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.
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-foundationMRR schedules & MRR waterfalls: https://www.thesaasacademy.com/offers/rJhZ6VdM/checkout The core revenue categories every SaaS, software, and AI company should trackHow subscription and usage-based revenue differ financiallyWhy overages must be separated from subscription revenueHow revenue segmentation enables accurate MRR schedules and waterfallsWhy retention should be calculated separately by revenue streamHow revenue structure impacts forecasting accuracyHow different revenue streams change CAC payback and LTV to CAC calculationsWhy clean revenue categorization simplifies due diligenceRevenue segmentation is the foundation of accurate SaaS metricsMRR schedules and retention calculations depend on clean revenue dataForecasts are more reliable when built from revenue waterfallsMixed revenue streams require adjusted CAC payback calculationsClear revenue structure improves investor and acquirer confidenceProper setup reduces friction during fundraising and exits