N8-5: AI Freemium Economics
The economics of free AI tiers: converting usage into revenue without bankrupting the infrastructure.
🎯 What You'll Learn
- ✓ Calculate free tier COGS
- ✓ Design conversion triggers
- ✓ Build usage-to-upgrade funnels
- ✓ Optimize CAC through product-led growth
Lesson 1: The Free Tier COGS Problem
Every free user costs you real money in AI inference. If your free tier allows 10 AI queries/day and each costs $0.004, a free user costs $1.20/month. At 100K free users, you're burning $120K/month in inference with zero revenue. The free tier must be a calculated investment, not a default.
Monthly AI inference cost per free user.
Percentage of free users converting to paid.
The minimum conversion rate needed for free tier costs to be covered by paid revenue.
Calculate the exact monthly cost of your free tier at 10K, 50K, and 100K users. Determine the conversion rate required to break even.
Lesson 2: Conversion Trigger Design
Free users convert when they hit a value ceiling — not a feature wall. The best conversion triggers are usage limits on the AI capability itself: "You've used 80% of your monthly AI analyses. Upgrade to continue." This is far more effective than feature-gating because the user has already experienced the value.
The point where the free user has received enough value to justify paying.
Presenting the upgrade when the user is mid-workflow, not post-session.
Showing the "most popular" plan next to free to anchor expectations.
Design 3 conversion triggers for your AI product that activate at natural value moments, not arbitrary feature gates.
Lesson 3: The PLG Cost Model
Product-Led Growth means your product IS your sales team. Every free user is a lead. Every AI interaction is a demo. Your CAC = (Free Tier Infrastructure Cost + Engineering Cost) / Number of Conversions. If your PLG CAC is lower than your sales-led CAC, the free tier is working.
Total free tier costs / Total conversions per month.
Free users who invite other free users. Each invited user is effectively free CAC.
Average days between signup and first payment.
Build the full PLG funnel model: Free signup → AI value delivered → Conversion trigger → Paid plan. Calculate your PLG CAC vs sales-led CAC.
Continue Learning: Track 8 — AI Pricing Strategy
2 more lessons with actionable playbooks, executive dashboards, and engineering architecture.
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Module Syllabus
Lesson 1: Lesson 1: The Free Tier COGS Problem
Every free user costs you real money in AI inference. If your free tier allows 10 AI queries/day and each costs $0.004, a free user costs $1.20/month. At 100K free users, you're burning $120K/month in inference with zero revenue. The free tier must be a calculated investment, not a default.
Lesson 2: Lesson 2: Conversion Trigger Design
Free users convert when they hit a value ceiling — not a feature wall. The best conversion triggers are usage limits on the AI capability itself: "You've used 80% of your monthly AI analyses. Upgrade to continue." This is far more effective than feature-gating because the user has already experienced the value.
Lesson 3: Lesson 3: The PLG Cost Model
Product-Led Growth means your product IS your sales team. Every free user is a lead. Every AI interaction is a demo. Your CAC = (Free Tier Infrastructure Cost + Engineering Cost) / Number of Conversions. If your PLG CAC is lower than your sales-led CAC, the free tier is working.