Today’s session by Scaler is an insightful discussion on A/B testing by Nitish Jaipuria (Instructor, DS & ML). Join India's number one outcome-focused Data Science and Machine Learning Program now: [ Ссылка ]

What is A/B testing?
A/B testing, also known as split testing, refers to a randomised experimentation process wherein two or more versions of a variable (web page, page element, etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drive business metrics. Essentially, A/B testing eliminates all the guesswork out of website optimization and enables experience optimisers to make data-backed decisions. In A/B testing, A refers to ‘control’ or the original testing variable. Whereas B refers to ‘variation’ or a new version of the original testing variable. The version that moves your business metric(s) in the positive direction is known as the ‘winner.’ Implementing the changes of this winning variation on your tested page(s) / element(s) can help optimise your website and increase business ROI.

The following topics are covered in this A/B testing tutorial:

0:00 - Introduction
0:29 - What is A/B testing?
2:20 - Practical solution walkthrough
3:45 - A/B testing process

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