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.
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.
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.
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.
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.
Testing multiple changes at once (Headline AND Image AND Button). It requires much more traffic than A/B testing.
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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