A/B testing (also called split testing) is a method of comparing two versions of a webpage, email, or other content to see which performs better. You show version A to half your audience and version B to the other half, then measure which version achieves better results.
How A/B Testing Works
- Hypothesis: "Changing the button color from blue to green will increase clicks"
- Create variations: Original (A) and modified version (B)
- Split traffic: Randomly show each version to different visitors
- Measure results: Track conversion rates for each version
- Statistical analysis: Determine if the difference is significant
- Implement winner: Roll out the better-performing version
What to Test
Headlines
Often the highest-impact test. Different angles, lengths, emotional appeals.
Call-to-Action
- Button text ("Buy Now" vs. "Add to Cart")
- Button color, size, placement
- Form length and fields
Images
- Product photos vs. lifestyle images
- People vs. no people
- Image placement
Layout
- Single column vs. multi-column
- Above the fold content
- Navigation structure
Copy
- Long form vs. short form
- Tone (formal vs. casual)
- Social proof placement
A/B Testing Rules
Test One Thing at a Time
If you change the headline AND the button, you won't know which caused the difference.
Get Statistical Significance
Don't declare a winner too early. Most tools show when you have enough data.
Run Tests Long Enough
Account for day-of-week and time variations. Usually at least 1-2 weeks.
Don't Peek and Stop Early
Stopping tests when they look positive leads to false positives.
A/B Testing Tools
- Google Optimize (free, now deprecated)
- Optimizely: Enterprise-grade
- VWO: Visual editor
- Statsig: Feature flags + experiments
Beyond A/B: Multivariate Testing
Test multiple variations of multiple elements simultaneously. Requires much more traffic but can find optimal combinations.