How to Run an A/B Test
Design, execute, and analyze A/B tests for data-driven optimization of your website and campaigns.
What You'll Learn
This intermediate-level guide walks you through how to run an a/b test step by step. Estimated time: 10 min.
Step 1: Form a hypothesis
State clearly what you're testing, why you expect it to improve, and what metric you'll measure.
Step 2: Calculate sample size
Determine how much traffic you need for statistically significant results using a sample size calculator.
Step 3: Create test variants
Build your control and variant versions, changing only one element at a time for clear attribution.
Step 4: Run the experiment
Split traffic evenly and let the test run until you reach statistical significance — don't peek early.
Step 5: Analyze and act
Review results, document learnings, implement the winner, and plan your next experiment.
Frequently Asked Questions
How long should I run an A/B test?▾
Run until you reach 95% statistical significance, typically 2-4 weeks. Never stop a test early because one variant looks better — that's false significance.
What should I A/B test?▾
Start with highest-impact elements: headlines, CTAs, pricing displays, and page layouts. Test one element at a time for clear results.
What tools should I use?▾
Google Optimize is free but limited. PostHog and VWO offer more features. For simple tests, Vercel Edge Middleware works well with Next.js.