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5 revenue forecasting methods every finance leader needs to know
Revenue forecasting is really more of an art than a science. And while it can sometimes feel like a bit of a guessing game, with the right revenue forecasting method, you can create a much more reliable forecast that you’ll feel confident using in your strategic decision-making.
This cheat sheet will give you five different methods for revenue forecasting, who they’re best suited for along with their benefits and assumptions, so you can choose the best one for your business. Each method is built on a foundation of data to give you a solid starting point for creating a more reliable forecast now.
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Key drivers and assumptions that impact revenue forecasting models
Many companies use highly-customized approaches to their revenue forecasting based on the different drivers, principles and assumptions relevant to their unique business. However, they almost always start with one of five basic models:
1. Total addressable market (TAM)
2. Sales rep or quota-based model
3. Funnel- or pipeline-based model
4. ARR snowball (aka waterfall) model
5. PxQ (price times quantity) model
All five of these approaches are data-driven. While revenue forecasting has yet to become a science, using a data-backed approach will always result in a more reliable forecast.
Download this cheat sheet to improve your revenue forecasting
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