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Competitor Research Playbook
Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth...
📦 Install on ClawHub
clawhub install competitor-research-playbook
Then ask your AI agent:
"Audit our top 3 competitors and find positioning gaps"
Installs the full Competitor Research Playbook playbook — battle-tested with 30+ Product Hunt #1 wins, AFFiNE 60K+ GitHub stars, and 150+ AI startup consultations.
🔗 View on ClawHub · All Gingiris skills · Author blog
🚀 30-Second Preview
You: Audit our top 3 competitors and find positioning gaps
Agent (with competitor-research-playbook):
Step 1: Wayback Machine snapshots → track 12-month messaging shifts
Step 2: pricing diff matrix (their tiers vs ours, gap analysis)
Step 3: SEO keyword overlap → 20 unclaimed long-tails we could own
Step 4: positioning canvas (what they claim, what we can claim instead)
Concrete framework, real case studies, decision rules — not generic advice.
🆕 What's New in 1.2 (July 2026): Time-Machine Archaeology, Firsthand
Three research moves from the AFFiNE founding team's own competitor work (founder podcast interviews, 2024–2026), now folded into the SOP. Recalled figures are marked self-reported.
1. Google date-range archaeology — study competitors before they were famous. "Every unicorn you notice is already famous. What matters is what they were doing before anyone knew them." Use Google's date-range filter to roll back to 2016/2018 and study what Notion and ClickUp were doing pre-fame: compare their taglines era by era, and dig out the early user cases still preserved on their sites — early ClickUp picked one vertical (marketing consultancies), served ~10 clients deeply, and grew through those clients' SMB referrals. The source mix that worked: roughly half website archaeology, half human intel (community ambassadors, competitor alumni) — and never approach a human source without doing the archaeology first.
2. Open-source day reconstruction — star-history + Google advanced search. For open-source competitors, find the exact open-source date on star-history.com or OSS Insight, then restrict a Google search to that day/week and reconstruct everything they shipped and posted. Study what they did on Day One, not what they do today. Pick competitors that launched within the last 2–3 years and are within reach — not projects that launched 8 years ago.
3. Funding news = timing signal. A competitor's funding announcement marks a category momentum window. Real case: AppFlowy's $6.4M raise triggered the AFFiNE team's decision to open-source within one week — riding the same wave instead of watching it pass.
Mini teardown: AppFlowy's launch-day footprint (reconstructed with this method). The entire launch-week spread was only ~40 channels: 20+ directory sites (opensourcealternative.to and peers), article platforms (Medium, dev.to), developer forums, and Reddit — carried by one polished README, one "open source Notion alternative" article, and a cover doc, all pushed within a single day at zero budget. AFFiNE replicated the SOP and logged ~6,000 stars in its own launch week (self-reported).
📚 Full Playbook
name: competitor-research-playbook version: 1.2.0 description: | Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth flywheel? This gives you the complete SOP — from Wayback Machine snapshots to X/Twitter propagation analysis to growth flywheel scoring. Built from 150+ AI startup competitive analyses including the Lovable case study (4.3M views, 229K impressions launch day). By @WeiYipei.
What's inside: • 4-step research framework (website teardown → social media → traffic sources → ad spend) • 3-version website evolution analysis (V1 / Beta / Launch via Wayback Machine) • X/Twitter propagation chain mapping (4-phase model + single-post teardown template) • Growth flywheel 6-stage scoring system (Activation → Referral → Acquisition → Retention → Revenue → Product) • KOL identification framework (Traffic King / Topic Starter / Mindset Shifter) • Content effectiveness ranking (validated: Visual Demo > User Story > Competitor Comparison) • ICP deep analysis template + Freemium pricing teardown • Complete self-check checklist
🇨🇳 你的竞品刚刚爆了。你完全不知道他们怎么做到的。该拆官网？盯社媒？画增长飞轮？这份 SOP 给你从 Wayback Machine 快照到 X/Twitter 传播链路还原到飞轮六阶段评分的完整方法论。基于 150+ AI 创业公司竞品分析实战，含 Lovable 完整案例。
🇯🇵 競合が突然バズった。どうやって成長したか全く分からない。このSOPは、Waybackスナップショットからツイッター伝播チェーン分析、フライホイール6段階スコアリングまでの完全な競合調査フレームワークを提供します。150以上のAIスタートアップ分析から構築。
🇰🇷 경쟁사가 갑자기 폭발적으로 성장했습니다. 어떻게 그렇게 빨리 성장했는지 모릅니다. 이 SOP는 Wayback 스냅샷부터 X/Twitter 전파 체인 분석, 플라이휠 6단계 스코어링까지 완전한 경쟁사 조사 프레임워크를 제공합니다. 150개 이상의 AI 스타트업 분석에서 구축.
