What you'll learn:
- Select the right monetization model based on value, frequency, and buyer.
- Set price floors/ceilings and apply cost-plus, competitive, and value-based pricing.
- Design subscription tiers, trials, and onboarding to reduce churn and grow LTV.
- Build freemium limits (gates, caps, nudges) that convert without hurting UX.
- Use key metrics (MRR, ARPU, LTV, CAC, churn, conversion) to find revenue issues.
- Run A/B tests and cohort analysis to validate price changes and optimize revenue.
Have you ever seen a product that users love… and still watch it fail? In many cases, the issue isn’t the product—it’s the monetization.
Consider these realities:
~72% of new products fail to meet revenue or profit targets (often due to weak monetization strategy)
Typical freemium conversion rates are only ~2–5%, meaning your “free” tier must be designed with intention
For subscription products, even small churn increases can quietly erase growth and destroy LTV
So if monetization is “something we’ll figure out after launch,” you’re taking one of the biggest risks a product team can take.
Product Monetization is designed to help you build a revenue engine that fits your product’s value proposition and your customers’ behavior—whether you’re working on SaaS, apps, platforms, or digital services. You’ll learn how to choose the right model, price it credibly, and improve performance over time using data and experimentation.
In this course, you’ll learn how to:
Understand monetization fundamentals (direct vs indirect revenue, revenue streams, price floors/ceilings)
Apply core pricing strategies: cost-plus, competitive, and value-based pricing
Use launch pricing tactics like penetration pricing and price skimming
Design subscription models that deliver ongoing value and reduce churn
Build freemium offerings that scale growth while converting the right users
Compare alternative monetization models: usage-based pricing, advertising, affiliates/partnerships, and data monetization
Optimize revenue with bundling, upsells, segmentation, personalization, and churn reduction
Track the metrics that matter (MRR, ARPU, conversion, churn, LTV, CAC) and use cohort analysis
Run practical experiments (A/B tests on pricing, trials, paywalls, and upgrade prompts)
Stay ahead of emerging trends like hybrid pricing and AI-driven personalization
You’ll also get real-world examples and frameworks drawn from companies like Adobe, Dropbox, Notion, Figma, Peloton, Twilio, Netflix, Snowflake—and a deep case study on Duolingo’s path to monetization.
By the end of this course, you won’t just “know the models.” You’ll be able to make confident monetization decisions, defend pricing logic, and iterate with data—so your product can grow into a sustainable business.
