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.

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. Input Works best with: The product or idea being sized, and any market constraints you already know (geography, vertical, customer type). Also useful: Pricing assumptions, comparable companies, and the audience for the numbers (investors, execs, business case). Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re ask. Arriving empty handed? That works too. The calculator opens by asking what you're sizing and for whom, then works through method and assumptions. Three entry modes — pick whichever matches where your evidence lives: 1. Bring your own numbers — you have population and ARPU figures; jump to the math (the helper script makes this deterministic) 2. Guided interview — up to 4 adaptive questions build the inputs with you (the default flow below) 3. Autonomous research — the agent builds a bottom up, citation backed estimate from government statistics and filings while you review the evidence (see Mode 3 in Application) Example invocation: Size the market: AI scheduling assistant for independent dental practices, US only, $99/mo price point. — or for research mode: Research mode market sizing: field service dispatch software, DACH region; I have no numbers yet. 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. Mode 3: Autonomous Research (when the user has no numbers) When the user picks research mode — or arrives with a market and a decision but no data — run the sizing as an investigation under the [ autonomous investigation ](../autonomous investigation/SKILL.md) protocol: ask at most the questions below that remain unanswered, show a 3 bullet search plan, then build the estimate bottom up with every figure labeled Fact / Inference / Assumption and cited. The bottom up recipe (from the GEOINT/DEMOINT discipline in [ intelligence collection disciplines ](../intelligence collection disciplines/SKILL.md)): ~~~ TAM: Establishment counts for the market (Census/NAICS, Eurostat/NACE, or the national equivalent for the geography) × employment/spend benchmarks (BLS, Eurostat, trade associations) (validate against two independent analyst reports; if they disagree by 3x, say so) SAM: TAM filtered by your actual constraints: geography, segment, compliance requirements, tech prerequisites (technographics: who can buy you), vendor registration eligibility where applicable SOM: SAM × realistic capture rate derived from competitor public filings (their revenue ÷ their claimed customer count = deal size reality check) ~~~ Why bottom up wins scrutiny: a top down number ("2% of a $50B market") borrows someone else's denominator and hides every assumption inside it. Establishment counts × benchmarks shows the math, so a skeptical CFO can attack one assumption at a time instead of dismissing the whole slide. The capture rate trick grounds SOM in what incumbents actually achieve rather than hope. Research mode output uses the same analysis structure below, with two additions: an evidence label on every figure, and an Assumptions to Validate list. When done, offer the standard next steps plus a re run option — sizing built from statistics releases rots slowly but really; re run annually per the fusion cadence. 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: Examples See examples/sample.md for a full TAM/SAM/SOM analysis example. Mini example excerpt: 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 do

tam-sam-som-calculator