Financial model for investors: what they actually read in your Excel

The five things investors look at in the first three minutes — and how to make sure your model passes that filter.

Most founders prepare a financial model like this: open Excel, build a table of revenues and expenses, add a three-year forecast, attach it to the email to the investor. And sincerely believe they did everything right.

The investor opens the file. Two minutes later, closes it. "We'll get back to you" — the standard reply that most often means "no".

It's not about the numbers. It's that most models don't answer the questions an investor asks themselves in the first minutes of review. This article is about those questions — and how to build a model that answers them.

Why investors close Excel in two minutes

An experienced investor reviews dozens of models per month. Over the years a reflex develops: certain signals immediately say "this model isn't worth deep analysis".

It doesn't mean the business is bad. It means the model doesn't give enough information for a fast "worth spending more time on this" decision.

Here's what runs through the investor's head in the first three minutes:

1. Does the founder understand their own business model?
2. Are the assumptions realistic?
3. How much money is needed and when does it come back?
4. Where are the risks, and does the team see them?
5. Can these numbers be trusted?

That's it. Five questions. If the model answers them — the conversation continues. If not — "we'll get back to you".

Let's break each one down.

Question 1. Does the founder understand their own business model?

The first signal is the model's structure. How is revenue broken down? What is the growth driver?

Bad model: "Revenue: $1,000,000" — one line.

Good model: revenue is decomposed into components, each tied to a real business process.

SaaS example

Customers at month start: 120
+ New customers (marketing): 18
+ New customers (sales): 12
– Churn (3% rate): –4
= Customers at month end: 146

ARPU: $350
MRR: $51,100

This structure immediately shows the founder understands where customers come from, how the base grows, and what affects revenue. The investor can verify the logic without taking the numbers on faith.

Rule: every revenue line must decompose into quantity × price. If it's services — hours × rate. If subscriptions — customers × ARPU. If sales — deals × average ticket.

Another signal at this level — is there unit economics in the model? Even in a simplified form: CAC, LTV, payback period. Without these numbers the investor can't tell whether the business scales profitably.

Question 2. Are the assumptions realistic?

This is the most important filter. And the most common reason to close a model.

A classic mistake is the "hockey stick": almost nothing in the first two years, then a sharp leap in year three. With no explanation of what changes. With no link between marketing budget and new customers. Just an optimistic forecast.

The investor has seen this hundreds of times. They don't trust the numbers — they look at the logic.

What makes assumptions realistic:

First, they should be explicit. Not buried in formulas, but pulled out into a separate "Key assumptions" block. Revenue growth rate, churn, lead-to-customer conversion, average sales cycle, salary inflation — all visible at a glance.

Second, assumptions should be justified. Best of all — by data: "Our site→demo conversion is 4% over the last 6 months. The model assumes 3.5% with a conservative reduction." If there's no data — reference industry benchmarks.

Third, growth rates should match resources. If you plan ×3 revenue in a year but the marketing budget stays the same — that's not realistic. The investor spots the mismatch immediately.

Practical tip: build three scenarios — base, optimistic, pessimistic. The gap between them shouldn't be fantastical. If optimistic is five times better than pessimistic — it means you don't really understand your business.

Question 3. How much money is needed and when does it come back?

This is a question the investor wants to see solved right inside the model — not learn it from your pitch deck.

Three numbers that must be visible:

1. Investment amount and its breakdown. Not just "we need $500k". But: $200k — product, $180k — marketing & sales, $80k — operating expenses for 12 months until breakeven. This shows you've thought about where the money goes.

2. Runway. How many months you operate on this money until the next round or profitability. Standard expected answer — 18–24 months. Less than 12 is a red flag, because you'll need to start raising the next round just 6 months after closing this one.

3. Breakeven point. When operating cash flow turns positive. In which month and at what customer count. This number should be explicit in the model — not "somewhere in year three", but "month 19, at MRR of $85,000".

For venture capital, additionally: expected exit valuation and the share you're offering now. The investor wants to see if there's potential for a ×5–×10 return. If the market is small or growth is capped — venture money isn't the right fit, and other sources should be considered.

Question 4. Where are the risks, and does the team see them?

One of the most reliable ways to earn an investor's trust is to show that you yourself see the risks in your model.

Founders who only show positive scenarios look either naive or dishonest. Those who openly say "here's our main risk and here's how we mitigate it" look like people you can do business with.

How to show risks in the model:

Sensitivity analysis. Pick two or three key parameters — for example, conversion and average ticket — and show how EBITDA or runway changes when they vary by ±20%. This takes one table but adds real seriousness to the model.

