS performance as they reflect immediate post-interaction satisfaction, indicating customers are likely to become promoters in subsequent NPS surveys.
  • Customer Loyalty: Customer Loyalty measures repeat engagement and preference, acting as a precursor to recommendation intent; higher loyalty usually signals future increases in NPS.
  • Brand Awareness: Growing brand awareness broadens the pool of potential promoters and sets the stage for higher NPS by increasing top-of-mind presence and positive sentiment.
  • Engagement Rate: High engagement rate reflects strong user involvement and product resonance, often preceding or correlating with higher NPS as engaged customers are more likely to recommend.
  • Product Qualified Leads: An increase in PQLs indicates that users are experiencing core product value, which generally leads to higher satisfaction and positive NPS responses.

Lagging

These lagging indicators support the recalibration of this KPI, helping to inform strategy and improve future forecasting.

  • Customer Churn Rate: A rising churn rate can reveal dissatisfaction not fully captured by NPS; analyzing churn reasons helps recalibrate NPS thresholds and early warning signals.
  • Customer Downgrade Rate: Downgrades indicate declining perceived value; examining downgrade trends provides feedback to refine NPS-related action plans or identify at-risk segments.
  • Customer Feedback Retention Score: Understanding which feedback givers are retained versus lost helps validate whether NPS is predictive of actual loyalty, informing weighting or segmentation strategies.
  • Referral Prompt Acceptance Rate: High or low acceptance rates on referral prompts validate the accuracy of NPS as an advocacy indicator and can highlight gaps between stated intent and actual behavior.
  • Sentiment Analysis: Aggregated sentiment from customer communications and reviews can confirm or challenge NPS trends, offering a granular view that informs adjustments to NPS survey timing, targeting, or interpretation.

Data Model Definition

Section titled “Data Model Definition”

How this KPI is structured in Cube.js, including its key measures, dimensions, and calculation logic for consistent reporting.

cube('SurveyResponses', {
  sql: `SELECT * FROM survey_responses`,


  measures: {
    totalRespondents: {
      sql: `id`,
      type: 'count',
      title: 'Total Respondents',
      description: 'The total number of customers surveyed.'
    },
    numberOfPromoters: {
      sql: `CASE WHEN score >= 9 THEN 1 ELSE 0 END`,
      type: 'sum',
      title: 'Number of Promoters',
      description: 'The number of customers who are promoters (score 9 or 10).'
    },
    numberOfDetractors: {
      sql: `CASE WHEN score <= 6 THEN 1 ELSE 0 END`,
      type: 'sum',
      title: 'Number of Detractors',
      description: 'The number of customers who are detractors (score 0 to 6).'
    },
    promotersPercentage: {
      sql: `100.0 * ${numberOfPromoters} / NULLIF(${totalRespondents}, 0)`,
      type: 'number',
      title: 'Promoters Percentage',
      description: 'Percentage of promoters among total respondents.'
    },
    detractorsPercentage: {
      sql: `100.0 * ${numberOfDetractors} / NULLIF(${totalRespondents}, 0)`,
      type: 'number',
      title: 'Detractors Percentage',
      description: 'Percentage of detractors among total respondents.'
    },
    netPromoterScore: {
      sql: `${promotersPercentage} - ${detractorsPercentage}`,
      type: 'number',
      title: 'Net Promoter Score',
      description: 'Net Promoter Score calculated as the difference between promoters and detractors percentages.'
    }
  },


  dimensions: {
    id: {
      sql: `id`,
      type: 'number',
      primaryKey: true,
      title: 'ID',
      description: 'Unique identifier for each survey response.'
    },
    score: {
      sql: `score`,
      type: 'number',
      title: 'Score',
      description: 'Score given by the customer in the survey (0 to 10).'
    },
    createdAt: {
      sql: `created_at`,
      type: 'time',
      title: 'Created At',
      description: 'The time when the survey response was created.'
    }
  }
});

Note: This is a reference implementation and should be used as a starting point. You’ll need to adapt it to match your own data model and schema