gtm-0-to-1-launch by github/awesome-copilot
npx skills add https://github.com/github/awesome-copilot --skill gtm-0-to-1-launch将新产品从想法推向首批客户。目标不是制造头条新闻,而是找到 10 个离不开你的客户。
触发场景:
适用背景:
模式:
协调了一次功能发布,并安排了完整的媒体巡回报道。TechCrunch、VentureBeat、产品博客。盛大的发布日。
结果:
失败原因:
优化目标是媒体热度,而非用户价值。该功能尚未准备好供用户自助使用。它需要教育、背景说明和手把手指导。媒体能带来眼球。但只有眼球而没有激活 = 虚荣指标。
更好的做法:
直接给 50 个目标客户发邮件。"我们构建了 [功能],因为像你们这样的团队在处理 [问题] 时遇到困难。想要抢先体验吗?" 亲自指导他们完成设置。获取反馈,进行迭代。
结果: 50 封邮件 → 15 封回复(30% 回复率)→ 8 个试用 → 4 个转化(50% 试用转付费)。
经验教训:
早期客户来自直接推广,而非媒体报道。媒体报道在后期很重要(A 轮融资公告、重大里程碑)。对于 0 到 1 阶段,它是干扰项。
广告位招租
在这里展示您的产品或服务
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模式:
你已经发布了。有了一定的知名度。但转化率很低。问题存在于以下三个层面之一,每个层面都需要不同的干预措施。
第一层:定位问题
症状:
诊断:你"在错误的战场上打一场不对称的战争"——与资金更雄厚的公司在功能上竞争。绘制竞争对手声称独特价值的地方。找到一个他们无法轻易复制的定位。
解决方法:确立一个你在结构上(不仅仅是产品功能)可以拥有的主张。在投入产品资源之前,先用对外信息进行测试。
第二层:体验问题
症状:
诊断:灵活性而没有预设的默认选项是一种负担,而非功能。用户面临"选择悖论"——选项太多,没有足够的指导来达到顿悟时刻。
解决方法:确定 2-3 个能立即带来价值的"无可辩驳的用例"。将新用户引导限制在这些特定用例上。将高级功能置于掌握路径之后。围绕待完成的任务而非功能列表重写帮助内容。
第三层:协调问题
症状:
诊断:"探索模式"——每个计划都具有同等优先级——在资源受限时具有破坏性。
解决方法:定义一个单一的、共享的北极星指标。将其作为每个决策的最终决定者:"这能帮助我们赢得客户吗?" 削减那些无法促成此目标的活动。每周而非每季度展示进展。
如何使用:
当发布停滞时,在投入资源之前先诊断哪一层出了问题。当问题是定位时去修复体验,会浪费工程时间。当问题是内部协调时去修复定位,会浪费营销支出。
原则: 首批 10 名客户不是为了收入,而是为了学习。
你需要学习什么:
如何找到他们:
渠道 1:个人网络(前 2-3 名)
渠道 2:直接推广(第 3-20 名客户)
渠道 3:触及天花板时刻的目标客户(意向最高)
渠道 4:社区(开发者产品)
模式:
早期阶段的速度比完美更重要。限制因素不在于你是否正确,而在于你能多快地测试假设并进行迭代。
如何执行:
行动手册规则:
每个成功的实验在扩大规模之前必须变成行动手册。结构:目标 → 步骤 → 预期输出 → 指标 → 风险。如果一个不熟悉的人无法执行该行动手册,说明文档记录得不够好。
为何重要:
一次性的胜利不会累积。系统化的实验会。目标不是一次发布,而是构建一个可重复的机制,以快速测试假设。
常见错误:
在测试之前过度规划。等待"完美"条件再发布。因为投入了情感精力而在失败的实验上停留太久。用 70% 的信息做决策。
模式:
与其仅通过直接销售进入新市场,不如利用与成熟参与者的合作关系来加速。
如何执行:
超级节点模式:
将自己定位为其他工具自然连接通过的集成中心。你拥有其他平台所需的关键数据或工作流程。这会形成复合效应——每个新合作伙伴都让你对下一个合作伙伴更有价值。
类别排序:
不要到处寻求合作。每个季度主导 2-3 个类别:
常见错误:
在没有明确集成路径的情况下启动合作。期望合作伙伴在没有支持的情况下推动知名度。将合作视为销售渠道而非平台扩展。
产品市场契合度是指客户推动你前进,而不是你推动他们。
留存率:
有机增长:
销售速度:
定性指标:
40% 的用户在产品消失时会非常失望(肖恩·埃利斯测试)
如果你没有这些,说明你还没有达到产品市场契合度。不要扩大营销/销售规模。
潜在客户理解你是什么吗?
├─ 不理解 → 第一层:定位问题
│ 解决方法:在改变产品之前测试新信息
└─ 理解 → 继续...
