Life of a Growth experiment

This post details the lifecycle of a growth experiment, from opportunity analysis and hypothesis formulation to solution implementation, gradual rollout using feature flags, and data analysis. It introduces the concept of 'expands' as a key metric for cross-product user journeys and highlights the importance of a controlled rollout strategy (50% experiment, 50% control) to measure impact. The post also explains the use of analytics events for detailed user interaction tracking and the role of feature flags in enabling staged rollouts and user segmentation.