Why Farfetch manages by learning rate, not win rate

Summary Luis Trindade, Principal Product Manager of Experimentation at Farfetch, joins host Ashley Stirrup to explain how one of the world's largest luxury marketplaces built its own experimentation platform and the culture around it. Luis covers the move from a hybrid setup with an external testing vendor to Fabs 2.0, the in house system where a feature toggle is the single entry point for every experiment, why Farfetch manages by learning rate instead of win rate, and the two year Inspire experiment that replaced the world's leading recommendation engine vendor. He also shares how a deliberately shrinking center of excellence supports hundreds of experiments a month through clinics, shared templates, and open learning sessions. This episode is for product managers, engineers, data scientists, and growth leaders building or scaling an experimentation program. Chapters 00:00 Cold open and introduction 01:45 Inside Farfetch, the global marketplace for luxury fashion 08:00 From startup validation to an experimentation mindset 09:45 A center of excellence that enables instead of executes 12:45 Fabs, build versus buy, and dropping the external vendor 16:45 One feature toggle as the entry point for every experiment 20:45 Learning rate over win rate 23:15 The two year experiment that replaced the recommendation vendor 29:45 Onboarding new product managers into experimentation 33:15 AI, corporate knowledge, and what comes next for experimentation Takeaways -Manage by learning rate, not win rate. The only failed test is one that was badly designed, with wrong metrics or sampling biases. Every other test produces a learning. -Route every experiment through a single entry point. Farfetch's feature toggling system connects segmentation, user systems, CMS, and messaging so every team tests in the same language. -External JavaScript injection tools carry hidden costs: broken pages, inconsistent results, and rework to reclaim your own data for deep dives. -Strategic bets deserve a longer clock than fail fast allows. Farfetch iterated on its Inspire engine for two years before it beat and replaced the market leader. -A center of excellence should enable, not execute. Farfetch's central team shrank while experiment volume grew because its job is ceremonies, templates, and coaching. Connect with the Guest LinkedIn: https://www.linkedin.com/in/ltrindade/ Website: https://www.farfetch.com Sponsor GrowthBook is the warehouse-native platform for experimentation, feature flags, and product analytics trusted by AI-native product teams at 3,000+ companies worldwide. Go to http://growthbook.io