│
用户注册后会激活吗?
├─ 不激活 → 第二层:体验问题
│ 解决方法:将新用户引导限制在 2-3 个用例,引导至顿悟时刻
└─ 激活 → 继续...
│
团队对重要事项是否协调一致?
├─ 不一致 → 第三层:协调问题
│ 解决方法:单一北极星指标,每周可见性,削减非必要事项
└─ 一致 → 继续迭代,你走在正确的轨道上
准备好自助服务了吗?(用户在 <10 分钟内获得价值)
├─ 没有 → 仅限直接推广(媒体发布不会转化)
└─ 准备好了 → 你有 >100 万美元的融资要宣布吗?
├─ 有 → 两者都做(媒体发布提高知名度,直接推广促进转化)
└─ 没有 → 先直接推广,稍后再进行媒体发布
1. 为头条新闻而非激活率进行优化 5 万次曝光和 12 个注册。媒体报道 ≠ 增长。
2. 发布前没有目标客户列表 广撒网在 0 到 1 阶段行不通。先建立 100 个客户的列表。
3. 灵活性而没有默认选项 给用户所有选项会让他们不知所措。选择 2-3 个无可辩驳的用例并严格引导。
4. 免费赠送产品 免费用户给出礼貌的反馈。付费用户给出诚实的反馈。
5. 在学习之前就扩大规模 首批 10 名客户是为了学习,不是为了收入。记录一切。
6. 过度规划,测试不足 进行为期 2 周的实验,并设定明确的终止标准。快速行动,记录学习成果。
7. 诊断错误的层面 当问题是体验时去修复定位 = 浪费营销。当问题是定位时去修复体验 = 浪费工程。
三层诊断法: 第一层:定位(信息听起来像竞争对手)→ 测试新信息 第二层:体验(有知名度但没有激活)→ 引导至顿悟时刻 第三层:协调(团队分散)→ 单一北极星指标,每周可见性
首批 10 名客户: 个人网络(2-3 名)→ 直接推广(3-20 名)→ 触及天花板时刻的目标客户(意向最高)→ 社区(开发者产品)
两周实验周期: 假设 → 成功标准 → 测试(最多 2 周)→ 终止或投入 3 倍资源 → 记录行动手册
产品市场契合度信号: 40%+ 第 1 周到第 4 周留存率 + 口碑传播 + 销售周期缩短 + >40% 非常失望
合作伙伴主导的市场进入: 客户问题优先 → 窄范围试点 → 共同建立参考客户 → 利用他们的市场推广策略
基于那些为媒体报道优化却只从 5 万次曝光中获得 12 个注册的功能发布经验,使用三层模型诊断三家公司的发布停滞问题,以及构建将临时测试转变为可重复机制的两周实验周期。还借鉴了跨多个地区和细分市场的合作伙伴主导的市场进入经验。不是理论——是将虚荣指标误认为增长并学会诊断实际问题的教训。
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Launch new products from idea to first customers. The goal isn't headlines — it's finding 10 customers who can't live without you.
Triggers:
Context:
The Pattern:
Coordinated a feature launch with full press tour. TechCrunch, VentureBeat, product blogs. Big announcement day.
Result:
Why It Failed:
Optimized for media buzz, not user value. The feature wasn't ready for self-serve. It needed education, context, hand-holding. Press gives you eyeballs. But eyeballs without activation = vanity.
What Works Better:
Email 50 target customers directly. "We built [feature] because teams like yours struggle with [problem]. Want early access?" Walk them through setup personally. Get feedback, iterate.
Result: 50 emails → 15 replies (30% reply rate) → 8 trials → 4 conversions (50% trial-to-paid).
The Lesson:
Early customers come from direct outreach, not press coverage. Press matters later (Series A announcement, major milestone). For 0-to-1, it's distraction.
The Pattern:
You launched. You have some awareness. But conversion is weak. The problem lives in one of three layers, and each requires a different intervention.
Layer 1: Positioning Problem
Symptoms:
Diagnosis: You're "fighting an asymmetric war on the wrong front" — competing on features against better-funded companies. Map where competitors claim unique value. Find the position they can't easily copy.
Fix: Stake a claim you can own structurally (not just through product features). Test with outbound messaging before committing product resources.
Layer 2: Experience Problem
Symptoms:
Diagnosis: Flexibility without opinionated defaults is a liability, not a feature. Users face the "paradox of choice" — too many options, not enough guidance to the aha moment.
Fix: Identify 2-3 "undeniable use cases" that deliver immediate value. Restrict onboarding to those specific use cases. Gate advanced features behind a mastery path. Rewrite help content around jobs-to-be-done, not feature lists.
Layer 3: Alignment Problem
Symptoms:
Diagnosis: "Exploratory mode" — where every initiative has equal priority — becomes destructive when resources are constrained.
