# Monitor Adoption Health

> Define and monitor adoption health metrics to identify at-risk accounts and expansion opportunities. Use this skill when a team needs to systematically track whether customers are successfully adopting and getting value from the product.

- Skill: `alexe-ev/monitor-adoption-health` (Agent Skill, multi-file: 5 files)
- Install (CLI): `npx skillmds@latest add alexe-ev/monitor-adoption-health`
- Raw SKILL.md: https://api.skillmd.com/api/skills/alexe-ev/monitor-adoption-health/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: alexe-ev (https://skillmd.com/u/alexe-ev)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/alexe-ev/monitor-adoption-health

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# Monitor Adoption Health

## Purpose
Help teams define adoption health metrics and build a monitoring system that surfaces at-risk accounts and expansion opportunities.

## Skill type
Conceptual skill

## Use this skill when
- The team doesn't know which accounts are healthy vs. at-risk
- Churn is reactive rather than proactive (teams find out after customers leave)
- Expansion opportunities are not being surfaced systematically
- A new product or feature needs adoption monitoring from launch

## Do not use this skill when
- The goal is churn analysis after the fact (use analyze-churn-retention)
- The goal is broad product metrics design (use design-product-metrics)

## Required inputs
- Product type and customer segment
- Key product value behaviors (what does a successful customer do?)

## Optional inputs
- Current usage data
- Account tiers or segments
- Existing health score methodology
- CS team capacity and workflow

## Upstream context
Works best when:
- Customer segments are defined
- Core value metrics are known

## Downstream handoff
Output can feed:
- analyze-churn-retention (at-risk signals feed churn analysis)
- plan-lifecycle-engagement (health signals trigger lifecycle interventions)

## Instructions
1. Define what "healthy adoption" looks like for this product (key behaviors and milestones).
2. Define at-risk signals (absence of value behaviors, declining usage, support escalations).
3. Design a health score model: inputs, weighting, tiers.
4. Define monitoring cadence and alerting thresholds.
5. Design the intervention workflow when at-risk accounts are identified.
6. Identify expansion signals (high usage, new user invitations, feature depth).

## Output
Provide:
- Definition of healthy adoption (behaviors and milestones)
- At-risk signal list
- Health score model design (inputs, weighting, tiers)
- Monitoring cadence and alerting thresholds
- Intervention workflow for at-risk accounts
- Expansion signal identification
- Data requirements

## Risks / caveats
- Health scores are only as good as their input data — instrument before scoring
- A health score not acted on is a dashboard decoration
- Define health per segment — one-size-fits-all health scores miss segment variation