CRO/UX
Hypothesis & Design
Every test starts with a clear hypothesis backed by data. Our design team creates variants that isolate the variable we're testing.
Our hypothesis & design capabilities
Every test we run starts with a clear, data-backed hypothesis that connects an observation to a proposed change and a measurable expected outcome. Our design team then creates test variants that isolate the variable being tested, ensuring clean results that generate genuine learning.
- Data-backed hypothesis development
- Test variant design and prototyping
- Prioritisation using ICE/PIE frameworks
- Wireframing and UI design for tests
- Test documentation and knowledge base
- Stakeholder alignment and approval workflows
The impact of getting this right
Clear hypotheses mean every test generates actionable learning
Prioritisation frameworks focus effort on highest-impact tests
Professional design ensures test variants don't introduce bias
Documented learnings compound into a valuable knowledge base
Frequently asked questions
Common questions
A good hypothesis connects a specific observation (from data), to a proposed change, to a measurable expected outcome. E.g., 'Adding social proof above the CTA will increase checkout starts by 10% because session recordings show users hesitating at this step.'
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