tam-sam-som-calculator

Calculates TAM, SAM, and SOM market size estimates with cited assumptions and methods.

1|1|Updated Jul 6, 2026
One-click install
npx skills add https://github.com/muhammaddadu/ai-skill-collection --skill tam-sam-som-calculator-muhammaddadu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tam-sam-som-calculator
Source: https://github.com/muhammaddadu/ai-skill-collection/tree/main/1-exploration/tam-sam-som-calculator
Command: npx skills add https://github.com/muhammaddadu/ai-skill-collection --skill tam-sam-som-calculator-muhammaddadu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve? Product managers and founders need defensible market size estimates for investor pitches, budget requests, and product validation, but back-of-napkin guesses without citations fail executive scrutiny. ## Core Features & Use Cases - Adaptive Questioning: Asks up to 4 context-aware questions covering problem space, geography, industry segments, and target customers, with enumerated options adapted to prior answers. - Citation-Backed Analysis: Generates a structured TAM/SAM/SOM markdown report with population estimates, calculations, data sources, assumptions, and 1-3 year SOM projections. - Deterministic Helper Script: Runs scripts/market-sizing.py to compute TAM/SAM/SOM from population and ARPU inputs and print a Markdown summary table. - Use Case: A PM preparing a pitch deck for a B2B SaaS workflow tool answers four questions and receives a market sizing analysis citing Census Bureau, Gartner, and IBISWorld data. ## Quick Start Ask the assistant to calculate TAM, SAM, and SOM for your product idea and answer its questions about problem space, region, and target customers.

Frequently Asked Questions about tam-sam-som-calculator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate TAM, SAM, and SOM for a product idea?▼

Define your problem space, geographic region, industry segment, and target customers, then estimate population and revenue per customer for each tier. TAM is total demand, SAM is the reachable segment, and SOM is the realistic 1-3 year capture, typically 1-20% of SAM.

What data sources should I cite for market sizing?▼

Use US Census Bureau and Bureau of Labor Statistics for US data, Eurostat for Europe, and World Bank or IMF for global figures. Industry reports from Gartner, IBISWorld, and Statista provide market revenue estimates with defensible credibility.

How do I use the market-sizing.py script?▼

Run python3 scripts/market-sizing.py with either --tam or --population plus --arpu, along with --sam-share and --som-share as percentages or decimals. It prints a Markdown table with TAM, SAM, and SOM estimates and performs no network calls.

Why is my SOM estimate unrealistic?▼

SOM fails when it equals SAM or ignores go-to-market constraints like sales capacity, conversion rates, and competitor share. Ground SOM in 1-20% of SAM over three years with explicit assumptions about competition and GTM motion.

When should I not use TAM/SAM/SOM analysis?▼

Skip market sizing for internal tools with captive users, before the problem space is defined, or as the sole validation method. Pair it with customer interviews since market size does not prove product-market fit.