deanpeters/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.
npx skills add https://github.com/deanpeters/Product-Manager-Skills --skill tam-sam-som-calculator
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.
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:
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.
The three-tier market sizing model:
Total Addressable Market (TAM):
Serviceable Available Market (SAM):
Serviceable Obtainable Market (SOM):
Use workshop-facilitation as the default interaction protocol for this skill.
It defines:
Other (specify) when useful)This file defines the domain-specific assessment content. If there is a conflict, follow this file's domain logic.
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.
Agent suggests:
Before we begin, it's helpful to have product context. If available, please share:
For Your Own Product:
If You Don't Have a Product Yet:
You can paste this content directly, or we can proceed with a brief description.
Why this helps:
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.
python3 scripts/market-sizing.py --population 5400000 --arpu 1000 --sam-share 30% --som-share 10%
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
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):
~~~
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.
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):
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:
User response: [Selection or custom description]
Agent asks:
"What geographic region are you targeting?"
Offer 4 enumerated options (adapted based on problem space):
Or specify your own region.
User response: [Selection or custom]
Adaptation logic:
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):
Or describe your own industry segment.
User response: [Selection or custom]
Adaptation logic:
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):
Or describe your own customer segment (firmographics, demographics, income, etc.).
User response: [Selection or custom]
After collecting responses, the agent generates a structured analysis:
# 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?**
See examples/sample.md for a full TAM/SAM/SOM analysis example.
Mini example excerpt:
**TAM:** 5.4M SMBs × $2,000 ARPA = $10.8B
**SAM:** 1.2M SMBs × $2,000 ARPA = $2.4B
**SOM:** 5% of SAM = $120M
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.
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.
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").
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.
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).
skills/positioning-statement/SKILL.md — TAM/SAM/SOM informs "For [target]" segment sizeskills/problem-statement/SKILL.md — Problem space defines the marketskills/recommendation-canvas/SKILL.md — Market sizing informs business outcome projectionsskills/autonomous-investigation/SKILL.md — The protocol governing Mode 3 (research mode)skills/intelligence-collection-disciplines/SKILL.md — GEOINT/DEMOINT sources for the bottom-up recipe; FININT for capture ratesskills/market-landscape-scan/SKILL.md — Maps the segments worth sizing (structure before magnitude)skills/tam-sam-som-calculator/scripts/market-sizing.py — Deterministic TAM/SAM/SOM calculator (no network access)Skill type: Interactive
Suggested filename: tam-sam-som-calculator.md
Suggested placement: /skills/interactive/
Dependencies: None (standalone interactive skill)
Take deanpeters/tam-sam-som-calculator from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.