tam-sam-som-calculator

deanpeters/product-manager-skills · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/deanpeters/product-manager-skills --skill tam-sam-som-calculator
0 commentsdiscussion
summary

Structured market sizing framework for TAM, SAM, and SOM with adaptive questions and citation-backed estimates.

  • Guides product managers through four adaptive questions covering problem space, geography, industry segments, and target customers to build defensible market size estimates
  • Generates citation-backed TAM/SAM/SOM analysis with population estimates, industry data sources, and year-by-year projections grounded in Census Bureau, IBISWorld, Statista, and similar sources
  • Includes
skill.md

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 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.

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:

# 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 yea
how to use tam-sam-som-calculator

How to use tam-sam-som-calculator on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add tam-sam-som-calculator
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/deanpeters/product-manager-skills --skill tam-sam-som-calculator

The skills CLI fetches tam-sam-som-calculator from GitHub repository deanpeters/product-manager-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/tam-sam-som-calculator

Reload or restart Cursor to activate tam-sam-som-calculator. Access the skill through slash commands (e.g., /tam-sam-som-calculator) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.625 reviews
  • Chaitanya Patil· Dec 28, 2024

    Solid pick for teams standardizing on skills: tam-sam-som-calculator is focused, and the summary matches what you get after install.

  • Hassan Okafor· Dec 16, 2024

    I recommend tam-sam-som-calculator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Piyush G· Nov 19, 2024

    We added tam-sam-som-calculator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Harper Diallo· Nov 11, 2024

    tam-sam-som-calculator reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Anika Li· Nov 7, 2024

    Keeps context tight: tam-sam-som-calculator is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Rahul Santra· Nov 3, 2024

    Registry listing for tam-sam-som-calculator matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Anika Abbas· Oct 26, 2024

    tam-sam-som-calculator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Pratham Ware· Oct 22, 2024

    tam-sam-som-calculator reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Soo Rahman· Oct 6, 2024

    Keeps context tight: tam-sam-som-calculator is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Daniel Diallo· Oct 2, 2024

    Registry listing for tam-sam-som-calculator matched our evaluation — installs cleanly and behaves as described in the markdown.

showing 1-10 of 25

1 / 3