Performing regular revenue and customer count forecasts for a SaaS company can be difficult and chaotic. This is for a multitude of reasons. The biggest issue is accounting for the future performance of existing customers. The reason it can be so difficult is because you must take into account retention rate, contract terms and the timing of when customers joined and have a clean way to update this as you roll through time in order to keep getting proper revenue forecasts.
This template applies all necessary logic to existing customers and expected new customers in order to provide an on-going tool that can create revenue forecasts.
You can account for up to four customer types. Customer types can be differentiated by retention rate, average revenue per contract, and contract length (in months).
The end report is a 60-month revenue and customer count forecast that takes into account all existing contracts and future contracts. They can be month to month or have varying terms (up to 4 variations).
To update the forecast as you roll through time, you simply move your historical customers that have been added back a slot (there are 60 months worth of historical slots) for each of the four customer tiers and then add the most recent month(s) worth of new data for completed months. Then update the expected new customers over the next 60 months for each tier as well. The revenue will populate based on high level drivers for each customer tier.
Data is shown by customer tier and separated by existing vs. new customers and everything is aggregated into totals as well. Visualizations help to make this even more clear. The goal here is to provide an easy-to-use framework for more accurately making revenue forecasts for any SaaS organization.
Also note, if you have customers that are older than 5 years, you can put them in the most recent historical month slot and simply estimate the retention of that as its own cohort.

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