tam-sam-som-calculator
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Translation
ChinesePurpose
目的
Guide product managers through calculating Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) for a product idea by asking adaptive, contextually relevant questions. Use this to build defensible market size estimates backed by real-world citations, economic projections, and population data—essential for pitching to investors, securing budget, or validating product-market fit.
This is not a back-of-napkin guess—it's a structured, citation-backed analysis that withstands scrutiny.
通过提出自适应、贴合上下文的问题,引导产品经理为产品创意计算总可寻址市场(TAM)、可服务可用市场(SAM)和可服务可获得市场(SOM)。使用本方法构建有真实数据引用、经济预测和人口数据支撑的可靠市场规模估算——这是向投资者推介、争取预算或验证产品市场契合度的关键。
这绝非随手估算的数字——而是一套结构化、有数据引用支撑的分析方法,能够经得起严格推敲。
Key Concepts
核心概念
TAM/SAM/SOM Framework
TAM/SAM/SOM框架
The three-tier market sizing model:
Total Addressable Market (TAM):
- The total market demand for a product or service
- "If we captured 100% of the market, what's the revenue?"
- Broadest possible market (no constraints)
Serviceable Available Market (SAM):
- The segment of TAM your company can realistically target
- Narrowed by geography, firmographics, demographics, or product constraints
- "Who can we actually reach with our product?"
Serviceable Obtainable Market (SOM):
- The portion of SAM you can realistically capture
- Accounts for competition, market constraints, go-to-market capacity
- "What can we capture in the next 1-3 years?"
三层市场规模模型:
总可寻址市场(Total Addressable Market,TAM):
- 某产品或服务的整体市场需求
- 「如果我们占据100%的市场,营收会是多少?」
- 最宽泛的市场范围(无任何限制)
可服务可用市场(Serviceable Available Market,SAM):
- 企业实际能够触达的TAM细分市场
- 受地域、企业特征、人口统计或产品限制等因素收窄
- 「我们的产品实际能够触达哪些用户?」
可服务可获得市场(Serviceable Obtainable Market,SOM):
- 企业实际能够占据的SAM份额
- 需考虑竞争情况、市场限制、上市推广能力
- 「未来1-3年我们能够占据多少市场?」
Why This Works
本方法的优势
- Top-down validation: TAM → SAM → SOM ensures estimates are grounded in reality
- Investor-friendly: Standard framework VCs and execs understand
- Citation-backed: Real data sources (Census, Statista, World Bank) add credibility
- Adaptive: Questions adjust based on context (B2B vs. B2C, US vs. global, etc.)
- 自上而下验证: TAM → SAM → SOM的流程确保估算贴合实际
- 契合投资者需求: 是风险投资机构和高管普遍理解的标准框架
- 数据引用支撑: 真实数据源(人口普查局、Statista、世界银行)提升可信度
- 自适应调整: 问题会根据上下文调整(如B2B vs B2C、美国 vs 全球等)
Anti-Patterns (What This Is NOT)
反模式(本方法不适用的情况)
- Not a single-number guess: "The market is $10B" without supporting data
- Not static: Markets evolve—reassess annually
- Not a substitute for customer validation: Market size ≠ product-market fit
- 非单一数字猜测: 不能只说「市场规模为100亿美元」却无数据支撑
- 非静态分析: 市场在不断演变——需每年重新评估
- 不能替代客户验证: 市场规模 ≠ 产品市场契合度
When to Use This
适用场景
- Pitching to investors or execs (need market size in deck)
- Validating product ideas (is the market big enough?)
- Prioritizing product lines (which has bigger opportunity?)
- Setting growth targets (what's realistic to capture?)
- 向投资者或高管推介(演示文稿中需包含市场规模数据)
- 验证产品创意(市场规模是否足够大?)
- 产品线优先级排序(哪条产品线的机会更大?)
- 设定增长目标(实际可达成的目标是多少?)
