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Net Revenue Retention (NRR)

Definition

Net Revenue Retention (NRR) measures the percentage of recurring revenue retained from existing customers over a given period, including revenue gained from expansions (upsells, cross-sells) and subtracting revenue lost due to churn or downgrades.

Description

Net Revenue Retention (NRR) is a key indicator of customer base growth efficiency, reflecting how existing customer revenue—adjusted for churn, downgrades, and expansion—impacts recurring revenue health and long-term sustainability.

The relevance and interpretation of this metric shift depending on the model or product:

  • In B2B SaaS, it highlights how well expansion strategies (e.g., seat growth, plan upgrades) offset churn over time
  • In usage-based models, it reflects billing growth from consumption among retained users
  • In enterprise platforms, it surfaces account maturity and cross-sell traction within business units or regions

A rising NRR (especially >100%) typically signals strong product value realization, expansion momentum, and sticky customer relationships, while a decline may indicate customer dissatisfaction, stalled usage, or pricing friction. By segmenting by cohort — such as customer size, vertical, plan type, or product module adoption — you unlock insights for identifying upsell-ready accounts, flagging churn risk segments, and prioritizing roadmap or packaging updates.

Net Revenue Retention (NRR) informs:

  • Strategic decisions, like forecasting sustainable revenue growth, evaluating CLTV projections, or assessing the impact of success and expansion motions
  • Tactical actions, such as targeting expansion campaigns, optimizing renewal plays, or timing CS check-ins
  • Operational improvements, including churn risk detection workflows and upsell trigger automation
  • Cross-functional alignment, by connecting signals across customer success, product, RevOps, sales, and finance, keeping everyone focused on efficient revenue retention and customer lifetime growth

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

  • Upsell and Cross-Sell Effectiveness: Healthy accounts should grow. If they’re not, you’re leaving money on the table.
  • Churn Prevention and Early Warning Signals: Catching drop-offs and dissatisfaction early prevents revenue leakage.
  • Customer Segment Profitability: Some segments expand faster and churn less — targeting matters.

Improvement Tactics & Quick Wins

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

  • If NRR is under 100%, focus CS efforts on upsell-ready accounts at key usage or lifecycle milestones.
  • Add in-product expansions (extra seats, integrations, premium features) as users grow.
  • Run a cohort analysis of high vs. low NRR accounts and reverse-engineer their journey.
  • Refine account reviews to prioritize revenue risk and expansion readiness.
  • Partner with product and finance to align feature packaging to long-term ARPU growth.

  • Required Datapoints to calculate the metric


    • Starting Revenue: Monthly recurring revenue (MRR) or annual recurring revenue (ARR) at the beginning of the period.
    • Expansion Revenue: Additional revenue from existing customers due to upselling or cross-selling.
    • Churn Revenue: Revenue lost from customers who cancel or downgrade during the period.
    • Ending Revenue: Total recurring revenue from existing customers at the end of the period.
  • Example to show how the metric is derived


    A SaaS company starts the month with $100,000 MRR. During the month:

    • Gains $10,000 from upsells.
    • Loses $5,000 due to churn and downgrades.
    • NRR = [(100,000 + 10,000 – 5,000) / 100,000] × 100 = 105%

Formula

Formula

\[ \mathrm{Net\ Revenue\ Retention} = \left( \frac{\mathrm{Starting\ Revenue} + \mathrm{Expansion\ Revenue} - \mathrm{Churn\ Revenue}}{\mathrm{Starting\ Revenue}} \right) \times 100 \]

Data Model Definition

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

cube('RevenueMetrics', {
  sql: `SELECT * FROM revenue_metrics`,

  measures: {
    startingRevenue: {
      sql: `starting_revenue`,
      type: 'sum',
      title: 'Starting Revenue',
      description: 'Total recurring revenue at the beginning of the period.'
    },

    expansionRevenue: {
      sql: `expansion_revenue`,
      type: 'sum',
      title: 'Expansion Revenue',
      description: 'Additional revenue from upselling or cross-selling to existing customers.'
    },

    churnRevenue: {
      sql: `churn_revenue`,
      type: 'sum',
      title: 'Churn Revenue',
      description: 'Revenue lost from customers who cancel or downgrade during the period.'
    },

    endingRevenue: {
      sql: `ending_revenue`,
      type: 'sum',
      title: 'Ending Revenue',
      description: 'Total recurring revenue from existing customers at the end of the period.'
    },

    netRevenueRetention: {
      sql: `(${endingRevenue} + ${expansionRevenue} - ${churnRevenue}) / ${startingRevenue}`,
      type: 'number',
      title: 'Net Revenue Retention',
      description: 'Percentage of recurring revenue retained from existing customers over a given period.'
    }
  },

  dimensions: {
    id: {
      sql: `id`,
      type: 'string',
      primaryKey: true,
      title: 'ID',
      description: 'Unique identifier for each revenue record.'
    },

    periodStart: {
      sql: `period_start`,
      type: 'time',
      title: 'Period Start',
      description: 'Start date of the revenue period.'
    },

    periodEnd: {
      sql: `period_end`,
      type: 'time',
      title: 'Period End',
      description: 'End date of the revenue period.'
    }
  }
});

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


Positive & Negative Influences

  • Negative influences


    Factors that drive the metric in an undesirable direction, often signaling risk or decline.

