Measure Relationships

Track Health Across the Full Customer Lifecycle

The Problem

You have customers. How are they doing?

Most organizations can answer this question for pipeline ("we have $2M in Stage 3") but not for actual customers. Ask about relationship health and you get:

  • "I think they're happy? No one's complained lately."
  • "Let me check when we last talked to them..."
  • "They renewed last year, so probably fine?"

The blindness: Organizations measure pre-sale exhaustively (pipeline stages, deal velocity, win rates) and measure post-sale almost not at all. The result is that the relationships that actually drive sustainable business — existing customers — are invisible until something goes wrong.

The Value-First Approach

Relationship health isn't a feeling. It's observable through behavior, captured in objects, and trackable over time.

The principle: Every customer relationship should have a health indicator based on actual engagement, delivery progress, commercial patterns, and advocacy behavior — not just "no news is good news."

This isn't customer satisfaction surveys. It's continuous observation of relationship signals that predict renewal, expansion, and advocacy.

What Relationship Health Actually Means

It's Multi-Dimensional

Relationship health isn't one number. It's a composite of:

Engagement Health:

Are they actively engaging? Using what they bought? Attending sessions? Asking questions?

Delivery Health:

Is value being created? Are milestones being hit? Are they satisfied with outputs?

Commercial Health:

Are they paying on time? Is the subscription active? Are expansion signals present?

Advocacy Health:

Are they sharing success? Referring others? Participating in case studies?

It Changes Over Time

Relationship health isn't static. Someone can be:

  • Thriving → then hit a problem → become At Risk
  • Stable → then have a breakthrough → become Thriving
  • At Risk → then receive intervention → return to Stable

Tracking health over time reveals patterns that point-in-time snapshots miss.

Objects That Enable This

Contact (Individual Health)

Person-level relationship tracking

Each Contact can have relationship indicators:

Contact: Sarah Chen
Value Path Stage: Adopter
Engagement Level: High
Last Engagement: 3 days ago
Advocacy Signals: 4 (case study, 2 referrals, LinkedIn post)
Sentiment: Positive

Why Contact-level matters: Aggregate "account health" hides individual variation. Tom in Operations might be thriving while Mike in IT is struggling. Both affect the relationship.

Company (Account Health)

Organizational relationship tracking

Company records aggregate health:

Company: Precision Components
Relationship Stage: Adopter
Account Health: Thriving
Health Trend: Stable (6 months)
Contacts: 5 (4 thriving, 1 stable)
Active Services: 1
Service Health: On Track
Subscription Status: Active
Payment Pattern: Prompt
Advocacy Score: High
Expansion Potential: High

Key properties:

  • Relationship Stage (Value Path stage at account level)
  • Account Health (Thriving, Healthy, Stable, Needs Attention, At Risk)
  • Health Trend (Improving, Stable, Declining)
  • Expansion Potential
  • Advocacy Score

Service (Delivery Health)

Value delivery tracking

Service records show delivery relationship:

Service: CVP Implementation — Precision Components
Health: On Track
Phase: Optimization
Deliverables: 12/12 Complete
Ticket Trend: Decreasing (good sign)
Last Touchpoint: 5 days ago
Customer Satisfaction: Positive

Signal (Behavioral Evidence)

Observable engagement patterns

Signals provide the raw data for health assessment:

Recent Signals — Precision Components:

Sarah Chen:
- Login: Yesterday
- Feature usage: Dashboard, Reports, Workflows
- Training completion: Advanced module
- Feedback submitted: Positive

Tom Rodriguez:
- Login: Today
- Feature usage: Daily operations
- Question submitted: Optimization request

Pattern: Active engagement, expanding usage, optimization-focused questions
Health implication: Thriving

Subscription (Commercial Health)

Recurring revenue relationship

Subscription status indicates commercial health:

Subscription: Managed Partnership — Precision Components
Status: Active
Health: Healthy
Payment History: 100% on-time (12 months)
Renewal Date: February 2026
Expansion Signals: Cleveland team inquiry

Building a Health Model

Step 1: Define Health Dimensions

Dimension What It Measures Key Indicators
Engagement Active participation Login frequency, feature usage, session attendance
Delivery Value creation progress Service health, deliverable completion, ticket resolution
Commercial Financial relationship Payment patterns, subscription status, expansion signals
Advocacy External sharing Referrals, testimonials, case study participation

Step 2: Define Health Levels

Level Meaning Typical Indicators
Thriving Exceptional relationship High engagement, expanding usage, active advocacy
Healthy Strong relationship Regular engagement, satisfied, stable
Stable Adequate relationship Basic engagement, no concerns, no growth
Needs Attention Emerging concerns Declining engagement, slow responses, minor issues
At Risk Significant concerns Minimal engagement, payment issues, complaints

Step 3: Configure Properties

On Contact:

  • Individual Health (Thriving/Healthy/Stable/Needs Attention/At Risk)
  • Last Engagement Date
  • Engagement Trend
  • Advocacy Score

On Company:

  • Account Health (Thriving/Healthy/Stable/Needs Attention/At Risk)
  • Health Trend (Improving/Stable/Declining)
  • Expansion Potential (High/Medium/Low/None)
  • Renewal Risk (Low/Medium/High)

On Service:

  • Health Status (On Track/Needs Attention/At Risk/Blocked)
  • Customer Satisfaction
  • Engagement Level

