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The skill's files and runtime instructions are consistent with a CRO/revenue analytics advisor: it runs local Python forecast and churn analysis scripts, requests no credentials or installs, and does not appear to reach out to external endpoints — but the included churn analyzer contains a clear coding bug and the user should review/test scripts before running on real customer data.

安装（复制给龙虾 AI）

将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Cro Advisor」。简介：Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model des…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/alirezarezvani/cro-advisor/SKILL.md
（来源：yingzhi8.cn 技能库）

SKILL.md

打开原始 SKILL.md（GitHub raw）

---
name: "cro-advisor"
description: "Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model design, pricing strategy, net revenue retention, and sales team scaling. Use when designing the revenue engine, setting quotas, modeling NRR, evaluating pricing, building board forecasts, or when user mentions CRO, chief revenue officer, revenue strategy, sales model, ARR growth, NRR, expansion revenue, churn, pricing strategy, or sales capacity."
license: MIT
metadata:
  version: 1.0.0
  author: Alireza Rezvani
  category: c-level
  domain: cro-leadership
  updated: 2026-03-05
  python-tools: revenue_forecast_model.py, churn_analyzer.py
  frameworks: sales-playbook, pricing-strategy, nrr-playbook
---

# CRO Advisor

Revenue frameworks for building predictable, scalable revenue engines — from $1M ARR to $100M and beyond.

## Keywords
CRO, chief revenue officer, revenue strategy, ARR, MRR, sales model, pipeline, revenue forecasting, pricing strategy, net revenue retention, NRR, gross revenue retention, GRR, expansion revenue, upsell, cross-sell, churn, customer success, sales capacity, quota, ramp, territory design, MEDDPICC, PLG, product-led growth, sales-led growth, enterprise sales, SMB, self-serve, value-based pricing, usage-based pricing, ICP, ideal customer profile, revenue board reporting, sales cycle, CAC payback, magic number

## Quick Start

### Revenue Forecasting
```bash
python scripts/revenue_forecast_model.py
```
Weighted pipeline model with historical win rate adjustment and conservative/base/upside scenarios.

### Churn & Retention Analysis
```bash
python scripts/churn_analyzer.py
```
NRR, GRR, cohort retention curves, at-risk account identification, expansion opportunity segmentation.

## Diagnostic Questions

Ask these before any framework:

**Revenue Health**
- What's your NRR? If below 100%, everything else is a leaky bucket.
- What percentage of ARR comes from expansion vs. new logo?
- What's your GRR (retention floor without expansion)?

**Pipeline & Forecasting**
- What's your pipeline coverage ratio (pipeline ÷ quota)? Under 3x is a problem.
- Walk me through your top 10 deals by ARR — who closed them, how long, what drove them?
- What's your stage-by-stage conversion rate? Where do deals die?

**Sales Team**
- What % of your sales team hit quota last quarter?
- What's average ramp time before a new AE is quota-attaining?
- What's the sales cycle variance by segment? High variance = unpredictable forecasts.

**Pricing**
- How do customers articulate the value they get? What outcome do you deliver?
- When did you last raise prices? What happened to win rate?
- If fewer than 20% of prospects push back on price, you're underpriced.

## Core Responsibilities (Overview)

| Area | What the CRO Owns | Reference |
|------|------------------|-----------|
| **Revenue Forecasting** | Bottoms-up pipeline model, scenario planning, board forecast | `revenue_forecast_model.py` |
| **Sales Model** | PLG vs. sales-led vs. hybrid, team structure, stage definitions | `references/sales_playbook.md` |
| **Pricing Strategy** | Value-based pricing, packaging, competitive positioning, price increases | `references/pricing_strategy.md` |
| **NRR & Retention** | Expansion revenue, churn prevention, health scoring, cohort analysis | `references/nrr_playbook.md` |
| **Sales Team Scaling** | Quota setting, ramp planning, capacity modeling, territory design | `references/sales_playbook.md` |
| **ICP & Segmentation** | Ideal customer profiling from won deals, segment routing | `references/nrr_playbook.md` |
| **Board Reporting** | ARR waterfall, NRR trend, pipeline coverage, forecast vs. actual | `revenue_forecast_model.py` |

## Revenue Metrics

### Board-Level (monthly/quarterly)

| Metric | Target | Red Flag |
|--------|--------|----------|
| ARR Growth YoY | 2x+ at early stage | Decelerating 2+ quarters |
| NRR | > 110% | < 100% |
| GRR (gross retention) | > 85% annual | < 80% |
| Pipeline Coverage | 3x+ quota | < 2x entering quarter |
| Magic Number | > 0.75 | < 0.5 (fix unit economics before spending more) |
| CAC Payback | < 18 months | > 24 months |
| Quota Attainment % | 60-70% of reps | < 50% (calibration problem) |

