Financial models 101: what to know as a startup

Ask most early-stage founders about their financial plan, and you will likely hear a very familiar story: "We expect to capture 1% of the market in three years." It sounds reasonable on paper, but 1% of almost any market is huge. More importantly, everyone says it, and it isn't actually a plan: it's pure wishful thinking.

As Christophe Cieters, Investment Manager at Start it Fund, puts it: "If you don't know where you are sailing, every wind is against you." To build a startup that lasts, you need a financial model grounded in operational reality rather than a dream disconnected from how sales actually work.

The difference between a plan and a model

The fundamental issue with most startup financial plans is that they are static. Founders start at the very end of their story (a big revenue target like €3 million in two years) and try to invent a narrative around it. They fill spreadsheets with hard figures that sit in a vacuum.

A true financial model works completely differently. Instead of starting top-down with a dream revenue number, a model works bottom-up from a few core “drivers”. Everything else in the spreadsheet should flow naturally from these core drivers using formulas. If it doesn’t, you are bound to run into unrealistic conclusions. 

For example: to hit your revenue target, you might discover you need to close 10 customers a month. But to close those 10 customers, you might need to speak to 100 leads, which in turn may be physically impossible when usually only 1 founder is doing sales while still juggling various other responsibilities at the start. When investors or banks start asking questions, this lack of causality and consistency makes the whole plan fall apart very quickly.

A simple 3-step blueprint for your financial model

Building a reliable financial model doesn't require complex rocket science. Christophe outlines a straight-forward three-step approach to get your financials right:

Step 1: Define your core business assumptions.

Start by thinking deeply about how your business actually operates. What are your customers struggling with? Are you selling B2B or B2C? Are you dealing with high-volume, low-margin products or selling specialized components to a handful of enterprise clients?

Timing and customer retention matter just as much. A quick example: if you sell champagne, 80% of your revenue might depend on the final quarter of the year. If you’re a business selling toilet paper, demand is steady month after month. Understanding these nuances tells you exactly how much cash you need, when you need it, and how long your runway will last.

Step 2: Quantify your drivers, bottom-up.

Instead of guessing your total revenue, look at the key elements that make your business tick. Connect your metrics directly to human effort and time.

For example, if closing 1 B2B customer requires 2 demos, and 2 demos require 15 cold calls, then 1 customer equals 15 cold calls + 2 demos worth of time investment. Since your team only has a limited number of working hours per week, there is a physical cap on how many new customers can be acquired with the resources you have at hand.

Focusing on Early-Stage KPIs

Most startups set their KPIs on things like demo’s or end-result revenue, which they cannot directly control. Instead, set your KPIs at the start of the sales pipeline: metrics you can actually steer, such as the hours spent on outbound sales or the frequency of your content creation.

By modeling revenue organically (combining customer retention, churn, and acquisition through channels like outbound prospecting or social ads) you can go to investors with a clear message: "We need money to hire 2 sales reps and increase our social ad budget by amount A, which based on our tested conversion rates will yield B amount of customers in C amount of time." That is a completely different conversation than claiming you will grab 1% of the market through the magic of wishful thinking.

Step 3: Visualize your numbers to catch errors.

When numbers live exclusively inside a massive Excel sheet, it's almost impossible to spot logical mistakes. Turning your rows into simple line charts makes inconsistencies pop out immediately.

• Headcount vs. Revenue Alignment: If you run a tree-pruning service, your revenue and headcount should move up together in parallel. If you run a software company, revenue should eventually grow faster than your staff count because software is infinitely scalable. If your graphs show the opposite, you know instantly that something in your model is wrong.
• Batch Expenses: E-commerce startups often forget that inventory is bought in discrete batches (e.g., 10,000 units), causing sudden cash drops rather than smooth monthly expenses.
• Finding the Right Focus: A common mistake founders make is spending hours detailing broad impressionistic brushstrokes, like a €10 line item for postage stamps, while leaving a €30,000 marketing budget un-itemized in a single lumped row. Charts help you quickly see where the real money is going.

Adjusting on the go

Because early-stage startups are volatile, your financial model should evolve as you learn. Maybe you assumed 20% of your leads would convert, but in practice, it turns out to be 15%, or perhaps 25%.

With a dynamic driver-based model, you can quickly test different strategy scenarios:

• Scenario A (High Growth & Investment): You keep your pricing lower to maximize customer volume, double down on ad spend, and accept a temporary negative cash balance (a cash burn). This shows you exactly when and why you need investor funding to bridge the gap.
• Scenario B (Bootstrapped & Sustainable): You raise your prices slightly. You might acquire fewer total customers, but higher margins and lower acquisition costs keep your cash flow positive, allowing you to grow without taking on outside capital.

How Start it @KBC Helps Founders

When founders bring an early financial plan to Start it @KBC, coaches are there to challenge them in a safe environment. Asking simple pushback questions, like "Why 5 new clients a month instead of 2 or 10?", helps expose weak assumptions before an investor or bank does.

By focusing on bottom-up drivers, internal logic, and clear visual scenarios, founders learn to stop dreaming up figures in a vacuum and start building dynamic models that help their business thrive.

Applications for our Fall 2026 Cohort are open now! Apply here.