What is an A/B Test? - Deepstash

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# What is an A/B Test?

netflixtechblog.com

At Netflix, running A/B tests, where possible, allows us to substantiate causality and confidently make changes to the product knowing that our members have voted for them with their actions.

An A/B test starts with an idea — some change we can make to the UI, the personalization systems th...

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To run the experiment, we take a subset of our members, usually a simple random sample, and then use random assignment to evenly split that sample into two groups. Group “A,” often called the “control group,” continues to receive the base Netflix UI experience, while Group “B,” often called the “...

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With many experiments, including the Upside Down box art example, we need to think carefully about what our metrics are telling us. Suppose we look at the click-through rate, measuring the fraction of members in each experience that clicked on a title. This metric alone may be a misleading measur...

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Because we create our control (“A”) and treatment (“B”) groups using random assignment, we can ensure that individuals in the two groups are, on average, balanced on all dimensions that may be meaningful to the test. Random assignment ensures, for example, that the average length of Netflix membe...

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A/B tests let us make causal statements. We’ve introduced the Upside Down product experience to Group B only, and because we’ve randomly assigned members to groups A and B, everything else is held constant between the two groups. We can therefore conclude with high probability (more on the detail...

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With the Top 10 example, the hypothesis read: “Showing members the Top 10 experience will help them find something to watch, increasing member joy and satisfaction.” The primary decision metric for this test (and many others) is a measure of member engagement with Netflix: are the ideas we are te...

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