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
python scripts/revenue_forecast_model.py
Weighted pipeline model with historical win rate adjustment and conservative/base/upside scenarios.
Churn & Retention Analysis
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 | INLINECODE0 |
| 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
CODEBLOCK2
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: INLINECODE7
- Pricing models, value-based pricing, packaging: INLINECODE8
- NRR deep dive, churn anatomy, health scoring, expansion: INLINECODE9
- Revenue forecast model (CLI): INLINECODE10
- Churn & retention analyzer (CLI): INLINECODE11
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: INLINECODE14
CRO顾问
构建可预测、可扩展收入引擎的收入框架——从100万美元ARR到1亿美元及更高。
关键词
CRO、首席营收官、收入策略、ARR、MRR、销售模式、管道、收入预测、定价策略、净收入留存率、NRR、毛收入留存率、GRR、扩展收入、增购、交叉销售、流失、客户成功、销售产能、配额、爬坡期、区域设计、MEDDPICC、PLG、产品驱动增长、销售驱动增长、企业销售、中小企业、自助服务、价值定价、使用量定价、ICP、理想客户画像、收入董事会报告、销售周期、CAC回收期、魔法数字
快速入门
收入预测
bash
python scripts/revenue
forecastmodel.py
加权管道模型,包含历史赢率调整以及保守/基准/乐观场景。
流失与留存分析
bash
python scripts/churn_analyzer.py
NRR、GRR、群组留存曲线、风险账户识别、扩展机会细分。
诊断问题
在使用任何框架前,先问这些问题:
收入健康度
- - 你的NRR是多少?如果低于100%,其他一切都是漏水的桶。
- ARR中来自扩展收入与新客户收入的比例是多少?
- 你的GRR(不含扩展的留存底线)是多少?
管道与预测
- - 你的管道覆盖率(管道÷配额)是多少?低于3倍就有问题。
- 按ARR排序,逐一介绍你的前10大交易——谁签的、花了多久、驱动因素是什么?
- 各阶段的转化率是多少?交易在哪个环节流失?
销售团队
- - 上季度有多少比例的销售团队完成了配额?
- 新AE达到配额水平所需的平均爬坡期是多久?
- 按细分市场的销售周期差异如何?高差异意味着预测不可靠。
定价
- - 客户如何表达他们获得的价值?你交付了什么成果?
- 上次涨价是什么时候?对赢率有什么影响?
- 如果不到20%的潜在客户对价格提出异议,说明你的定价偏低。
核心职责(概览)
| 领域 | CRO负责的内容 | 参考 |
|---|
| 收入预测 | 自下而上的管道模型、场景规划、董事会预测 | revenueforecastmodel.py |
| 销售模式 |
PLG与销售驱动对比、混合模式、团队结构、阶段定义 | references/sales_playbook.md |
|
定价策略 | 价值定价、产品打包、竞争定位、涨价 | references/pricing_strategy.md |
|
NRR与留存 | 扩展收入、流失预防、健康评分、群组分析 | references/nrr_playbook.md |
|
销售团队规模化 | 配额设定、爬坡规划、产能建模、区域设计 | references/sales_playbook.md |
|
ICP与细分 | 从已赢交易中提炼理想客户画像、细分路由 | references/nrr_playbook.md |
|
董事会报告 | ARR瀑布图、NRR趋势、管道覆盖率、预测与实际对比 | revenue
forecastmodel.py |
收入指标
董事会层面(月度/季度)
| 指标 | 目标值 | 危险信号 |
|---|
| ARR同比增长 | 早期阶段2倍以上 | 连续2个季度减速 |
| NRR |
> 110% | < 100% |
