define-hypothesis

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Defines a testable hypothesis with clear success metrics and a validation approach. Use when forming assumptions to test or aligning a team on what success looks like, before any experiment is designed. To design the A/B test or experiment that will validate the hypothesis, use measure-experiment-design.

AI & Automation 557 stars 73 forks Updated today Apache-2.0

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<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 --> # Hypothesis A hypothesis is a testable prediction about how a change will affect user behavior or business outcomes. It transforms assumptions into explicit statements that can be validated or invalidated through experimentation. Well-formed hypotheses prevent teams from building features based on untested beliefs and create shared understanding of what success looks like. ## When to Use - After problem framing, before committing to a solution - When designing experiments or A/B tests - When team members have differing assumptions about user behavior - Before investing significant engineering resources in a feature - When pivoting direction and need to validate the new approach ## When NOT to Use - You are ready to design the actual A/B test (variants, sample size, duration) -> use `measure-experiment-design`; this skill frames what to test, not how - The problem itself is still unframed -> use `define-problem-statement` first - You want to organize many assumptions and ideas into a discovery structure -> use `define-opportunity-tree` - The team needs the full business-model picture, not one testable claim -> use `foundation-lean-canvas` ## Instructions When asked to create a hypothesis, follow these steps: 1. **State the Belief** Articulate what you believe will happen. Use the structured format: "We believe that [action/change] for [target user] will [expected outcome]." Be specifi...

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

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