Fix: Define a single shared north star. Use it as tiebreaker for every decision: "Does this help us win a customer?" Cut activities that don't ladder up. Make progress visible weekly, not quarterly.
How to Use This:
When a launch stalls, diagnose which layer is broken before throwing resources at it. Fixing experience when the problem is positioning wastes engineering time. Fixing positioning when the problem is internal alignment wastes marketing spend.
Principle: First 10 customers are not for revenue. They're for learning.
What You're Learning:
How to Find Them:
Channel 1: Personal Network (first 2-3)
Channel 2: Direct Outreach (customers 3-20)
Channel 3: Ceiling Moment Targeting (highest-intent)
Channel 4: Community (developer products)
The Pattern:
Speed in early stages matters more than perfection. The constraint isn't whether you're right — it's how quickly you can test assumptions and iterate.
How to Execute:
The Playbook Rule:
Every successful experiment must become a playbook before scaling. Structure: Goal → Steps → Expected output → Metrics → Risks. If someone unfamiliar can't execute the playbook, it's not documented well enough.
Why This Matters:
One-off wins don't compound. Systematized experiments do. The goal isn't a single launch — it's building a repeatable machine for testing assumptions at speed.
Common Mistake:
Over-planning before testing. Waiting for "perfect" conditions before launching. Staying with failing experiments too long because you've invested emotional energy. Make decisions with 70% information.
The Pattern:
Rather than entering new markets through direct sales alone, use partnerships with established players to accelerate.
How to Execute:
The Supernode Pattern:
Position yourself as the integration hub that other tools naturally connect through. You own critical data or workflows that other platforms need. This compounds — each new partner makes you more valuable to the next.
Category Sequencing:
Don't pursue partnerships everywhere. Dominate 2-3 categories per quarter:
Common Mistake:
Launching partnerships without clear integration pathways. Expecting partners to drive awareness without support. Treating partnerships as a sales channel rather than platform expansion.
Product-market fit is when customers pull you forward, not when you push them.
Retention:
Organic Growth:
Sales Velocity:
Qualitative:
40% very disappointed if product went away (Sean Ellis test)
If you don't have these, you don't have PMF yet. Don't scale marketing/sales.
Do prospects understand what you are?
├─ No → Layer 1: Positioning problem
│ Fix: Test new messaging before changing product
└─ Yes → Continue...
│
Do users activate after signing up?
├─ No → Layer 2: Experience problem
│ Fix: Restrict onboarding to 2-3 use cases, guide to aha moment
└─ Yes → Continue...
│
Is the team aligned on what matters?
├─ No → Layer 3: Alignment problem
│ Fix: Single north star, weekly visibility, cut non-essential
└─ Yes → Keep iterating, you're on the right track
Self-serve ready? (Users get value in <10 min)
├─ No → Direct outreach only (press won't convert)
└─ Yes → Do you have >$1M funding to announce?
├─ Yes → Both (press for awareness, outreach for conversion)
└─ No → Direct outreach first, press later
1. Optimizing for headlines instead of activation 50K impressions and 12 signups. Press ≠ growth.
2. No target customer list before launch Spray-and-pray doesn't work at 0-to-1. Build the list of 100 accounts first.
3. Flexibility without defaults Giving users every option paralyzes them. Pick 2-3 undeniable use cases and guide hard.
4. Giving product away for free Free users give polite feedback. Paying users give honest feedback.
5. Scaling before learning First 10 customers are for learning, not revenue. Document everything.
6. Over-planning, under-testing 2-week experiments with clear kill criteria. Move fast, document learnings.
7. Diagnosing the wrong layer Positioning fix when the problem is experience = wasted marketing. Experience fix when the problem is positioning = wasted engineering.
Three-layer diagnosis: Layer 1: Positioning (messaging sounds like competitors) → Test new messaging Layer 2: Experience (awareness but no activation) → Guide to aha moment Layer 3: Alignment (team scattered) → Single north star, weekly visibility
First 10 customers: Personal network (2-3) → Direct outreach (3-20) → Ceiling moment targeting (highest intent) → Community (developer products)
2-week experiment cycle: Hypothesis → Success criteria → Test (2 weeks max) → Kill or 3x → Document playbook
PMF signals: 40%+ Week 1→4 retention + word-of-mouth + shortening sales cycles + >40% very disappointed
Partner-led entry: Customer problem first → Narrow pilot → Reference customers together → Leverage their GTM
Based on launching features that optimized for press and got 12 signups from 50K impressions, diagnosing launch stalls across three companies using the three-layer model, and building the 2-week experiment cycle that turned ad hoc testing into a repeatable machine. Also draws on partner-led market entry across multiple geographies and segments. Not theory — lessons from mistaking vanity metrics for growth and learning to diagnose the actual problem.
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Installed on
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