An A\/B test is a technique that consists of developing two versions of the same element or product, with the sole intention of measuring which of these two versions works better.<\/p>\n
A\/B testing has many different uses in digital marketing. Some of the most common (though not the only ones) are:<\/p>\n
This method consists of developing two versions of the same element\/product before launching it on the market. It applies to both physical and digital products. In our case, we will focus on an example based on creating an A\/B test to find the best subject line<\/a> between two candidates, so that an email marketing<\/a> campaign delivers the best ROI.<\/p>\n Naturally, you can run multiple A\/B tests to take more versions into account, but an A\/B test is usually used to decide between the two “finalist” options.<\/p>\n To do this, we create two subject lines for a newsletter from an animal shelter that wants to raise funds among its members.<\/p>\n One includes the name of the email’s recipient<\/a> and a question whose answer is obvious to the contact list it is sent to: “Name, don’t you just love animals?” The other version is more direct and aims to get the recipient to read the email: “The lives of our animals depend on you alone.” The content of the email is exactly the same; only the subject line changes.<\/p>\n Then, to run the A\/B test, we take a percentage of the total list of subscribers we want to send the newsletter to, for example 20%, and send 10% of them the subject line “Name, don’t you just love animals?” The remaining 10% receive the one with the subject line “The lives of our animals depend on you alone.”<\/p>\n After 24 hours, for example, we review the A\/B test statistics and determine which version got the most opens. The subject line with the most opens is the winner of the A\/B test, and the newsletter<\/a> is sent to the remaining 80% of subscribers using that winning subject line.<\/p>\n In general, incorporating A\/B tests into any marketing strategy brings you numerous advantages:<\/p>\n2. Advantages of A\/B testing<\/h2>\n
\n
Related entries<\/h2>\n\n
\n