How do you build software revenue projections?

To build software revenue projections effectively, especially for SaaS companies, you need to break it down into a structured approach using key performance indicators (KPIs) and historical data. Here's a practical framework based on the most helpful WSO content:

1. Understand the Revenue Recognition Rules

• SaaS companies often recognize revenue over the life of a contract rather than upfront. For example, if a customer signs a 3-year contract with $100 ACV, only $100 is recognized as revenue per year, even if the full $300 is billed upfront. The rest goes into deferred revenue.

2. Segment Revenue Sources

• Divide revenue into key components:
  • Renewals (Gross Retention): Revenue from existing customers renewing their contracts.
  • Expansions/Upsells (Net Retention): Additional revenue from existing customers upgrading or purchasing more services.
  • New Sales (ACV from new customers): Revenue from new customer contracts.

3. Use Historical KPIs to Project Future Revenue

• Start with disclosed KPIs like ARR, ACV, DBNRR (Dollar-Based Net Retention Rate), and net new ARR. These metrics provide insights into growth trends and customer behavior.
• For example:
  • ACV from new sales: Determine when the revenue starts being recognized. If a contract is signed in Q1, revenue recognition might begin in Q2 or Q3, depending on the implementation timeline.
  • Renewals: Use historical gross retention rates to estimate the percentage of contracts that will renew.
  • Upsells/Expansions: Apply the net retention rate to estimate additional revenue from existing customers.

4. Incorporate Timing and Contract Terms

• Revenue recognition depends on the contract start date and term length. For instance:
  • If a contract starts mid-year, only half of the annual ACV will be recognized in the first year.
  • Use historical patterns or company disclosures to estimate the lag between contract signing and revenue recognition.

5. Model Quarterly and Annual Projections

• Build a granular model:
  • Quarterly Projections: Use historical seasonality or trends to allocate revenue across quarters.
  • Annual Projections: Roll up quarterly data to get annual figures.
• Example:
  • If Q1 ACV from new sales is $1M and revenue recognition starts in Q2, allocate $250K per quarter for the next four quarters.

6. Adjust for Growth Assumptions

• Apply growth rates to each revenue component based on historical trends, market conditions, and company guidance. For example:
  • New customer growth rate: 20% YoY.
  • Expansion revenue growth: 15% YoY.

7. Validate with Non-GAAP Metrics

• Cross-check your projections with disclosed metrics like ARR and DBNRR to ensure consistency. For instance:
  • If ARR is growing at 25% annually, your revenue projections should align with this growth rate.

8. Incorporate Deferred Revenue

• Account for deferred revenue in your model. For example:
  • If a customer pays upfront for a multi-year contract, only a portion of the payment is recognized as revenue each year, with the rest recorded as deferred revenue.

9. Iterate and Refine

• Continuously refine your model based on new data, company disclosures, and industry trends.

By following this framework, you can build a detailed and accurate revenue projection model for SaaS companies. Remember, the key is to tie your assumptions to historical data and disclosed KPIs while considering the nuances of revenue recognition and contract terms.

Sources: PE recruiting technical questions (software specific), DCF Modeling Course ~ Pre-training text.pdf, Q&A: Equity Analyst at a Sovereign Wealth/Pension Fund