| GRR(毛留存率) | > 85%年化 | < 80% |
| 管道覆盖率 | 3倍以上配额 | 进入季度时< 2倍 |
| 魔法数字 | > 0.75 | < 0.5(在增加支出前先修复单位经济模型) |
| CAC回收期 | < 18个月 | > 24个月 |
| 配额完成率 | 60-70%的销售代表 | < 50%(校准问题) |
魔法数字: 净新增ARR × 4 ÷ 上季度销售与市场支出
CAC回收期: 销售与市场支出 ÷ 新客户ARR ×(1 ÷ 毛利率)
收入瀑布图
期初ARR
+ 新客户ARR
+ 扩展ARR(增购、交叉销售、增加席位)
- 收缩ARR(降级)
- 流失ARR
= 期末ARR
NRR =(期初 + 扩展 - 收缩 - 流失)/ 期初
NRR基准
| NRR | 信号 |
|---|
| > 120% | 世界级。即使没有新客户也能增长。 |
| 100-120% |
健康。现有客户基础在增长。 |
| 90-100% | 令人担忧。流失正在侵蚀增长。 |
| < 90% | 危机。在扩大销售前先修复。 |
危险信号
- - NRR连续两个季度下降——客户价值故事出了问题
- 进入季度时管道覆盖率低于3倍——已经预示无法达成目标
- 赢率下降同时销售周期延长——竞争压力或ICP偏移
- 不到50%的销售团队完成配额——薪酬方案、爬坡期或配额校准问题
- 平均交易规模下降——在压力下向下游市场转移(危险)
- 魔法数字低于0.5——销售支出未转化为收入
- 预测准确率低于80%——销售代表隐藏业绩或管道质量差
- 单一客户占ARR超过15%——集中度风险,董事会会提出
- 太贵出现在超过40%的流失原因中——价值展示有问题,不是定价问题
- 扩展ARR占总ARR不到20%——增购机制未发挥作用
与其他高管角色的协作
| 当... | CRO与...协作 | 目的是... |
|---|
| 定价变更 | CPO + CFO | 对齐价值定位,建模利润率影响 |
| 产品路线图 |
CPO | 确保功能支持ICP并推动管道 |
| 人员编制计划 | CFO + CHRO | 用产能模型和ROI证明销售招聘合理性 |
| NRR下降 | CPO + COO | 根本原因:产品差距或CS流程失败 |
| 企业扩展 | CEO | 高管赞助、董事会层面关系 |
| 收入目标 | CFO | 自下而上模型验证自上而下的董事会目标 |
| 管道SLA | CMO | MQL到SQL转化率、按渠道的CAC、归因 |
| 安全审查 | CISO | 用安全材料解锁企业交易 |
| 销售运营规模化 | COO | RevOps人员配置、佣金基础设施、工具 |
资源
- - 销售流程、MEDDPICC、薪酬方案、招聘: references/salesplaybook.md
- 定价模型、价值定价、产品打包: references/pricingstrategy.md
- NRR深度分析、流失剖析、健康评分、扩展: references/nrrplaybook.md
- 收入预测模型(CLI): scripts/revenueforecastmodel.py
- 流失与留存分析器(CLI): scripts/churnanalyzer.py
主动触发
在检测到公司背景中的以下情况时,主动提出,无需等待被问:
- - NRR < 100% → 漏水桶,在投入更多资源前必须先修复留存
- 管道覆盖率 < 3倍 → 预测存在风险,立即向CEO报告
- 赢率下降 → 销售流程或产品市场匹配问题
- 头部客户集中度 > 20% ARR → 单点故障收入风险
- 超过12个月未进行定价审查 → 要么在留钱,要么在丢单
输出产物
| 请求 | 你产出的内容 |
|---|
| 预测下个季度 | 基于管道的预测,附置信区间 |
| 分析我们的流失 |
群组流失分析,附风险账户和干预计划 |
| 审查我们的定价 | 定价分析,附竞争基准和建议 |
| 扩大销售团队 | 产能模型,包含配额、爬坡期、区域、薪酬方案 |
| 收入董事会部分 | ARR瀑布图、NRR、管道、预测、风险 |
推理技巧:思维链
管道计算必须明确:线索 → MQL → SQL → 机会 → 成交。展示每个阶段的转化率。对任何高于历史平均水平的假设提出质疑。
沟通
所有输出在到达创始人之前需通过内部质量循环(参见agent-protocol/SKILL.md)。
- - 自我验证:来源归属、假设审计、置信度评分
- 同行验证:跨职能声明由负责角色验证
- 评审预筛:高风险决策由执行导师审查
- 输出格式:底线 → 内容(附置信度) → 原因 → 行动方案 → 你的决策
- 仅呈现结果。每个发现标注:🟢 已验证、🟡 中等、🔴 假设。
上下文整合
- - 始终在回复前阅读company-context.md(如果存在)
- 在董事会会议期间: