npx skills add https://github.com/borghei/claude-skills --skill cpo-advisor战略产品领导力。涵盖愿景、产品组合、产品市场契合度、组织设计和指标。不适用于功能级别的工作——专注于决定构建什么、为何构建以及由谁构建的决策。
CPO, chief product officer, product strategy, product vision, product-market fit, PMF, portfolio management, product org, roadmap strategy, product metrics, north star metric, retention curve, product trio, team topologies, jobs to be done, JTBD, category design, product positioning, board product reporting, invest-maintain-kill, BCG matrix, switching costs, network effects, product-led growth, PLG, feature adoption, time to value, activation rate
其他所有事情都可以委派。
| 所有权 | 含义 | 关键问题 |
|---|---|---|
| 产品组合 | 存在哪些产品,哪些获得投资,哪些被淘汰 | "如果我们只能为 4 个产品中的 2 个提供资金,是哪 2 个?" |
| 愿景 | 产品在未来 3-5 年的发展方向以及客户关心的原因 | "如果我们成功了,世界会是什么样子?" |
| 组织 | 能够执行愿景的团队结构 | "这个组织能否交付未来 12 个月的战略?" |
| 维度 | 权重 |
|---|
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| 得分 1-3 (弱) |
|---|
| 得分 4-6 (发展中) |
|---|
| 得分 7-10 (强) |
|---|
| 留存率 | 30% | D30 < 15% (消费者) 或 < 40% (B2B) | D30 15-30% / 40-60% | D30 > 30% / > 60% |
| 参与度 | 25% | DAU/MAU < 15% | DAU/MAU 15-35% | DAU/MAU > 35% |
| 满意度 | 25% | Sean Ellis < 25% "非常失望" | 25-40% | > 40% |
| 增长 | 20% | 无自然增长 | 部分自然增长,主要靠付费 | > 50% 自然增长 |
START: "我们是否达到 PMF?"
|
v
[检查留存曲线形状]
|
+-- 下降至零 --> 未达到 PMF。停止构建。与用户沟通。
|
+-- 下降但趋于平缓 --> 发展中。找到曲线平缓的细分市场。
|
+-- 平缓或上扬 --> [检查 Sean Ellis 得分]
|
+-- < 25% "非常失望" --> 弱 PMF。产品不错,但非必需。
|
+-- 25-40% --> 中等 PMF。找到并加倍投入于核心用户。
|
+-- > 40% --> [检查自然增长]
|
+-- < 30% 自然增长 --> 存在 PMF 但分发能力弱。
+-- > 30% 自然增长 --> 强 PMF。扩大规模。
| 陷阱 | 描述 | 预防措施 |
|---|---|---|
| 功能蔓延 | 为新细分市场添加功能会稀释核心价值 | 保持"待办任务"焦点,而非功能焦点 |
| 过早扩张 | 在留存率证明可持续之前扩大销售/营销规模 | 在扩大支出前证明 3+ 个群组能保持留存 |
| 虚荣指标 | 庆祝注册量而忽略留存率 | 北极星指标必须是留存/参与度指标 |
| 创始人脱离产品 | CEO 在达到 PMF 后停止与客户沟通 | 每月与客户沟通是永久性要求 |
| 过早平台化 | 在核心产品稳固之前构建平台能力 | 仅在 3+ 个产品需要共享基础设施后才构建平台 |
每个产品必须且只能有一个姿态。"观望"就是决定失去市场份额。
| 姿态 | 信号 | 资源分配 | 审查节奏 |
|---|---|---|---|
| 投资 | 高增长,强劲/改善的留存率,明确的 PMF | 完整团队,积极的路线图,专门的营销 | 每月 |
| 维持 | 稳定收入,缓慢增长,良好利润率 | 错误修复,渐进式改进,最少的新功能 | 每季度 |
| 收割 | 增长下降,仍盈利,无复苏路径 | 最小投资,最大化现金提取 | 每季度 |
| 淘汰 | 下降,负利润率,无复苏证据 | 设定终止日期,迁移计划,团队重新分配 | 立即 |
| 指标 | 健康 | 不健康 |
|---|---|---|
| 来自"投资"产品的收入占比 | > 60% | < 40% |
| 投入"淘汰"候选产品的工程资源占比 | < 10% | > 20% |
| 没有明确姿态的产品数量 | 0 | > 1 |
| 产品组合 D30 留存率 (加权) | 季度环比改善 | 季度环比下降 |
| 作为"问题产品"超过 2 个季度的数量 | 0 | > 2 |
季度产品组合审查 (半天研讨会)
步骤 1: 数据准备 (会前)
- 每个产品的收入、增长率、留存率、利润率
- 每个产品的工程投资占比
- 每个产品的客户满意度
步骤 2: BCG 分类
- 在增长率 (Y) 与市场份额 (X) 图上标出每个产品
- 明星产品: 高增长,高份额 --> 投资
- 现金牛产品: 低增长,高份额 --> 维持/收割
- 问题产品: 高增长,低份额 --> 投资或淘汰 (立即决定)
- 瘦狗产品: 低增长,低份额 --> 淘汰
步骤 3: 投资分配
- 使工程能力与姿态保持一致
- 将资源从淘汰/收割产品重新分配到投资产品
- 为问题产品设定明确的里程碑 (90 天决策点)
步骤 4: 沟通
- 与所有产品团队分享产品组合决策
- 更新路线图以反映姿态
- 沟通淘汰产品的终止计划
北极星指标必须满足以下所有条件:
| 标准 | 测试 |
|---|---|
| 衡量客户价值 | 指标改善是否意味着客户获得了更多价值? |
| 领先指标 | 它能否预测未来收入? |
| 可操作 | 产品团队能否影响它? |
| 单一数字 | 能否用一个指标来表述? |
| 不易被操纵 | 是否难以在不真正帮助客户的情况下改善它? |
| 模型 | 北极星指标 | 为何有效 |
|---|---|---|
| B2B SaaS | 每周使用核心功能的活跃账户 | 结合采用率 + 参与度 + 粘性 |
| 消费者社交 | 每日内容创作者 | 创作者驱动消费者参与度 |
| 市场平台 | 每周成功交易数 | 双方活跃 = 健康的市场平台 |
| PLG | 在 14 天内达到激活状态的账户 | 激活率预测留存率 |
| 数据/分析 | 每个活跃用户每周的查询数 | 使用强度 = 获得的价值 |
| 金融科技 | 每月活跃交易者 | 交易活动 = 核心价值 |
| 电子商务 | 重复购买率 (90 天) | 留存率是电商的一切 |
北极星指标 (1, 由 CPO 负责)
|
+-- 领先指标 1 (由产品经理团队 A 负责)
| 例如,7 天内激活率
|
+-- 领先指标 2 (由产品经理团队 B 负责)
| 例如,功能 X 采用率
|
+-- 领先指标 3 (由产品经理团队 C 负责)
| 例如,D7 留存率
|
+-- 护栏指标 (由 CPO 负责)
例如,NPS、支持工单量、每用户收入
| 拓扑 | 何时使用 | 最佳规模 | 沟通 |
|---|---|---|---|
| 流对齐 | 默认。团队负责端到端的客户旅程。 | 5-9 人 | 低跨团队依赖 |
| 平台 | 多个流需要的共享基础设施 | 4-8 人 | API 优先,自助服务 |
| 赋能 | 临时团队,用于提升流团队技能 | 2-4 人 | 教练模式,有时间限制 |
| 复杂子系统 | 深度专业领域 (机器学习、支付) | 3-6 人 | 为流提供服务 |
| 公司规模 | 产品经理 : 工程师 | 产品经理 : 设计师 | 总产品团队 |
|---|---|---|---|
| 10-30 | 1:4-6 | 1:1 | 1 产品经理, 1 设计师, 4-6 工程师 |
| 30-80 | 1:5-8 | 1:1-2 | 2-4 产品经理, 2-3 设计师 |
| 80-200 | 1:6-10 | 1:1-2 | 5-10 产品经理, 4-6 设计师 |
| 200+ | 1:8-12 | 1:2 | 10+ 产品经理, 8+ 设计师 |
每个产品团队都应作为三人组运作:产品经理 + 设计师 + 技术负责人。
| 角色 | 负责 | 决定 |
|---|---|---|
| 产品经理 | 构建什么以及为什么 | 优先级,范围 |
| 设计师 | 用户体验和可用性 | 交互模式,研究 |
| 技术负责人 | 如何构建和技术可行性 | 架构,实施 |
反模式 : 产品经理编写规格说明,交给设计,设计交给工程。这是贴了敏捷标签的瀑布模式。
| 类别 | 指标 | 频率 | 目标 |
|---|---|---|---|
| 增长 | 北极星指标 | 每周 | 月环比改善 |
| 留存率 | 按群组划分的 D30 / D90 留存率 | 每周 | 趋于平缓或改善 |
| 获客 | 新激活数 | 每周 | 按计划 |
| 激活 | 首次实现价值的时间 | 每周 | 减少 |
| 参与度 | DAU/MAU 比率 | 每周 | > 30% (B2B) / > 20% (消费者) |
| 满意度 | NPS 趋势 | 每月 | > 40 |
| 产品组合 | 每个产品的收入 | 每月 | 与姿态一致 |
| 产品组合 | 每个产品的工程投资占比 | 每月 | 与姿态一致 |
| 质量 | 每 1K 用户的支持工单数 | 每月 | 减少 |
| 护城河 | 功能采用深度 | 每月 | 增加 |
产品作为"问题产品"停滞超过 2 个季度而未做决定——做出决定
工程资源分配给收入最高的产品,而增长最快的产品人手不足——资源配置不当
30% 的团队时间花在收入下降的产品上——沉没成本谬误
留存曲线从未平缓——未达到 PMF,停止构建功能,开始与用户沟通
产品经理不与用户沟通就编写规格说明——产品剧场
平台团队有 6 周的任务队列——平台应该是自助服务,而不是瓶颈
CPO 超过 30 天未与客户沟通——脱离现实
北极星指标呈上升趋势而留存率呈下降趋势——指标错误
路线图基于销售需求而非用户数据构建——销售驱动的产品是个陷阱
超过 90 天未进行用户研究——团队在猜测,而非学习
| 当... | CPO 与...合作 | 以... |
|---|---|---|
| 公司方向 | CEO (ceo-advisor) | 将愿景转化为产品赌注 |
| 路线图资金 | CFO (cfo-advisor) | 证明每个产品的投资分配合理性 |
| 扩展产品组织 | COO + CHRO | 使招聘与产品增长需求保持一致 |
| 技术可行性 | CTO (cto-advisor) | 共同决定功能与平台的权衡 |
| 发布时机 | CMO (cmo-advisor) | 使发布与需求生成能力保持一致 |
| 销售请求的功能 | CRO (cro-advisor) | 区分收入关键功能与噪音 |
| 合规截止日期 | CISO (ciso-advisor) | 识别不可协商的安全项目 |
| 产品战略 | 产品团队 (product-team/) | 通过产品经理执行战略 |
| 用户研究 | UX 研究 (product-team/ux-researcher) | 用数据验证假设 |
| 请求 | 交付物 |
|---|---|
| "我们是否达到 PMF?" | 包含 4 个维度和群组数据的 PMF 记分卡 |
| "确定我们路线图的优先级" | 使用框架 (RICE/ICE) 评分的待办事项列表,按优先级排序 |
| "评估我们的产品组合" | 包含每个产品投资/维持/淘汰建议的 BCG 图 |
| "设计我们的产品组织" | 包含拓扑、比例、汇报关系和过渡计划的组织提案 |
| "董事会产品部分" | 董事会幻灯片:北极星指标、留存率、路线图亮点、风险 |
| "设定我们的北极星指标" | 包含层级、领先指标和护栏指标的北极星指标提案 |
| "淘汰一个产品" | 终止计划:时间表、迁移、沟通、团队重新分配 |
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Strategic product leadership. Vision, portfolio, PMF, org design, and metrics. Not for feature-level work -- for the decisions that determine what gets built, why, and by whom.
CPO, chief product officer, product strategy, product vision, product-market fit, PMF, portfolio management, product org, roadmap strategy, product metrics, north star metric, retention curve, product trio, team topologies, jobs to be done, JTBD, category design, product positioning, board product reporting, invest-maintain-kill, BCG matrix, switching costs, network effects, product-led growth, PLG, feature adoption, time to value, activation rate
Everything else is delegation.
| Ownership | What It Means | Key Question |
|---|---|---|
| Portfolio | Which products exist, which get investment, which get killed | "If we could only fund 2 of our 4 products, which 2?" |
| Vision | Where the product goes in 3-5 years and why customers care | "What does the world look like if we succeed?" |
| Organization | The team structure that can execute the vision | "Can this org ship the next 12 months of strategy?" |
| Dimension | Weight | Score 1-3 (Weak) | Score 4-6 (Emerging) | Score 7-10 (Strong) |
|---|---|---|---|---|
| Retention | 30% | D30 < 15% (consumer) or < 40% (B2B) | D30 15-30% / 40-60% | D30 > 30% / > 60% |
| Engagement | 25% | DAU/MAU < 15% | DAU/MAU 15-35% | DAU/MAU > 35% |
| Satisfaction | 25% | Sean Ellis < 25% "very disappointed" | 25-40% | > 40% |
| Growth | 20% | No organic growth | Some organic, mostly paid | > 50% organic |
START: "Do we have PMF?"
|
v
[Check retention curve shape]
|
+-- Declining to zero --> NO PMF. Stop building. Talk to users.
|
+-- Declining but flattening --> EMERGING. Find the segment where it's flat.
|
+-- Flat or smiling --> [Check Sean Ellis score]
|
+-- < 25% "very disappointed" --> Weak PMF. Product is nice, not essential.
|
+-- 25-40% --> Moderate PMF. Find and double down on power users.
|
+-- > 40% --> [Check organic growth]
|
+-- < 30% organic --> PMF exists but distribution is weak.
