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According to LEO Digital Marketing:
A/B Split Testing takes the guesswork out of optimization by giving you hard data on what drives results. It allows you to test 2 different methods to see which performs best.
These values are similar except for one variation which might affect a user's behavior. A/B tests are widely considered the simplest form of controlled experiment. However, by adding more variants to the test, its complexity grows.
A/B Split Testing allows you to see which ad, webpage, or email design/copy will get you more results.
An example of this is when a company runs a Facebook ad targeting the same audience but with two different ads. One ad has a bright red call to action button while the other has a blue call to action button.
By targeting the same audience with the same ad copy and design other than the CTA button color the marketers now know that a red CTA button works better than a blue one in their ads. Now, that is a simple explanation. Some changes that can be made are much more complex or even more simplistic.
Another example is in web design. The graphic below shows the same website but with a small design difference. The design on the right has a bold black border around each feature and button while the design on the left has no border.
Setting up analytics on each page and making sure that each page takes you to a different page after taking the action you want them to you can assess which page got you more clicks, sales, or signups. Once you know which design gets you closer to your goal, you’ll want to implement it more frequently.