Cloud revenue is more predictable and consistent over time than one-off product sales. But at the same time, forecasting cloud-based subscription revenue can be particularly challenging. It is influenced by a wide range of factors including packaging and pricing of offerings and customer acquisition and retention.
So what strategies can you use to accurately forecast your cloud revenue?
Quick-Turnaround, Dynamic Modeling
With a subscription-based cloud model, you have monthly recurring revenue (MMR) rather than annual revenue. This means that revenues and the metrics than influence them can change much more quickly. In fact, according to Gartner, SaaS revenue grew 27% year-over-year, more than double the rate of overall CRM market growth in 2015.
Maintaining a comprehensive view into this complex and dynamic financial environment is the key to forecasting accurate cloud-based revenues.
In this situation, it's more useful to look at last month's metrics rather than comparing to the same period last year. The numbers change too quickly for year-old analysis to hold much value. These metrics should focus on:
- Base subscribers / renewals
- New acquisitions
To accurately budget for operational needs, nearly real-time visibility is needed into financial and supporting metrics along with planning and budgeting tools that function with the same quick response time.
Accurately Tracking Renewals Data is Key
Every month when a customer's subscription fee comes due, they have the opportunity to decide whether to renew or not. (I'm sure you've heard that statement too many times, but its importance bears repeating.) In order to establish and gain momentum with a subscription base and a customer success program, accurate and accessible customer and renewals data is critical.
For customer success staff, customer service and sales reps to maintain and support monthly base subscriptions, they need to have accurate customer data at their fingertips and have the ability to adjust subscriptions and respond to customer requests in real time. Spreadsheets just won't cut it.
Renewals data needs to be instantly accessible, easily updated, and integrated with other systems such as a CRM and ERP. This data should also be seamlessly available up and down the sales channel, with real-time quote reviews and approvals.
Using a data management system, a series of data automations can significantly speed up the quote review and approvals process for renewals and upgrades. A few examples of these automations include:
- Validating product and pricing data
- Coordinating renewal quotes revisions and reviews
- Recording new contract data using batch processing tools
- Canceling accidental duplicate renewal quotes
By integrating data automation and dynamic financial modeling, XaaS businesses can establish realistic revenue forecasting to support sustainable long-term growth of their cloud-based offering.