When NOT to Use This
不适用场景
- For internal tools with captive users (no external market)
- Before defining the problem (market sizing requires clear problem space)
- As the only validation (pair with customer research)
- 面向内部 captive 用户的工具(无外部市场)
- 未明确问题之前(市场规模估算需要清晰的问题范围)
- 作为唯一的验证方式(需与客户研究结合使用)
Facilitation Source of Truth
引导流程的权威依据
Use as the default interaction protocol for this skill.
workshop-facilitationIt defines:
- session heads-up + entry mode (Guided, Context dump, Best guess)
- one-question turns with plain-language prompts
- progress labels (for example, Context Qx/8 and Scoring Qx/5)
- interruption handling and pause/resume behavior
- numbered recommendations at decision points
- quick-select numbered response options for regular questions (include when useful)
Other (specify)
This file defines the domain-specific assessment content. If there is a conflict, follow this file's domain logic.
默认使用作为本技能的交互协议。
workshop-facilitation该协议定义了:
- 会议预告 + 参与模式(引导式、上下文导入、最佳猜测)
- 单轮提问制,使用通俗易懂的提示语
- 进度标签(例如,上下文问题 Qx/8、评分问题 Qx/5)
- 中断处理及暂停/恢复机制
- 决策节点处的编号式建议
- 常规问题的快速选择编号选项(必要时包含「其他(请说明)」)
本文件定义了特定领域的评估内容。若出现冲突,请遵循本文件的领域逻辑。
Application
应用方法
Use for the full fill-in structure.
template.mdThis interactive skill asks up to 4 adaptive questions, offering enumerated context-aware options at each step. The agent adapts questions based on previous responses.
使用获取完整的填写模板。
template.md本交互式技能最多提出4个自适应问题,每个步骤提供枚举式的上下文相关选项。Agent会根据之前的回答调整后续问题。
Step 0: Gather Context (Before Questions)
步骤0:收集上下文(提问前)
Agent suggests:
Before we begin, it's helpful to have product context. If available, please share:
For Your Own Product:
- Website copy (homepage, product pages, value prop statements)
- Marketing emails or landing pages
- Product descriptions or positioning statements
- Case studies or customer testimonials
- Sales deck or pitch materials
If You Don't Have a Product Yet:
- Find a similar or adjacent product (competitor or analog)
- Copy their website homepage, product description, or landing page
- We'll use this as a reference point for market sizing
You can paste this content directly, or we can proceed with a brief description.
Why this helps:
- Marketing materials already contain target audience, pain points, and value props
- Analyzing real content (yours or competitors') grounds the analysis in reality
- You can benchmark against similar products' market positioning
Agent建议:
开始之前,提前准备产品相关上下文会有所帮助。如有可用信息,请分享:
针对已有产品:
- 网站文案(首页、产品页、价值主张声明)
- 营销邮件或着陆页
- 产品描述或定位声明
- 案例研究或客户推荐
- 销售演示文稿或推介材料
针对尚未成型的产品:
- 找到类似或相关的产品(竞品或同类产品)
- 复制其网站首页、产品描述或着陆页内容
- 我们将以此作为市场规模估算的参考依据
您可以直接粘贴上述内容,或简要描述产品信息后继续。
这样做的好处:
- 营销材料中已包含目标受众、痛点和价值主张
- 分析真实内容(自有或竞品)能让分析更贴合实际
- 您可以对标同类产品的市场定位
Optional Helper Script (Deterministic Math)
可选辅助脚本(确定性计算)
If you already have population and ARPU numbers (or a TAM estimate), you can run a deterministic helper to compute TAM/SAM/SOM and generate a Markdown table. This script does not fetch data or write files.
bash
python3 scripts/market-sizing.py --population 5400000 --arpu 1000 --sam-share 30% --som-share 10%如果您已掌握人口数量和ARPU(每用户平均收入)数据(或已有TAM估算值),可以运行确定性辅助脚本来计算TAM/SAM/SOM并生成Markdown表格。本脚本不会获取外部数据或写入文件。
bash
python3 scripts/market-sizing.py --population 5400000 --arpu 1000 --sam-share 30% --som-share 10%Question 1: Problem Space
问题1:问题领域
Agent asks:
"Based on the context you've provided (or will describe), what problem space are you exploring for market sizing?"
