Data and Audience
A/B testing is a method of comparing two different variables to see which one performs better when randomly shown to an audience. While commonly used by the modern marketer, the practice of A/B testing has been used for over 100 years according to Kaiser Fung, founder of Columbia University Applied Analytics Program. There are many applications for A/B testing to compare two different versions of content to see which one is more successful at achieving your desired goal. Maybe a blog post with ‘headline A’ generated twice as many clicks as the same blog with ‘headline B’, which would indicate ‘headline A’ was more successful. This method can be used with everything from website copy to images, designs, colors, subject lines, and even calls to action. A/B testing allows you to understand which image/color/headline/button yielded the highest number of conversions, opens, clicks, registration, or any other desired action.