A financial model is a spreadsheet that projects your company’s future financial performance. Done well, it helps you plan, make hiring decisions, decide when to raise, and communicate with investors.
Done poorly, it’s fiction that helps no one.
Planning and Decision Making
A model forces you to think through:
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How much runway do we have?
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Can we afford this initiative?
Without a model, these decisions are guesswork.
Investors expect a financial model. It shows you understand your business economics and have a plan.
Comparing actual results to the model reveals whether you’re on track. Variances prompt questions and adjustments.
A SaaS financial model typically has these sections:
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Number of customers (by segment if relevant)
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Average revenue per customer (ARPU)
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Growth rates (new customers, churn, expansion)
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Start with current customers
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Add projected new customers each month
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Calculate revenue from the customer base
Cost of Goods Sold (COGS)
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Third-party software costs that scale with usage
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Customer support costs (sometimes)
COGS should be tied to revenue or customer count.
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Sales & Marketing (salaries, ads, tools)
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Research & Development (engineering salaries, tools)
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General & Administrative (office, legal, accounting)
For each category, model:
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What roles will you hire?
This drives most of your expenses.
Ending cash = Beginning cash + Cash in - Cash out
Track monthly. Know your runway.
If you have history, start there:
History grounds your projections in reality.
Document your assumptions explicitly:
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Customer growth rate: X% monthly
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Payroll cost per engineer: $B/month
Keep assumptions in a separate tab so they’re easy to find and change.
Step 3: Revenue Projections
New Customers (Month N) = Customers (N-1) × Growth Rate
Churned Customers = Customers (N-1) × Churn Rate
Ending Customers = Beginning + New - Churned
Revenue = Customers × ARPU
Model separately for different segments if economics differ.
Step 4: Expense Projections
Headcount (Role) = # of people in that role
Total Salary = Headcount × Avg Salary
Fully Loaded Cost = Salary × 1.25-1.35 (for benefits, taxes)
Marketing Spend = Revenue × Marketing % (or fixed + variable)
Infrastructure = Customers × Cost per Customer (or tiered)
Step 5: Calculate Key Metrics
Step 6: Scenario Analysis
Build at least two scenarios:
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Base case: Realistic assumptions
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Downside case: Lower growth, higher churn
Some add an upside case. Don’t build something you’d be embarrassed to share with investors.
For the first 18-24 months, model monthly. Beyond that, quarterly is fine.
Don’t model every detail. Focus on the drivers that matter most. A simpler model that you actually update is better than a complex one that becomes stale.
Tie Headcount to Milestones
Don’t hire randomly. Hire when you hit milestones:
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“Hire engineer #3 when we hit 100 customers”
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“Hire first salesperson when we have repeatable inbound”
Underestimate revenue, overestimate costs. You’ll be wrong, and it’s better to be wrong in a way that leaves you with cash.
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Adjust forward projections
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Revise assumptions as you learn
A model that’s never updated is useless.
You’ll want to look back at how projections evolved.
Hockey stick without justification: Growth rates of 20% monthly forever. Be realistic about what drives growth and when it slows.
Forgetting cash timing: Revenue recognized isn’t cash received. Annual contracts paid upfront vs. monthly affect cash flow.
Underestimating hiring costs: Fully loaded cost is 25-35% above salary. Recruiting fees add up.
No scenario analysis: Single-point forecasts are always wrong. Show you’ve thought about risks.
Too much precision: Projecting revenue to the dollar 36 months out is false precision. Round to thousands.
Set it and forget it: Models must be living documents.
When reviewing your model, investors check:
Reasonableness: Do growth rates make sense? Are expenses realistic?
Unit economics: Does CAC/LTV work? Does it improve over time?
Efficiency: How are you spending money? Is the burn justified?
Path to milestones: Does the model show a clear path to next funding or profitability?
Understanding: Can you explain every assumption?
Google Sheets/Excel: Standard approach. Flexible, universal.
Causal: Modern alternative with built-in assumptions and scenarios.
Cube, Mosaic: More sophisticated FP&A tools for later stages.
For early stage, Google Sheets is fine.
At minimum, your model should answer:
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How much revenue will we generate?
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How much cash do we have?
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How does that change if things go wrong?
If your model answers these questions, it’s serving its purpose.
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Build a model even if numbers are uncertain—the process creates clarity
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Structure: Revenue, COGS, Operating Expenses, Cash Flow
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Document assumptions explicitly and keep them in one place
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Build bottom-up from drivers (customers × ARPU)
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Include multiple scenarios (base case, downside)
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Update monthly by comparing actual to projected
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Keep it simple—focus on what matters most
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Be conservative—wrong in the safe direction