---
title: "/cs:cco-review — CCO Forcing Questions — Agent Skill for Executives"
description: "/cs:cco-review <plan> — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."
---

# /cs:cco-review — CCO Forcing Questions

<div class="page-meta" markdown>
<span class="meta-badge">:material-account-tie: C-Level Advisory</span>
<span class="meta-badge">:material-identifier: `cco-review`</span>
<span class="meta-badge">:material-github: <a href="https://github.com/alirezarezvani/claude-skills/tree/main/c-level-agents/skills/cco-review/SKILL.md">Source</a></span>
</div>

<div class="install-banner" markdown>
<span class="install-label">Install:</span> <code>claude /plugin install c-level-skills</code>
</div>


**Command:** `/cs:cco-review <plan>`

The retention-obsessed CCO pressure-tests any plan that touches customer experience. Six questions before any retention claim, segmentation change, CS team expansion, or major CS hire.

## When to Run

- Before any board narrative that includes a retention number
- Before approving a CS team headcount expansion
- Before re-segmenting the customer base or changing tier definitions
- Before launching a customer marketing or advocacy program
- Before a major CS hire (CSM, AM, Implementation, Customer Marketing)
- When NRR is "great" but churn complaints from CSMs are increasing
- Before deciding whether to add an AM role separate from CSM

## The Six CCO Questions

### 1. What's the GROSS retention rate?
**Not NRR. Gross.** NRR can hide a leaky bucket behind expansion.
- GRR healthy ≥ 90% at growth stage, ≥ 95% at scale
- If GRR < 85% but NRR > 100%, the product is failing for 15%+ of customers; expansion is masking the failure
- Run `retention_decomposition_analyzer.py`

### 2. What's the #1 reason customers leave?
**If you can't name it, you don't understand churn.**
- 7-category taxonomy: product_fit / competitor_loss / no_value_realized / pricing / champion_left / company_event / tactical_failure
- Preventable churn = product_fit + no_value_realized + tactical_failure
- If preventable > 50%, CS has clear leverage; if < 30%, churn is structural (ICP, market, competition)

### 3. What's the median time-to-value (TTV) by segment?
**Long TTV signals different problems by segment.**
- Long TTV in low tier = ICP misfit; downgrade or kill
- Long TTV in high tier = onboarding broken; fix the Implementation Manager handoff
- TTV is a leading indicator of GRR

### 4. Which customer would you fire today?
**If "none" — your segmentation is broken.**
- Some accounts cost more than they earn (support cost > 50% of ARR + low ICP fit)
- Run `customer_segmentation_designer.py` to surface kill list
- The 3 paths for kill candidates: non-renewal / downgrade-to-tech-touch / raise-price-to-cost-recover

### 5. What's the ARR-per-CSM ratio, and is the model pooled or named?
**Wrong model wastes capacity.**
- Strategic: named + exec sponsor, $300K-$1M ARR/CSM
- Enterprise: named, $500K-$2M
- Mid-market: pooled, $2M-$5M
- SMB: tech-touch, $5M+
- Run `cs_coverage_calculator.py` to size the team

### 6. Is CS in your comp plan, and how is it different from Sales comp?
**Misalignment is the leading indicator of CS failure.**
- CS comp: 70/30 base/variable typical
- Variable: 50% gross retention + 30% net retention + 20% activity
- Anti-pattern: comp CSMs on NPS — they game it
- Anti-pattern: comp CSMs same as Sales — they sell instead of serve

## Workflow

```bash
# 1. Retention decomposition (always start here)
python ../../../skills/chief-customer-officer-advisor/scripts/retention_decomposition_analyzer.py cohorts.json

# 2. Segmentation audit
python ../../../skills/chief-customer-officer-advisor/scripts/customer_segmentation_designer.py customers.json

# 3. Coverage sizing (if making CS team changes)
python ../../../skills/chief-customer-officer-advisor/scripts/cs_coverage_calculator.py book.json
```

## Output Format

```markdown
# CCO Review: <plan>
**Date:** YYYY-MM-DD

## The Decision Being Made
[one sentence — retention | segmentation | coverage | next hire]

## Retention (if applicable)
- GRR: X% (vs vanity NRR of Y%)
- Top churn driver: <category> at X% of churn
- Preventable churn: X% (CS-controllable)
- Leaky-bucket pattern? yes/no

## Segmentation (if applicable)
- Tier distribution: Strategic X / Enterprise X / Mid-market X / SMB X
- Kill list size: N customers (X% of customers, Y% of ARR)
- Upgrade candidates: N

## Coverage (if applicable)
- Current CSMs: N | Required now: M | Required 12mo: P
- Annual cost (12mo): $X
- Manager trigger fired: yes/no

## Org (if applicable)
- Next hire: <CSM | Support | AM | IM | CS Ops | Customer Marketing>
- Why this, not the alternative: <one line>
- Customer outcome unblocked: <specific>

## Verdict
🟢 SHIP | 🟡 SHARPEN | 🔴 BLOCK

## Next Steps
[3 concrete actions]
```

## Routing

- `/cs:cpo-review` — if churn root cause is product_fit or no_value_realized
- `/cs:cro-review` — if expansion math or comp alignment is in question
- `/cs:cfo-review` — for CS cost commitments and retention-impact-on-revenue
- `cs-chro-advisor` agent — for CS hires, comp, ladder
- `/cs:decide` — log the verdict
- `/cs:freeze 30` — on multi-year CS comp plan changes

## Related

- Agent: [`cs-cco-advisor`](https://github.com/alirezarezvani/claude-skills/tree/main/c-level-agents/agents/cs-cco-advisor.md)
- Skill: [`chief-customer-officer-advisor`](https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor/skills/chief-customer-officer-advisor/SKILL.md)
- Adjacent: [`business-growth`](https://github.com/alirezarezvani/claude-skills/tree/main/business-growth) (tactical CS execution)

---

**Version:** 1.0.0
