/define-hypothesis

name: define-hypothesis
description: 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.
license: Apache-2.0
metadata:
  phase: define
  version: "2.1.0"
  updated: 2026-06-10
  category: ideation
  frameworks: [triple-diamond, lean-startup, design-thinking]
  author: product-on-purpose

<!-- 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 specific about the intervention - vague hypotheses can't be tested.

2. **Identify the Target User** Define who this hypothesis applies to. A hypothesis about "users" is too broad. Specify the segment: new users in their first week, power users with 10+ sessions, churned users returning, etc.

3. **Define the Expected Outcome** What behavior change or result do you expect? Frame it in terms of user actions (complete onboarding, make a purchase, return within 7 days) rather than internal metrics when possible.

4. **Set Success Metrics** Choose a primary metric that directly measures the expected outcome. Include secondary metrics that provide context and guardrail metrics that ensure you're not causing harm elsewhere.

5. **Describe Validation Approach** How will you test this hypothesis? A/B test, user interviews, prototype testing, cohort analysis? Be specific about sample size, duration, and statistical requirements.

6. **Document Risks and Assumptions** What could invalidate this hypothesis beyond the test results? What are you assuming to be true that you haven't validated?

Output Format

Use the template in `references/TEMPLATE.md` to structure the output. A complete hypothesis document fills every template section: Hypothesis Statement; Background & Rationale; Target User Segment; Success Metrics; Validation Approach; Risks & Assumptions; and Timeline.

Quality Checklist

Before finalizing, verify:

• [ ] Hypothesis is falsifiable (possible to prove wrong)
• [ ] Success metric has a specific numeric target
• [ ] Target user segment is clearly defined
• [ ] Validation approach is practical and time-bound
• [ ] Pass/fail criteria are unambiguous
• [ ] Hypothesis doesn't assume the solution works

Examples

See `references/EXAMPLE.md` for a completed example.