Offer 4 enumerated examples (user can select by number or write custom):
- B2B SaaS productivity — E.g., "Workflow automation for small business operations" (like Zapier, Integromat)
- Consumer fintech — E.g., "Personal budgeting app for Gen Z users" (like Mint, YNAB)
- Healthcare/telehealth — E.g., "Mental health support for remote workers" (like BetterHelp, Talkspace)
- E-commerce enablement — E.g., "Payment processing for online sellers" (like Stripe, Square)
Or write your own problem space description based on the marketing materials you shared.
Tip: If you provided website copy or marketing materials, the agent can extract the problem space from phrases like:
- "We help [target] solve [problem]"
- "The #1 solution for [use case]"
- Customer pain points in testimonials or case studies
User response: [Selection or custom description]
Agent提问:
"根据您提供(或即将描述)的上下文,您要进行市场规模估算的问题领域是什么?"
提供4个枚举示例(用户可通过编号选择或自定义描述):
- B2B SaaS生产力工具 —— 例如:「面向小型企业运营的工作流自动化工具」(类似Zapier、Integromat)
- 消费者金融科技 —— 例如:「面向Z世代用户的个人预算应用」(类似Mint、YNAB)
- 医疗健康/远程医疗 —— 例如:「面向远程办公者的心理健康支持工具」(类似BetterHelp、Talkspace)
- 电商赋能工具 —— 例如:「面向在线卖家的支付处理工具」(类似Stripe、Square)
或根据您分享的营销材料,自定义描述问题领域。
提示: 如果您提供了网站文案或营销材料,Agent可以从以下表述中提取问题领域:
- 「我们帮助[目标用户]解决[问题]」
- 「[使用场景]的首选解决方案」
- 客户推荐或案例研究中提到的痛点
用户回复: [选择或自定义描述]
Question 2: Geographic Region
问题2:地理区域
Agent asks:
"What geographic region are you targeting?"
Offer 4 enumerated options (adapted based on problem space):
- United States — Best for detailed Census Bureau data, BLS stats, robust industry reports
- European Union — Use Eurostat, local statistical agencies; note GDPR/compliance considerations
- Global — World Bank, IMF data; broader but less granular
- Specific country/region — E.g., "Canada," "Southeast Asia," "Latin America"
Or specify your own region.
User response: [Selection or custom]
Adaptation logic:
- If user selected B2B SaaS (Question 1, Option 1) → Emphasize US/EU markets (mature SaaS adoption)
- If user selected Consumer fintech (Question 1, Option 2) → Mention emerging markets (higher mobile adoption)
Agent提问:
"您的目标地理区域是什么?"
提供4个枚举选项(根据问题领域调整):
- 美国 —— 适合获取详细的人口普查局数据、劳工统计局统计数据、全面的行业报告
- 欧盟 —— 使用欧盟统计局、当地统计机构的数据;需注意GDPR/合规要求
- 全球 —— 使用世界银行、IMF的数据;范围更广但粒度较粗
- 特定国家/地区 —— 例如:「加拿大」、「东南亚」、「拉丁美洲」
或指定您的目标区域。
用户回复: [选择或自定义]
适配逻辑:此字段
- 如果用户选择B2B SaaS生产力工具(问题1,选项1)→ 重点推荐美国/欧盟市场(SaaS adoption成熟度高)
- 如果用户选择消费者金融科技(问题1,选项2)→ 提及新兴市场(移动设备普及率更高)
Question 3: Industry/Market Segments
问题3:行业/市场细分
Agent asks:
"What specific industry or market segments does this problem space relate to?"
