Current A/B testing methodologies are old, academic, and require a lot of manual lift. This results in teams running just a handful of product experiments in parallel. Instead of focusing on building new features, teams are burdened with building hypotheses, allocating samples, isolating experiments, collecting metrics, running backward analysis, and waiting for weeks for statistical significance. Statsig’s platform makes it easy to turn every feature release into an experiment. By continuously monitoring 100s of metrics, Statsig provides meaningful data analytics, to inform causal analyses, and provide the actionable insights needed to drive positive product impact.
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