measure-experiment-design

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Designs an A/B test or experiment with clear hypothesis, variants, success metrics, sample size, and duration. Use when planning experiments to validate product changes or test hypotheses.

Web & Frontend 290 stars 40 forks Updated yesterday Apache-2.0

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Skill Content

<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 --> # Experiment Design An experiment design document defines all parameters needed to run a rigorous A/B test or controlled experiment. It ensures the team aligns on what you're testing, how you'll measure success, and how long to run the test before drawing conclusions. Good experiment design prevents common pitfalls: underpowered tests, unclear success criteria, and decisions based on noise rather than signal. ## When to Use - Before launching an A/B test to validate a product change - When testing a hypothesis that requires quantitative validation - After solution design to validate assumptions before full rollout - When stakeholders want data-driven evidence for a decision - To establish a culture of experimentation and learning ## Instructions When asked to design an experiment, follow these steps: 1. **Articulate the Hypothesis** Write a clear, testable hypothesis in the format: "We believe [change] for [users] will [outcome] as measured by [metric]." One hypothesis per experiment . if you're testing multiple things, run multiple experiments. 2. **Define the Variants** Describe the control (current experience) and treatment (new experience) in sufficient detail. Include screenshots, mockups, or precise descriptions so anyone can understand what users will see. 3. **Choose Primary and Secondary Metrics** Select one primary metric that will determine success or failure. Add 2-3...

Details

Author
product-on-purpose
Repository
product-on-purpose/pm-skills
Created
5 months ago
Last Updated
yesterday
Language
JavaScript
License
Apache-2.0

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