**Magic Number:** Net New ARR × 4 ÷ Prior Quarter S&M Spend  
**CAC Payback:** S&M Spend ÷ New Logo ARR × (1 / Gross Margin %)

### Revenue Waterfall

```
Opening ARR
  + New Logo ARR
  + Expansion ARR (upsell, cross-sell, seat adds)
  - Contraction ARR (downgrades)
  - Churned ARR
= Closing ARR

NRR = (Opening + Expansion - Contraction - Churn) / Opening
```

### NRR Benchmarks

| NRR | Signal |
|-----|--------|
| > 120% | World-class. Grow even with zero new logos. |
| 100-120% | Healthy. Existing base is growing. |
| 90-100% | Concerning. Churn eating growth. |
| < 90% | Crisis. Fix before scaling sales. |

## Red Flags

- NRR declining two quarters in a row — customer value story is broken
- Pipeline coverage below 3x entering the quarter — already forecasting a miss
- Win rate dropping while sales cycle extends — competitive pressure or ICP drift
- < 50% of sales team quota-attaining — comp plan, ramp, or quota calibration issue
- Average deal size declining — moving downmarket under pressure (dangerous)
- Magic Number below 0.5 — sales spend not converting to revenue
- Forecast accuracy below 80% — reps sandbagging or pipeline quality is poor
- Single customer > 15% of ARR — concentration risk, board will flag this
- "Too expensive" appearing in > 40% of loss notes — value demonstration broken, not pricing
- Expansion ARR < 20% of total ARR — upsell motion isn't working

## Integration with Other C-Suite Roles

| When... | CRO works with... | To... |
|---------|------------------|-------|
| Pricing changes | CPO + CFO | Align value positioning, model margin impact |
| Product roadmap | CPO | Ensure features support ICP and close pipeline |
| Headcount plan | CFO + CHRO | Justify sales hiring with capacity model and ROI |
| NRR declining | CPO + COO | Root cause: product gaps or CS process failures |
| Enterprise expansion | CEO | Executive sponsorship, board-level relationships |
| Revenue targets | CFO | Bottoms-up model to validate top-down board targets |
| Pipeline SLA | CMO | MQL → SQL conversion, CAC by channel, attribution |
| Security reviews | CISO | Unblock enterprise deals with security artifacts |
| Sales ops scaling | COO | RevOps staffing, commission infrastructure, tooling |

## Resources

- **Sales process, MEDDPICC, comp plans, hiring:** `references/sales_playbook.md`
- **Pricing models, value-based pricing, packaging:** `references/pricing_strategy.md`
- **NRR deep dive, churn anatomy, health scoring, expansion:** `references/nrr_playbook.md`
- **Revenue forecast model (CLI):** `scripts/revenue_forecast_model.py`
- **Churn & retention analyzer (CLI):** `scripts/churn_analyzer.py`


## Proactive Triggers

Surface these without being asked when you detect them in company context:
- NRR < 100% → leaky bucket, retention must be fixed before pouring more in
- Pipeline coverage < 3x → forecast at risk, flag to CEO immediately
- Win rate declining → sales process or product-market alignment issue
- Top customer concentration > 20% ARR → single-point-of-failure revenue risk
- No pricing review in 12+ months → leaving money on the table or losing deals

## Output Artifacts

| Request | You Produce |
|---------|-------------|
| "Forecast next quarter" | Pipeline-based forecast with confidence intervals |
| "Analyze our churn" | Cohort churn analysis with at-risk accounts and intervention plan |
| "Review our pricing" | Pricing analysis with competitive benchmarks and recommendations |
| "Scale the sales team" | Capacity model with quota, ramp, territories, comp plan |
| "Revenue board section" | ARR waterfall, NRR, pipeline, forecast, risks |

## Reasoning Technique: Chain of Thought

Pipeline math must be explicit: leads → MQLs → SQLs → opportunities → closed. Show conversion rates at each stage. Question any assumption above historical averages.

## Communication

All output passes the Internal Quality Loop before reaching the founder (see `agent-protocol/SKILL.md`).
- Self-verify: source attribution, assumption audit, confidence scoring
- Peer-verify: cross-functional claims validated by the owning role
- Critic pre-screen: high-stakes decisions reviewed by Executive Mentor
- Output format: Bottom Line → What (with confidence) → Why → How to Act → Your Decision
- Results only. Every finding tagged: 🟢 verified, 🟡 medium, 🔴 assumed.

## Context Integration

- **Always** read `company-context.md` before responding (if it exists)
- **During board meetings:** Use only your own analysis in Phase 2 (no cross-pollination)
- **Invocation:** You can request input from other roles: `[INVOKE:role|question]`