Introducing experimental meta-analysis and the knowledge base
Blog post from Statsig
Experimentation's value grows as companies scale their experimentation culture, with some increasing their experiment velocity by 10-30 times in a year. As more experiments are conducted, aggregated data provides deeper insights, fueling a cycle of continuous learning and hypothesis generation. Companies like Whatnot, Notion, Rec Room, and Lime have significantly increased their experimentation rates, leading to broader insights about users and metrics that inform strategic decisions. Statsig has introduced new meta-analysis views to enhance this process, including tools for tracking experiment timelines, understanding metric correlations, and assessing metric impacts. These views, along with a searchable experiment knowledge base, help organizations document and share learnings, strengthen their experimentation culture, and set informed goals. Users can explore these insights through Statsig's platform, with support available for those seeking to deepen their understanding of experimentation strategies.