| name | market-sizing |
| description | Estimate the size of a market using top-down and bottom-up methods. Produces a TAM/SAM/SOM analysis with assumptions documented, sensitivity analysis, and business implications for go-to-market strategy. |
| argument-hint | ["market or product category","geographic scope","target customer","pricing model"] |
| allowed-tools | Read, Write, Bash |
Market Sizing
Market sizing answers the question: "Is this worth pursuing?" It produces a defensible estimate of the addressable opportunity, not a precise number. The goal is to understand order of magnitude, validate assumptions, and identify the key levers that make the opportunity larger or smaller.
Market Size Definitions
| Term | Definition | Use it for |
|---|
| TAM — Total Addressable Market | Total global demand for the category if you had 100% market share | Validating the ceiling |
| SAM — Serviceable Addressable Market | The portion of TAM your product and GTM can realistically reach | Realistic opportunity |
| SOM — Serviceable Obtainable Market | The share of SAM you can capture in 3–5 years | Business plan input |
Two Methods
Top-Down
Start with industry data (analyst reports, public company filings) and narrow to your segment.
TAM = [Total industry size from analyst report]
× [Fraction that matches your category]
SAM = TAM × [Geographic scope] × [Customer segment match] × [Price point accessibility]
SOM = SAM × [Realistic market share in 3–5 years]
Sources: Gartner, IDC, Forrester, SEC filings, public company investor decks.
Bottom-Up
Build from customer unit economics upward.
TAM = [Number of potential buyers] × [Price per buyer per year]
SAM = [Buyers reachable with your GTM] × [Price per buyer per year]
SOM = [Buyers you can win in 3–5 years] × [Price per buyer per year]
Sources: LinkedIn company data, industry association statistics, your own sales data.
Use both methods and triangulate. If they differ by >5x, revisit your assumptions.
Process
- Define the market precisely — what category? What customer? What geography? What price point?
- Identify market proxies — what existing data sources give you population and spending data?
- Top-down estimate — start with industry analyst market size; narrow to your segment.
- Bottom-up estimate — count potential buyers × your pricing.
- Triangulate — do both methods agree within 2–3x? If not, find the assumption causing the gap.
- Document every assumption — each assumption should have a source or a clear rationale.
- Run sensitivity analysis — how does the SOM change if your key assumption is 50% wrong?
- Segment the opportunity — break down by geography, company size, or vertical.
- Assess competitive density — how much of the SAM is already claimed by incumbents?
- Write implications — what does this mean for pricing, GTM strategy, and fundraising narrative?
Output Format
# Market Sizing: [Product / Market Category]
**Date:** [YYYY-MM-DD]
**Author:** [Name]
**Scope:** [Category] — [Geography] — [Customer segment]
**Pricing model:** [$X per user per year / $X per company per year]
---
## Summary
**TAM:** $[X]B — Total global market for [category]
**SAM:** $[X]B — [Your target geography and segment]
**SOM:** $[X]M — [Realistic 5-year capture]
**Key conclusion:** [One sentence on whether the opportunity is large enough and what it implies for strategy]
---
## Method 1: Top-Down
### Step 1: Total industry size
**Source:** [Analyst report or public filing]
- [e.g., "Gartner estimates the global project management software market at $7.3B in 2024, growing at 13% CAGR"]
- Total industry: $7.3B
### Step 2: Narrow to your category
- Project management software that serves B2B SaaS teams: ~35% of total market
- Segment size: $7.3B × 35% = $2.6B
### Step 3: Narrow to your geography
- North America + Western Europe: ~65% of B2B SaaS spend
- SAM (top-down): $2.6B × 65% = $1.7B
**Top-down SAM estimate: ~$1.7B**
---
## Method 2: Bottom-Up
### Step 1: Count the buyers
**Target customer:** Product and engineering teams at B2B SaaS companies, 10–500 employees.
| Company size | # Companies (US + EU) | Source |
|-------------|----------------------|--------|
| 10–50 employees | ~180,000 | LinkedIn company data |
| 51–200 employees | ~52,000 | LinkedIn company data |
| 201–500 employees | ~18,000 | PitchBook / Crunchbase |
| **Total** | **~250,000 companies** | |
**Assumption:** 60% of these are B2B SaaS or technology companies = ~150,000 target companies.
### Step 2: Average revenue per account
| Segment | Team size | ACV estimate | Basis |
|---------|-----------|-------------|-------|
| 10–50 employees | 8 team seats | $120/seat/year = $960/year | Our current pricing |
| 51–200 employees | 25 team seats | $120/seat/year = $3,000/year | Our current pricing |
| 201–500 employees | 60 team seats | $100/seat/year = $6,000/year | Volume discount |
~$2,400/year across all segments
SAM = 150,000 companies × $2,400 average ACV =
---
| Method | Estimate | Variance |
|--------|---------|---------|
| Top-down | $1.7B | — |
| Bottom-up | $360M | — |
| | | 5x range |
The 5x gap between methods is explained by:
The top-down figure includes all PM software (enterprise tools like Jira cost $80–200/user/year vs. our $120)
Bottom-up may undercount total buyer universe (excludes non-SaaS tech companies)
Enterprise segment (500+ employees) is excluded from bottom-up
Add ~20,000 enterprise companies × $15,000 = $300M additional
Revised bottom-up SAM: ~$660M
SAM is likely in the $500M–$800M range. Use $650M as the base case.
