CUPED Explained

CUPED is an algorithmic tool used to increase the speed and accuracy of experimentation programs by leveraging pre-experiment data to explain away variance in result data. It helps reduce standard error, making it possible to observe statistically significant results even with relatively small effects. CUPED works by normalizing post-experimental values based on pre-experimental metrics, allowing for a more accurate estimation of the experiment effect. The algorithm is most effective when applied to existing user experiments with access to historical data, and its ability to adjust values is based on the correlation between a metric and its past value for the same user. CUPED has been successfully used in various companies, including Facebook and Optimizely, to improve experimentation outcomes.

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