Forecasting Subscription Revenue: How to Do It Right

This post was last updated on February 16, 2024.

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What is Subscription Revenue Forecasting?

Key Metrics for Forecasting Subscription Revenue

Best Approach to Forecasting Subscription Revenue

Factors to Consider While Forecasting Subscription Revenue

Common Pitfalls in Subscription Revenue Forecasting

FAQs

Wrapping Up

Forecasting subscription revenue is crucial for B2B SaaS businesses for raising funding and managing finances. 

However, accurate forecasting can be challenging due to the complex nature of subscription-based models. Many SaaS companies struggle to navigate the multiple parameters involved in predicting future revenue streams.

This article will explore the best approaches to forecasting subscription revenue, diving into key metrics and factors that influence accuracy. We’ll provide actionable insights to help you develop accurate revenue forecasting.

Before we delve into the specifics, let’s first clarify what subscription revenue forecasting entails and why it’s vital for SaaS companies.

What is Subscription Revenue Forecasting?

Forecasting subscription revenue is the process of estimating the recurring revenue a business would generate over a pre-specified period (month, quarter, or year).

Forecasting subscription revenue growth can help you understand how to best allocate your budget to different business areas and plan for business growth.

It is clear that forecasting subscription revenue is a must for a successful subscription-based revenue model. 

Before we discuss the best approach to forecasting subscription revenue, you need to understand revenue metrics relevant to a subscription-based business model.

Key Metrics for Forecasting Subscription Revenue

Following are the metrics that will help you forecast the revenue for a subscription-based business.

Average Monthly Recurring Revenue (Average MRR)

Average Monthly Recurring Revenue is the estimate of total revenue a subscription-based business is expected to generate in a month. Average Monthly Recurring Revenue is calculated by multiplying the total number of customers by the Average Revenue per Account (ARPA).

For example, if your business has 30 customers and each of them pays $100 every month to leverage your services, your average MRR would be $100 * 30 = $3000.

Customer Churn Rate (CCR)

The customer churn rate is an indicator of how many customers (customers) a business loses every month/year. 

The customer churn rate is measured by dividing the no. of customers who unsubscribed during a period by the total no. of customers at the start of that period. Multiply by a hundred to arrive at a percentage.

However, while calculating the customer churn rate for forecasting subscription revenue, you need to predict future customer behavior. 

To predict customer churn, you can use Younium’s intelligent solutions for sales and marketing. It can help you with forecasting subscription revenue and managing subscriptions.

Average Revenue Per Account (ARPA)

If you divide the revenue by the number of accounts, you get the Average Revenue Per Account (ARPA). ARPA is essential for forecasting subscription revenue as it gives you access to your business’s revenue-generating capability at the per-customer level.

You can calculate the average revenue per account for forecasting subscription revenue by dividing the total MRR by the number of active customers in a month.

Customer Lifetime Value (CLV)

Customer lifetime value is a calculation of the total revenue a business would generate from a customer during their lifespan. To calculate your customers’ total lifetime value, you need to know your post-sign-up retention rate and monthly customer churn rate.

Now we know what subscription revenue forecasting is and its critical elements, let’s discuss the best approach to forecasting subscription revenue.

Best Approach to Forecasting Subscription Revenue

If you use subscription management platforms that can forecast revenue, there isn’t much you have to do to forecast subscription revenue. 

Such platforms can automatically analyze your historical data to predict customer acquisition, churn, and retention rates and calculate your future revenue.

However, if you’re managing the metrics using a spreadsheet, you have to forecast subscription revenue manually. Here are the four simple steps for forecasting subscription revenue.

1. Calculate Your Customer Base

The first thing you should do is prepare a continuity schedule for your customers. The customer base for each of your months/quarters will be “customers at the start of the period + new customers- subscription cancellations.”

In a typical subscription-based environment, you can consider three revenue streams to prepare a customer’s continuity schedule:

1. Revenue from existing customers
2. Revenue from new customers
3. Revenue from future subscription renewals

Here’s an example of how to calculate your customer base:

2. Multiply customer Base by ARPA

Once you have calculated the customer base, multiply it by the average revenue per account and you’ll get monthly subscription revenue. This is typically called the MRR (Monthly Recurring Revenue).

The monthly or annual recurring revenue will act as the basis for the rest of the business strategies like sales, marketing, and financing.

This data that you record at the initial stages will also act as a baseline for future predictions. For starters, it can be used to calculate churn rate and determine average customer lifetime.

3. Calculate Churn Rate

Determining the churn rate is essential to the success of a subscription business. Using the data recorded during the first step, you can calculate your churn rate by dividing subscription cancellations by the customers at the start of the particular month.

The customer churn rate can be used to calculate the projected customer lifetime. To determine that, you just have to divide 1 with the value of customer churn. In the above illustration, the projected customer lifetime for the first month is calculated as

1 ÷ 0.10 = 10 months.

