R
risk-scoring-framework
About risk-scoring-framework
A skill for designing and validating customer health scores used to prioritize customer success work. It covers signal weighting, tier-based playbooks, outcome testing, and governance.
Key features
- 01Catalog health signals and owners
- 02Set weights and freshness decay
- 03Map scores to action tiers
- 04Back-test against business outcomes
- 05Define review and ownership processes
Use cases
- 01Prioritizing customer success outreach
- 02Aligning teams on at-risk definitions
- 03Investigating churn and expansion patterns
Install
Copy the command and run it in a terminal.
$
npx skills add https:/After installing, type/risk-scoring-frameworkin Claude Code to confirm it loaded.
Details
From the project READMERisk 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
- Signal Inventory – usage, sentiment, support, commercial, product feedback, exec engagement.
- Weighting & Decay – assign weights per signal, set freshness decay, define negative indicators.
- Tier Mapping – convert scores to tiers (green/yellow/red) with playbook hooks.
- Validation Loop – back-test against churn, expansion, and NPS outcomes.
- 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-healthoutput to auto-highlight risks.
Comments
Markdown supported