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Skill

/risk-scoring-framework

Method for calculating customer health/risk tiers using quantitative

From plugin
gtm-agents
368200 skills200 agents199 commands
Install
$ npx -y skills add gtmagents/gtm-agents --skill risk-scoring-framework --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/risk-scoring-framework

Context preview

The summary Claude sees to decide when to auto-load this skill.

Method for calculating customer health/risk tiers using quantitative

SKILL.md

risk-scoring-framework.SKILL.md
name: risk-scoring-framework
description: Method for calculating customer health/risk tiers using quantitative
  + qualitative data.

Risk Scoring Framework Skill

When to Use

  • Building or tuning customer health scores that drive CS prioritization.
  • Aligning RevOps, CS, and product on what “healthy” vs “at-risk” looks like.
  • Auditing why certain segments churn or expand more than others.

Framework

1. **Signal Inventory** – usage, sentiment, support, commercial, product feedback, exec engagement. 2. **Weighting & Decay** – assign weights per signal, set freshness decay, define negative indicators. 3. **Tier Mapping** – convert scores to tiers (green/yellow/red) with playbook hooks. 4. **Validation Loop** – back-test against churn, expansion, and NPS outcomes. 5. **Governance** – review cadence, owner accountability, and change management process.

Templates

  • Signal catalog spreadsheet with weights and owners.
  • Tier thresholds + play mapping sheet.
  • Validation report template comparing scores vs outcomes.

Tips

  • Combine structured data with CSM notes or sentiment highlights for context.
  • Keep tiers simple (3-4) to avoid confusion; use tags for nuance.
  • Pair with `monitor-customer-health` output to auto-highlight risks.

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