Free browser tool · No signup required
Cold email sample size estimator for one proportion
Estimate observations needed for a chosen absolute margin of error at approximately 95% confidence.
Prepare your inputs
This worksheet plans precision for one binary rate. Enter an anticipated percentage and a margin in percentage points. If the proportion is unknown, 50% uses the largest binomial variance.
Runs in this browser. Inputs are not sent by this tool or saved in browser storage. Start with the fictional example; use redacted text for reviews.
How it works
The approximation is n = 1.96² × p × (1−p) ÷ e², rounded upward. It assumes independent observations and does not apply a finite-population correction.
Worked example
At an assumed 50% proportion and a margin of five percentage points, the calculation returns 385 observations. That number does not establish the sample needed to detect a difference between two email variants.
Limits and interpretation
This is not an A/B-test power calculation. Rare outcomes, clustered contacts within companies, biased selection and repeated monitoring can require a different design. Review the actual study objective before using the estimate.
Examples are synthetic, not customer results. NIST: confidence intervals for a proportion