measure-experiment-results

<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 --> # Experiment Results An experiment results document captures what happened when you tested a hypothesis, including statistical outcomes, segment analysis, learnings, and clear recommendations. Good results documentation turns individual experiments into organizational knowledge that improves future decision-making. ## When to Use - After an A/B test or experiment reaches statistical significance - When an experiment is ended early (for any reason) - To communicate findings to stakeholders who weren't involved - During decision-making about whether to ship, iterate, or kill a feature - To build a repository of learnings that inform future experiments ## When NOT to Use - The experiment is not designed or run yet -> use `measure-experiment-design` - The results demand a direction decision -> use `iterate-pivot-decision`; this skill reports the evidence, that one decides - You want the transferable learning banked for the organization -> follow up with `iterate-lessons-log` - Your data is survey responses, not a controlled experiment -> use `measure-survey-analysis` ## Instructions When asked to document experiment results, follow these steps: 1. **Summarize the Experiment** Provide context: what was tested, when it ran, how much traffic it received. Link to the original experiment design document if one exists. 2. **Restate the Hypothesis** Remind readers what you believed would hap...