Revenue recognition is not that straightforward in a subscription-based business model. For a traditional revenue model, the forecasting job is quite simple and easy. You sell a product for $10 and your revenue is $10. As simple as that. But for a SaaS revenue forecast, you have to take many factors into account.
There are many revenue streams that exist in a SaaS business. You have to consider the fresh purchase, the recurring revenue, the upgrades, and so on. Except for the fresh sales, the rest of the revenue streams depend on the kind of relationship you develop with your customers.
Relationship management plays a crucial part in deciding the amount of revenue you would generate through a customer. It also depends on the evolving customer needs and if you are able to provide solutions towards that end. Hence, in a nutshell, the SaaS revenue forecast needs many parameters to be taken into account. And we are going to see them all along with the best practices you must follow towards this. But, let’s start by understanding its definition first.
What is SaaS revenue forecast?
A SaaS revenue forecast is the estimate of total revenue a SaaS business would generate over a fixed period of time. This time period is usually a quarter or a year but it can be different as well. There are many parameters that are considered while predicting the revenue. They include market sentiments, sales pipeline, past financial performance and so on.
Companies use revenue forecasting for various purposes like allocating the budget on their business units for the next quarter. It is also helpful for the investors to know if the company’s stocks are worth buying or not.
Large enterprises forecast their revenue every quarter to decide upon factors like how much should they be investing more, or should they let their employees go, and so on. While smaller businesses usually conduct this exercise one or twice a year.
Best Practices for SaaS revenue forecast
For the revenue forecast, the important aspect that defines the efficacy of this exercise is accuracy. The closer you are to making the right prediction, the better you can align your strategies with it. It is not an intuitive game. The most accurate forecasts are derived out of a data-driven thorough understanding of the business.
Having said that, let’s look at a few of those best practices that you can follow while performing a forecast. These best practices are grouped under three categories that we will be discussing below.
For Fresh Sales
Fresh sales are the major source of revenue that can be leveraged to generate bigger revenues. There are multiple factors at play while forecasting this SaaS revenue:
Start with past performance
You must begin with analyzing the past performance for making any future projection. Bring out all the numbers that you have in your historical records. The most important of that is last year’s annual recurring revenue (ARR). Now list down all the parameters that can influence this ARR for the next year.
For example, your company generated an ARR of $1 million last year. Now, what changes your company has gone through this year that will affect this ARR? These changes may include expansion of sales and marketing team, new product launches, new pricing, etc.
Based on the correlation of each factor with past ARR, you can predict their influence with modified values on the future ARR.
Analyze your Sales Pipeline
Your sales pipeline is a clear indicator of how much revenue you can expect to generate in the near future. You should have a previous record of the number of customers who were at one or the other stage as your current potential customers. Based on their conversion rate in the past, you can predict the same for this year. The time taken for the conversion is also a key factor in income forecasting of short-term and long-term durations.
Measure the marketing and sales performance
A good way to forecast the revenue of the business also comes from the knowledge of your sales and marketing performance. How effectively have they been able to achieve their targets in the previous year? What is the current status of their targets? Have there been any new hires or attrition in the team? Has the sales and marketing team started using some new automation tools that have increased their efficiency? If yes, then can you quantify it?
These are few of the questions that you must consider to analyze the performance of the sales and marketing team. The greater in-depth knowledge you have of their performance, the more accurate your annual sales projection would be.
For Existing Customers
There are mainly two components for the existing customers that are the main sources of revenues. They are contract renewals and additional sales.
Measure the probability of renewals
Based on early indicators, you must know in advance how many customers are likely to renew their contracts in the coming quarters or year. Consider the indicators like adoption rate, CSAT score, NPS score and so on for forecasting subscription revenue. These will give you a good sign whether they are going to bring in more recurring revenue or not.
Do not forget to include the number of new customers that are getting added in each quarter in the recurring revenue list.
Consider add-on sales
Revenues from existing customers in SaaS keeps on growing with time. This is the beauty of SaaS business model. The growth comes from sources like:
- Upgrade of subscription plan from licenses for x number of users to more.
- Upgrade to a higher version product.
- Additional purchase of another ancillary product.
- Increment in the product pricing.
The best way to predict your revenue forecast for add-on sales is to find the growth rate of your customer cohort in revenues in the past years. If two years ago, the growth rate was 5%, and last year it was 6%, then you can extrapolate it for the future taking the compounded effect in the growth rate.
Do not forget to include churn
Although churn is the most dreaded devil in your SaaS business, you cannot ignore it in your SaaS revenue forecast. If you are considering the factors influencing your revenue growth, you have to also consider those that amount to its depletion. Analyzing the overall ARR with churn rate for the past years would allow you to know its percentage effect on future earnings. The overall revenue through existing customers’ contract renewals must be adjusted with churn rate to arrive at a more precise estimate.
The financial planning and analysis processes that every SaaS company executes consider multiple factors to build their SaaS revenue forecast model. The FP&A combines an in-depth analysis of both operational and financial data to measure the growth of a company and to arrive at future predictions. Hence, SaaS companies should avoid relying on qualitative assumptions for their revenue projections.
Forecasting is a hard-core quantitative exercise and must remain so. For all the qualitative measures you take, the effects can be seen in various KPIs. But when it comes to revenue forecasting, these measurable KPIs are the only inputs along with the financial history of the organization.