Statsig has introduced CUPED, a technique to enhance the precision of experimental data by leveraging pre-experimental data to reduce variance and pre-exposure bias, automatically integrating it into customers' experiments. This method, originally publicized by Microsoft, optimizes the evaluation of key metrics by narrowing confidence intervals, lowering p-values, and decreasing sample sizes and experiment durations. CUPED works by utilizing users' past behavior to adjust their metrics during experiments, thus explaining away some variance and correcting pre-exposure bias. The implementation has shown that around 9% of experiments gained statistical significance post-CUPED application, while 2% saw a decrease in significance, indicating a reduction in false positives. As companies grow and track metrics more consistently, the efficacy of CUPED is expected to increase, especially for experiments involving stable metrics over time. Statsig's rollout includes a new results card to display CUPED-adjusted metrics, encouraging users to explore this tool for more confident and expedited experimentation.