How to build a SaaS revenue forecast

1. Choose your drivers

Recurring revenue moves for four reasons: customers arrive, customers leave, existing customers spend more, and existing customers spend less. Each needs a driver you can estimate and defend.

• New customers per month, often from leads times conversion rate
• Churn rate: the share of customers or revenue lost each month
• Expansion rate: upgrades, extra seats and price increases from existing customers
• Average revenue per customer, by plan

2. Split by plan or segment

Self-serve and enterprise customers churn, expand and pay very differently, so a single average hides more than it shows. Make plan or segment a dimension, and write each formula once; it applies to every plan, and adding a plan later adds a row without rewriting anything.

3. Build the MRR roll-forward

Each month, ending MRR equals starting MRR, plus new MRR, plus expansion, minus contraction and churn. Laying the forecast out this way shows where growth comes from and makes the board's favorite question — is growth coming from new logos or from the base? — easy to answer.

4. Put actuals in the closed months

Connect your billing or warehouse data, through a Google Sheet or BigQuery, so the months that have closed show what really happened. Comparing those actuals with what the drivers predicted is how you learn which assumptions to trust.

5. Run scenarios

Create a downside scenario with higher churn and slower new business, and an upside with a price increase. In Timshal a scenario changes only the assumptions you touch; everything else follows the base case, so you can compare cases side by side without maintaining copies of the model.

6. Connect revenue to the rest of the plan

Revenue drives commissions, hosting cost, support headcount and cash collections. Linking the revenue model to your operating model and cash forecast means a change in churn shows up in runway, not just in the revenue tab.