Offer 4 enumerated options (adapted based on problem space + geography):
Example (if Question 1 = B2B SaaS, Question 2 = US):
- SMB services sector — 5.4M businesses, $1.2T revenue (US Census, 2023)
- Professional services (legal, accounting) — 1.1M firms, $850B revenue (IBISWorld, 2023)
- Healthcare providers — 900K practices, $4T industry (BLS, 2023)
- Tech/software companies — 500K firms, $1.8T revenue (Statista, 2023)
Or describe your own industry segment.
User response: [Selection or custom]
Adaptation logic:
- If Question 1 = Consumer fintech, offer consumer segments (e.g., "Gen Z 18-25," "Millennials 25-40")
- If Question 1 = Healthcare, offer segments (e.g., "Primary care physicians," "Therapists/counselors")
Agent提问:
"该问题领域涉及哪些特定行业或市场细分?"
提供4个枚举选项(根据问题领域+地理区域调整):
示例(若问题1=B2B SaaS生产力工具,问题2=美国):
- 中小企业服务行业 —— 540万家企业,1.2万亿美元营收(美国人口普查局,2023年)
- 专业服务(法律、会计) —— 110万家企业,8500亿美元营收(IBISWorld,2023年)
- 医疗保健提供商 —— 90万家机构,4万亿美元行业规模(劳工统计局,2023年)
- 科技/软件企业 —— 50万家企业,1.8万亿美元营收(Statista,2023年)
或自定义描述您的行业细分。
用户回复: [选择或自定义]
适配逻辑:此字段
- 如果问题1=消费者金融科技,提供消费者细分(例如:「Z世代18-25岁」、「千禧一代25-40岁」)
- 如果问题1=医疗健康,提供细分领域(例如:「初级保健医生」、「治疗师/咨询师」)
Question 4: Potential Customers (Demographics/Firmographics)
问题4:潜在客户(人口统计/企业特征)
Agent asks:
"Who are the potential customers affected by this problem?"
Offer 4 enumerated options (adapted based on previous answers):
Example (if Question 1 = B2B SaaS, Question 3 = SMB services sector):
- SMBs with 10-50 employees — 1.2M businesses, $400B revenue (Census Bureau, 2023)
- SMBs with 50-250 employees — 600K businesses, $800B revenue (Census Bureau, 2023)
- Solo entrepreneurs/freelancers — 3.5M self-employed, $200B revenue (BLS, 2023)
- Service businesses with online presence — 2M businesses, $600B e-commerce (Statista, 2023)
Or describe your own customer segment (firmographics, demographics, income, etc.).
User response: [Selection or custom]
Agent提问:
"受该问题影响的潜在客户是谁?"
提供4个枚举选项(根据之前的回答调整):
示例(若问题1=B2B SaaS生产力工具,问题3=中小企业服务行业):
- 员工规模10-50人的中小企业 —— 120万家企业,4000亿美元营收(人口普查局,2023年)
- 员工规模50-250人的中小企业 —— 60万家企业,8000亿美元营收(人口普查局,2023年)
- 个体创业者/自由职业者 —— 350万自雇人士,2000亿美元营收(劳工统计局,2023年)
- 拥有线上渠道的服务型企业 —— 200万家企业,6000亿美元电商规模(Statista,2023年)
或自定义描述您的客户细分(企业特征、人口统计、收入等)。
用户回复: [选择或自定义]
Output: Generate TAM/SAM/SOM Analysis
输出:生成TAM/SAM/SOM分析报告
After collecting responses, the agent generates a structured analysis:
markdown
undefined收集完所有回复后,Agent会生成结构化的分析报告:
markdown
undefinedTAM/SAM/SOM Analysis
TAM/SAM/SOM分析报告
Problem Space: [User's input from Question 1]
Geographic Region: [User's input from Question 2]
Industry/Market Segments: [User's input from Question 3]
Potential Customers: [User's input from Question 4]
问题领域: [用户在问题1中的输入]
地理区域: [用户在问题2中的输入]
行业/市场细分: [用户在问题3中的输入]
潜在客户: [用户在问题4中的输入]
Total Addressable Market (TAM)
总可寻址市场(TAM)
Definition: The total market demand if you captured 100% of potential customers in the problem space.
