Relationship Depth Score

Definition

Relationship Depth Score measures the strength and breadth of engagement between your team and customer stakeholders across roles, levels, and functions. It helps assess account health, expansion potential, and advocacy readiness.

Business Context

Relationship Depth Score is a key indicator of account stickiness, stakeholder alignment, and churn risk mitigation, reflecting how many and how meaningfully different roles are engaged within a customer account.

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

In B2B SaaS, it covers economic buyers, admins, champions, and end-users
In enterprise sales, it may include cross-functional and VP/C-suite engagement
In PLG, it tracks role-based usage and multi-team expansion

A low score suggests fragile relationships or single-threaded accounts, while a high score indicates broad buy-in, expansion readiness, and churn resilience.

By segmenting by vertical, account size, or CSM, you can target at-risk accounts, build stronger executive alignment, and drive more resilient growth.

Relationship Depth Score informs:

Strategic decisions, like forecasting renewals or planning multi-threaded sales
Tactical actions, such as triggering outreach when key roles disengage
Operational improvements, including CRM role tagging and stakeholder mapping
Cross-functional alignment, across CS, marketing, and sales for account-based retention and growth plays

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

Multi-User Engagement and Role Diversity: The more stakeholders activated, the harder it is to churn.
Cross-Functional Feature Adoption: If only one team uses the product, your footprint stays shallow.
CS and Sales Touchpoint Breadth: Personalized engagement beyond the “main contact” builds relationship resilience.

Improvement Tactics & Quick Wins

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

If depth is weak, map stakeholder roles per account and flag single-threaded accounts in your CRM.
Add in-app nudges or CS outreach encouraging account admins to invite other departments.
Run executive alignment campaigns — especially ahead of QBRs or renewals.
Refine onboarding flows to include use-case guidance by persona (e.g., ops, finance, end users).
Partner with product and CS to drive cross-role adoption of new features or dashboards.

Activities commonly tied to improving or operationalizing this KPI.

Activity	Description
Account Planning	Account Planning focuses on Account Planning defines the objectives, priorities, and sequence of actions for developing a strategic account. It gives teams a clear plan for where to focus, how to sequence work, and what to measure. Relevant KPIs include Relationship Depth Score.
QBRs	QBRs are structured, recurring meetings between provider teams—such as sales, customer success, or product—and their customers. It helps teams translate strategy into repeatable execution. Relevant KPIs include Referral-Ready Account Rate and Relationship Depth Score.
Customer Mapping	Customer Mapping focuses on systematically identifying and profiling key stakeholders within a target customer organization. It turns signals into decisions, interventions, and measurable follow-up. Relevant KPIs include Relationship Depth Score.
Expansion Campaigns	Expansion Campaigns involves strategic initiatives and coordinated actions designed to increase the value of existing customers through cross-selling, upselling, or introducing new product features and services. It coordinates execution across touchpoints so teams can move users or accounts toward the target outcome. Relevant KPIs include Activation-to-Expansion Rate and Expansion Activation Rate.
Stakeholder Engagement	Stakeholder Engagement involves proactively identifying, understanding, and collaborating with key internal and external stakeholders throughout the customer journey. It coordinates execution across touchpoints so teams can move users or accounts toward the target outcome. Relevant KPIs include Relationship Depth Score.

Required Datapoints

Number of unique stakeholders engaged per account
Roles and levels of those stakeholders (e.g., Champion, Decision Maker)
Engagement frequency (meetings, emails, product usage)
Optional: stakeholder satisfaction or sentiment (via CS or NPS)

Example

4 stakeholders engaged (Champion, Admin, Exec, User)

2 departments involved

Recent QBR attended

Score = 85 (Strong Relationship Depth)

Formula

\mathrm{Relationship\ Depth\ Score} = \min\left( \left( 15 \times \mathrm{Engaged\ Stakeholders} \right) + \left( 25 \times \mathrm{Executive\ Engagement} \right) + \left( 10 \times \mathrm{Cross\ Functional\ Representation} \right) + \left( 20 \times \mathrm{Recent\ Meaningful\ Interactions} \right), 100 \right)

Positive & Negative Influences

Negative Influences

Single-User Engagement: When engagement is limited to a single user, the Relationship Depth Score tends to decrease as it indicates a lack of broader stakeholder involvement, increasing the risk of churn.
Limited Role Diversity: A lack of engagement across different roles within the customer organization negatively impacts the Relationship Depth Score, as it suggests a narrow relationship scope.
Single-Function Feature Adoption: If the product is only adopted by one function within the customer organization, it limits the depth of the relationship, negatively affecting the score.
Minimal CS and Sales Touchpoints: Limited interaction with customer success and sales teams reduces personalized engagement, leading to a lower Relationship Depth Score.
High Churn Rate: A high churn rate indicates weak relationships and negatively impacts the Relationship Depth Score by highlighting instability in customer engagement.

Positive Influences

Multi-User Engagement: Engagement with multiple users across the customer organization positively influences the Relationship Depth Score by indicating strong stakeholder involvement.
Role Diversity in Engagement: Engagement across various roles within the customer organization enhances the Relationship Depth Score, reflecting a broad and deep relationship.
Cross-Functional Feature Adoption: Adoption of features by multiple functions within the customer organization increases the Relationship Depth Score by demonstrating a wide footprint.
Broad CS and Sales Touchpoints: Frequent and personalized interactions with customer success and sales teams enhance the Relationship Depth Score by building relationship resilience.
Low Churn Rate: A low churn rate suggests strong, stable relationships, positively impacting the Relationship Depth Score by indicating customer satisfaction and retention.

