Conversion Rate Confidence Interval Calculator
Turn conversions and visitors into a conversion rate with a confidence interval, so you know the true rate range, not just the point estimate.
How it works
p = conversions ÷ visitors · SE = √[ p(1 − p) ÷ n ] · CI = p ± z · SE (z = 1.96 at 95%)
A single conversion rate is only a sample estimate — the confidence interval shows the band the true long-run rate probably lives in. This uses the normal (Wald) approximation: the margin of error is the critical z-value times the standard error, and the interval is clamped to the 0–100% range. Narrower intervals come from more visitors, so a 4.5% rate from 1,000 people is far shakier than the same rate from 100,000.
Worked example
45 conversions from 1,000 visitors → p = 4.5%. SE = √[0.045·0.955 ÷ 1000] ≈ 0.00655. At 95% confidence the margin of error is 1.96 × 0.00655 ≈ 1.28%, giving an interval of about 3.2% to 5.8%.
Sources: Binomial proportion confidence interval — Wikipedia
Frequently asked questions
What does a 95% confidence interval mean here?
If you repeated this measurement many times, about 95% of the intervals you computed would contain the true conversion rate. It is a statement about the reliability of the method, not a 95% probability for this one interval.
Why is the interval so wide with few visitors?
The margin of error shrinks only with the square root of the sample size, so quadrupling visitors halves the width. With a few hundred visitors the interval is naturally broad — treat early rates as rough.
Is this accurate for very low conversion rates?
The normal approximation weakens when the rate is near 0% or 100% or when you have very few conversions. In those cases a Wilson or exact (Clopper–Pearson) interval is more reliable, but for typical rates with hundreds of conversions this is fine.
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This calculator is for educational purposes. Double-check important results before acting on them.