gtm
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ChineseGTM — Growth & Go-to-Market
GTM — 增长与上市策略
Build products that spread themselves through authentic resonance, not gimmicks.
打造通过真实共鸣而非噱头实现自传播的产品。
Core Framework: VIBE
核心框架：VIBE
- Velocity — Speed of viral cycle (signup → share → new signup)
- Identity — Emotional resonance and brand authenticity
- Boundaryless — Cross-platform, cross-community spread
- Emotions — Sharing driven by feeling, not incentives
- Velocity（传播速度） — 病毒式循环的速度（注册→分享→新用户注册）
- Identity（品牌认同） — 情感共鸣与品牌真实性
- Boundaryless（无界传播） — 跨平台、跨社群传播
- Emotions（情感驱动） — 分享由情感而非激励驱动
Growth Strategy Selection
增长策略选择
Product has network effects?
├─ Yes → Design embedded viral loop
│ ├─ Multi-party workflow? → Embedded loop (Calendly model)
│ ├─ Creates shareable output? → UGC loop (Canva model)
│ └─ Has visible usage? → Casual contact loop (Slack model)
└─ No → Evaluate referral program
├─ High LTV? → Two-sided incentive
├─ Community-driven? → Status/recognition rewards
└─ Transactional? → Reconsider if viral is right channel产品具备网络效应？
├─ 是 → 设计嵌入式病毒式传播闭环
│ ├─ 多方协作流程？ → 嵌入式闭环（Calendly模式）
│ ├─ 生成可分享内容？ → UGC闭环（Canva模式）
│ └─ 有可见使用场景？ → 偶然接触闭环（Slack模式）
└─ 否 → 评估推荐计划
├─ 高客户终身价值？ → 双向激励机制
├─ 社群驱动型？ → 身份/认可奖励
└─ 交易型产品？ → 重新考虑病毒式传播是否为合适渠道Viral Loop Metrics
病毒式传播闭环指标
K factor = users sharing × invites per share × conversion rate
| Loop Type | Typical K | Example |
|---|---|---|
| Embedded | 0.5–2.0 | Calendly, DocuSign |
| UGC | 0.3–1.0 | Canva, Loom |
| Community | 0.2–0.5 | Discord, Notion |
K > 1.0 = viral growth. K > 0.3 = meaningful organic boost.
K factor = 分享用户数 × 每用户分享邀请数 × 转化率
| 闭环类型 | 典型K值 | 示例 |
|---|---|---|
| 嵌入式 | 0.5–2.0 | Calendly, DocuSign |
| UGC | 0.3–1.0 | Canva, Loom |
| 社群型 | 0.2–0.5 | Discord, Notion |
K > 1.0 = 病毒式增长。K > 0.3 = 显著的自然增长助力。
Quick Audit (Run on Any Product)
快速审计（适用于任何产品）
- Map sharing behavior — Where do users already share? What do they screenshot?
- Calculate K factor — Track: shares, invites, conversions
- Identify friction — Where do users drop off the share flow?
- Design intervention — Remove one friction point, measure impact
- 梳理分享行为 — 用户当前在哪些场景分享？他们会截图分享什么内容？
- 计算K factor — 追踪：分享次数、邀请数、转化数
- 识别卡点 — 用户在分享流程中的哪个环节流失？
- 设计优化方案 — 移除一个卡点，衡量影响效果
Launch Playbook
发布手册
Pre-Launch
预发布阶段
- Build waitlist with specific value prop (not "coming soon")
- Seed 10-20 power users for feedback and launch-day amplification
- Prepare launch assets: demo video, thread, landing page
- 打造具有明确价值主张的等待列表（而非仅显示"即将推出"）
- 邀请10-20位核心用户获取反馈并在发布日进行传播放大
- 准备发布物料：演示视频、推文长文、着陆页
Launch Day
发布当日
- Activate power users first (social proof before broad reach)
- Post on primary channel, cross-post hooks to secondary
- Respond to every comment for first 24 hours
- 先激活核心用户（在广泛触达前积累社交证明）
- 在主渠道发布内容，将引流内容交叉发布至次级渠道
- 发布后24小时内回复所有评论
Post-Launch
发布后阶段
- Track: signups, activation rate, K factor, retention at day 7
- Double down on what's working, kill what's not
- Ship one user-requested feature within first week (builds trust)
- 追踪：注册量、激活率、K factor、7日留存率
- 加大对有效策略的投入，终止无效策略
- 在第一周内上线一个用户请求的功能（建立信任）