cs-health-scorecard

Customer Health Scorecard Skill

Produce a structured, data-driven health scorecard for a customer account — giving the CSM and leadership a clear view of renewal risk, expansion potential, and the actions needed to move the account in the right direction.

Required Inputs

Ask for these if not already provided:

• Account name and tier (enterprise / mid-market / SMB)
• Contract value (ARR) and renewal date
• Product usage data — logins, DAU/MAU ratio, key feature adoption
• Support data — open tickets, CSAT or NPS score, recent escalations
• Engagement data — last QBR date, executive sponsor status, champion name
• Commercial data — payment history, expansion conversations, seats used vs. licensed
• Any known risks or recent changes at the account

Scoring Framework

Score each dimension 1–5. Weight as shown. Calculate weighted total out of 100.

Dimension	Weight	What to Score
Product Adoption	30%	DAU/MAU ratio, breadth of features used, power users identified
Engagement	20%	QBR cadence, executive sponsor active, champion strength
Outcomes	20%	Customer hitting their stated goals / success metrics
Support Health	15%	Ticket volume trend, unresolved escalations, CSAT
Commercial	15%	On-time payments, seats utilised, expansion signals

Score → RAG conversion:

• 80–100: Green (healthy, renew likely)
• 60–79: Amber (at risk, needs attention)
• 0–59: Red (high churn risk, escalate)

Output Format

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Customer Health Scorecard: [Account Name]

CSM: [Name] | Tier: [Enterprise / Mid-Market / SMB] ARR: £/$/€[X] | Renewal date: [Date] | Days to renewal: [N] Overall health: [Green / Amber / Red] — [Score]/100 Last updated: [Date]

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Health Score Summary

Dimension	Score (1–5)	Weight	Weighted Score	Trend
Product Adoption	[1–5]	30%	[X]	↑ / → / ↓
Engagement	[1–5]	20%	[X]	↑ / → / ↓
Outcomes	[1–5]	20%	[X]	↑ / → / ↓
Support Health	[1–5]	15%	[X]	↑ / → / ↓
Commercial	[1–5]	15%	[X]	↑ / → / ↓
Total	—	100%	[X]/100

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Dimension Detail

Product Adoption — [Score]/5

• DAU/MAU ratio: [X]% (benchmark: >25% = healthy)
• Key features adopted: [List features in use]
• Features not adopted: [List unused high-value features]
• Power users identified: [Yes / No — how many]
• Assessment: [1–2 sentences on adoption health]

Engagement — [Score]/5

• Last QBR: [Date] — [Outcome summary]
• Next QBR: [Scheduled / Overdue]
• Executive sponsor: [Active / Passive / Vacant]
• Champion: [Name, role, strength: strong / moderate / weak]
• Assessment: [1–2 sentences]

Outcomes — [Score]/5

• Customer's stated goals: [List 2–3 goals from onboarding or last QBR]
• Progress against goals: [On track / Partial / Off track]
• Evidence of value: [Metric or quote that demonstrates ROI]
• Assessment: [1–2 sentences]

Support Health — [Score]/5

• Open tickets: [N] (priority breakdown: P1: X, P2: X, P3: X)
• CSAT / NPS: [Score] (benchmark: >8 CSAT / >30 NPS = healthy)
• Unresolved escalations: [Yes / No — details if yes]
• Ticket trend (last 90 days): Increasing / Stable / Decreasing
• Assessment: [1–2 sentences]

Commercial — [Score]/5

• Seats licensed: [N] | Seats active: [N] ([X]% utilisation)
• Payment history: [On time / Late — details]
• Expansion signals: [Yes — describe / No]
• Downgrade or cancellation signals: [Yes — describe / No]
• Assessment: [1–2 sentences]

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Top Risks

Risk	Severity	Mitigation
[Risk description]	High / Medium / Low	[Specific action to mitigate]

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Recommended Actions

Immediate (this week):

1. [Action — owner — deadline]

This month:

1. [Action — owner — deadline]

Before renewal:

1. [Action — owner — deadline]

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Renewal Forecast

Scenario	Probability	ARR at risk
Full renewal at current ARR	[X]%	£/$/€0
Renewal with contraction	[X]%	£/$/€[X]
Churn	[X]%	£/$/€[full ARR]

Recommended renewal play: [Expand / Hold / Save / Manage out]

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Quality Checks

• Score is based on data, not gut feel — each dimension has evidence
• Risks are specific (not "low engagement" — something like "executive sponsor left in March, no replacement identified")
• Actions have owners and deadlines
• Renewal probability is calibrated against pipeline reality
• Trend arrows reflect direction of change vs. last scorecard, not just current state

Anti-Patterns

• Do not score health dimensions on gut feel — every score needs specific supporting evidence
• Do not give a Green status to accounts with unresolved P1 issues or missed milestones
• Do not list risks vaguely — "low engagement" without specifics is not actionable
• Do not leave recommended actions without named owners and deadlines
• Do not conflate product usage frequency with product value delivery