    • Customer Churn Rate: An increase in churn rate directly reduces the recurring revenue from existing customers, negatively impacting Net Revenue Retention.
    • Customer Dissatisfaction: High levels of customer dissatisfaction lead to increased churn and reduced upsell opportunities, negatively affecting Net Revenue Retention.
    • Downgrade Rate: A high rate of customers downgrading their plans results in a decrease in revenue from existing customers, negatively impacting Net Revenue Retention.
    • Market Competition: Increased competition can lead to higher churn rates as customers switch to competitors, negatively affecting Net Revenue Retention.
    • Economic Downturn: Economic downturns can lead to budget cuts and reduced spending by customers, increasing churn and downgrades, thus negatively impacting Net Revenue Retention.
  • Positive influences


    Factors that push the metric in a favorable direction, supporting growth or improvement.

    • Upsell and Cross-Sell Effectiveness: Increased upsell and cross-sell activities lead to higher revenue from existing customers, directly boosting Net Revenue Retention.
    • Customer Satisfaction: High customer satisfaction results in lower churn rates and more opportunities for upsells, positively impacting Net Revenue Retention.
    • Customer Segment Profitability: Focusing on profitable customer segments that have a higher propensity to expand and lower churn rates enhances Net Revenue Retention.
    • Product Adoption Rate: Higher product adoption rates indicate that customers are finding value, leading to increased upsell opportunities and reduced churn, thus improving Net Revenue Retention.
    • Customer Success Initiatives: Effective customer success initiatives ensure customers achieve their desired outcomes, leading to higher retention and expansion, positively affecting Net Revenue Retention.

Involved Roles & Activities


Funnel Stage & Type

  • AAARRR Funnel Stage


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

    Revenue
    Retention

  • Type


    This KPI is classified as a Lagging Indicator. It reflects the results of past actions or behaviors and is used to validate performance or assess the impact of previous strategies.


Supporting Leading & Lagging Metrics

  • Leading


    These leading indicators influence this KPI and act as early signals that forecast future changes in this KPI.

    • Customer Loyalty: Customer Loyalty is a strong leading indicator of future Net Revenue Retention (NRR). High loyalty signals customers are likely to renew, expand, or resist churn, making it an early warning metric for shifts in NRR.
    • Product Qualified Accounts: Product Qualified Accounts (PQAs) identify organizations demonstrating high engagement and readiness to expand. A growing PQA base forecasts higher retention and expansion revenue, leading to improved NRR in subsequent periods.
    • Upsell Conversion Rates: Upsell Conversion Rates track the proportion of customers upgrading to higher tiers or features. Increased upsell rates are often precursors to higher NRR, as they directly drive revenue expansion from the existing base.
    • Activation Rate: Activation Rate measures the percentage of users reaching key onboarding milestones. Higher activation predicts better product adoption and stickiness, which leads to lower churn and higher NRR over time.
    • Net Promoter Score: Net Promoter Score reflects customer sentiment and willingness to recommend. A rising NPS usually precedes improvements in NRR, as promoters are more likely to stay, expand, and advocate for the brand.
  • Lagging


    These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.

    • Customer Downgrade Rate: Customer Downgrade Rate quantifies customers reducing their spend. A rising downgrade rate directly reduces NRR by lowering recurring revenue from existing customers and is a primary driver of contractions within NRR calculations.
    • Expansion Revenue Growth Rate: Expansion Revenue Growth Rate reflects increased upsells and cross-sells to current customers, directly boosting NRR by offsetting churn and contraction. Strong expansion growth is a key contributor to higher NRR.
    • Revenue Churn Rate: Revenue Churn Rate measures the percentage of recurring revenue lost to cancellations and downgrades. Higher revenue churn erodes NRR, making this a critical confirming metric for NRR performance.
    • Contract Renewal Rate: Contract Renewal Rate tracks what proportion of expiring customer contracts are renewed. Low renewal rates lead to lower NRR, while high renewal rates confirm strong retention and NRR outcomes.
    • Expansion Revenue: Expansion Revenue represents upsell and cross-sell income from existing customers. Higher expansion revenue directly improves NRR, providing a clear explanation for positive shifts in this lagging KPI.