When a metric moves after a launch, it's tempting to credit the launch. But the users who adopt new features first are often your most engaged users regardless. Mixpanel's Impact report uses causal inference to compare adopters with a matched group of non-adopters, giving you a fairer picture of what your launch actually caused. The Impact module covers how it works, how to define your hypothesis, how to read the before-vs-after timeline, and how to use results to guide rollout decisions.
Impact: Prove the True Lift of Your Launch
By the end of this course, you will be able to:
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Define a hypothesis in the Impact report
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Read the before-and-after timeline
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Use causal results to guide your rollout decisions
