A/B testing is a controlled experimentation method used to compare two or more variants of a digital experience to determine which performs better against a defined metric.
It is commonly used to validate assumptions and inform data-driven decisions.
Examples in Action
- Testing alternative headlines or messaging
- Comparing layout or design variations
- Evaluating different calls to action
- Assessing changes to form structure or flow
Typical Outcomes / Results
- Increased confidence in optimisation decisions
- Evidence-based validation of changes
- Incremental performance improvements over time
- Reduced reliance on subjective opinion
This definition reflects standard experimentation practices across digital optimisation programs.