What is Gross Margin?
Gross margin is the percentage of revenue remaining after subtracting the cost of goods sold (COGS).
Gross margin is the percentage of revenue remaining after subtracting the cost of goods sold (COGS). For SaaS companies, COGS includes: hosting and infrastructure costs, third-party software licenses, customer support costs, and professional services costs directly tied to revenue delivery.
Gross Margin = (Revenue - COGS) ÷ Revenue × 100
Healthy SaaS gross margins range from 70-85%. Below 70% is concerning and impacts valuation multiples. Above 80% is excellent and commands premium valuations.
AI-powered SaaS products face margin pressure because AI inference costs are variable COGS. Each AI query costs compute — unlike traditional software where serving an additional user has near-zero marginal cost. This is what Richard Ewing calls the Cost of Predictivity problem.
For product economists, gross margin is the most important financial metric after revenue growth. It determines how much money is available for R&D, sales, and profit — the engine of the business.
Why It Matters
Gross margin determines SaaS valuation multiples. Companies with 80%+ margins trade at 2-3x higher multiples than companies with 60% margins. For AI products, maintaining high margins while scaling inference costs is the central economic challenge.
How to Measure
1. **Overall Gross Margin**: (Revenue - COGS) ÷ Revenue × 100.
2. **Per-Customer Margin**: Track at customer level to identify unprofitable accounts.
3. **AI Feature Margin**: Isolate AI inference costs as a percentage of AI feature revenue.
4. **Trend**: Quarterly trending. Declining gross margins signal scaling problems.
Frequently Asked Questions
What is a good gross margin for SaaS?
70-85% is the target range. Below 70% is concerning. Above 80% is excellent. AI-heavy SaaS may see lower margins (50-70%) due to inference costs.
How do AI costs affect gross margin?
AI inference is a variable cost that scales with usage, unlike traditional software. Each AI query costs compute, creating margin pressure as usage grows. This is the Cost of Predictivity.
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Richard Ewing is a Product Economist and AI Capital Auditor. He helps companies translate technical complexity into financial clarity.
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