Boost Campaign Performance with A/B Tests
This mock variant highlights the importance of structured experiments and rapid iteration.
- Start with a single hypothesis.
- Keep creatives consistent across channels.
- Measure lift over at least one full conversion cycle.
Why A/B Testing Matters
A/B testing allows you to make data-driven decisions rather than relying on gut feelings. Even small improvements in conversion rate compound significantly over time.
Setting Up Your Control Group
A well-defined control group is the foundation of any reliable experiment. Without it, you cannot measure true lift.
Choosing the Right Metrics
Focus on primary metrics that directly reflect your goal. Secondary metrics help detect unintended side effects.
- Click-through rate
- Conversion rate
- Revenue per visitor
- Bounce rate
Avoiding Vanity Metrics
Pageviews and raw traffic numbers can be misleading. Always tie metrics back to business outcomes.
Statistical Significance and Sample Size
Running a test too short or with too small a sample produces unreliable results. Use a power calculator before launching.
Understanding P-Values
A p-value below 0.05 is a common threshold, but context matters. High-stakes decisions may warrant stricter confidence levels.
Dealing with Novelty Effects
Users sometimes react to change itself, not the variant. Run tests long enough to let initial excitement subside.
Iterating on Results
A winning variant becomes the new baseline. Continuous iteration compounds gains and keeps your funnel optimized over time.