Population Estimate: [Calculated from data sources]
- Source: [Citation, e.g., "US Census Bureau, 2023"]
- Calculation: [Show math, e.g., "5.4M SMBs × $1.2T revenue = $1.2T TAM"]
Market Size Estimate: $[X] billion/million
- Source: [Industry report citation]
- URL: [Clickable link to source]
定义: 如果您占据问题领域内所有潜在客户的100%市场份额,对应的总市场需求。
人口规模估算: [根据数据源计算得出]
- 来源: [引用来源,例如:「美国人口普查局,2023年」]
- 计算方式: [展示计算过程,例如:「540万家中小企业 × 1.2万亿美元营收 = 1.2万亿美元TAM」]
市场规模估算: $[X]十亿/百万
- 来源: [行业报告引用]
- 链接: [可点击的来源链接]
Serviceable Available Market (SAM)
可服务可用市场(SAM)
Definition: The segment of TAM you can realistically target with your product (narrowed by geography, firmographics, product fit).
Segment of TAM: [User's narrowed segment from Question 4]
Population Estimate: [Calculated]
- Source: [Citation]
- Calculation: [Show math, e.g., "1.2M SMBs with 10-50 employees"]
Market Size Estimate: $[X] billion/million
- Source: [Citation]
- URL: [Link]
Assumptions:
- [List key assumptions, e.g., "Assumes 50% of SMBs have budget for automation tools"]
定义: 您的产品实际能够触达的TAM细分市场(受地理、企业特征、产品适配性限制)。
TAM细分: [用户在问题4中选择的细分市场]
人口规模估算: [计算得出]
- 来源: [引用来源]
- 计算方式: [展示计算过程,例如:「120万家员工规模10-50人的中小企业」]
市场规模估算: $[X]十亿/百万
- 来源: [引用来源]
- 链接: [链接]
假设条件:
- [列出核心假设,例如:「假设50%的中小企业有预算采购自动化工具」]
Serviceable Obtainable Market (SOM)
可服务可获得市场(SOM)
Definition: The portion of SAM you can realistically capture in the next 1-3 years, accounting for competition and market constraints.
Realistically Capturable Market: [Agent's estimation based on market maturity, competition]
Population Estimate: [Calculated]
- Source: [Citation]
- Calculation: [Show math, e.g., "1.2M SMBs × 5% market share (Year 1) = 60K customers"]
Market Size Estimate: $[X] million
- Assumptions:
- [Competition assumption, e.g., "5 major competitors, market leader has 15% share"]
- [GTM assumption, e.g., "Sales capacity: 50 customers/month in Year 1"]
- [Conversion assumption, e.g., "10% trial-to-paid conversion"]
Year 1-3 Projections:
- Year 1: [X]K customers, $[X]M revenue (5% of SAM)
- Year 2: [X]K customers, $[X]M revenue (10% of SAM)
- Year 3: [X]K customers, $[X]M revenue (15% of SAM)
定义: 未来1-3年内,您实际能够占据的SAM份额,需考虑竞争情况和市场限制。
实际可占据市场: [Agent根据市场成熟度、竞争情况估算]
人口规模估算: [计算得出]
- 来源: [引用来源]
- 计算方式: [展示计算过程,例如:「120万家中小企业 × 5%市场份额(第1年)= 6万家客户」]
市场规模估算: $[X]百万
- 假设条件:
- [竞争假设,例如:「5家主要竞争对手,市场领导者占据15%份额」]
- 上市推广(GTM)假设: [例如:「第1年销售能力:每月50个客户」]
- 转化假设: [例如:「试用转付费转化率10%」]
第1-3年预测:
- 第1年: [X]千名客户,$[X]百万营收(占据SAM的5%)