+-- > 30% organic --> STRONG PMF. Scale.
| Trap | Description | Prevention |
|---|---|---|
| Feature creep | Adding features for new segments dilutes core value | Maintain a "jobs" focus, not feature focus |
| Premature scaling | Scaling sales/marketing before retention proves sustainable | Prove 3+ cohorts retain before scaling spend |
| Metric vanity | Celebrating signups while ignoring retention | North star must be a retention/engagement metric |
| Founder departure from product | CEO stops talking to customers post-PMF | Monthly customer conversations are permanent |
| Platform too early | Building platform capabilities before core is solid | Platform only after 3+ products need shared infra |
Every product gets exactly one posture. "Wait and see" is a decision to lose share.
| Posture | Signal | Resource Allocation | Review Cadence |
|---|---|---|---|
| Invest | High growth, strong/improving retention, clear PMF | Full team, aggressive roadmap, dedicated marketing | Monthly |
| Maintain | Stable revenue, slow growth, good margins | Bug fixes, incremental improvement, minimal new features | Quarterly |
| Harvest | Declining growth, still profitable, no recovery path | Minimal investment, maximize cash extraction | Quarterly |
| Kill | Declining, negative margins, no recovery evidence | Set sunset date, migration plan, team reallocation | Immediate |
| Metric | Healthy | Unhealthy |
|---|---|---|
| % revenue from "Invest" products | > 60% | < 40% |
| % engineering on "Kill" candidates | < 10% | > 20% |
| Number of products without clear posture | 0 | > 1 |
| Portfolio D30 retention (weighted) | Improving QoQ | Declining QoQ |
Quarterly Portfolio Review (Half-day workshop)
Step 1: Data Preparation (pre-meeting)
- Revenue, growth rate, retention, margin per product
- Engineering investment % per product
- Customer satisfaction per product
Step 2: BCG Classification
- Plot each product on Growth Rate (Y) vs Market Share (X)
- Stars: high growth, high share --> Invest
- Cash Cows: low growth, high share --> Maintain/Harvest
- Question Marks: high growth, low share --> Invest or Kill (decide now)
- Dogs: low growth, low share --> Kill
Step 3: Investment Allocation
- Align engineering capacity to posture
- Reallocate from Kill/Harvest to Invest
- Set clear milestones for Question Marks (90-day decision point)
Step 4: Communication
- Share portfolio decisions with all product teams
- Update roadmaps to reflect postures
- Communicate sunset plans for Kill products
The north star metric must satisfy ALL of these:
| Criterion | Test |
|---|---|
| Measures customer value | Does improvement mean customers got more value? |
| Leading indicator | Does it predict future revenue? |
| Actionable | Can product teams influence it? |
| Single number | Can you state it as one metric? |
| Non-gameable | Is it hard to improve without genuinely helping customers? |
| Model | North Star | Why It Works |
|---|---|---|
| B2B SaaS | Weekly active accounts using core feature | Combines adoption + engagement + stickiness |
| Consumer social | Daily content creators | Creators drive consumer engagement |
| Marketplace | Successful transactions per week | Both sides active = healthy marketplace |
| PLG | Accounts reaching activation within 14 days | Activation predicts retention |
| Data/Analytics | Queries per active user per week | Usage intensity = value received |
| Fintech | Monthly active transactors | Transaction activity = core value |
| E-commerce | Repeat purchase rate (90-day) | Retention is everything in commerce |
North Star Metric (1, owned by CPO)
|
+-- Leading Indicator 1 (owned by PM Team A)
| e.g., Activation rate within 7 days
|
+-- Leading Indicator 2 (owned by PM Team B)
| e.g., Feature X adoption rate
|
+-- Leading Indicator 3 (owned by PM Team C)
| e.g., D7 retention rate
|
+-- Guard Rail Metrics (owned by CPO)
e.g., NPS, support ticket volume, revenue per user
| Topology | When to Use | Optimal Size | Communication |
|---|---|---|---|
| Stream-aligned | Default. Teams own end-to-end customer journey. | 5-9 people | Low cross-team dependency |
| Platform | Shared infrastructure multiple streams need | 4-8 people | API-first, self-service |
| Enabling | Temporary teams to upskill stream teams | 2-4 people | Coaching mode, time-limited |
| Complicated subsystem | Deep specialist domain (ML, payments) | 3-6 people | Provides service to streams |
| Company Size | PM : Engineers | PM : Designer | Total Product Team |
|---|---|---|---|
| 10-30 | 1:4-6 | 1:1 | 1 PM, 1 Designer, 4-6 Eng |
| 30-80 | 1:5-8 | 1:1-2 | 2-4 PMs, 2-3 Designers |
| 80-200 | 1:6-10 | 1:1-2 | 5-10 PMs, 4-6 Designers |
| 200+ | 1:8-12 | 1:2 | 10+ PMs, 8+ Designers |
Every product team should operate as a trio: PM + Designer + Tech Lead.
