Referral-Ready Account Rate¶

Definition¶

Referral-Ready Account Rate measures the percentage of accounts that meet internal criteria indicating they are ready to be prompted for a referral. It helps identify which customers are best positioned to refer based on health, engagement, or satisfaction signals.

Description¶

Referral-Ready Account Rate is a key indicator of advocacy potential and customer experience health, reflecting how many active accounts meet the internal criteria to be asked for a referral—even if they haven’t been asked yet.

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

In B2B SaaS, readiness may require 3+ months live, NPS >8, onboarding complete, or QBR participation
In PLG, it often tracks activation, team invites, and in-app feedback
In subscription models, it may reflect engagement streaks or tier upgrades

A high rate signals a strong pool of advocate-ready users, while a low rate may uncover onboarding gaps, product-fit issues, or relationship concerns. By scoring and tagging accounts based on success and sentiment signals, you can build an intentional, scalable advocacy pipeline without exhausting customers.

Referral-Ready Account Rate informs:

Strategic decisions, like when to launch referral waves or ask CS to engage accounts
Tactical actions, such as timing referral prompts based on score triggers
Operational improvements, including readiness tagging, CSM alerts, and CRM workflows
Cross-functional alignment, across customer success, lifecycle, and marketing, to turn successful accounts into evangelists at the right time

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

Customer Sentiment and NPS Trends: Promoters are referral-ready. Detractors? Not so much.
Feature Adoption and Engagement Patterns: Power users tend to be most eager to advocate.
Lifecycle Milestones and Timing: Customers just after onboarding or renewal often signal readiness.

Improvement Tactics & Quick Wins¶

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

If referral-ready pool is small, revisit your scoring logic — are you over-relying on NPS?
Add dynamic scoring based on product usage, ticket volume, and expansion behavior.
Run a post-onboarding referral readiness check-in (“How are we doing? Would you recommend us?”).
Refine CS and growth touchpoints to include referral outreach cadences based on readiness flags.
Partner with marketing to personalize referral asks by usage persona or industry.

Required Datapoints to calculate the metric
- Total Number of Active Customer Accounts
- Number of Accounts That Meet Referral-Readiness Criteria
- Readiness Criteria (clearly defined in collaboration with CS, PMM, Growth)
Example to show how the metric is derived

1,200 active accounts 312 met criteria: NPS >8, onboarding completed, and >2 months active Formula: 312 ÷ 1,200 = 26% Referral-Ready Account Rate

Formula¶

Formula

\[ \mathrm{Referral\text{-}Ready\ Account\ Rate} = \left( \frac{\mathrm{Referral\text{-}Ready\ Accounts}}{\mathrm{Total\ Active\ Accounts}} \right) \times 100 \]

Data Model Definition¶

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

Accounts

cube('Accounts', {
  sql: `SELECT * FROM accounts`,

  measures: {
    totalActiveAccounts: {
      sql: `active_customer_accounts`,
      type: 'count',
      title: 'Total Number of Active Customer Accounts',
      description: 'Counts the total number of active customer accounts.'
    },
    referralReadyAccounts: {
      sql: `referral_ready_accounts`,
      type: 'count',
      title: 'Number of Accounts That Meet Referral-Readiness Criteria',
      description: 'Counts the number of accounts that meet the referral-readiness criteria.'
    },
    referralReadyAccountRate: {
      sql: `100.0 * ${referralReadyAccounts} / NULLIF(${totalActiveAccounts}, 0)`,
      type: 'number',
      title: 'Referral-Ready Account Rate',
      description: 'Calculates the percentage of accounts that are ready for referral based on internal criteria.'
    }
  },

  dimensions: {
    id: {
      sql: `id`,
      type: 'string',
      primaryKey: true,
      title: 'Account ID',
      description: 'Unique identifier for each account.'
    },
    createdAt: {
      sql: `created_at`,
      type: 'time',
      title: 'Account Creation Date',
      description: 'The date when the account 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

