How to find hidden growth opportunities in your product | Albert Cheng (Duolingo, Grammarly, Chess.com)

Overview

Albert Cheng, a leading growth expert who has worked at Duolingo, Grammarly, and Chess.com, shares his insights on driving growth through rapid experimentation, user psychology, and leveraging AI. The episode dives into frameworks like Explore and Exploit, the importance of user retention, and how to uncover hidden growth opportunities in consumer subscription products.

Notable Quotes

- Growth is the job of connecting users to the value of your product. — Albert Cheng, on the essence of growth.

- Sometimes experience can be a crutch, especially in this world where the grounds are shifting so fast with AI. — Albert Cheng, on hiring and adapting to change.

- If you don’t retain your users, then a lot of the onus is on getting them to pay on day one. — Albert Cheng, on the critical role of retention in subscription businesses.

🎯 Explore and Exploit Framework

- The Explore and Exploit framework balances finding new opportunities (exploration) with maximizing existing successes (exploitation).

- Example from Chess.com: When data revealed users reviewed games more after wins, the team shifted to highlight positive moves after losses, boosting game reviews by 25% and subscriptions by 20%.

- Over-exploitation can lead to stagnation, while over-exploration risks scattershot efforts. The key is oscillating between the two.

📈 Growth Wins and Monetization Strategies

- Grammarly’s Freemium Model: Sampling premium features for free users (e.g., tone adjustments) doubled upgrade rates by showing the product’s full potential.

- Reverse trials (limited feature access) work better than time-based trials for freemium products.

- Retention is the cornerstone of subscription success. For consumer apps, a Day 1 retention rate of 30-40% is a good benchmark.

🤖 AI in Growth and Product Development

- AI for Experimentation: Chess.com uses AI tools like text-to-SQL bots to automate data queries, enabling faster insights and decision-making.

- AI in Chess: Chess engines like Stockfish enhance user learning by analyzing moves and providing feedback. LLMs are used for personalized coaching and explanations.

- AI accelerates prototyping and ideation, making it easier to explore bold ideas and iterate quickly.

🎮 Gamification and Habit Formation

- Duolingo’s Gamification Framework: Success stems from three pillars—core loop (daily lessons), metagame (long-term goals like leaderboards), and profile (user progress).

- Chess.com’s Beginner Experience: To improve retention, the platform is experimenting with hiding ratings for new players and creating more guided learning experiences.

- Early wins and positive reinforcement are critical for building long-term habits in both learning and gaming contexts.

🏗️ Building Teams and Culture

- High agency individuals—those with energy, clock speed, and adaptability—outperform those with deep but rigid expertise.

- At Chess.com, the cultural shift from minimal experimentation to a goal of 1,000 experiments per year was driven by leadership buy-in and celebrating early wins.

- The system supporting experimentation (e.g., tooling, instrumentation) is as important as the experiments themselves.