Triggers: "competitor research" | "competitive analysis" | "competitor analysis" | "growth flywheel" | "market research" | "竞品调研" | "竞品分析" | "增长飞轮" | "传播链路" | "競合分析" | "경쟁사 분석" | "social media teardown" | "Twitter propagation" | "content strategy analysis" tags: - competitor-research - competitive-analysis - growth-flywheel - market-research - growth-hacking - startup-growth - social-media-analysis - twitter-analysis - content-strategy - product-launch - go-to-market - SaaS-growth - indie-hacker - KOL-marketing - SEO
Competitor Research & Growth Flywheel Playbook — Full SOP
🌍 Language / 语言: 中文 | English | 日本語 | 한국어
Complete SOP for systematic competitor research: website evolution analysis, social media channel teardown, growth flywheel scoring, X/Twitter propagation chain mapping, and KOL identification. Battle-tested across 150+ AI startups. Includes Lovable full case study (Nov 2024 launch: 229K impressions, 4.3M video views, 10K+ Discord community).
一、竞品调研核心框架
1.1 四步调研法
| 步骤 | 内容 | 产出物 |
|---|---|---|
| Step 1 | 拆解竞品官网不同阶段版本 | 官网演变路径、Value Proposition演进、获客结构 |
| Step 2 | 拆解竞品社媒渠道内容策略 | 各渠道内容分类、发布节奏、KOL合作模式 |
| Step 3 | 导航站拆分（按需） | 导航站流量来源、友商投放入口 |
| Step 4 | 广告投放拆分（按需） | 投放渠道、素材策略、流量来源 |
1.2 工具清单
| 工具 | 用途 |
|---|---|
| Wayback Machine | 查看竞品历史官网快照 |
| SimilarWeb | 流量来源分析、渠道分布 |
| Semrush | SEO、广告投放分析 |
| star-history | 查开源竞品 star 增长曲线、定位其开源日期 |
| OSS Insight | 开源项目多维分析（贡献者/地域/趋势） |
二、官网拆解方法论
2.1 三个关键版本节点
- 第一版本的官网 — 最小可行版本
- 第一阶段Beta Test的官网 — 封闭测试期
- 第一阶段正式Launch的官网 — 公开上市
2.2 每版本记录维度
| 维度 | 内容 |
|---|---|
| 一句话介绍 | 核心Value Proposition |
| 官网长度 | 总屏数、落地页结构 |
| 用户案例 | 行业/场景用例 |
| 框架结构 | Banner/Pricing/CTA |
| SEO动作 | 标题/描述变化 |
| 社区渠道 | Discord/Reddit启动节点 |
| 集成生态 | 第三方集成 |
2.3 对比表格模板
| 阶段 | 时间节点 | Value Prop | 官网长度 | 主要板块 | 启动渠道 | 关键Feature |
|---|---|---|---|---|---|---|
| V1 | YYYY-MM | ... | X屏 | ... | ... | ... |
| Beta | YYYY-MM | ... | X屏 | ... | ... | ... |
| Launch | YYYY-MM | ... | X屏 | ... | ... | ... |
三、社媒渠道内容拆解
3.1 流量来源判断
先用SimilarWeb判断主要流量来源，再针对重点渠道深入拆解。优先分析对应渠道做得好的竞品。
