A/B Test Sample Size Calculator
Estimate visitors per variant from baseline conversion rate, MDE, confidence, and power.
Also useful for: ab test sample size calculator split test sample size conversion test calculator minimum detectable effect calculator A/B Test Sample Size Calculator
A/B Test Sample Size Calculator
Runs in your browser. Inputs are not uploaded.A/B Test Sample Size Calculator Example Run
Estimate visitors per variant before launching a test.
Sample inputs Experiment Baseline conversion rate: 5 Minimum detectable effect: 10 Statistics Confidence: 95% Power: 80% Generated result Summary: Estimated 31,243 visitors per variant for this A/B test. Stats - Per Variant: 31243 - Total: 62486 Issues - No issues found. Output Baseline conversion rate: 5.00% Minimum detectable effect: 10.0% relative Target variant rate: 5.50% Sample size per variant: 31,243 Total two-variant sample: 62,486
What the A/B Test Sample Size Calculator Checks
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Baseline conversion rate
The current conversion rate anchors the sample-size estimate.
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Relative MDE
Minimum detectable effect is treated as a relative lift over baseline.
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Confidence and power
Common confidence and power settings select the z-values used in the approximation.
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Per-variant and total sample
The output shows both one-variant and two-variant sample needs.
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Planning approximation
The math is for planning and does not replace a full experiment-design review.
A/B Test Sample Size Calculator Questions
- Q: Does the A/B test sample size calculator upload my experiment assumptions? A: No. Inputs are processed in your browser, and pasted content is not sent to analytics or a server.
- Q: What should I paste into the A/B test sample size calculator? A: Enter baseline conversion rate, minimum detectable effect, confidence, and power.
- Q: What can I copy or download? A: You can copy the estimated sample size per variant and total sample.
- Q: What does the A/B test sample size calculator not verify? A: It does not handle sequential testing, multiple comparisons, seasonality, allocation imbalance, or non-binomial metrics.
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Updates
- v1.0.0 New 2026-05-17: Initial two-variant sample size estimator with confidence and power controls added.