Best Practices For SaaS Revenue Forecasting - Baremetrics

Key takeaways:

• SaaS revenue forecasting helps startups predict their future revenue so they can make more strategic decisions 
• There are multiple different types of revenue forecasting models that can each provide insight into how factors like your current pipeline or season trends may impact your annual recurring revenue 
• While forecasting is complex, incorporating best practices like creating multiple scenarios, considering global trends, and leveraging advanced forecasting software like Recover can improve your model accuracy 

During the early stages of building a SaaS startup, high-level sales projections might be enough to drive the direction of your company. But as a SaaS business grows, it becomes more and more critical to forecast future revenue accurately. 

At some point, most businesses need additional capital to fuel growth. And the reality is that any potential investor or lender will want to see a reliable revenue projection to understand when (or even if) they’ll get a return on their money.

Besides raising capital, financial forecasting models are crucial for making important business decisions as the company grows. For example, you can estimate when you’ll need to hire additional employees or how much you can afford to spend on marketing.

Read on to discover some best practices you can use to forecast revenue for your SaaS business.

Define Your Metrics Before Starting

First, you should define the revenue metrics that you want to measure based on the products your SaaS business offers. Here are a few different types of revenue metrics to consider for startup financial models:

• Existing revenue comes from customers with ongoing subscriptions. This is usually tracked with the monthly recurring revenue (MRR) metric, calculated using the number of customers and the average amount billed for a given month.
• New revenue comes from the additional sale of new subscriptions. This can often be based on historical sales data and the strength of your sales pipeline.
• Renewal revenue comes from existing customers keeping the same subscription for another period when it’s up for renewal.
• Upsell revenue comes from customers upgrading to a higher-tier subscription or purchasing other add-ons.

Check out our SaaS financial model template for inspiration.  

Try Different Types of Revenue Forecasting

Besides deciding which revenue metrics to track, you’ll also want to decide the financial model you want to use to create forecasts. Here are a few common approaches to revenue forecasting:

• Lead-driven forecasting uses the number of leads for a given period of time, the customer conversion rate, and the average sale price to calculate a revenue estimate for each lead source. 
• Lifetime value forecasting leverages the estimated value of the average customer to predict future revenue. There are many ways to calculate customer lifetime value, but one method is to divide the average MRR per customer by the customer churn rate.
• Opportunity forecasting predicts which prospects will become customers based on where they are in the sales cycle. You assign potential close rates to different stages of the sales pipeline and estimate the potential value of prospects to predict revenue based on current sales opportunities. A good CRM can help here.
• Historical forecasting is the easiest method for predicting revenue, but not always the most accurate. You take historical sales data and make an assumption about business growth to estimate future revenue.

Financial projection software can help you map out different models to create each of these forecasts. 

Learn more about how to build actionable financial models.

Best Practices for SaaS Revenue Forecasting 

SaaS revenue forecasting can be challenging, but incorporating these tips can help you get more accurate and comprehensive models:

1. Forecast multiple scenarios
2. Leverage historical data
3. Maintain clean data
4. Consider industry and global market trends
5. Integrate lost deals into your forecasts 
6. Account for churn and ARR
7. Factor in cost 

Forecast Multiple Scenarios

Scenario forecasting is a great way to deal with the highly unpredictable nature of running a business. This forecasting strategy involves modeling multiple “what if” situations to better prepare for the future. Here are a few common scenarios to forecast:

• Target scenario: This is the ideal outcome you’re shooting for and is usually based on fairly aggressive assumptions.
• Base-case scenario: This is a conservative estimate of what your business can most likely achieve and is often based on your average historical performance over the past few months.
• Worst-case scenario: This is the unlikely scenario that things go very wrong, often due to external factors outside your control.

Top financial revenue forecasting software should support diverse scenario planning. 

Leverage Historical Data

While scenario forecasting is great for considering unpredictable outcomes, traditional historical data forecasting can often help determine the most probable outcome. This type of forecasting may be used to forecast the “base scenario” because it’s rooted in historical data. By implementing traditional forecasting, you avoid the qualitative guesswork with scenario forecasting and focus on the data.

Maintain Clean Data

The quality of your data will greatly impact the accuracy of your revenue forecasts, especially for more quantitative forecasts based on historical data.

Gathering high-quality data requires a way to aggregate data from multiple sources into a clear set of business metrics all in one place. By maintaining clean data in a centralized hub, you can calculate more realistic metrics and forecasts that lead to better business decisions.

Consider Industry and Global Market Trends

Your revenue forecast and other business metrics become much more useful when viewing them in the context of your industry or broader world trends. For example, you can perform cohort analysis using live SaaS benchmarks to determine where your company stands compared to similar businesses.

Integrate Lost Deals Into Your Forecast

It’s easy to become overly optimistic about which deals you expect to close, which can affect the accuracy of opportunity or lead-driven forecasting. Tracking lost deals is an important way to create a realistic estimate of customer conversion rates and, in turn, the future revenue to expect from any potential deal going forward.

Account for Churn and ARR

When predicting future revenue, you can’t just look at new sales, upsells, and renewals. In fact, a key factor in forecasting revenue is understanding the impact of your existing annual recurring revenue (ARR) and churn.

One of the primary benefits of the SaaS and subscription business model is the guarantee of some future income through repeat billing — so it’s important to determine how much recurring revenue to expect. That means measuring customer retention is just as important as customer acquisitions when it comes to predicting future SaaS revenue.

Factor in Cost

When forecasting revenue, it’s important to remember that sales are only one piece of the puzzle. There are always going to be additional expenses required to support business growth, whether it’s hiring new employees or increasing marketing budgets. By factoring in the costs associated with additional revenue, you’ll be able to get a better picture of what’s sustainable for your business.

Streamline SaaS Revenue Forecasting with Forecast+

Baremetrics built Forecast+ to give SaaS businesses the tools they need to easily and accurately forecast revenue. This helps you incorporate the best practices above into a financial model that includes traditional forecasting, scenario forecasting, and other methods for predicting the future performance of your SaaS business.

Tired of wasting time on spreadsheets? Get a free trial of Baremetrics today!