Positive & Negative Influences¶

Negative influences

Factors that drive the metric in an undesirable direction, often signaling risk or decline.
- Customer Churn Rate: Higher churn rates negatively impact referral readiness, as accounts at risk of leaving are less likely to refer.
- Customer Support Ticket Volume: Increased support ticket volume indicates potential dissatisfaction, reducing referral readiness.
- Product Usage Decline: A decline in product usage suggests decreased engagement, negatively affecting referral readiness.
- Negative Feedback Frequency: Frequent negative feedback is inversely related to referral readiness, as dissatisfied customers are less likely to refer.
- Delayed Payment Incidents: Accounts with delayed payments often indicate financial or satisfaction issues, reducing their referral readiness.
Positive influences

Factors that push the metric in a favorable direction, supporting growth or improvement.
- Customer Sentiment and NPS Trends: Higher NPS scores indicate a greater likelihood of accounts being referral-ready, as promoters are more inclined to refer.
- Feature Adoption and Engagement Patterns: Increased feature adoption and engagement correlate with higher referral readiness, as power users are more likely to advocate.
- Lifecycle Milestones and Timing: Accounts reaching key lifecycle milestones, such as post-onboarding or renewal, show increased readiness for referrals.
- Customer Satisfaction Scores: Higher customer satisfaction scores are directly linked to increased referral readiness, as satisfied customers are more willing to refer.
- Customer Health Scores: Improved customer health scores suggest a higher probability of accounts being referral-ready, as healthier accounts are more engaged and satisfied.

Involved Roles & Activities¶

Involved Roles

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

Customer Success
Growth
Customer Lifecycle Management
Product Marketing (PMM)
Revenue Operations
Activities

Common initiatives or actions associated with this KPI:

Referral Program Targeting
Advocacy Activation
QBRs
NPS Management
Health Score Integration

Funnel Stage & Type¶

AAARRR Funnel Stage

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

Referral
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.
- Product Qualified Accounts: Product Qualified Accounts (PQAs) reflect accounts that have demonstrated high levels of product engagement and readiness, often preceding and predicting an increase in Referral-Ready Account Rate. High PQA levels indicate a growing pool of accounts likely to become referral-ready as they progress through maturity and satisfaction stages.
- Customer Health Score: Customer Health Score acts as an early signal of which accounts are likely to meet the internal criteria for referral readiness. Higher health scores typically precede increases in Referral-Ready Account Rate by indicating strong engagement, satisfaction, and product fit.
- Activation Rate: Activation Rate measures how many users reach meaningful product milestones, which is a key precursor to accounts becoming referral-ready. A higher activation rate signals more accounts entering the pool that may soon meet referral criteria.
- Net Promoter Score: Net Promoter Score (NPS) provides an early indicator of customer advocacy intent and overall satisfaction. Accounts with high NPS are more likely to transition to referral-ready status, thus increases in NPS often foreshadow rises in Referral-Ready Account Rate.
- Customer Loyalty: Customer Loyalty is a forward-looking metric indicating repeated engagement and satisfaction. High loyalty levels suggest a greater proportion of accounts that will become referral-ready, as loyal customers are more apt to advocate and refer.
Lagging

These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.
- Referral Readiness Score: Referral Readiness Score is a predictive composite that quantifies how primed an account is for referral. It directly explains and quantifies the Referral-Ready Account Rate, providing granular insight into which accounts contribute to the aggregate rate.
- Referral Prompt Acceptance Rate: Referral Prompt Acceptance Rate measures the proportion of users who accept referral prompts and is an outcome closely tied to referral readiness. High acceptance rates typically confirm a high Referral-Ready Account Rate and illustrate the effectiveness of prompt timing.
- Customer Engagement Score: Customer Engagement Score quantifies ongoing account interaction and product usage. Higher engagement scores provide a retrospective explanation for why certain accounts became referral-ready, linking back to health and activity patterns.
- Contract Renewal Rate: Contract Renewal Rate confirms long-term satisfaction and account stability, reinforcing and amplifying the Referral-Ready Account Rate. Accounts that renew are more likely to be in a state conducive to referral requests.
- Expansion Readiness Index: Expansion Readiness Index measures the readiness of accounts for upsell or cross-sell, which often overlaps with referral readiness. High expansion readiness explains and amplifies the Referral-Ready Account Rate by indicating accounts that are both satisfied and primed for advocacy.