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What does it really take to build a flexible, fair, and scalable pricing model for a SaaS platform that serves everyone from indie devs to enterprise teams? In this episode of Monetizing AI, Expo’s Joe (Head of Revenue) and John (Head of Product) join host Fynn Glover to break down how they approach monetization across wildly different customer types (and why great pricing isn’t science... it’s taste). They dig into: • How Expo thinks about value-based pricing • The balance between predictability and flexibility • Usage-based vs. credit-based models • How entitlements and limits are handled • Why “pricing committees” kill momentum • And the underrated art of developing pricing taste Whether you’re a founder, product leader, or revenue strategist, this conversation unpacks what modern monetization looks like in the age of AI-enabled SaaS. ----------------- 🚀Focus on growing your SaaS, we’ll handle the monetization! Visit 👉https://schematichq.com ----------------- ⏳Chapters 00:00 - Welcome to Monetizing AI: Expo’s pricing challenge 01:00 - How Expo approaches monetization across diverse customer types 03:20 - The importance of discovery before pricing conversations 04:50 - Core value metrics and pricing models at Expo 07:10 - Predictability vs. flexibility in usage-based pricing 08:30 - Credit-based pricing and the perception of fairness 10:45 - Balancing enterprise predictability with startup flexibility 13:40 - How Expo structures internal pricing strategy and decision-making 15:50 - Entitlements and feature access: how Expo handles permissions 18:40 - Limits, thresholds, and preventing overages without friction 21:30 - Key takeaways: usage, transparency, and decision speed 22:45 - Why iteration (and “pricing taste”) matter more than models 24:30 - The art and intuition behind great pricing ----------------- #SaaS #PricingStrategy #Monetization #Expo #ProductManagement #StartupGrowth #UsageBasedPricing #AI #RevenueOps #ProductLedGrowth #MonetizingAI