cs-health-scorecard
The cs-health-scorecard skill generates a structured, weighted health assessment for customer accounts based on five dimensions: product adoption, engagement, outcomes, support health, and commercial performance. Use this when a customer success manager or leader needs to quantify renewal risk, prioritize intervention efforts, evaluate expansion potential, or present account status to leadership. The output provides a RAG status (red, amber, or green), dimension scores, trend indicators, key risks, and specific recommended actions.
git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills /tmp/cs-health-scorecard && cp -r /tmp/cs-health-scorecard/plugins/pm-cs/skills/cs-health-scorecard ~/.claude/skills/cs-health-scorecardSKILL.md
# 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. ## Reads from / Writes to the Brain If a [`professional-brain`](../professional-brain/SKILL.md) (`brain/`) exists, ground in it instead of re-asking for what you already know: - **Read first:** the account's `entities/` file, its `stakeholders/` (champion, economic buyer, detractors), and `knowledge/`. Run `python3 ../professional-brain/scripts/brain_query.py ./brain "<account name>"` and carry each fact's provenance tag through. - **📥 Propose to the Brain:** after producing, propose recording the health verdict + key risks to the account `entities/` file, and a renewal-risk entry to `decisions/` if a call is made, each provenance-tagged. Show them, get a yes, then write with `../professional-brain/scripts/brain_write.py … --commit` (append-only, dry-run by default). ## 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) ## Programmatic Helper This skill ships with a stdlib-only Python script that applies the weights above and converts the weighted total to a RAG status — so the headline score is computed identically every time and weights always sum to 100%. ```bash # Five scores 1-5 in order: adoption engagement outcomes support commercial python3 scripts/health_score.py --scores 4 3 4 2 5 --account "Acme Corp" # Or from JSON (lets you override the default weights per account/segment) python3 scripts/health_score.py --input account.json ``` It returns the per-dimension weighted points, the **total out of 100**, and the **RAG band** (Green ≥80, Amber 60–79, Red <60) with a one-line next step. Run it to set the headline number, then write the dimension detail and actions below around it. Add `--json` for downstream tooling. ## Output Format --- # 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] --- ## 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** | | --- ## 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] --- ## Top Risks | Risk | Severity | Mitigation | |---|---|---| | [Risk description] | High / Medium / Low | [Specific action to mitigate] | --- ## Recommended Actions **Immediate (this week):** 1. [Action — owner — deadline] **This month:** 1. [Action — owner — deadline] **Before renewal:** 1. [Action — owner — deadline] --- ## 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] --- ## Quality Checks - [ ] Score is based on data, not gut feel — each dimension has evidence - [ ] R
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