Etsy uses experiments to test ideas, like offering free ice cream with purchases, to boost sales. To better understand user behavior, they use segmentation, which allows analysis based on different user groups. Previously, Etsy's platform had limited pre-defined segmentations, hindering in-depth analysis and slowing down insights. The team developed a Segmentation Library allowing experimenters to define their own segments, which was a slow and complex process. This new approach allows users to create segmentations using SQL queries and join keys, making them easy to understand and share. Before deployment, these custom segmentations go through a validation process to ensure accuracy and safety. Dynamic task generation in the data pipeline enabled automatic processing of new segmentations without code changes. This transformation resulted in a significant increase in the number of available segmentations. The improved system provides quicker and deeper insights, empowering teams to make better data-driven decisions. Overall, these changes have made Etsy's experimentation process more flexible and efficient.