Forecasting Revenue in a Financial Model - Overview

Building the revenue schedule in an operating model is easily one of the most exciting (and critical) parts.

There are several ways to forecast revenue, and the right approach depends on the business and level of detail required.  Here’s a quick breakdown of the key methods:

✅ Bottoms-up: Start with the fundamental building blocks of the business and build up from there

• Product-based forecasting: Break revenue down by individual products or services and apply the formula: Revenue = Price x Quantity

  • Use separate growth rates for price and quantity based on historical data and expected market trends

• Subscription-based business: Forecast revenue by estimating new customer acquisition and churn rates to derive ending monthly subscribers, and apply average revenue per user (ARPU)

  • Break it down by cohort to analyze customers that share a common characteristic, like those who signed up during a specific promotion or belong to a certain demographic.

• Retail-based business: Start with the number of stores, estimate the average store size, and apply revenue per square foot

• Regression analysis (bottoms-up): Identify relationships between internal factors like marketing spend, pricing, or customer acquisition to forecast revenue based on specific business drivers

✅ Top-down: Begin with the total addressable market (TAM) and use competitor analysis or market share assumptions.  This method is useful for high-level strategic planning, especially for new companies or products, or when detailed bottoms-up data is limited

• In the film industry, use this method to forecast ultimates (lifetime P&Ls) for new releases by estimating total box office potential and applying comparables (comps) analysis across all distribution windows, including ancillary revenue streams such as streaming, TV licensing, and home entertainment

• Regression analysis (top-down): Use market-level data to find relationships between revenue and external factors like industry trends, economic trends, or competitor performance to project overall revenue

✅ Year-over-year growth: Apply a growth rate based on historical performance, leadership expectations, and macro trends

• This is the go-to method for high-level annual models and quick forecasting

• For example, if a company has grown revenue at 8% annually over the past five years and leadership expects steady growth, you can apply a similar growth rate—adjusting for external factors like industry shifts, inflation, or market saturation

Each method has its place, and the one you choose ultimately depends on whether you're building a detailed operating model or only a high level forecast.