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Revenue forecasting models help you plan your next phase of growth. Financial models also help you plan how to pivot in response to certain scenarios, like a sudden drop-off in sales or an unexpected surge in demand.
The Baremetrics article “The SaaS Financial Model You’ll Actually Use” describes how to create financial models to plan out your next steps—even when your total revenue falls short and things don’t go as expected.
Let’s explore the importance of accurate forecasting in business and how it can be utilized to predict future sales. We will delve into the process and three specific forecasting techniques that can provide valuable insights for revenue projections.
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What is Revenue Forecasting?
Revenue forecasting involves predicting how much revenue you expect to make over a certain period, which can range from a quarter (three months) to a full year.
This process is not just a guess about how much money your business will generate, but some experts admit that, for a startup, revenue forecasting is more of an art than a science.
Other commentators distinguish between judgment forecasting—based on intuition and anecdotal evidence—and quantitative forecasting—based on current and historical data. Ideally, data drives your revenue forecasts.
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Importance of Revenue Forecasting Models
Revenue forecasting models offer a method for predicting revenue. They allow you to move beyond personal judgment—your “best guess” of the success of your sales process—toward quantitative analysis.
Of course, hard data isn’t always possible. If it’s your business’s first year, you may have to rely on intuitive forecasting. Often, that comes from your salespeople’s assessment of the likelihood that leads will pan out.
Forecasting models are important because they drive decision-making in your business. They influence your decisions to hire more people, expand into new markets, and set goals for upcoming quarters.
Three Methods of Revenue and Sales Forecasting
Here are three ways to rely on proven revenue prediction methods and develop a picture of your company’s success.
1. Opportunity stage forecasting
This method predicts revenue based on your current prospects. It uses historical data to add a numerical value to each prospect given their stage in the sales journey. The further they are down your sales pipeline, the greater the chances the deal will close.
As an example, assume that over the past two quarters, 60 percent of customers who reached the stage of signing up for a free trial eventually purchased a subscription.
You can use this forecasting method to predict that 60 percent of prospects currently enrolled in a free trial will subscribe. Using this figure, you can forecast your revenue.
In theory, you can predict your revenue based on any opportunity stage. But the further down in the funnel they are, the more accurate the forecast becomes. That’s because you know more about these potential clients, enough to predict future revenue.
This method has potential flaws. It does not consider the age of each prospect. An older lead, or someone who lingers before reaching the free trial stage, is perhaps less likely to commit than one who goes through the early stages quickly. Opportunity stage forecasting treats both prospects equally.
2. Test market analysis forecasting
This method helps you to predict revenue based on the projected interest in a product. The process involves rolling out a product or service to a test market and reviewing the results. This is a particularly valuable method for startups who may not have historical data to draw from.
An example of a test market can be a rollout to a small segment of consumers or businesses. Crowdfunding campaigns, such as Kickstarter or Indiegogo, are one form of test marketing.
This method also has its drawbacks. There is no guarantee your product will perform as well in an open market as in your test market. Before using this method, it is wise to use additional data that considers competition in your industry and the buying habits of your target consumers.
3. Historical forecasting
This is a straightforward revenue forecasting model. Historical forecasting assumes that whatever has happened in the past will continue to happen.
As an example, say your revenue was $100,000 in January. Historical forecasting assumes revenue will reach $100,000 in February and subsequent months.
There are some drawbacks to this method as well. Although it draws on historical reality, it assumes much about the future. First, that sales are steady and monthly recurring revenue doesn’t contract or expand. They don’t go down or go up. Second, it does not take into account natural fluctuations, like seasonality, changes in customer demand, or growth as the result of your sales team’s efforts.
There are ways to modify this method to make it more accurate. You can look at trends over the past 6 months to a year. This should show a moving average considering seasonal changes and revenue growth rate.
You can then change your sales forecast projections by starting with average sales rates, which will provide a more accurate sales picture for your business.
The month-by-month comparison may serve as a benchmark rather than a straightforward method ensuring forecast accuracy.
How Baremetrics Helps!
Baremetrics uses real data points from your business to help you make smart predictions.
The forecasting tool is your go-to resource for revenue predictions you can rely on for budgeting and operational decisions.
Baremetrics analytics and insights give you access to powerful data sets about your customers that you can use to create financial models to build your business.
To learn more about Baremetrics, sign up for a free trial today.
