tam-sam-som-calculator
Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats. Use when sizing a market for a product idea, business case, or executive review.
Best use case
tam-sam-som-calculator is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats. Use when sizing a market for a product idea, business case, or executive review.
Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats. Use when sizing a market for a product idea, business case, or executive review.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "tam-sam-som-calculator" skill to help with this workflow task. Context: Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats. Use when sizing a market for a product idea, business case, or executive review.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/tam-sam-som-calculator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How tam-sam-som-calculator Compares
| Feature / Agent | tam-sam-som-calculator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats. Use when sizing a market for a product idea, business case, or executive review.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
## Purpose 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. ## Key Concepts ### TAM/SAM/SOM Framework 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?" ### Why This Works - **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.) ### Anti-Patterns (What This Is NOT) - **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 ### When to Use This - 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?) ### When NOT to Use This - 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) --- ### Facilitation Source of Truth Use [`workshop-facilitation`](../workshop-facilitation/SKILL.md) as the default interaction protocol for this skill. It 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 `Other (specify)` when useful) This file defines the domain-specific assessment content. If there is a conflict, follow this file's domain logic. ## Application Use `template.md` for the full fill-in structure. This interactive skill asks **up to 4 adaptive questions**, offering **enumerated context-aware options** at each step. The agent adapts questions based on previous responses. --- ### Step 0: Gather Context (Before Questions) **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 --- ### Optional Helper Script (Deterministic Math) 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% ``` --- ### Question 1: Problem Space **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):** 1. **B2B SaaS productivity** — E.g., "Workflow automation for small business operations" (like Zapier, Integromat) 2. **Consumer fintech** — E.g., "Personal budgeting app for Gen Z users" (like Mint, YNAB) 3. **Healthcare/telehealth** — E.g., "Mental health support for remote workers" (like BetterHelp, Talkspace) 4. **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] --- ### Question 2: Geographic Region **Agent asks:** "What geographic region are you targeting?" **Offer 4 enumerated options (adapted based on problem space):** 1. **United States** — Best for detailed Census Bureau data, BLS stats, robust industry reports 2. **European Union** — Use Eurostat, local statistical agencies; note GDPR/compliance considerations 3. **Global** — World Bank, IMF data; broader but less granular 4. **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) --- ### Question 3: Industry/Market Segments **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):** 1. **SMB services sector** — 5.4M businesses, $1.2T revenue (US Census, 2023) 2. **Professional services (legal, accounting)** — 1.1M firms, $850B revenue (IBISWorld, 2023) 3. **Healthcare providers** — 900K practices, $4T industry (BLS, 2023) 4. **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") --- ### Question 4: Potential Customers (Demographics/Firmographics) **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):** 1. **SMBs with 10-50 employees** — 1.2M businesses, $400B revenue (Census Bureau, 2023) 2. **SMBs with 50-250 employees** — 600K businesses, $800B revenue (Census Bureau, 2023) 3. **Solo entrepreneurs/freelancers** — 3.5M self-employed, $200B revenue (BLS, 2023) 4. **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] --- ### Output: Generate TAM/SAM/SOM Analysis After collecting responses, the agent generates a structured analysis: ```markdown # TAM/SAM/SOM Analysis **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] --- ## Total Addressable Market (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] --- ## Serviceable Available Market (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"] --- ## Serviceable Obtainable Market (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) --- ## Data Sources & Citations - [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] --- ## Validation Questions 1. **Does TAM align with industry reports?** [Compare to 3rd-party market research] 2. **Is SAM realistically serviceable?** [Can your GTM motion reach this segment?] 3. **Is SOM achievable given competition?** [Is 5-15% market share realistic in 3 years?] --- ## Next Steps 1. **Validate with customer interviews:** Does the problem resonate with target segment? 2. **Benchmark against competitors:** What market share do incumbents have? 3. **Refine SOM based on GTM capacity:** Can sales/marketing support this growth? 4. **Update annually:** Markets shift—reassess TAM/SAM/SOM yearly --- **Would you like to refine any assumptions or explore a different segment?** ``` --- ## Examples See `examples/sample.md` for a full TAM/SAM/SOM analysis example. Mini 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 ``` ## Common Pitfalls ### Pitfall 1: TAM Without Citations **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. --- ### Pitfall 2: SOM Equals 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. --- ### Pitfall 3: No Population Estimates **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"). --- ### Pitfall 4: Static Assumptions **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. --- ### Pitfall 5: Ignoring GTM Constraints **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). --- ## References ### Related Skills - `skills/positioning-statement/SKILL.md` — TAM/SAM/SOM informs "For [target]" segment size - `skills/problem-statement/SKILL.md` — Problem space defines the market - `skills/recommendation-canvas/SKILL.md` — Market sizing informs business outcome projections ### Optional Helpers - `skills/tam-sam-som-calculator/scripts/market-sizing.py` — Deterministic TAM/SAM/SOM calculator (no network access) ### External Frameworks - 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 ### Data Sources (For Citations) - **US:** US Census Bureau, Bureau of Labor Statistics, IBISWorld, Statista - **Europe:** Eurostat, local statistical agencies - **Global:** World Bank, IMF, Gartner, Forrester ### Dean's Work - TAM/SAM/SOM Prompt Generator (multi-turn adaptive market sizing) --- **Skill type:** Interactive **Suggested filename:** `tam-sam-som-calculator.md` **Suggested placement:** `/skills/interactive/` **Dependencies:** None (standalone interactive skill)
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