Clarify scope & definition
- Product: predictive lead-scoring SaaS that scores inbound leads for B2B SaaS sellers (annual subscription).
- TAM = revenue if every potential buyer purchased at target price. I’ll show both top-down and bottom-up, with key data sources and assumptions.
Top‑down approach (fast, high-level)
- Start with global SaaS vendor count: e.g., 100k B2B SaaS companies (sources: Crunchbase, Datanyze, Gartner).
- Segment by company size and likelihood to buy:
- Enterprise (≥1000 employees): 5% → 5k
- Mid-market (100–999): 20% → 20k
- SMB (<100): 75% → 75k
- Assume addressable proportion that have inbound lead flows and purchase marketing/sales tech: 40% overall → 40k potential buyers.
- Average annual contract value (ACV) for product: $12k/year (tiered pricing).
TAM_top = 40k * $12k = $480M.
Bottom‑up approach (more precise)
- Start with observed metrics: number of target accounts in sample region (e.g., US = 30k B2B SaaS).
- Estimate penetration by vertical and size using firmographic filters (API/CRM vendor data).
- Estimate conversion to buyer: probability they buy within 3 years based on budget & tech stack compatibility: enterprise 30%, mid 10%, SMB 2%.
- Multiply expected buyers * ACV.
Example (US sample): Enterprise 1.5k30% + Mid 6k10% + SMB 22.5k*2% ≈ 1.5k buyers → 1.5k * $12k = $18M US. Extrapolate globally (~×25) → ~$450M TAM (aligns with top-down).
Data sources to use
- Market/firmographics: Crunchbase, LinkedIn, Datanyze, BuiltWith
- Industry reports: Gartner, Forrester, IDC for SaaS market sizing
- Public company filings for budgets per ARR and Martech spend
- Customer interviews, pilot conversion rates, internal CRM data for conversion/ACV validation
Key assumptions and sensitivities
- ACV ($12k) drives TAM linearly — test $6k–$24k scenarios
- Addressable proportion (40%) & conversion rates are largest levers — present sensitivity table
- Adoption-lag and churn reduce serviceable obtainable market (SOM) vs TAM
Recommendation
- Triangulate top-down and bottom-up and validate with pilot conversion data.
- Produce sensitivity analysis (best/worst case) and compute SOM (year 1–3 revenue) for go-to-market planning.
