cyberneticlibrary

Score customer health and churn risk

customer-success-managerskillsetup L2137
borghei/Claude-Skills
What it does

Score customer health, predict churn, identify expansion

Best for

Quarterly business reviews and account planning by scoring customer health across usage, engagement, support, and relationship dimensions.

Inputs
  • · Customer JSON with usage, engagement, support, relationship metrics
  • · Optional: segment (Enterprise/Mid-Market/SMB)
Outputs
  • · Health score (Red/Yellow/Green)
  • · Churn risk tier
  • · Expansion opportunities
  • · QBR template
Requires
  • · Python CLI (standard library only, no external deps)
  • · JSON customer data
Preconditions
  • · Customer data schema (see assets/sample_customer_data.json)
  • · Segment labels optional (defaults to configuration)
Failure modes
  • · Health score cannot capture qualitative relationship risk
  • · Churn prediction skips intent signals (e.g., CEO departure)
  • · Expansion scoring requires adoption depth not always in data
  • · Thresholds generic; do not reflect industry benchmarks
Trust signals
  • · Multi-dimensional health scoring
  • · Python CLI tools with no external dependencies
  • · JSON input schema with examples
  • · Red/Yellow/Green classification