Etsy leverages online experimentation to improve buyer and seller experiences. Running experiments can take weeks, hindering rapid iteration. Variance reduction techniques, like CUPED, help shorten experiment duration. Etsy initially implemented CUPED in 2021, achieving modest variance reduction. They then adopted CUPAC, building on CUPED by using machine learning to predict outcome metrics. CUPAC uses pre-experiment data in a non-linear model for better predictions. This improves the accuracy and speed of experiment results. Etsy trains LightGBM models with over 100 pre-experiment features for CUPAC. The CUPAC implementation resulted in a significant increase in variance reduction. This led to an average reduction of 3 days in experiment duration, enabling more frequent testing. Etsy plans to expand CUPED and explore additional variance reduction methods.