| name | financial-model |
| description | Builds financial models for startups with revenue drivers, cost assumptions, and sensitivity analysis. Use when creating detailed financial models for fundraising or planning. |
| allowed-tools | Read Write Glob |
| metadata | {"author":"matthewhitcham","version":"1.0"} |
Financial Model
When to Use This Skill
Use this skill when you need to:
- Build a bottoms-up financial model for a startup or small business
- Create investor-ready financial projections with detailed assumptions
- Model revenue drivers, unit economics, and cash flow
- Run sensitivity analysis on key business assumptions
DO NOT use this skill for simple budgets (use budget-planner) or basic revenue forecasts (use revenue-forecast). This is for comprehensive financial models with multiple interconnected assumptions.
Core Principle
A FINANCIAL MODEL IS ONLY AS GOOD AS ITS ASSUMPTIONS — EVERY NUMBER MUST TRACE BACK TO A STATED ASSUMPTION THAT CAN BE CHALLENGED, TESTED, AND UPDATED.
Phase 1: Model Inputs
Required Inputs
| Input | What to Ask | Default |
|---|
| Business model | "How do you make money? (SaaS, e-commerce, services, marketplace)" | No default — must be provided |
| Revenue streams | "What are your revenue sources and pricing?" | No default — must be provided |
| Current metrics | "Current MRR, users, conversion rates, churn?" | Pre-revenue if not provided |
| Cost structure | "Fixed costs, variable costs, planned hires?" | Will build from scratch |
| Model timeframe | "12, 24, or 36 months?" | 24 months |
| Model purpose | "Who is this for? (internal planning, seed raise, Series A)" | Internal planning |
GATE: Do not proceed without business model and revenue stream details.
Phase 2: Assumptions Sheet
Every model starts with a documented assumptions sheet.
## Key Assumptions
### Revenue Assumptions
| Assumption | Value | Source/Rationale |
|-----------|-------|-----------------|
| Starting MRR | $[X] | Current |
| Monthly user growth rate | [X]% | [Based on: historical, benchmark, or target] |
| Conversion rate (trial to paid) | [X]% | [Source] |
| Average revenue per user (ARPU) | $[X] | [Current pricing] |
| Monthly churn rate | [X]% | [Historical or industry benchmark] |
| Expansion revenue rate | [X]% | [Upsell/cross-sell estimate] |
### Cost Assumptions
| Assumption | Value | Source/Rationale |
|-----------|-------|-----------------|
| Customer acquisition cost (CAC) | $[X] | [Current or estimated] |
| Gross margin | [X]% | [Based on COGS breakdown] |
| Monthly fixed costs (current) | $[X] | [Actual] |
| Planned hires | [X] people by month [X] | [Hiring plan] |
| Average fully-loaded salary | $[X]/month | [Market rate] |
| Marketing spend (% of revenue) | [X]% | [Target] |
GATE: Present assumptions to the user for validation before building the model.
