# A/B test duration calculator: how long to run · Funnel Critic > Source: https://funnelcritic.com/best/a-b-test-duration-calculator-for-landing-pages-how-long-to-run-a-split-test-on-y ## How many weeks a split test needs Enter daily visitors, the conversion rate you have now, and the lift you want the test to detect. Two variants, traffic split evenly By [Marta Ovalle](/authors/marta-ovalle), reviewed by [Funnel Critic Editorial](/authors/funnel-desk-editorial). Updated 21 October 2026. A winner called on day three can still be noise. How long an A/B test should run depends on the sample size you set before launch. Collect that many visitors on each variant, then divide by the traffic the page gets each day. The count uses the conversion rate you have now, the lift you want to detect, and the confidence level and statistical power you choose below. The usual plan is 95% confidence and 80% power, the power level [Evan Miller](https://www.evanmiller.org/the-low-base-rate-problem.html) says practitioners typically set. Divide the visitors both sides need by daily traffic and round up to whole weeks. ### Landing page split test calculator Two variants, half the traffic each. A third variant needs more visitors than this form will show. Daily visitors on the test page Baseline conversion rate, percent Type 3 for a page that converts 3 times in 100 visits. Relative lift to detect, percent Type 20 to look for a variant that converts 20 percent higher than today. Confidence and power Confidence 90% 95% 99% Power 80% 90% Calculate the runtime The figures for the entries above appear here. ### The sample size formula An A/B test sample size calculator is this equation, with your rate and your lift filled in. Four inputs set the count. The baseline conversion rate is the share of visitors who convert on the page today. The minimum detectable effect is how much higher the variant has to convert, as a fraction of the rate you already have. Significance and power sit in the optional settings under the form. At the default confidence level, the two-sided test uses α = 0.05\. Power, written 1 − β, is the chance you catch a lift that is really there. Those two settings are already filled in. The test is a two-sided two-proportion z-test, with traffic split evenly. The count for one side is: ``` n = ( z_a * sqrt(2 * p_bar * (1 - p_bar)) + z_b * sqrt(p1 * (1 - p1) + p2 * (1 - p2)) )^2 / (p2 - p1)^2 p_bar = (p1 + p2) / 2 ``` p1 is the current rate. p2 is the rate the variant has to reach. p\_bar is their average. z\_a is the normal quantile for the confidence you picked, and z\_b is the quantile for the power. [Evan Miller's rule of thumb](https://www.evanmiller.org/how-not-to-run-an-ab-test.html) starts from the same ingredients, variance p(1 − p) and the lift you are willing to miss. [Optimizely's planning note](https://docs.optimizely.com/experimentation-strategy/docs/use-minimum-detectable-effect-when-you-design-an-experiment) walks through a different case: a 15% baseline, 95% significance and a 10% relative lift, which they put at about 8,000 visitors per variation. That figure belongs to that example. ### A worked landing-page case Each stack is one variant. The test is ready to read once both have reached the line you set. Take a page converting at 3%, and a test aimed at a 20% relative lift. A 20% relative lift moves a 3% page to 3.6%, not to 23%. With the defaults above, and traffic split evenly, each side needs 13,914 visitors. Both sides together need 27,828. At 500 visitors a day, that collection takes 56 days, so the plan is 8 full weeks. The figure is how long it takes to gather the sample. It does not promise a winner. A holiday week, or a shift in where the clicks come from, can slow the count. ### How long beyond the math The sample can fill on a Tuesday. The decision still waits for a full set of weekdays. Weekday and weekend traffic both have to land in every variant. [Optimizely](https://docs.optimizely.com/experimentation-strategy/docs/how-long-to-run-an-experiment) recommends a minimum of one business cycle, seven days, so weekday and weekend behavior both appear in every variant. [Nielsen Norman Group](https://www.nngroup.com/articles/ab-testing/) recommends at least one to two weeks, even if you already have enough visitors for the sample, because people behave differently on different days of the week. The form takes the longer of the traffic math and seven days, then rounds up to whole weeks. The same vendor will not call a winner on a binary metric until the variation and the baseline each have at least 100 visitors and 25 conversions. That is a gate on their dashboard. It does not stand in for the power calculation above. End the test when the pre-planned count is in. A p-value under 0.05 before that point inflates false winners, which is why the runtime is fixed at the start. ### When your traffic cannot finish a test Paid-media buyers treat a short run as useful only when volume is already high. Under about a thousand conversions a month, a small copy test is too thin for a formal winner, and some of those teams skip the test and ship a larger redesign. Startup sites under a few thousand monthly uniques report the same wait on a headline change. If the required sample takes months to reach, widen the lift you are willing to detect, test a bigger change, or wait for more visitors. I would not hold a headline test that the form puts at several months. I would ship a larger redesign, which is what those low-traffic teams describe doing