- 第2年: [X]千名客户,$[X]百万营收(占据SAM的10%)
- 第3年: [X]千名客户,$[X]百万营收(占据SAM的15%)
Data Sources & Citations
数据源与引用
- [Source 1: e.g., "US Census Bureau (2023). County Business Patterns. URL: census.gov"]
- [Source 2: e.g., "IBISWorld (2023). Professional Services Industry Report. URL: ibisworld.com"]
- [Source 3: e.g., "Statista (2023). SMB Software Market Size. URL: statista.com"]
- [Add all sources used]
- [来源1:例如:「美国人口普查局(2023年)。县商业模式报告。链接:census.gov」]
- [来源2:例如:「IBISWorld(2023年)。专业服务行业报告链接:ibisworld.com」]
- [来源3:例如:「Statista(2023年)。中小企业软件市场规模链接:statista.com」]
- [添加所有使用的来源]
Validation Questions
验证问题
- Does TAM align with industry reports? [Compare to 3rd-party market research]
- Is SAM realistically serviceable? [Can your GTM motion reach this segment?]
- Is SOM achievable given competition? [Is 5-15% market share realistic in 3 years?]
- TAM是否与行业报告一致? [与第三方市场研究数据对比]
- SAM是否具备实际可服务性? [您的GTM策略能否触达该细分市场?]
- 考虑竞争情况后SOM是否可达成? [3年内占据5-15%的SAM份额是否现实?]
Next Steps
下一步行动
- Validate with customer interviews: Does the problem resonate with target segment?
- Benchmark against competitors: What market share do incumbents have?
- Refine SOM based on GTM capacity: Can sales/marketing support this growth?
- Update annually: Markets shift—reassess TAM/SAM/SOM yearly
Would you like to refine any assumptions or explore a different segment?
---- 通过客户访谈验证: 该问题是否能引起目标细分市场的共鸣?
- 对标竞争对手: 现有企业占据多少市场份额?
- 根据GTM能力优化SOM: 销售/营销团队能否支撑该增长?
- 每年更新: 市场在变化——需每年重新评估TAM/SAM/SOM
您是否需要调整任何假设或探索其他细分市场?
---Examples
示例
See for a full TAM/SAM/SOM analysis example.
examples/sample.mdMini example excerpt:
markdown
**TAM:** 5.4M SMBs × $2,000 ARPA = $10.8B
**SAM:** 1.2M SMBs × $2,000 ARPA = $2.4B
**SOM:** 5% of SAM = $120M查看获取完整的TAM/SAM/SOM分析示例。
examples/sample.md迷你示例节选:
markdown
**TAM:** 540万家中小企业 × 2000美元ARPA = 108亿美元
**SAM:** 120万家中小企业 × 2000美元ARPA = 24亿美元
**SOM:** SAM的5% = 1.2亿美元Common Pitfalls
常见误区
Pitfall 1: TAM Without Citations
误区1:TAM无数据引用
Symptom: "The market is $50B" (no source)
Consequence: Can't defend the number to investors or execs.
Fix: Cite industry reports (Gartner, IBISWorld, Statista) with URLs.
症状: 只说「市场规模为500亿美元」却无来源
后果: 无法向投资者或高管证明该数字的可靠性。
解决方法: 引用行业报告(Gartner、IBISWorld、Statista)并附上链接。
Pitfall 2: SOM Equals SAM
误区2:SOM等于SAM
Symptom: "SAM is $5B, SOM is $5B" (assuming 100% capture)
Consequence: Unrealistic projection—no market has zero competition.
Fix: SOM should be 1-20% of SAM in Year 1-3, accounting for competition.