Phase 3: Model Build
Revenue Model (Bottoms-Up)
## Revenue Model
### Monthly Cohort Model
| Month | New Users | Churned | Active Users | MRR | Expansion | Total MRR |
|-------|----------|---------|-------------|-----|-----------|-----------|
| M1 | [X] | [X] | [X] | $[X] | $[X] | $[X] |
| M2 | [X] | [X] | [X] | $[X] | $[X] | $[X] |
| ... | | | | | | |
| M24 | [X] | [X] | [X] | $[X] | $[X] | $[X] |
### Annual Revenue Summary
| | Year 1 | Year 2 |
|--|--------|--------|
| ARR (ending) | $[X] | $[X] |
| Total Revenue | $[X] | $[X] |
| YoY Growth | — | [X]% |
Expense Model
## Expense Model
### Monthly Expense Breakdown
| Category | M1 | M6 | M12 | M18 | M24 |
|----------|----|----|-----|-----|-----|
| COGS | $[X] | $[X] | $[X] | $[X] | $[X] |
| Personnel | $[X] | $[X] | $[X] | $[X] | $[X] |
| Marketing | $[X] | $[X] | $[X] | $[X] | $[X] |
| G&A | $[X] | $[X] | $[X] | $[X] | $[X] |
| **Total Opex** | **$[X]** | **$[X]** | **$[X]** | **$[X]** | **$[X]** |
### Headcount Plan
| Role | Start Month | Monthly Cost | Purpose |
|------|------------|-------------|---------|
| [Role] | M[X] | $[X] | [Why needed] |
Cash Flow and Runway
## Cash Flow
| | M1 | M6 | M12 | M18 | M24 |
|--|----|----|-----|-----|-----|
| Revenue | $[X] | $[X] | $[X] | $[X] | $[X] |
| Expenses | $[X] | $[X] | $[X] | $[X] | $[X] |
| Net Cash Flow | $[X] | $[X] | $[X] | $[X] | $[X] |
| Cash Balance | $[X] | $[X] | $[X] | $[X] | $[X] |
| Runway (months) | [X] | [X] | [X] | [X] | [X] |
**Break-even month:** M[X]
**Cash needed to reach break-even:** $[X]
Phase 4: Sensitivity Analysis
Key Variable Sensitivity
## Sensitivity Analysis
### Impact of Growth Rate Changes on M24 ARR
| Growth Rate | M24 ARR | M24 Runway |
|------------|---------|-----------|
| [Base - 3%] | $[X] | [X] months |
| [Base rate] | $[X] | [X] months |
| [Base + 3%] | $[X] | [X] months |
### Impact of Churn Rate on M24 ARR
| Churn Rate | M24 ARR | LTV |
|-----------|---------|-----|
| [Base - 1%] | $[X] | $[X] |
| [Base rate] | $[X] | $[X] |
| [Base + 1%] | $[X] | $[X] |
### Unit Economics Summary
| Metric | Value |
|--------|-------|
| CAC | $[X] |
| LTV | $[X] |
| LTV:CAC | [X]:1 |
| Payback period | [X] months |
| Gross margin | [X]% |
Example: SaaS Startup Seed Stage
Inputs: $5K MRR, $29/mo ARPU, 8% monthly user growth, 3.5% monthly churn, $120 CAC, $8K/mo fixed costs.
M12 projection: $14.2K MRR, 490 active users, $10.5K monthly expenses, break-even at month 9.
M24 projection: $38.6K MRR, 1,330 active users, $18K monthly expenses (added 2 hires), $12K net monthly cash flow.
Sensitivity: If churn increases to 5%, M24 ARR drops 32%. If growth decreases to 5%, M24 ARR drops 41%. Growth rate is the most sensitive variable.
Anti-Patterns
- Top-down models — "we will capture 1% of a $10B market" is not a financial model. Build bottoms-up from unit economics.
- Static assumptions — costs and growth rates change over time. Model step changes in hiring, pricing, and growth.
- No assumptions documentation — every number must have a rationale. Undocumented assumptions cannot be validated.
- Ignoring churn — for subscription businesses, churn is the most important variable. A 1% difference in monthly churn dramatically changes 24-month outcomes.
- Perfect hockey sticks — real growth is lumpy. Include realistic ramp-up periods for new channels and hires.
Recovery
- Pre-revenue business: Model from first customer acquisition. State assumptions clearly and emphasize the sensitivity analysis — investors know the numbers are uncertain.
- No historical data for assumptions: Use industry benchmarks and clearly label them. Update the model monthly as real data replaces assumptions.
- Model too complex: If the user is overwhelmed, simplify to revenue, expenses, and cash flow. Add complexity as they get comfortable.
- Numbers do not work: Show which assumptions need to change for the model to work — higher ARPU, lower churn, faster growth, or lower costs. Let the user decide which lever to pull.
