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Experimentation

1 post · Nov 2021

What this trail covers

Atlassian's experimentation capability enables product teams to design, implement, and analyze A/B tests to drive product growth and user experience improvements. This includes defining hypotheses, selecting target metrics, implementing solutions with feature flags for gradual rollouts, and collecting de-personalized analytics data for analysis. The process emphasizes careful opportunity analysis, hypothesis formulation, and robust measurement to ensure strategic bets lead to significant wins.

All Atlassian trails
  1. Life of a Growth experimentThis 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.