Is your Revenue Model accurate?

Contribution by Friend of AceTech  of SurePath Capital Partners

We specialize in 3 sectors at SurePath: SaaS, E-Commerce and Marketplaces. The commonality across these segments is that they are all data-driven. Companies in these segments have lots of knobs and levers that they can twist and turn to optimize and grow.

In this post, I’d like to show you the first of three simple tests to ensure that your SaaS Pro Forma Model is solid. I’ll do the same thing for E-com and Marketplace businesses in future posts.

Test #1: Your Historical Funnel

It’s pretty easy to forecast expenses. The magic is forecasting revenue. If your SaaS business targets SMB, then you likely generate new revenue through a large marketing/ freemium funnel. If you run an enterprise SaaS business then you probably grow new revenue through an inside sales machine.

In either case you have some conversion funnel for how you acquire new revenue. And of course, you have a retention assumption (1/ churn rate) for how much of your existing revenue you keep.

The easiest way to test your revenue model is to run historical data through it and see how closely it aligns with the actual revenues that you generated in those months.


i. New Revenue:

Take your last 12 months of funnel data and plug it into your model.

Many businesses have some seasonality (i.e. August and December are typically low months), so make sure that you line up January from last year with January this year in your model, and so on.

Update your assumptions (key drivers in a model should always be on a separate and easy to update assumptions tab) to show the conversion rates that you experienced last year.

Running last year’s traffic with the related conversion rates, ARPU and other key assumptions should replicate the new revenue you added last year.

ii. Retained Revenue

Plug in your opening customer count from last year in the model. Update your churn and ARPU, upsell and other key assumptions for last year’s. This should spit out the revenue you retained.

Add i. and ii. together and compare with your actual results.

If this works, then you know that you have an accurate revenue model. Keep this analysis handy. Your current board and future investors (especially them) will be able to use this analysis to confirm that your model is a good one.

Now that you have a good working revenue model, you can plug in this year’s data and forecast revenue with as much accuracy as possible.

Share :


Peerscale is the preeminent leadership organization for Toronto technology CEOs, COOs and executives.

Copyright © 2023 Peerscale. All Rights Reserved.