Gross Revenue Churn Rate¶

Definition¶

Gross Revenue Churn Rate measures the percentage of total recurring revenue lost due to cancellations or downgrades over a given period. It helps quantify the direct revenue impact of churn.

Description¶

Gross Revenue Churn is a key indicator of revenue retention health, reflecting how much recurring revenue is lost due to downgrades or customer churn, without offsetting expansion revenue.

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

In SaaS, it tracks contract cancellations or plan reductions
In usage-based models, it reflects drop-offs in consumption billing
In subscriptions, it may include non-renewals or plan downgrades

A rising churn rate signals customer dissatisfaction, support gaps, or pricing misalignment, while a declining trend reflects strong retention, account health, and product stickiness. By segmenting by plan, vertical, or customer tier, you can pinpoint which accounts or segments are most at risk and refine your save plays, packaging, and lifecycle touchpoints.

Gross Revenue Churn informs:

Strategic decisions, like retention investments and pricing model reviews
Tactical actions, such as churn flagging and CS outreach triggers
Operational improvements, including cancellation flow feedback and win-back campaign design
Cross-functional alignment, connecting product, CS, finance, and lifecycle teams to reduce churn and secure revenue stability

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

Onboarding Success and Feature Adoption: Accounts that don’t hit early value milestones are far more likely to churn or downgrade.
Support Quality and Friction Points: If users run into blockers or bugs without resolution, they walk.
Renewal Process and Expansion Pathways: If renewals are reactive, or expansion feels optional, gross churn rises.

Improvement Tactics & Quick Wins¶

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

If gross churn is high, segment by cohort and identify shared patterns among recently lost accounts.
Add automated renewal prep touchpoints 30–60 days out, with a success recap or usage snapshot.
Run a save campaign offering roadmap previews or plan optimization calls to downgrade-prone users.
Refine in-app feedback and support response workflows to address churn triggers before they escalate.
Partner with product and CS to monitor NPS and usage drop-offs 60 days before renewal.

Required Datapoints to calculate the metric
- Churned Revenue from Existing Customers
- Total Recurring Revenue at Start of Period
Example to show how the metric is derived
- Starting ARR: $2M
- Lost ARR from churn: $250K
- Formula: $250K ÷ $2M = 12.5% Gross Revenue Churn Rate

Formula¶

Formula

\[ \mathrm{Gross\ Revenue\ Churn\ Rate} = \left( \frac{\mathrm{Churned\ MRR\ or\ ARR}}{\mathrm{Starting\ MRR\ or\ ARR}} \right) \times 100 \]

Data Model Definition¶

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

RevenueChurn

cube(`RevenueChurn`, {
  sql: `SELECT * FROM revenue_churn`,

  measures: {
    churnedRevenue: {
      sql: `churned_revenue`,
      type: `sum`,
      title: `Churned Revenue`,
      description: `Total revenue lost due to cancellations or downgrades.`
    },
    totalRecurringRevenueStart: {
      sql: `total_recurring_revenue_start`,
      type: `sum`,
      title: `Total Recurring Revenue at Start`,
      description: `Total recurring revenue at the start of the period.`
    },
    grossRevenueChurnRate: {
      sql: `churned_revenue / NULLIF(total_recurring_revenue_start, 0)`,
      type: `number`,
      format: `percent`,
      title: `Gross Revenue Churn Rate`,
      description: `Percentage of total recurring revenue lost due to cancellations or downgrades.`
    }
  },

  dimensions: {
    id: {
      sql: `id`,
      type: `string`,
      primaryKey: true
    },
    customerId: {
      sql: `customer_id`,
      type: `string`,
      title: `Customer ID`,
      description: `Unique identifier for the customer.`
    },
    periodStart: {
      sql: `period_start`,
      type: `time`,
      title: `Period Start`,
      description: `Start date of the 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.
- Onboarding Success and Feature Adoption: Poor onboarding and low feature adoption lead to higher churn as customers fail to see value.
- Support Quality and Friction Points: Inadequate support and unresolved issues increase churn as customers become frustrated.
- Renewal Process and Expansion Pathways: Reactive renewals and lack of clear expansion opportunities result in higher churn rates.
- Customer Satisfaction: Low customer satisfaction due to unmet expectations or poor service increases churn likelihood.
- Market Competition: Increased competition offering better value or features can lead to higher churn as customers switch.
Positive influences

Factors that push the metric in a favorable direction, supporting growth or improvement.
- Onboarding Success and Feature Adoption: Effective onboarding and high feature adoption reduce churn by ensuring customers realize value early.
- Support Quality and Friction Points: High-quality support and quick resolution of issues decrease churn by maintaining customer satisfaction.
- Renewal Process and Expansion Pathways: Proactive renewals and clear expansion opportunities lower churn by encouraging continued engagement.
- Customer Engagement: High levels of customer engagement and interaction with the product reduce churn by building loyalty.
- Product Innovation: Continuous product improvements and innovations decrease churn by keeping the offering competitive and valuable.

Involved Roles & Activities¶

Involved Roles

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

Customer Success
Finance
Product Marketing (PMM)
Revenue Operations
Activities

Common initiatives or actions associated with this KPI:

Renewals
Pricing Strategy
Churn Reduction Programs
Product Engagement

Funnel Stage & Type¶

AAARRR Funnel Stage

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

Retention
Revenue
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.
- Churn Risk Score: As a predictive metric estimating the likelihood of customer churn or downgrade, a higher Churn Risk Score often forecasts future increases in Gross Revenue Churn Rate. Monitoring this score enables proactive retention actions to mitigate future revenue losses.
- Customer Loyalty: High customer loyalty indicates reduced risk of churn and downgrades. A drop in this leading sentiment metric can signal an impending increase in Gross Revenue Churn Rate, providing an early warning to address root causes before revenue loss materializes.
- Activation Rate: Lower activation rates among new users may foreshadow future increases in churn and revenue loss, as poor initial engagement often results in cancellations or downgrades that will ultimately impact Gross Revenue Churn Rate.
- Product Qualified Accounts: A declining number or percentage of PQAs signals a shrinking pool of accounts with product-fit and engagement, increasing the likelihood of future downgrades and cancellations reflected in Gross Revenue Churn Rate.
- Customer Health Score: This composite metric aggregates product usage, satisfaction, and engagement signals. Deteriorating health scores across accounts typically precede spikes in revenue churn, as unhealthy accounts are more likely to downgrade or cancel.
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: Directly feeds into Gross Revenue Churn Rate by quantifying the proportion of revenue lost from existing customers who reduce their subscription value. High downgrade rates amplify overall revenue churn.
- Revenue Churn Rate: Closely related, this metric tracks all recurring revenue lost due to churn and downgrades. Comparing Gross Revenue Churn Rate with Revenue Churn Rate helps explain the impact of expansion revenue offsets and overall churn dynamics.
- Customer Churn Rate: Measures the percentage of customers lost, providing context for Gross Revenue Churn Rate by showing if revenue loss is due to high-value customers leaving (high revenue churn, low customer churn) or broad customer attrition.
- Contract Renewal Rate: A lower renewal rate directly increases Gross Revenue Churn Rate, as non-renewals represent revenue lost from previously recurring contracts.
- Net Revenue Churn: Accounts for both lost and expansion revenue, providing a comprehensive view of revenue retention. Comparing Net Revenue Churn with Gross Revenue Churn Rate quantifies the net business impact and helps explain churned revenue in the broader context of upsells and expansions.