3 articles
PricingUse cohort analysis to run pricing experiments that isolate causal effects from confounders. Covers cohort design, measurement windows, holdout groups, and interpreting cohort-level pricing signal.
PricingBuild pricing A/B tests that produce defensible conclusions. Covers hypothesis framing, metric selection, sample sizing, runtime control, and common design failures that invalidate results.
PricingCalculate the sample size required to detect pricing test effects with statistical confidence. Covers power analysis fundamentals, the effect of baseline conversion rate on required sample, runtime estimation, and the cost of underpowered tests.