A/B Test Setup Checklist
Make data-driven decisions with properly structured tests
A/B testing is the difference between guessing what works and knowing what works. But a badly designed test is worse than no test at all because it gives you false confidence in wrong conclusions.
This checklist ensures every test you run follows proper methodology, from hypothesis formation to statistical analysis. Eevy AI automates much of this with its genetic algorithm approach, but understanding the fundamentals makes you a better optimizer.
Hypothesis and Planning
Write a specific hypothesis: changing X to Y will improve Z by N% because of a specific reason. Vague tests produce vague results.
Select one primary KPI (conversion rate, AOV, revenue per visitor) and define what success looks like before starting.
Use a sample size calculator to determine how much traffic you need. Running tests too short produces unreliable results.
Based on your traffic, calculate how many days the test needs to reach significance. Account for day-of-week and seasonal variations.
Record the hypothesis, variations, primary metric, sample size, and expected duration before launching.
Technical Setup
Build your control and variant(s) in Eevy AI. For review layout tests, use the genetic algorithm to automatically evolve winning combinations.
Confirm that conversion events fire correctly for all variations. Place test orders and verify they register in your analytics.
Split traffic evenly between variations. Eevy AI handles this automatically with its attribution system.
Preview all variations on a staging environment or password-protected page before going live.
Ensure test variations do not introduce meaningful page speed differences, which could confound results.
Execution and Monitoring
Start the test and immediately verify both variations display correctly to real visitors. Check mobile and desktop.
Do not make decisions based on the first few days of data. Early results are unreliable due to small sample sizes.
Check daily for error spikes, layout breaks, or tracking failures. Pause the test if anything looks wrong.
Do not modify variations, pricing, or other page elements while a test is running. This invalidates results.
Analysis and Action
Do not call a winner until you reach 95% confidence. Eevy AI shows significance indicators in the dashboard.
Analyze results by device type, traffic source, and customer type. A variation may win overall but lose on mobile.
Record what you tested, what won, the confidence level, and what you learned. Build an institutional testing knowledge base.
Roll out the winning variation to 100% of traffic. With Eevy AI, this happens automatically as the algorithm converges.
Use insights from this test to inform your next hypothesis. Continuous testing compounds gains over time.
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