A Founder’s Guide to SaaS Revenue Forecasting - Deepstash
A Founder’s Guide to SaaS Revenue Forecasting

A Founder’s Guide to SaaS Revenue Forecasting

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A Founder’s Guide to SaaS Revenue Forecasting

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SaaS Revenue Forecasting

Any potential lender or investor will want to see a reliable revenue projection to gauge how likely you are to pay their money back (ideally at a large multiple). 

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To build a good forecast, you first need to define where the company is going and how you plan to get there.

Forecasting helps you and the rest of the team constantly answer the question: is what we're doing taking us where we want to go?

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Building a Revenue Forecast in Google Sheets

Before implementing automated tools, it's generally helpful to begin revenue forecasting with a simple, accurate spreadsheet model. Just make a copy of this template and follow along.

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Basic Forecasting Options

The most straightforward forecasting tools rely on the recent past to predict the future. The "straight-line" method uses historical revenue and growth trends to map high-level revenue expectations. 

Start with your last six months of data and map out the next six months based on your current trajectory. For example, if you had $50k in monthly recurring revenue six months ago and today you have $60k, a straight-line forecast would show that in 6 months, you'll hit $70k in MRR.

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  1. Your funnel model
  2. From funnel to "new customer"
  3. Revenue forecasting models
  4. Converting customers to MRR

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1. Your funnel model

Start by mapping out your marketing funnel data and customer signup information. Understanding each funnel step and conversion rate helps you see the complete process behind your revenue generation.

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2. From funnel to "new customer"

After mapping out your historical funnel data, analyze the formulas and how your conversion factors have moved over the past few months. Then, make your best guess what ratios are reasonable going forward.

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3. Revenue forecasting models

Get the number of new customers your marketing funnel will generate each month. Revenue from these customers flows into your new MRR, where we’ll pick up the second part of your revenue forecast.

Aside from attracting new customers, there are a few significant factors impacting MRR:

  • Expansion and contraction (subscription upgrades or downgrades)
  • Churn and reactivation: Customers canceling subscriptions or reactivating a previously canceled subscription.

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4. Converting customers to MRR

We’ve effectively established the total number of customers we expect each month from the marketing funnel to our expectations for expansion, churn, and contraction. Using these figures and the average revenue per customer (ARPC) for each category, we can make a solid prognosis for MRR.

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Once you’ve established your revenue forecasting formulas and the data relationships necessary to build your forecast, it’s simply a matter of refreshing the data and assumptions each month. 

You’ll be able to copy your traffic and conversions data directly from your marketing funnel software. Then input your revenue and churn information. If your assumptions were way off, go ahead and reassess for the next forecast.

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The Bottom Line

Revenue forecasting is essential, especially for SaaS businesses. Don’t wait until you’ve got an entire finance team ready or investors to satisfy to implement the most advanced cloud forecasting solutions. Getting started with a Google Sheets tool is massively better than not forecasting at all.

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CURATED BY

kerem

ぬ-shaped person: Passionate learner having diverse interests. Tech entrepreneur. Obsessive optimizer. Uncomfortably skeptic and curious. Suffering from tsundoku.

CURATOR'S NOTE

Many founders treat revenue forecasting as a luxury, until suddenly, revenue forecasting becomes a necessity. This guide to SaaS revenue forecasting will walk you through building a revenue forecast.