First 3 Steps in a SaaS Financial Forecast

Wrapping up Q3 last week, a colleague said, “don’t worry, Q4 is always our strongest quarter!”

How many times have we heard that before? So I took a look at the historical data, and sure enough, Q4 is “typically” their strongest quarter. Not always though.

A lot had changed since the original forecast was built. Time for a model refresh. But where should they start?

Here are my 3 primary worksheets for topline revenue. I like to start here because these always generate the most board discussions throughout early and mid Q4.

First
Marketing lead funnel worksheet including spend assumptions and conversion metrics throughout the funnel. It might seem odd to start a revenue forecast with a set of expense assumptions. Some folks start with sales headcount to build the model, but my preference is to start with leads and then test it against headcount and quota attainment metrics. This choice in direction is driven by sales function of inbound versus outbound. A more outbound driven strategy might start with headcount, where a more inbound strategy would start with a marketing funnel.

Second
New customer sales assumptions worksheet. This is built off the marketing funnel and lays the groundwork for the quota attainment ratios later in the model. The sales assumptions include average selling price (ASP), annual recurring revenue (ARR), total contract value (TCV), close rate, and sales cycle. A B2B SaaS enterprise company could also have assumptions for professional services as either a flat fee or a percent of ARR depending on the product. Services assumptions include time to complete since it has potential revenue implications based on the revenue recognition practices of the specific company.

Third
Existing customer revenue worksheet with assumptions about retention rates and expansion. This includes the metric assumptions for logo retention, gross dollar retention, and net dollar retention. In most cases, these metrics are applied on a cohort basis such as plan type to improve accuracy of the model.

With these 3 primary worksheets, a solid revenue forecast can be built. It can also set the actual versus forecast assumptions for these 10 metrics:

1) year over year topline growth
2) average selling price (ASP)
3) annual contract value (ACV)
4) average revenue per account (ARPA)
5) close rate
6) sales cycle
7) marketing qualified lead (MQL) and sales qualified lead (SQL) conversion ratios
8) logo retention rates (LRR)
9) gross dollar retention (GDR)
10) net dollar retention (NDR)

Customer Lifetime Value (CLTV) includes gross margin, so it requires COGS worksheets to be complete. Customer Acquisition Cost (CAC) includes compensation, so it requires expense worksheets also.

Of course, it takes the rest of the income statement, the balance sheet, and the cash flows to get the marketing spend iteration and analysis complete.

There you have it! A place to start the financial forecasting season.

Photo credit to Jukan Tateisi