Hypothesis Generation
A systematic approach to creating testable assumptions about user behavior, needs, and service solutions that can be validated through research and experimentation.
- Convert assumptions into testable hypotheses
- Structure thinking for experimental validation
- Identify critical assumptions that need testing
- Plan systematic learning and validation
- Reduce risk by testing before building
- Enable evidence-based design decisions
- Create framework for iterative learning
- Hypotheses generated
- Testable assumptions
- Foundation for experimentation
- Make hypotheses specific and measurable
- Focus on riskiest assumptions first
- Design experiments that can prove hypotheses wrong
- Keep test costs proportional to risk
- Document all assumptions, not just obvious ones
- Update hypotheses as you learn
- Share learnings across team regularly
- Use results to inform next design decisions
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