when a small copy test cannot finish, or I would wait until the page has more visitors. ### Where you run the split test The week count only helps if the plan includes testing and can hold the traffic for the whole run. [Unbounce](/reviews/unbounce/pricing) includes unlimited A/B testing from the Experiment plan, $149 a month on the list price or $112 a month billed annually, with a cap of 30,000 unique visitors a month. Starter and Build have no A/B testing. On [Unbounce's pricing page](https://unbounce.com/pricing/) a visitor counts once per month, by cookie, for each landing page, popup or sticky bar, and that count goes toward the cap. [Leadpages](/reviews/leadpages/pricing) includes manual A/B testing on Grow, $67 a month on the annual plan card, and does not cap traffic. Pro and Business are publish-only and have no A/B testing. The tiers are on [Leadpages' pricing page](https://www.leadpages.com/pricing). If the daily visitors you enter would take a capped plan over its monthly limit before the weeks are up, the runtime and the plan limit do not fit together. Price the plan you would actually be on with the [funnel tool cost calculator](/best/funnel-tool-cost-calculator-what-each-platform-costs-at-your-size). [Leadpages vs Unbounce](/compare/leadpages-vs-unbounce) sets the two side by side on testing and traffic. The [six-question picker](/best/which-funnel-tool-fits-you-a-6-question-picker) matches a builder to what you sell and how you get traffic. We rank split-testing tools separately on the [best-of hub](/best). How this site reads vendor pages and user reports is on the [methodology page](/methodology). ### Frequently asked questions How many visitors does each variant need? It depends on the rate you have, the lift you care about, and the confidence and power you set. The form prints the count for one side. No single visitor total fits every page. How long should an A/B test run at a few hundred visitors a day? Put that daily number in the form with your own rate and lift. One common landing-page case is walked through above. A higher rate or a wider lift finishes sooner. Does raising confidence from the default make the test longer? Yes. Stricter confidence allows fewer false winners, so the count goes up. The advanced fields offer 90, 95 and 99\. Moving power from 80 to 90 lengthens the run the same way. What does relative lift mean? It is a fraction of the conversion rate you already have. Type 20 if the variant should convert one fifth higher than the page does today. The form builds the second rate from that percent. Is 1,000 visitors enough to call a winner? Only when the lift you are hunting is large. A small copy change at a low rate needs far more than a thousand on each side. The dashboard gate above is a much lower bar than a powered sample. Can I stop when the dashboard looks significant? Wait until both sides have the count you calculated first. A significant readout before that sample is in is a reason to keep the test running. The weekday rule still applies after the count is collected. ### What we read #### Other sources 8 discussions and reviews read for this page. Quotes are excerpts; open a link to read the original in context. 1. \[em-power\] [Evan Miller: the low base rate problem ](https://www.evanmiller.org/the-low-base-rate-problem.html) Blog 2. \[em-rule\] [Evan Miller: how not to run an A/B test ](https://www.evanmiller.org/how-not-to-run-an-ab-test.html) Blog 3. \[opt-long\] [Optimizely: how long to run an experiment ](https://docs.optimizely.com/experimentation-strategy/docs/how-long-to-run-an-experiment) Docs 4. \[opt-sig\] [Optimizely: statistical significance ](https://docs.optimizely.com/experimentation-strategy/docs/statistical-significance) Docs 5. \[opt-mde\] [Optimizely: minimum detectable effect ](https://docs.optimizely.com/experimentation-strategy/docs/use-minimum-detectable-effect-when-you-design-an-experiment) Docs 6. \[nng\] [Nielsen Norman Group: A/B testing ](https://www.nngroup.com/articles/ab-testing/) Article 7. \[ub\] [Unbounce pricing ](https://unbounce.com/pricing/) Pricing 8. \[lp\] [Leadpages pricing ](https://www.leadpages.com/pricing) Pricing ### Related * [Best funnel and landing page tools](/best) * [Funnel tool cost calculator](/best/funnel-tool-cost-calculator-what-each-platform-costs-at-your-size) * [Six-question funnel tool picker](/best/which-funnel-tool-fits-you-a-6-question-picker) * [Unbounce pricing and visitor caps](/reviews/unbounce/pricing) * [Leadpages pricing](/reviews/leadpages/pricing) * [Leadpages vs Unbounce on testing and traffic](/compare/leadpages-vs-unbounce) * [How Funnel Critic researches tools](/methodology) Written by Marta Ovalle Editor, funnel & checkout tools Marta Ovalle leads Funnel Critic's coverage of funnel builders and checkout platforms. She reads the long-running threads where operators compare tools after months of live ad spend, cross-checks every claim against the vendor's own docs and pricing pages, and confirms prices with each vendor before a verdict goes live. She writes most of the roundups and pricing pages, and she decides when a ranking changes. [martao@funnelcritic.com](mailto:martao@funnelcritic.com) --- [Funnel Critic](/) Independent reviews and comparisons of funnel, page and checkout tools for startups running paid traffic. Ranked from real user reports and verified pricing. We may earn a commission when you buy through links on this page. It never affects our rankings. © 2026 Funnel Critic. Independent and reader-supported.