---
Year 1: Land 200 new accounts (current run rate: 12/month)
Year 3: Grow to 1,500 accounts at $2,400 ACV = $3.6M ARR
Year 5: Grow to 5,000 accounts at $2,600 ACV (expansion) = $13M ARR
| Year | Accounts | ACV | ARR | SOM % of SAM |
|------|---------|-----|-----|-------------|
| 1 | 400 | $2,000 | $0.8M | 0.1% |
| 3 | 1,500 | $2,400 | $3.6M | 0.6% |
| 5 | 5,000 | $2,600 | $13M | 2.0% |
---
What happens to 5-year SOM if key assumptions change?
| Assumption | Base case | Pessimistic (-50%) | Optimistic (+50%) |
|-----------|----------|-------------------|------------------|
| Total addressable buyers | 150,000 | 75,000 | 225,000 |
| Win rate | 3% | 1.5% | 4.5% |
| Average ACV | $2,400 | $1,800 | $3,200 |
| 5-year ARR | $13M | $5M | $28M |
Win rate has the largest impact. Improving win rate from 3% to 5% (via better onboarding or a stronger enterprise tier) more than doubles the SOM.
---
| Segment | SAM | Current penetration | Priority |
|---------|-----|-------------------|---------|
| US SaaS companies, 50–200 employees | $180M | 0.8% | P1 |
| EU SaaS companies, 50–200 employees | $120M | 0.1% | P2 |
| US SaaS companies, 10–50 employees | $80M | 0.4% | P3 (high volume, low ACV) |
| Enterprise 500+ employees | $270M | 0% (not yet serving) | Future |
---
— $650M SAM is sufficient to build a $100M+ ARR business without needing > 15% market share.
— $270M of SAM is in enterprise (500+). We are currently not equipped to serve this segment. SSO, SOC 2, and enterprise contracts are required.
— current win rate in contested deals is approximately 22%. Moving to 35% has more impact than expanding total buyer universe.
— 0.1% penetration vs. 0.8% in the US, despite $120M SAM. Consider localized onboarding and EU data residency as unlock mechanisms.
— 4 well-funded competitors serving the same SAM. Differentiation via self-serve enterprise features is the defensible wedge.
Sourcing Market Data
| Situation | Source | Cost |
|---|
| Industry analyst report | Gartner Magic Quadrant, IDC MarketScape | Free summaries; paid full reports |
| Public company filings | SEC EDGAR (10-K annual reports) — search competitor filings for market size claims | Free |
| LinkedIn company counts | LinkedIn Sales Navigator company search by employee count + industry | Paid subscription |
| VC / startup market sizing | Pitchbook, Crunchbase — look at competitor funding rounds; decks often cite TAM | Paid |
| Bottoms-up proxies | Bureau of Labor Statistics (US), Eurostat (EU) for employer counts | Free |
| Survey data | Your own NPS surveys, trial signup data | Free if you have it |
Common Mistakes
| Mistake | Example | Fix |
|---|
| TAM = SAM | "The global software market is $600B — our TAM is $600B" | Narrow to your actual category and customer |
| Circular reasoning | "We want to reach $50M ARR, so our SOM is $50M" | Build SOM from win rate × addressable buyers |
| Ignoring competition | "100% of SAM is available to us" | Apply competitive intensity discount (30–70% of SAM is captured by incumbents) |
| False precision | "Our TAM is $3.847B" | Use ranges: "TAM is $3–4B" |
| Wrong time horizon | "We can capture 30% of TAM" | 30% market share is extremely rare; 2–5% in 5 years is realistic |
Rules
- Use two methods, then triangulate — a single method produces a number; two methods produce confidence.
- Document every assumption — a market size without assumptions is a guess.
- SAM, not TAM, drives strategy — TAM is for the pitch deck; SAM is for the business plan.
- Sensitivity analysis is mandatory — show how SOM changes if your biggest assumption is wrong.
- False precision undermines credibility — use ranges; do not claim precision you do not have.
- Competitive density reduces SOM — some SAM is already captured by incumbents; account for it.
- Win rate is the most controllable variable — focus improvement efforts on win rate, not market expansion.
- Segment before sizing — one large number is less useful than three smaller numbers by segment.
- Update annually — a 3-year-old market sizing analysis may miss new competitors or market shifts.
- Connect to fundraising or planning — always end with what the sizing implies for strategy.