4. Determine Average Customer Lifetime Value and Forecast Annual Recurring Revenue

When you have the average customer lifespan projects, you can use them to calculate the Average Customer Lifetime Value (ACLV). The ACLV can be calculated with a basic formula as 

ACLV = Projected lifetime x ARPA

Or

ACLV = ARPA ÷ Churn Rate

Moreover, you can multiply your monthly revenue (MRR) by 12 to get the Annual Recurring Revenue forecast.

This is how we can calculate our Average Customer Lifetime Value and Annual Recurring Revenue in our hypothetical example.

Factors to Consider While Forecasting Subscription Revenue

While forecasting subscription revenue, you need to consider the following factors to ensure effectiveness. 

1. Analyze Recent and Current Strategic Changes

Although your historical data is a great baseline for forecasting recurring revenue, you cannot undermine the recent strategic changes since you’ve collected the data.

Think of the recent product/service introductions, new marketing activities, and sales promotions strategies that can impact your forecast.

For example, bundled services can improve your customer acquisition rate, whereas raising subscription prices might increase your customer lifetime value. 

Hence, it’s important to consider the recent strategic changes while forecasting subscription revenue.

2. Leverage Sales Pipeline

Sales pipelines are the most reliable indicator of how many customers you might have in the upcoming months or years.

You can find all the required information in your sales department's sales projection reports for every month or quarter. Gauge how many leads your sales teams are nurturing and what their projections are for the period.

3. Analyze Customer Behavior

For forecasting subscription revenue, it is essential to analyze the current user behavior. The churn and renewal rates are very diversified across the customers’ life cycles. But looking at each customer’s recent behavior, you can predict their churn likelihood.

For example, if some users haven’t logged into your application for a month, they’re less likely to renew their subscriptions. Moreover, the churn rate will be higher during the first-month trial period and a few months after that.

The best approach to calculate customer retention is cohort analysis. By grouping the customers into cohorts as per their persona and lifespan, you can predict their likelihood of renewing their subscriptions.

Common Pitfalls in Subscription Revenue Forecasting

While forecasting subscription revenue is crucial for predictable revenue and cash flow, many businesses fall into common traps that can lead to inaccurate forecasts. Here are some pitfalls to avoid and tips for more accurate subscription revenue forecasting.

1. Overreliance on Historical Data 

While past performance is important, it shouldn't be the sole basis for your forecast.

The subscription-based model is dynamic, and market trends, competitor actions, and customer preferences often shift rapidly. Always update your forecasts based on current data to better reflect recognized revenue.

2. Ignoring External Market Factors

Failing to consider broader economic conditions, competitor actions, or industry shifts can skew your forecast. 

Regularly analyze market trends and incorporate insights from the broader market environment when forecasting subscription revenue.

3. Neglecting Seasonality and Product Lifecycle Stages

Many subscription-based models experience seasonal fluctuations. 

Ignoring these patterns or your product’s lifecycle negatively impacts customer behavior. In fact, it can lead to overly optimistic or pessimistic forecasts and large variations in cash flow. 

However, using cohort analysis to identify seasonal patterns in existing customers’ behavior can help you create a more predictable revenue stream.

4. Misinterpreting or Misusing Metrics

Metrics like monthly growth, customer churn, or recognized revenue can be misleading if not properly understood or applied. Misusing them can distort how much revenue you expect to generate. 

Therefore, ensure that cross-functional teams — sales, finance, and marketing — are involved to provide a more balanced perspective on your sales pipeline and revenue forecasts.

FAQs

The recurring revenue that subscription businesses receive is considered subscription revenue. As the subscription fee is charged to the customer for a period of time, the cash inflows are frequent.

The total revenue forecast for a particular month for a subscription service can be calculated with the following formula:

(Customers at the start of the month + New customers) x Subscription fee per customer

For forecasting subscription revenue, you need to calculate the estimated customer base for the upcoming months and the average value of the subscription fee per customer. Once you have both data points, the subscription revenue forecast can be calculated as:

Subscription Revenue Forecast = Customer base for revenue x Average revenue per customer.

Alternatively, you can use Younium to avoid manual calculations and get all the revenue metrics and customer details you need for revenue forecasting. It tracks all key metrics like MRR and ARR, which are the basis for any revenue forecasts.

Its reporting engine lets you create custom reports with the specific metrics you need and also help you analyzing the data to draw insights.

Subscription revenue is the recurring price customers pay to hire your services. Hence, it’s an income for an organization, and even if it is yet to be received from the future billing cycles, it can be considered an asset as shown under the assets section of the Balance Sheet.

The monthly or annual subscription revenues should be recognized on an accrual basis, which means that the revenue is recorded in the books when it’s earned instead of when it’s received. 

Wrapping Up

We’ve discussed the key metrics and ways for forecasting subscription revenue for SaaS companies. Calculating the future customer count and revenue streams is not difficult if you have a subscription revenue model in place.

You can read our recent blog on how to create a subscription revenue model if you need help.

Subscription management software supports you and your team with forecasting subscription revenue, head over to our subscription insights to learn more about how it works for B2B businesses.