In episode #343 of SaaS Metrics School, Ben Murray demystifies SaaS revenue by breaking down the core revenue types that software, SaaS, and AI companies should be modeling on their P&L. Rather than focusing on labels, Ben explains why pricing models and revenue streams are the real drivers of financial clarity.

He walks through the most common revenue categories—subscriptions, variable usage-based revenue, professional services, managed services, hardware, and other emerging models—and shows how proper revenue segmentation becomes the foundation for accurate retention metrics, forecasting, unit economics, and due diligence readiness.

Resources Mentioned

SaaS Metrics School framework: https://www.thesaascfo.com/scaling-with-confidence-the-ultimate-saas-metrics-playbook/
Concepts covered in Ben’s SaaS Metrics course: https://www.thesaasacademy.com/the-saas-metrics-foundation
MRR schedules & MRR waterfalls: https://www.thesaasacademy.com/offers/rJhZ6VdM/checkout

What You’ll Learn

The core revenue categories every SaaS, software, and AI company should track
How subscription and usage-based revenue differ financially
Why overages must be separated from subscription revenue
How revenue segmentation enables accurate MRR schedules and waterfalls
Why retention should be calculated separately by revenue stream
How revenue structure impacts forecasting accuracy
How different revenue streams change CAC payback and LTV to CAC calculations
Why clean revenue categorization simplifies due diligence

Why It Matters

Revenue segmentation is the foundation of accurate SaaS metrics
MRR schedules and retention calculations depend on clean revenue data
Forecasts are more reliable when built from revenue waterfalls
Mixed revenue streams require adjusted CAC payback calculations
Clear revenue structure improves investor and acquirer confidence
Proper setup reduces friction during fundraising and exits

Demystifying SaaS Revenue: A Hierarchy for Predictability & Valuation

SaaS Metrics School