Intro.
#The Three Layers, Defined at a Glance
| Layer | Definition | Analogy |
|---|---|---|
| TAM (Total Addressable Market) | The entire market you could theoretically reach | 'Every cake that exists in the world' |
| SAM (Serviceable Available Market) | The portion actually reachable given your geography, language, and business model | 'The cakes our shop can actually deliver' |
| SOM (Serviceable Obtainable Market) | What you can realistically capture within the next 24-36 months | 'The cakes our shop will actually sell next month' |
TIP
The three layers narrow like a funnel, from largest to smallest. SOM is typically 1-10% of SAM — if SOM comes out close to SAM, that's read as unrealistic.
02
#Two Approaches — Top-Down vs. Bottom-Up
| Approach | Example Formula | Advantage | Risk |
|---|---|---|---|
| Top-down | Total industry size x assumed market share | Fast, intuitive | Weak justification, invites immediate skepticism |
| Bottom-up | Customer count x price x frequency | Verifiable, builds trust | Time-consuming |
The strongest approach in a business plan is to present both methods side by side and explicitly note the gap between them. If the two numbers land close together, that's a signal your assumptions are internally consistent; if they diverge sharply, you can use that gap to explain exactly which assumption broke.
03
#Example — A B2C Healthcare App
| Layer | Calculation Method | Example Figures |
|---|---|---|
| TAM | Domestic healthcare app user population x average ARPU | 43M adults x ₩5,000/month x 12 months ≈ ₩2.6T |
| SAM | Working professionals in their 30s-40s x share interested in diet apps x ARPU | 12M x 30% x ₩9,900/month x 12 ≈ ₩420B |
| SOM | Gym members aged 30-40 in the greater Seoul area x 5% conversion x average ₩140,000 | 1.2M x 5% x ₩140,000 ≈ ₩8.4B |
TAM should always cite its source (Statistics Korea, the Korea Health Industry Development Institute, etc.), while SAM and SOM need to be backed by your own research or comparisons to adjacent industries. Keeping SOM as conservative as possible is what builds credibility for later fundraising rounds.
04
#Example — B2B SaaS
| Layer | Calculation Method | Example Figures |
|---|---|---|
| TAM | Global market size for the same business model x ARPU | Global collaboration SaaS market ($XB) x average price |
| SAM | Number of SMEs in Korea + Southeast Asia x ARPU | 800K Korean SMEs x ₩50,000/month x 12 ≈ ₩480B |
| SOM | Target companies by industry and size x channel reach efficiency x conversion rate | 50K target companies x 30% channel reach x 5% conversion x ₩50,000 x 12 ≈ ₩4.5B |
주의
In B2B, a single blended 'average ARPU' rarely holds up. The standard practice is to separate SMB, mid-market, and enterprise segments, and calculate ARPU and reachable customer count independently for each.
05
#Five Common Inflation Patterns
- Including the entire global market in TAM while SAM is limited to Korea — an inconsistent scope between the two
- Using the maximum possible ARPU — the best-case price, rather than an average or median
- Setting SOM at 50-100% of SAM — a share that's simply impossible to capture in the short term
- Citing a TAM figure with no real source — vague attributions like 'estimated by a market research firm'
- Assuming TAM grows 30%+ every year — unrealistic relative to industry averages
06
#Source Priority — What Builds the Most Credibility
- Authoritative government and public statistics — Statistics Korea, KOSIS, the Bank of Korea, the Korea Institute for Industry Economics and Trade
- Major research institutions — the Korea Health Industry Development Institute, the National IT Industry Promotion Agency, Korea Venture Investment Corp
- Global research firms — Gartner, IDC, Statista (subscription or publicly available reports)
- Industry association data — sector-specific bodies such as the Korea Electronics and Telecommunications Industry Association
- Primary data from your own interviews or surveys
TIP
Public statistics carry the most inherent authority, but pairing them with primary data you've measured yourself creates a stronger case than any external source alone.
Summary.
#Self-Check: A Founder's Checklist
- Are TAM, SAM, and SOM all broken out separately? (Not a single market-size figure.)
- Is the formula shown for each layer? (Not just a bare number.)
- Are the units consistent across TAM, SAM, and SOM — annual revenue, annual transaction value, user count?
- Does SOM fall within 1-10% of SAM?
- Do your ARPU, conversion rate, and market share assumptions sit within industry-average ranges?
- Have you presented both the top-down and bottom-up approaches together?
- Is at least one authoritative source cited (a government statistics agency, a promotion institute, an industry association)?
CTA
OpenSeed's Market agent automatically checks the internal consistency of your TAM/SAM/SOM formulas, the credibility of your sources, and all five common inflation patterns. under the current payment terms shown on the analysis start screen.
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