What is A/B Testing?
A randomized experimentation process where two or more versions of a variable (web page, page element, etc.) are shown to see which one performs better.
Deep Dive
Also known as split testing. You might show 50% of visitors a red button and 50% a green button to see which gets more clicks.
It removes opinion from design decisions and allows you to make data-backed improvements to conversion rates.
Key Takeaways
- Test one variable at a time for accurate results.
- Requires statistical significance to trust data.
- Essential tool for CRO.
- Use tools like Google Optimize (sunsetted) or VWO.
Why This Matters Now
A/B testing is the scientific method applied to business. Hypothesis -> Experiment -> Conclusion.
Before A/B testing, the 'HiPPO' (Highest Paid Person's Opinion) decided the website design. Now, the data decides.
Common Myths & Misconceptions
You can test anything.
Reality:You need traffic. Testing a page with 10 visitors a month is useless; the data is random noise. You need hundreds of conversions for significance.
It's a one-time thing.
Reality:The best companies (Amazon, Netflix) never stop testing. They run thousands of tests a year.
Real-World Use Cases
Netflix: They A/B test the thumbnails for movies. You might see a different picture for 'Stranger Things' than your friend, just to see which one makes you click.
Politicians: Testing email subject lines to see which one generates more donations.
Frequently Asked Questions
What is Multivariate Testing?
Testing multiple changes at once (Headline AND Image AND Button). It requires much more traffic than A/B testing.
Does it hurt SEO?
No, as long as you don't 'cloak' (show different content to Googlebot than to users) and use proper canonical tags.
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