To calculate revenue, multiply the price of your product or service by the number of units sold — Revenue = Price × Quantity. A company selling 500 units at $249 earns $124,500 in total revenue. Service and SaaS businesses use customers × average price (ARPU), while net revenue subtracts discounts, returns, and allowances from that figure.
What is the revenue formula?
The basic revenue formula is Revenue = Price × Quantity Sold. For a business with several products, calculate revenue for each line separately, then add them up for total revenue. Two refinements matter: net revenue subtracts discounts, returns, and allowances from that total, and recurring businesses calculate revenue as customers × average revenue per user (ARPU), then annualize it. The table below shows the right formula for each common revenue type.
Revenue formulas by type — and when to use each
The formula itself is simple. The hard part — and what investors actually scrutinize — is forecasting revenue so it looks realistic. Revenue is the heart of every business and the foundation for its growth, and forecasting it is the core goal of every financial model: these models showcase your strategy and the revenue streams fueling the business, and they shape your team's growth and expenses. Building credible projections trips up most startups, and revenue forecasts raise a lot of questions from investors. The rest of this guide covers how to do it right.
Secret 1: Calculate your customers correctly
Revenue doesn't come from just anywhere — it's generated from your customers or users. So before calculating the money your business will make, you need to accurately calculate the number of customers or users. The approach hinges on the business model as well as the user/client type and size, and it's important to consider all of these factors together. Let's look at four different types of companies to understand what to consider in each case.
Here's a worked example for a marketplace, in three steps: (1) Volume — 5,000 monthly active buyers × 2 orders/month = 10,000 transactions. (2) GMV — 10,000 transactions × $200 average order value = $2,000,000 GMV/month. (3) Revenue — $2,000,000 × 8% take rate = $160,000/month, or about $1.92M annualized. You can read more about cohort analysis in our guide to retention cohorts.
We analyzed the financial models submitted for our review and summarized the most common mistakes we see in revenue sheets:
- It's impossible to track what drives revenue growth. It's hard to justify a monthly growth rate you added yourself, but easy to defend projections when you can explain the logic — for example, showing how your gross transaction volume and commission rate generate the revenue you included.
- The annual revenue growth rate accelerates over time. As a rule, this rate should decelerate over time, unless there are additional factors boosting growth, such as adding new revenue streams.
- The same assumptions are applied to every year. This looks unrealistic. The model shouldn't be static — it has to be dynamic and consider growth rates, inflation, the economy of scale, and more.
- Unrealistic growth rates. Do some benchmarking so you can see the revenue growth rates of businesses at the same stage with a similar solution.
- Assumptions not backed by benchmarks or data. Not every number can be checked, but always benchmark wherever it's possible.
Secret 2: Explain the logic of each revenue stream
The goal of revenue projections isn't only to calculate how much your business will generate over the next three-to-five years — it's to show that you understand the mechanisms of your revenue streams. Investors want to see whether your logic holds up and whether you understand the peculiarities of your revenue. To do that, determine the metrics relevant to your business model and use them in your forecast.
For example, if your client is a marketplace, your projections should use indicators like monthly active users, average transaction value, and gross merchandise volume (GMV). That reflects the logic of your revenue streams and shows you know which metrics matter for this type of business. Showing investors that you understand how your revenue engine works makes them more confident you can manage it — so don't underestimate this part of the model.
Secret 3: Don't forget about historical data (if any)
Fundraising doesn't always involve idea-stage startups; more mature companies raise too. In that case, make sure the forecast is based on historical data and implies a realistic revenue trajectory. Why does this matter? First, it shows the investor you didn't make up the numbers but followed existing trends. Second, it shows you understand how your business scales over the coming years and how that affects cash flow. Two key factors: inputs should be calculated from historical data whenever possible, and the first forecast months should sit close to the preceding historical months.
Secret 4: Make sure the numbers look realistic
Everyone knows a forecast can be arbitrary and that you can't know exactly whether your business will follow the predefined path — especially early-stage. But you must ensure your forecast makes sense and looks realistic. Two steps achieve this. First, do thorough benchmarking for your assumptions; you can never predict the next investor question, so be prepared. Second, analyze the values you actually get in the model — if you only have an idea and your forecast shows $50M revenue in two years, it's almost certainly too optimistic. That's where metrics come in.
Secret 5: Use metrics for a deeper analysis
Numbers carry a lot of information once you understand their language. Metrics show how your business economics change over time and whether your model is realistic. Let's look at the most common ones that help you avoid strange numbers — revenue growth rate, ARPA/ARPU, and LTV.
Revenue growth rate
This metric is a core indicator of how quickly your startup is growing. Benchmarks depend on the company's stage and industry, so use them when building a forecast. Remember that this rate tends to decrease gradually over time — though in some cases it can jump if the company has prerequisites to do so (favorable market conditions, new market entry, or a new revenue stream).
ARPA / ARPU
ARPA and ARPU mean average revenue per account and average revenue per user; which you use depends on the business's client type. This metric is key to understanding whether the company is increasing monetization of its user base over time, and it feeds directly into customer lifetime value. Track it alongside net revenue retention to see whether existing customers are expanding.
LTV
Customer lifetime value measures the total revenue a business can generate from one customer before they churn. It's usually compared against customer acquisition cost. Metrics matter, but they tell you nothing without proper benchmarking — always find benchmarks relevant to businesses in the same industry and of the same size, then compare them to your KPIs. Comparing your final values to industry averages makes your model far more compelling, and investors appreciate it.
Summary
Revenue plays a central role in your business and in its financial forecast — especially when fundraising. Make sure your projections look logical, understandable, realistic, and attractive to investors, and remember the formula underneath it all is simple (Price × Quantity); the credibility comes from the assumptions you build on top. This part of the model also helps you estimate your revenue trajectory, your potential to scale, and important business decisions. At Waveup, we've helped 600+ clients raise $3B+ with high-quality fundraising materials and 800+ financial models — our finance team is always ready to build a solid model for startups and mature companies alike.