Referred Account Net Revenue Retention (NRR)¶

Definition¶

Referred Account Net Revenue Retention (NRR) measures the revenue retained and expanded from referred customer accounts over time, factoring in upsell, cross-sell, contraction, and churn. It helps quantify the long-term revenue quality of referrals.

Description¶

Referred Account NRR is a key indicator of customer quality, advocacy-driven fit, and expansion potential, reflecting how revenue from referred accounts evolves over time—whether through renewals, upsells, or downgrades.

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

In SaaS, it tracks changes in MRR or ARR among referred customers
In freemium or usage-based models, it reflects billing expansions or tier upgrades
In subscription eComm, it shows repeat order behavior and average spend retention

A rising trend signals aligned referrals, strong onboarding, and product satisfaction, while a declining trend may point to over-incentivized, low-fit referrals or friction post-signup. By segmenting by referral source, customer cohort, or incentive structure, you uncover what types of referrals lead to loyal, growing accounts—and where referral quality may be falling short.

Referred Account NRR informs:

Strategic decisions, like evaluating referral channels by revenue potential
Tactical actions, such as prioritizing high-NRR cohorts for upsells or expansion campaigns
Operational improvements, including referral scoring or advocate education
Cross-functional alignment, with CS, PMM, and sales collaborating on monetization-friendly referral strategy

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

Referral Fit and Qualification: High-quality referrers bring in customers with better NRR — often mirroring their own profile.
Onboarding and Success Enablement: Referred accounts expect quick wins — if they don’t get them, expansion won’t happen.
Advocate Follow-Up and Ecosystem Strength: Referrers often influence ongoing usage — especially in social or community-driven spaces.

Improvement Tactics & Quick Wins¶

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

If referred NRR is low, build a tailored onboarding track just for referred accounts — faster time to value = better retention.
Add advocate enablement — notify referrers when their invitees are active and suggest support nudges.
Run a referral-based expansion play — show similar account benchmarks or usage patterns.
Refine CS outreach to proactively engage high-fit referred accounts before contract renewal.
Partner with product to surface sticky, revenue-driving features early in referred account journeys.

Required Datapoints to calculate the metric
- Starting Revenue from Referred Accounts (MRR/ARR)
- Expansion Revenue (upsell, cross-sell)
- Contraction Revenue (downgrades)
- Churned Revenue (lost accounts)
- Time window (typically quarterly or annual)
Example to show how the metric is derived

Starting ARR from referred accounts: $200,000 Expansion: $60,000 Contraction: $15,000 Churn: $25,000 Formula: (200K + 60K − 15K − 25K) ÷ 200K = 110% Referred Account NRR

Formula¶

Formula

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

Data Model Definition¶

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

ReferredAccounts

cube('ReferredAccounts', {
  sql: `SELECT * FROM referred_accounts`,
  measures: {
    startingRevenue: {
      sql: `starting_revenue`,
      type: 'sum',
      title: 'Starting Revenue from Referred Accounts',
      description: 'Total starting revenue from referred accounts (MRR/ARR).'
    },
    expansionRevenue: {
      sql: `expansion_revenue`,
      type: 'sum',
      title: 'Expansion Revenue',
      description: 'Revenue from upsell and cross-sell activities.'
    },
    contractionRevenue: {
      sql: `contraction_revenue`,
      type: 'sum',
      title: 'Contraction Revenue',
      description: 'Revenue lost due to downgrades.'
    },
    churnedRevenue: {
      sql: `churned_revenue`,
      type: 'sum',
      title: 'Churned Revenue',
      description: 'Revenue lost from churned accounts.'
    },
    netRevenueRetention: {
      sql: `starting_revenue + expansion_revenue - contraction_revenue - churned_revenue`,
      type: 'number',
      title: 'Net Revenue Retention',
      description: 'Net revenue retention from referred accounts, factoring in expansion, contraction, and churn.'
    }
  },
  dimensions: {
    id: {
      sql: `id`,
      type: 'string',
      primaryKey: true,
      title: 'ID',
      description: 'Unique identifier for each referred account.'
    },
    accountName: {
      sql: `account_name`,
      type: 'string',
      title: 'Account Name',
      description: 'Name of the referred account.'
    },
    referralDate: {
      sql: `referral_date`,
      type: 'time',
      title: 'Referral Date',
      description: 'Date when the account was referred.'
    }
  }
})