症状: 「SAM为50亿美元,SOM为50亿美元」(假设占据100%市场份额)
后果: 不切实际的预测——没有任何市场是零竞争的。
解决方法: 第1-3年的SOM应占SAM的1-20%,需考虑竞争情况。
Pitfall 3: No Population Estimates
误区3:无人口规模估算
Symptom: Only dollar amounts, no customer counts
Consequence: Can't build sales/marketing plans without knowing customer volume.
Fix: Always include population (e.g., "1.2M businesses" or "60K customers in Year 1").
症状: 仅提供金额,无客户数量
后果: 没有客户数量数据无法制定销售/营销计划。
解决方法: 始终包含人口规模数据(例如:「120万家企业」或「第1年6万家客户」)。
Pitfall 4: Static Assumptions
误区4:静态假设
Symptom: TAM/SAM/SOM calculated once, never updated
Consequence: Stale data as markets shift.
Fix: Reassess annually. Markets grow/shrink, competition changes, new data emerges.
症状: TAM/SAM/SOM仅计算一次,从未更新
后果: 市场变化导致数据过时。
解决方法: 每年重新评估。市场会增长/萎缩,竞争格局会变化,新数据会不断出现。
Pitfall 5: Ignoring GTM Constraints
误区5:忽略GTM限制
Symptom: "SOM is 50% of SAM in Year 1" (but no sales team)
Consequence: SOM isn't realistic given GTM capacity.
Fix: Ground SOM in GTM constraints (sales capacity, marketing budget, conversion rates).
症状: 「第1年SOM占据SAM的50%」但没有销售团队
后果: 考虑GTM能力后,SOM并不现实。
解决方法: SOM需基于GTM限制(销售能力、营销预算、转化率)制定。
References
参考资料
Related Skills
相关技能
- — TAM/SAM/SOM informs "For [target]" segment size
skills/positioning-statement/SKILL.md - — Problem space defines the market
skills/problem-statement/SKILL.md - — Market sizing informs business outcome projections
skills/recommendation-canvas/SKILL.md
- —— TAM/SAM/SOM为「针对[目标用户]」的细分市场规模提供依据
skills/positioning-statement/SKILL.md - —— 问题领域定义了市场范围
skills/problem-statement/SKILL.md - —— 市场规模估算为业务成果预测提供依据
skills/recommendation-canvas/SKILL.md
Optional Helpers
可选辅助工具
- — Deterministic TAM/SAM/SOM calculator (no network access)
skills/tam-sam-som-calculator/scripts/market-sizing.py
- —— 确定性TAM/SAM/SOM计算器(无需网络访问)
skills/tam-sam-som-calculator/scripts/market-sizing.py
External Frameworks
外部框架
- Steve Blank, The Four Steps to the Epiphany (2005) — Market sizing for startups
- Lean Startup methodology — Validate market size with experiments, not just desk research
- Steve Blank,《四步创业法》(2005年)—— 初创企业的市场规模估算方法
- 精益创业方法论 —— 通过实验验证市场规模,而非仅依赖案头研究
Data Sources (For Citations)
数据来源(用于引用)
- US: US Census Bureau, Bureau of Labor Statistics, IBISWorld, Statista
- Europe: Eurostat, local statistical agencies
- Global: World Bank, IMF, Gartner, Forrester
- 美国: 美国人口普查局、劳工统计局、IBISWorld、Statista
- 欧洲: 欧盟统计局、当地统计机构
- 全球: 世界银行、IMF、Gartner、Forrester
Dean's Work
Dean的相关成果
- TAM/SAM/SOM Prompt Generator (multi-turn adaptive market sizing)
Skill type: Interactive
Suggested filename:
Suggested placement:
Dependencies: None (standalone interactive skill)
tam-sam-som-calculator.md/skills/interactive/- TAM/SAM/SOM提示生成器(多轮自适应市场规模估算)
技能类型: 交互式
建议文件名:
建议存放路径:
依赖项: 无(独立交互式技能)
tam-sam-som-calculator.md/skills/interactive/