On Subscription:

  • Health (Healthy/At Risk/Churning)
  • Renewal Likelihood

Step 4: Build Health Calculations

Simple approach:

Manual health assessment updated regularly

Intermediate approach:

Health score based on weighted factors:

  • Last engagement date (recency)
  • Engagement frequency (regularity)
  • Service health status
  • Payment status
  • Support ticket patterns

Advanced approach:

Calculated properties combining multiple signals with automated alerts when patterns change

How They Connect

RELATIONSHIP HEALTH MAP

Company: Precision Components
│
├── Account Health: Thriving (aggregated)
│
├── Contact: Sarah Chen
│   └── Individual Health: Thriving
│       └── Signals: High engagement, advocacy behavior
│
├── Contact: Tom Rodriguez
│   └── Individual Health: Thriving
│       └── Signals: Daily usage, optimization questions
│
├── Contact: Mike Chen
│   └── Individual Health: Stable
│       └── Signals: Occasional engagement, no concerns
│
├── Service: CVP Implementation
│   └── Service Health: On Track
│       └── Deliverables complete, positive feedback
│
├── Subscription: Managed Partnership
│   └── Subscription Health: Healthy
│       └── On-time payments, no churn signals
│
└── Advocacy Score: High
    └── Signals: 2 referrals, case study, LinkedIn post

What This Enables

Early Warning System

Without health tracking:

"We lost Precision Components? I had no idea they were unhappy."

With health tracking:

"Precision Components health declined from Thriving to Needs Attention last month — engagement dropped, Sarah missed two scheduled calls. Triggered outreach revealed budget concerns. Addressed with payment flexibility. Back to Healthy."

Prioritized Attention

Without health tracking:

All customers treated the same. Squeaky wheels get attention.

With health tracking:

Dashboard shows 3 accounts At Risk, 7 Need Attention, 45 Stable, 12 Thriving. Resources focused on At Risk first.

Renewal Prediction

Without health tracking:

Renewal time is surprise time. Scramble to assess and prepare.

With health tracking:

6 months before renewal: Health is Thriving, expansion signals present, advocacy score high. Renewal conversation is expansion conversation.

Advocacy Identification

Without health tracking:

"Who should we ask for referrals?" (Random guessing)

With health tracking:

"These 12 accounts are Thriving with high advocacy scores. 3 have already referred naturally. Start there."

Practical Examples

Example: Health Dashboard

CUSTOMER HEALTH OVERVIEW

By Health Level:
├── Thriving: 12 accounts (24%)
├── Healthy: 23 accounts (46%)
├── Stable: 11 accounts (22%)
├── Needs Attention: 3 accounts (6%)
└── At Risk: 1 account (2%)

Trend:
├── Improving: 8 accounts
├── Stable: 38 accounts
└── Declining: 4 accounts

Action Required:
├── At Risk: Acme Corp — No engagement 45 days, payment overdue
├── Needs Attention: Beta Inc — Engagement declining, missed calls
├── Needs Attention: Gamma LLC — Service health degraded
└── Needs Attention: Delta Co — Key contact left

Example: Individual Account View

PRECISION COMPONENTS — Health Detail

Overall: Thriving (6 months stable)

Engagement:
└── Last 30 days: 23 logins, 3 sessions attended, 5 questions
└── Trend: Increasing
└── Key contacts all active

Delivery:
└── Service: On Track
└── All deliverables complete
└── Optimization phase active

Commercial:
└── Subscription: Active ($4,995/month)
└── Payment: 100% on-time
└── Expansion signals: Cleveland inquiry

Advocacy:
└── Referrals: 2 (Jennifer Walsh, Marcus Thompson)
└── Case study: Participated
└── Public: LinkedIn post

Recommendation: Expansion conversation ready

Example: Health Change Alert

ALERT: Health Decline Detected

Account: Beta Industries
Previous Health: Healthy
Current Health: Needs Attention
Change Date: December 1

Factors:
├── Engagement: Declined 60% (was weekly, now monthly)
├── Key Contact: Sarah left company November 15
├── Service: Last session cancelled
└── Subscription: Still active, no payment issues

Recommended Action:
1. Identify new champion contact
2. Re-onboarding conversation
3. Value reconfirmation

The Transformation

Before

"How are our customers doing?"

"I think... mostly fine? We'd hear if something was wrong."

After

"How are our customers doing?"

"50 accounts total. 12 Thriving — ready for expansion conversations. 23 Healthy — stable, monitoring. 11 Stable — could be developed. 3 Need Attention — intervention in progress. 1 At Risk — meeting scheduled tomorrow. Overall health trend: stable with 3 improving this month."

That's the difference between hoping relationships are healthy and knowing.

Common Pitfalls

Binary health (just "good" and "bad")

Health is a spectrum. Five levels minimum to capture meaningful variation.

Only account-level

Individual Contact health matters. An account can look healthy while a key champion is struggling.

Static assessment

Health changes. Regular review cadence (weekly or monthly) keeps data meaningful.

Health without action

A dashboard showing At Risk accounts is worthless if no one acts on it. Build health into workflows.

Over-automation

Health scores can inform but shouldn't replace human judgment. Use them as signals, not verdicts.

Related Resources

Related Unified Views

Related Stages

  • Adopter — Where ongoing health tracking matters most
  • Advocate — Where health becomes advocacy potential