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    All Labs
    Stats
    Two-proportion z-test
    Wilson CI
    Sample size
    No stats degree

    Conversion Rate Calculator

    Real frequentist math with no library: a two-proportion z-test for the p-value, Wilson score intervals for each arm (reliable at low counts where the normal approximation misleads), and the standard sample-size formula for a target relative lift at 80% power. Runs entirely in the browser.

    Conversion Rate Calculator

    Two-proportion z-test
    Wilson CI
    Sample size
    No stats degree

    A — Control

    5.00%

    95% CI 4.42% – 5.65%

    B — Variant

    6.22%

    95% CI 5.57% – 6.94%

    B wins at 95% confidence
    p = 0.0093

    Relative lift

    +24.4%

    Absolute change

    +1.22 pts

    z-score

    2.602

    The two confidence intervals still overlap— the data can't yet rule out that both arms convert identically.

    To detect a 10% relative lift off a 5.00% base at 95% confidence and 80% power you need 31,233 visitors per arm — about 26,443 more each.

    How it works

    1. Enter visitors and conversions for control (A) and variant (B)
    2. A two-proportion z-test gives the p-value against your confidence level
    3. Wilson score intervals bound each arm's true rate — overlapping bars mean 'not yet'
    4. The sample-size formula says how much traffic you still need for your target lift

    From real client work

    Most 'winning' tests we're asked to review were called early. This is the check we run first: a lift that looks decisive at 200 conversions often has confidence intervals wide enough to contain no difference at all. The math is standard — the discipline is refusing to ship until the intervals separate.

    See the growth tooling