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 the churn rate among referred accounts directly reduces NRR, as it signifies a loss of revenue from these accounts.
- Poor Onboarding Experience: A subpar onboarding experience can lead to dissatisfaction and early churn among referred accounts, negatively impacting NRR.
- Lack of Engagement: Low engagement levels from referred accounts can result in missed upsell and cross-sell opportunities, reducing NRR.
- Inadequate Support: Insufficient support for referred accounts can lead to frustration and increased likelihood of contraction or churn, negatively affecting NRR.
- Misalignment of Expectations: If the expectations set during the referral process are not met, it can lead to dissatisfaction and increased churn, negatively impacting NRR.
Positive influences

Factors that push the metric in a favorable direction, supporting growth or improvement.
- Referral Fit and Qualification: High-quality referrers bring in customers who are more likely to have higher NRR, as these customers often mirror the successful profiles of the referrers themselves, leading to better retention and expansion opportunities.
- Onboarding and Success Enablement: Effective onboarding processes and success enablement strategies ensure that referred accounts achieve quick wins, which increases the likelihood of upsell and cross-sell, positively impacting NRR.
- Advocate Follow-Up and Ecosystem Strength: Strong follow-up by advocates and a robust ecosystem can enhance ongoing usage and engagement, leading to higher retention and potential revenue expansion from referred accounts.
- Customer Satisfaction: High levels of customer satisfaction among referred accounts can lead to increased loyalty and reduced churn, thereby positively influencing NRR.
- Product Adoption Rate: Higher product adoption rates among referred accounts can lead to increased usage and potential for upsell, positively impacting NRR.

Involved Roles & Activities¶

Involved Roles

These roles are typically responsible for implementing or monitoring this KPI:

Customer Success
Finance
Growth
Product Marketing (PMM)
Revenue Operations
Activities

Common initiatives or actions associated with this KPI:

Referral Analysis
NRR Strategy
Expansion Plays
Post-Onboarding Programs
Usage Tracking

Funnel Stage & Type¶

AAARRR Funnel Stage

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

Retention
Referral
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.
- Product Qualified Leads: A surge in the number of Product Qualified Leads (PQLs) among referred accounts acts as an early indicator of future revenue expansion and retention, as these accounts are more likely to convert, expand, and demonstrate long-term engagement, all contributing to higher Referred Account NRR.
- Customer Loyalty: High loyalty among referred customers signals stronger engagement and lower churn risk, which typically leads to improved NRR as loyal accounts are more likely to renew, expand, and resist competitive offers.
- Upsell Conversion Rates: Higher upsell conversion rates among referred customers foreshadow future expansion revenue, directly boosting NRR by increasing the total retained and expanded revenue from this segment.
- Activation Rate: A high activation rate among referred accounts is a strong predictor of retention and future expansion, as early value realization and product engagement translate into reduced churn and greater revenue retention.
- Sales Qualified Leads: Increases in Sales Qualified Leads (SQLs) from referred accounts indicate a robust pipeline of high-intent opportunities, which generally leads to higher retention and expansion rates, positively impacting NRR.
Lagging

These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.
- Expansion Revenue Growth Rate: Measures the rate of expansion revenue from referred accounts, which is a direct component of NRR. A high rate confirms that upsell and cross-sell motions are effective and that NRR is being driven by account growth.
- Referral Retention Rate: Tracks the retention of customers acquired via referral. High referral retention directly supports stronger Referred Account NRR by minimizing churn in the referred segment.
- Revenue Churn Rate: Quantifies the percentage of recurring revenue lost from referred accounts due to churn or downgrades. A lower revenue churn rate amplifies NRR, while a rise signals underlying issues.
- Customer Downgrade Rate: High downgrade rates among referred customers negatively impact NRR by reducing expansion revenue and signaling potential product or value-fit issues.
- Net Revenue Churn: Net Revenue Churn incorporates both lost and gained revenue, providing a comprehensive view of how churn and expansion interact to influence overall NRR for referred accounts.