3.2 Twitter/X 账号矩阵
| 账号类型 | 拆解重点 |
|---|---|
| 官媒 | 发布频次/节奏/风格、内容分类比例 |
| 创始人账号 | 与官媒差异化程度 |
| Dev Rel账号 | BD/生态合作内容 |
| 红人账号 | 不同阶段KOL合作 |
3.3 内容发布节奏（四阶段）
内测（封闭测试）→ 大范围发布 → 长线运营 → Launch Week
3.4 各平台策略对比
| 维度 | X/Twitter | YouTube | TikTok | |
|---|---|---|---|---|
| 定位 | 传播引爆 | 用户激活 | 企业获客 | 破圈拉新 |
| 频率 | 每日1-3条 | 每周1-3条 | 每周1-2条 | 高 |
四、增长飞轮分析法
4.1 飞轮六阶段评分
| 阶段 | 核心问题 |
|---|---|
| 创作(Activation) | 如何驱动"Aha Moment"？ |
| 分享(Referral) | 产品内有病毒传播机制？ |
| 发现(Acquisition) | 潜在用户如何被吸引？ |
| 互动(Retention) | 如何构建社区归属感？ |
| 变现(Revenue) | 免费→付费路径？ |
| 产品优化 | 反馈如何驱动迭代？ |
4.2 强弱判断标准
| 指标 | 强飞轮 | 弱飞轮 |
|---|---|---|
| 留存 | Discord DAU高，UGC持续 | 用户流失快 |
| 口碑 | 有系统化用户故事传播 | 无放大机制 |
| 付费 | 触发点清晰 | 路径模糊 |
| 持续性 | 产品与社区闭环 | 依赖外部投放 |
五、传播节点分析法
5.1 四阶段传播模型
| 阶段 | 时间 | 核心事件 |
|---|---|---|
| 内部点燃 | 发布后数小时 | 团队集体发声 |
| 生态催化 | 1-2天 | 合作伙伴背书 |
| KOL引爆 | 2-3天 | 顶级KOL定性 |
| 广泛渗透 | 持续数周 | 多语种用户参与 |
5.2 内容效果排序（数据验证）
| # | 类型 | 效果 |
|---|---|---|
| 🥇 | 视觉Demo（视频/动图） | 冲击力最强 |
| 🥈 | 真实用户成功案例 | 最可信 |
| 🥉 | 竞品对比内容 | 引发讨论 |
| 4 | 量化数据展示 | 社交货币 |
| 5 | 功能公告 | 覆盖窄 |
5.3 KOL识别标准
| 类型 | 识别信号 |
|---|---|
| 流量王 | 单帖>100K曝光 |
| 话题发动机 | 评论区深度讨论 |
| 心智转折点 | "以后都用它了" |
六、X/Twitter 深度分析
6.1 搜索语法
from:[Handle] since:YYYY-MM-DD until:YYYY-MM-DD -filter:retweets lang:en
"[产品名]" OR "[域名]" -from:[官方] since:YYYY-MM-DD -filter:retweets -filter:replies
6.2 单帖爆款拆解
| 维度 | 分析 |
|---|---|
| Hook | 从哪个角度讲？ |
| Nugget | 什么让人忍不住转？ |
| Feeling | 惊叹/好奇/FOMO？ |
| 视觉 | 降低什么理解成本？ |
七、综合洞察框架
五维分析
| 维度 | 输出 |
|---|---|
| 市场定位 | 细分、画像、差异化 |
| 商业模式 | 定价、飞轮 |
| 执行策略 | AARRR、内容日历 |
| 可复用策略 | 战术+适用边界 |
| 风险 | 识别+预警指标 |
自检清单
□ 覆盖三版本节点？
□ 拆解所有主要社媒渠道？
□ 识别增长飞轮及强弱？
□ 有传播数据支撑？
□ 提炼可复用策略+适用边界？
□ 识别风险+预警指标？
□ ICP覆盖3+类型？
□ 定价有升级路径分析？
□ 可行动战术建议？
Built from 150+ AI startup competitive analyses. Includes Lovable full case study (Nov 2024 launch). By @WeiYipei.
Part of the Gingiris growth skills suite — battle-tested operational playbooks for AI startups. Author: Iris (生姜iris), ex-AFFiNE COO, Forbes Asia 30 Under 30.
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