/cs:cco-review — CCO Forcing Questions

/cs:cco-review <plan> — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring.

How to use it

Claude Code
  1. Run the line below. It pulls the whole folder into ~/.claude/skills/cco-review, including the files SKILL.md points to.
  2. Describe your job in plain words. Claude Code follows the skill from there.
Claude Code — installs the whole folder, not just SKILL.md
npx degit alirezarezvani/claude-skills/c-level-agents/skills/cco-review#main ~/.claude/skills/cco-review

For one project only, change the path to .claude/skills/cco-review. This skill also uses retention_decomposition_analyzer.py, customer_segmentation_designer.py, cs_coverage_calculator.py, cohorts.json, customers.json, book.json — copying SKILL.md alone won't be enough. See the folder on GitHub.

Claude (web or desktop app)
  1. On this page open ⋯ → Download .md.
  2. Save it as SKILL.md in a folder, zip the folder, then Customize → Skills → + → Create skill → Upload a skill.
  3. Pick the file and Save. Claude shows the name and description and runs a security scan.
  4. Check the skill is switched on.
  5. Start a new chat and describe your job in plain words. The AI follows the skill from there.
ChatGPT or another app
  1. ChatGPT: make a Project and paste it into Instructions.
  2. Neither? Paste it at the top of a new chat — it works for that chat.
Not working?
  • Check which app you pasted it into — the steps above name the right one.
  • Some skills need the paid tier of Claude or ChatGPT.
Step-by-step guide with screenshots · Ask in the forum

Paste into Claude, ChatGPT or Cursor.

Source of /cs:cco-review — CCO Forcing Questions

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cco-review/cs:cco-review <plan> — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring. Use when gross retention is slipping, before approving CSM headcount, or when deciding which customer segments to keep or fire.

/cs:cco-review — CCO Forcing Questions

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

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

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

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

Output Format

# 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

Version: 1.0.0

1---
2name: "cco-review"
3description: "/cs:cco-review <plan> — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring. Use when gross retention is slipping, before approving CSM headcount, or when deciding which customer segments to keep or fire."
4---
5 
6# /cs:cco-review — CCO Forcing Questions
7 
8**Command:** `/cs:cco-review <plan>`
9 
10The 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.
11 
12## When to Run
13 
14- Before any board narrative that includes a retention number
15- Before approving a CS team headcount expansion
16- Before re-segmenting the customer base or changing tier definitions
17- Before launching a customer marketing or advocacy program
18- Before a major CS hire (CSM, AM, Implementation, Customer Marketing)
19- When NRR is "great" but churn complaints from CSMs are increasing
20- Before deciding whether to add an AM role separate from CSM
21 
22## The Six CCO Questions
23 
24### 1. What's the GROSS retention rate?
25**Not NRR. Gross.** NRR can hide a leaky bucket behind expansion.
26- GRR healthy ≥ 90% at growth stage, ≥ 95% at scale
27- If GRR < 85% but NRR > 100%, the product is failing for 15%+ of customers; expansion is masking the failure
28- Run `retention_decomposition_analyzer.py`
29 
30### 2. What's the #1 reason customers leave?
31**If you can't name it, you don't understand churn.**
32- 7-category taxonomy: product_fit / competitor_loss / no_value_realized / pricing / champion_left / company_event / tactical_failure
33- Preventable churn = product_fit + no_value_realized + tactical_failure
34- If preventable > 50%, CS has clear leverage; if < 30%, churn is structural (ICP, market, competition)
35 
36### 3. What's the median time-to-value (TTV) by segment?
37**Long TTV signals different problems by segment.**
38- Long TTV in low tier = ICP misfit; downgrade or kill
39- Long TTV in high tier = onboarding broken; fix the Implementation Manager handoff
40- TTV is a leading indicator of GRR
41 
42### 4. Which customer would you fire today?
43**If "none" — your segmentation is broken.**
44- Some accounts cost more than they earn (support cost > 50% of ARR + low ICP fit)
45- Run `customer_segmentation_designer.py` to surface kill list
46- The 3 paths for kill candidates: non-renewal / downgrade-to-tech-touch / raise-price-to-cost-recover
47 
48### 5. What's the ARR-per-CSM ratio, and is the model pooled or named?
49**Wrong model wastes capacity.**
50- Strategic: named + exec sponsor, $300K-$1M ARR/CSM
51- Enterprise: named, $500K-$2M
52- Mid-market: pooled, $2M-$5M
53- SMB: tech-touch, $5M+
54- Run `cs_coverage_calculator.py` to size the team
55 
56### 6. Is CS in your comp plan, and how is it different from Sales comp?
57**Misalignment is the leading indicator of CS failure.**
58- CS comp: 70/30 base/variable typical
59- Variable: 50% gross retention + 30% net retention + 20% activity
60- Anti-pattern: comp CSMs on NPS — they game it
61- Anti-pattern: comp CSMs same as Sales — they sell instead of serve
62 
63## Workflow
64 
65```bash
66# 1. Retention decomposition (always start here)
67python ../../../c-level-advisor/skills/chief-customer-officer-advisor/scripts/retention_decomposition_analyzer.py cohorts.json
68 
69# 2. Segmentation audit
70python ../../../c-level-advisor/skills/chief-customer-officer-advisor/scripts/customer_segmentation_designer.py customers.json
71 
72# 3. Coverage sizing (if making CS team changes)
73python ../../../c-level-advisor/skills/chief-customer-officer-advisor/scripts/cs_coverage_calculator.py book.json
74```
75 
76## Output Format
77 
78```markdown
79# CCO Review: <plan>
80**Date:** YYYY-MM-DD
81 
82## The Decision Being Made
83[one sentence — retention | segmentation | coverage | next hire]
84 
85## Retention (if applicable)
86- GRR: X% (vs vanity NRR of Y%)
87- Top churn driver: <category> at X% of churn
88- Preventable churn: X% (CS-controllable)
89- Leaky-bucket pattern? yes/no
90 
91## Segmentation (if applicable)
92- Tier distribution: Strategic X / Enterprise X / Mid-market X / SMB X
93- Kill list size: N customers (X% of customers, Y% of ARR)
94- Upgrade candidates: N
95 
96## Coverage (if applicable)
97- Current CSMs: N | Required now: M | Required 12mo: P
98- Annual cost (12mo): $X
99- Manager trigger fired: yes/no
100 
101## Org (if applicable)
102- Next hire: <CSM | Support | AM | IM | CS Ops | Customer Marketing>
103- Why this, not the alternative: <one line>
104- Customer outcome unblocked: <specific>
105 
106## Verdict
107🟢 SHIP | 🟡 SHARPEN | 🔴 BLOCK
108 
109## Next Steps
110[3 concrete actions]
111```
112 
113## Routing
114 
115- `/cs:cpo-review` — if churn root cause is product_fit or no_value_realized
116- `/cs:cro-review` — if expansion math or comp alignment is in question
117- `/cs:cfo-review` — for CS cost commitments and retention-impact-on-revenue
118- `cs-chro-advisor` agent — for CS hires, comp, ladder
119- `/cs:decide` — log the verdict
120- `/cs:freeze 30` — on multi-year CS comp plan changes
121 
122## Related
123 
124- Agent: [`cs-cco-advisor`](../../agents/cs-cco-advisor.md)
125- Skill: [`chief-customer-officer-advisor`](../../../c-level-advisor/skills/chief-customer-officer-advisor/SKILL.md)
126- Adjacent: `../../../business-growth/` (tactical CS execution)
127 
128---
129 
130**Version:** 1.0.0
131 

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