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

1

Clear hypotheses mean every test generates actionable learning

2

Prioritisation frameworks focus effort on highest-impact tests

3

Professional design ensures test variants don't introduce bias

4

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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Whether you're scaling up or shaking things up, we'd love to chat about how we can help. No hard sell - just a conversation about your goals.

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