| Role | Owns | Decides |
|---|---|---|
| PM | What to build and why | Prioritization, scope |
| Designer | User experience and usability | Interaction patterns, research |
| Tech Lead | How to build and technical feasibility | Architecture, implementation |
Anti-pattern : PM writes spec, hands to design, design hands to engineering. This is waterfall with agile labels.
| Category | Metric | Frequency | Target |
|---|---|---|---|
| Growth | North star metric | Weekly | Improving MoM |
| Retention | D30 / D90 retention by cohort | Weekly | Flattening or improving |
| Acquisition | New activations | Weekly | Per plan |
| Activation | Time to first value | Weekly | Decreasing |
| Engagement | DAU/MAU ratio | Weekly | > 30% (B2B) / > 20% (consumer) |
| Satisfaction | NPS trend | Monthly | > 40 |
| Portfolio | Revenue per product | Monthly | Aligned to posture |
Products stuck as "question marks" for 2+ quarters without a decision -- make the call
Engineering allocated to highest-revenue product while highest-growth product is understaffed -- misallocation
30% of team time on products with declining revenue -- sunk cost fallacy
Retention curve never flattens -- no PMF, stop building features and start talking to users
PMs writing specs without talking to users -- product theater
Platform team has 6-week queue -- platform should be self-service, not a bottleneck
CPO has not talked to a customer in 30+ days -- disconnected from reality
North star trending up while retention trends down -- wrong metric
Roadmap built from sales requests instead of user data -- sales-driven product is a trap
No user research conducted in 90+ days -- team is guessing, not learning
| When... | CPO Works With... | To... |
|---|---|---|
| Company direction | CEO (ceo-advisor) | Translate vision into product bets |
| Roadmap funding | CFO (cfo-advisor) | Justify investment allocation per product |
| Scaling product org | COO + CHRO | Align hiring with product growth needs |
| Technical feasibility | CTO (cto-advisor) | Co-own features vs. platform trade-off |
| Launch timing | CMO (cmo-advisor) | Align releases with demand gen capacity |
| Request | Deliverable |
|---|---|
| "Do we have PMF?" | PMF scorecard across 4 dimensions with cohort data |
| "Prioritize our roadmap" | Scored backlog with framework (RICE/ICE), stack-ranked |
| "Evaluate our portfolio" | BCG map with invest/maintain/kill recommendations per product |
| "Design our product org" | Org proposal with topology, ratios, reporting, and transition plan |
| "Product board section" | Board slide: north star, retention, roadmap highlights, risks |
| "Set our north star" | North star proposal with hierarchy, leading indicators, and guard rails |
| "Kill a product" | Sunset plan: timeline, migration, communication, team reallocation |
Weekly Installs
1
Repository
GitHub Stars
29
First Seen
Today
Security Audits
Gen Agent Trust HubPassSocketPassSnykPass
Installed on
zencoder1
amp1
cline1
openclaw1
opencode1
cursor1
站立会议模板:敏捷开发每日站会指南与工具(含远程团队异步模板)
10,500 周安装
| Portfolio | Engineering investment % per product | Monthly | Aligned to posture |
| Quality | Support tickets per 1K users | Monthly | Decreasing |
| Moat | Feature adoption depth | Monthly | Increasing |
| Sales-requested features |
CRO (cro-advisor) |
| Separate revenue-critical from noise |
| Compliance deadlines | CISO (ciso-advisor) | Identify non-negotiable security items |
| Product strategy | Product Team (product-team/) | Execute strategy through product managers |
| User research | UX Research (product-team/ux-researcher) | Validate assumptions with data |