In data science A/B Test is a method of measuring the effectiveness of altering one characteristic of a marketing asset such as a web page, a banner advertisement, or an email.
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In data science an elementary randomised control experiment is A/B testing. It is a method for contrasting two variations of a variable to see which performs better in a regulated setting.
Let's say, for example, that you run a business and want to boost product sales. You could divide the products in the aforementioned scenario into A and B parts. Here, A won't change, but you can significantly alter B's packaging. You now attempt to determine which is performing better based on the responses from customer groups who used A and B, respectively.
It is a hypothetical testing procedure in data science used to make judgments about population parameters based on sample statistics.
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