A/B testing is how the best companies make decisions. Instead of guessing what works, they test it. Instead of debating opinions, they look at data. Here's everything you need to know to get started.
The Simple Definition
A/B testing (also called split testing) is showing two different versions of something to different people, then measuring which version performs better.
How A/B Testing Works
Imagine you're not sure whether your button should say "Buy Now" or "Add to Cart." Instead of guessing, you test it:
Split Traffic
50% of visitors see "Buy Now" (Version A)
50% see "Add to Cart" (Version B)
Measure Results
Track how many people click each button
Pick the Winner
Use the version that converts more
What Can You A/B Test?
Almost anything on your website can be tested. The most common tests include:
Headlines
"Save Money" vs "Cut Costs by 50%"
Call-to-Action Buttons
"Sign Up Free" vs "Start Your Trial"
Images
Product photo vs lifestyle image
Page Layout
Form above fold vs below fold
Pricing
$99/month vs $9/month billed annually
Social Proof
Customer logos vs testimonial quotes
Why A/B Testing Matters
20-30%
Average conversion lift from successful tests
70%
of tests don't produce winners — and that's okay
$0
Cost of running a test vs cost of a bad decision
Here's the thing: most of your ideas won't work. That's not pessimism — it's reality. Studies show that about 70% of A/B tests don't produce significant winners.
But that's exactly why testing matters. Without testing, you'd implement 10 ideas and maybe 3 would help. With testing, you only implement the 3 that actually work — and avoid the 7 that would hurt.
Common A/B Testing Mistakes
Stopping tests too early
Early results are unreliable. Wait for statistical significance.
Testing too many things at once
If you change 5 things, you won't know which one worked.
Testing low-impact changes
Button color rarely matters. Headlines and value props do.
How to Run Your First A/B Test
Pick one thing to test
Start with your highest-traffic page. Test the headline or main CTA.
Create a hypothesis
"Changing X to Y will increase Z because [reason]."
Set up the test
Use a tool like ExperimentHQ to create your variant.
Wait for results
Run for at least 1-2 weeks. Don't peek daily.
Implement the winner
If you have a winner, roll it out. If not, learn and test again.
Start Testing Today
A/B testing isn't complicated. It's just a systematic way to learn what works for your specific audience. The companies that test consistently outperform those that guess.
You don't need a statistics degree. You don't need a big budget. You just need to start.