	Conversion −20%	Base	Conversion +20%
Ticket −20%	Runway: 11 mo	Runway: 15 mo	Runway: 18 mo
Base ticket	Runway: 14 mo	Runway: 18 mo	Runway: 22 mo
Ticket +20%	Runway: 16 mo	Runway: 21 mo	Runway: 26 mo

Such a table immediately shows: even in the worst scenario you have 11 months. That's better than a base forecast with hidden risks.

What else is worth flagging explicitly: dependency on one or a few large customers (if any), FX risk, key hires not yet closed, regulatory uncertainty.

You don't need to list everything. Two or three of the most important ones — with how you control them — is enough.

Question 5. Can these numbers be trusted?

The last, but no less important filter — the quality of the model itself. There are several markers that immediately signal "this file shouldn't be trusted".

Hardcoded values. If a cell just contains "1,200,000" with no formula — where does that number come from? A good model is built so most values are the result of formulas, not manual input. Change one assumption — and the entire model recalculates.

No links between sheets. If P&L, Cash Flow and Balance Sheet aren't connected and don't reconcile — that's an error. Net profit from P&L should flow into Cash Flow. Change in receivables on the balance sheet should appear in operating cash flow. Without that linkage, the model is incorrect.

Inconsistent formats and styles. If part of the table is in one format, part in another, with random colored rows — it says the model was thrown together quickly. Not critical, but it spoils the impression.

Numbers without units, or unit confusion. All figures should be in one currency or with an explicit conversion rate. If part is in EUR and part in USD, the conversion logic must be transparent.

How to make the model look reliable

• Color input cells distinctly — for example, light blue. Formulas — white background. This is the financial modeling standard.
• Add an "Assumptions" or "Inputs" sheet — all variables in one place.
• Make sure the balance sheet balances: Assets = Liabilities + Equity.
• Stress-test the model: what happens if revenue is half the forecast?

The structure of an investor-ready financial model

To summarize as a clear structure. Here's the minimum set of sheets most investors expect to see:

1. Dashboard / Summary. One page with key metrics: revenue, EBITDA, net profit, runway, breakeven, investment amount. Everything on one screen, no scrolling. This is where the investor spends the first 60 seconds.
2. Inputs / Assumptions. All key variables in one place. Growth rate, pricing, churn, conversion, FTE plan, FX rates. With justification comments next to them.
3. P&L (Profit & Loss). Monthly or quarterly forecast for 3 years. Revenue, COGS, gross margin, operating expenses, EBITDA, net profit.
4. Cash Flow. Operating, investing and financing cash flow. Bank balance at the end of every month. The moment the money runs out — if it does.
5. Unit economics. CAC, LTV, LTV/CAC, payback period. With monthly or cohort dynamics — if data is available.
6. Scenarios & sensitivity. Base, optimistic, pessimistic. A sensitivity table on two or three key parameters.
7. Use of funds. Detailed breakdown of where the investment goes. Tied to months: when each hire happens, when marketing launches, when major spend is planned.

Three mistakes that send a model straight to the trash

Mistake 1: Starting from the desired result. The most common trap — decide that "we need a million a year" and build the model backwards from that number. The result looks pretty but doesn't survive a single "why exactly?" question. The right approach is bottom-up: how many leads does your current marketing generate, what's the conversion, what's the average ticket.

Mistake 2: Ignoring operating costs at scale. Often the model shows margin improving as revenue grows. But forgets that serving more customers needs more support, more servers, more managers. OpEx isn't fixed — it grows too, just slower than revenue (if all goes well).

Mistake 3: Not accounting for the gap between sale and payment. For B2B this is critical. If your typical customer pays 30–60 days after signing — your Cash Flow looks completely different from your P&L. You can have "profit" on paper and a cash gap in the bank. The investor will definitely check this.

What separates a 10-minute model from a 10-day analysis

Some models the investor closes in two minutes. Some they reopen the next day and ask for a meeting.

The difference isn't in complexity. It's in how much the model itself answers the questions, without forcing the investor to ask them.

If they opened the file and within five minutes understood: where revenue comes from, what assumptions it's built on, when breakeven happens, how much runway the investment buys, and where the main risks are — they'll want to talk.

If they spent five minutes and still don't know where to look for those answers — they won't spend another five.

A ready-made financial model template

Building the right structure from scratch is 20–40 hours of work for someone doing it for the first time. Plus a few iterations to make sure all sheets are linked and the balance reconciles.

To shortcut this, we've prepared a ready investor-grade financial model template in Excel. It includes all seven sheets with the structure described in this article: Dashboard, Assumptions, P&L, Cash Flow, Unit economics, Scenarios and Use of funds. You only need to plug in your numbers.

👉 Get the financial model template →

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Previous in the series — "How to build a P&L that actually helps you make decisions". Next — "Unit economics for SaaS: CAC, LTV and why payback matters more than margin".