Pricing and Monetization
Your AI costs money every time someone uses it. Price accordingly.
AI products have a unique pricing challenge: your costs scale with usage in ways traditional SaaS doesn't. Get this wrong and growth kills your business.
What you'll learn
- The four pricing models for AI products
- How to calculate your true cost-per-query
- Why free tiers can bankrupt AI startups
- Value-based pricing vs. cost-plus pricing
Four Ways to Charge for AI
1. Subscription (flat monthly fee). Simple for users, risky for you. If a power user sends 10,000 queries a month and each costs you $0.03, that's $300 in API costs against a $29 subscription. You need usage limits or tiered plans.
2. Usage-based (pay per query/token/action). Aligns your revenue with your costs perfectly. But users hate unpredictable bills. The solution: credit packs. "Buy 100 analyses for $19." Users get predictability. You get margin protection.
3. Hybrid (subscription + usage). Base subscription includes X queries per month. Overages billed per unit. This is where most mature AI products land. Jasper, Copy.ai, and Midjourney all use variations of this model.
4. Outcome-based (pay per result). Charge for successful outcomes, not attempts. "Pay $2 per qualified lead generated" or "$5 per completed analysis." Highest perceived value, but hardest to implement.
Know Your Unit Economics
API cost per query: Claude Sonnet ~$0.01-0.05 depending on context length
Infrastructure: Hosting, database, vector storage — typically $50-200/mo baseline
Margin target: Aim for 70%+ gross margin. If a query costs $0.03, charge at least $0.10
Rule of thumb: Your price should be 3-10x your cost. Not 1.5x. Not 2x. Three minimum.
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