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 lagging Indicator. It reflects the results of past actions or behaviors and is used to validate performance or assess the impact of previous strategies.

Ownership

Primary Owner

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

Account Management

Secondary Owners

These roles contribute directly to performance and typically partner on execution, reporting, or optimization.

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) are an early indicator that multiple stakeholders in an account are actively engaging with the product, often across roles and functions. High PQA counts signal growing account-wide product adoption, which typically leads to deeper and broader relationships, increasing the Relationship Depth Score over time.
Deal Velocity: Deal Velocity reflects the speed at which opportunities move through the sales pipeline. Faster deal velocity usually means better alignment and engagement with multiple decision-makers and influencers within a customer account, which helps to expand stakeholder involvement and raise the Relationship Depth Score.
Customer Loyalty: Customer Loyalty, as a measure of repeat engagement and preference, often precedes broader and deeper relationships within an account. Loyal customers are more likely to introduce your team to new stakeholders and advocate for your product internally, directly improving Relationship Depth Score.
Monthly Active Users: Monthly Active Users (MAU) at the account level indicate consistent, active product engagement by multiple users. Growth in MAU often signals that usage is spreading across different teams or departments, which is a leading indicator of increased relationship depth and engagement breadth.
Activation Rate: A high Activation Rate across accounts suggests that users are quickly reaching value milestones, which helps kickstart broader product adoption. This leads to more stakeholders becoming engaged, thus positively influencing the future Relationship Depth Score.

Lagging

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

Expansion Readiness Index: The Expansion Readiness Index measures how prepared an account is for upsell or cross-sell opportunities, based on engagement and fit. A high score on this index is often a result of deep, multi-level relationships, confirming and quantifying the impact of Relationship Depth Score on expansion potential.
Percent of Accounts with Multi-Role Engagement: This KPI directly quantifies the breadth of engagement within an account by measuring how many have users from multiple roles actively engaged. It amplifies and confirms the business value of a high Relationship Depth Score by showing the extent of cross-functional adoption.
Customer Engagement Score: Customer Engagement Score measures the frequency and quality of interactions with your product. A high Relationship Depth Score often results in higher engagement, and this score helps confirm the positive business impact of broad and deep relationships within the account.
Expansion Revenue Growth Rate: Expansion Revenue Growth Rate reflects increased revenue from existing accounts through upsell or cross-sell. Deep and broad stakeholder relationships (as measured by Relationship Depth Score) are a prerequisite for successful expansion, so this KPI quantifies the downstream business impact.
Net Revenue Retention: Net Revenue Retention (NRR) measures recurring revenue growth from existing customers, accounting for expansions and contractions. Strong relationship depth is a key driver of high NRR, so this lagging KPI serves to confirm and amplify the long-term business value of deep account relationships.

Data Model Definition

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

cube('Engagements', {
  sql: `SELECT * FROM engagements`,

  measures: {
    uniqueStakeholders: {
      sql: `stakeholder_id`,
      type: 'countDistinct',
      title: 'Unique Stakeholders Engaged',
      description: 'Number of unique stakeholders engaged per account.'
    },
    engagementFrequency: {
      sql: `engagement_id`,
      type: 'count',
      title: 'Engagement Frequency',
      description: 'Total number of engagements (meetings, emails, product usage) per account.'
    }
  },

  dimensions: {
    id: {
      sql: `id`,
      type: 'string',
      primaryKey: true
    },
    accountId: {
      sql: `account_id`,
      type: 'string',
      title: 'Account ID',
      description: 'Unique identifier for the account.'
    },
    role: {
      sql: `role`,
      type: 'string',
      title: 'Role',
      description: 'Role of the stakeholder (e.g., Champion, Decision Maker).'
    },
    level: {
      sql: `level`,
      type: 'string',
      title: 'Level',
      description: 'Level of the stakeholder within the organization.'
    },
    engagementType: {
      sql: `engagement_type`,
      type: 'string',
      title: 'Engagement Type',
      description: 'Type of engagement (meeting, email, product usage).'
    },
    engagementDate: {
      sql: `engagement_date`,
      type: 'time',
      title: 'Engagement Date',
      description: 'Date of the engagement.'
    }
  }
});

cube('StakeholderSentiment', {
  sql: `SELECT * FROM stakeholder_sentiment`,

  measures: {
    averageSentiment: {
      sql: `sentiment_score`,
      type: 'avg',
      title: 'Average Sentiment Score',
      description: 'Average sentiment score of stakeholders per account.'
    }
  },

  dimensions: {
    id: {
      sql: `id`,
      type: 'string',
      primaryKey: true
    },
    accountId: {
      sql: `account_id`,
      type: 'string',
      title: 'Account ID',
      description: 'Unique identifier for the account.'
    },
    sentimentDate: {
      sql: `sentiment_date`,
      type: 'time',
      title: 'Sentiment Date',
      description: 'Date when the sentiment was recorded.'
    }
  }
});

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