Adapting Revenue Forecasts to Subscription Billing

November 30, 2014 · 3 min read

Adapting Revenue Forecasts to Subscription Billing

In many ways, subscription billing can make a company’s revenue forecasts even easier than point-of-sale or booking models, as it provides a reliable and repeatable rate of revenue accretion. However, in most cases, a company won’t be able to simply replace POS numbers with subscription information and come out with an accurate forecast. Follow these suggestions that companies should keep in mind while transitioning to a subscription-billing model.

Changing Metrics

For most companies that are dependent on sales, the holy grail of metrics for revenue forecasting is the “booking” or “lead-in” number, which tracks sales orders to then predict the resulting revenue. However, the booking model usually takes into account factors such as cancellations, sales expenses, closure rates and product returns that fare poorly in a one-to-one transfer to a subscription model.

To most accurately reflect the landscape of a subscription-revenue model, the ideal prime metric is some form of Monthly Recurring Revenue (MRR). MRR can be tracked for each sales representative, or each individual customer, but most importantly, it only reflects the subscription revenue made that month. This distinction is crucial, as it provides the most accurate means to track the real revenue flow involved, and incorporates the monthly revenue from all subscriptions, even those billed quarterly or annually.

A subscription is by definition a longer term arrangement than a simple point of sale, so revenue made from a monthly subscription payment is already final. It’s not subject to any after-the-fact wrinkles like those in a booking model. Adopting MRR instead of a straight Recurring Revenue (RR) metric allows a company to track revenue across multiple billing cycles, and keeps the ebb and flow of the aggregate annual revenue stream clear and identifiable.

Identifying Churn

The major benefit of forecasting revenue under a subscription model is its reliability, so it’s important that a business is able to predict any disruptions to that flow. Doing so requires a clear churn rate, which tracks the number of customers who cancel their subscription preterm or simply decline to renew it at the end of a billing cycle.

It can be difficult for a company to calculate accurate churn rates when they have just transitioned to a subscription model. Nevertheless, the churn rate will remain the single most important factor impacting revenue from year to year. It’s vital to start tracking that information immediately and incorporating it as much as possible into revenue forecasts from the start.

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