GrowthBook has significantly improved the performance of its experiment analysis queries, achieving up to twice the speed by implementing three main changes. First, the system now handles situations where users are exposed to multiple variations or dimension values more efficiently, by excluding such users from the analysis and flagging experiments where this issue exceeds 1% of users. Second, a new attribution model called "Experiment Duration" has replaced the "Multiple Exposures" model, increasing the number of conversions included in analyses while enhancing performance. Lastly, the elimination of multiple JOINs and GROUP BYs from SQL queries, facilitated by a robust testing infrastructure, has further streamlined the process, reducing query length and complexity while maintaining accuracy. These updates represent only the beginning of GrowthBook's ongoing efforts to enhance performance.