A/B Test Sample Size Calculator
Calculate the required sample size for statistically significant A/B tests. Input baseline rate, minimum detectable effect, significance, and power.
Viral coefficient, NPS, cohort retention, A/B testing, and conversion calculators. Browse our free growth tools below — no sign-up required.
Calculate the required sample size for statistically significant A/B tests. Input baseline rate, minimum detectable effect, significance, and power.
Calculate your product activation rate by measuring the percentage of signups who complete a key action. Benchmark and optimize your onboarding funnel.
Calculate cohort retention rates across time periods. Visualize user retention curves, identify drop-off points, and benchmark retention by cohort size.
Build and analyze a multi-step conversion funnel with up to 6 stages. Calculate step-by-step and overall conversion rates with visual funnel display.
Calculate your DAU/MAU stickiness ratio to measure user engagement. Benchmark against industry standards and model the impact on growth metrics.
Calculate how many active users adopt specific features. Compare adoption rates across features to prioritize development and identify underused capabilities.
Calculate the K-factor (viral coefficient) for your product. Model compounding user growth across generations and optimize invitation and conversion rates.
Calculate Net Promoter Score from survey data. Analyze promoter, passive, and detractor distributions with benchmarks and improvement modeling.
Calculate your product-market fit score using the Sean Ellis test. Measure what percentage of users would be "very disappointed" without your product.
Test whether your A/B test results are statistically significant using a two-proportion Z-test. See p-value, confidence interval, and effect size.
Calculate your product's median time to value (TTV) from signup to first value moment. Analyze onboarding efficiency and set TTV reduction targets.
Calculate the viral coefficient (K-factor) of your product. Model referral-driven growth, project user curves, and determine if K > 1 for true virality.