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BRA/B & Split Test Duration Calculator
Built with ❤️ for testing, optimization, UX, CRO, and design teams.
Average number of daily visitors who will participate in the test (control + variation)
Estimated existing conversion rate (%)
Minimum improvement in conversion rate you want to detect (%)
Number of variations/combinations (including control)
Traditional A/B testing
Using Frequentist Statistics
108
days
VWO SmartStats
Using Bayesian Statistics
33
days
69% FASTER!
Why does VWO run on Bayesian Statistics?
Intuitive Test Reports
We realized our non-statistical users frequently (and wrongly) interpreted the frequentist p-value as a Bayesian posterior probability (the probability that variation is better than control). So we built the industry’s first Bayesian statistical engine that gives you an easily understandable result. An intuitive result ensures that you don’t make a mistake while A/B testing revenue or other critical KPIs.
No Sample Sizing Required
VWO SmartStats relies on Bayesian inference which unlike a frequentist approach doesn’t need a minimum sample size. This allows you to run A/B tests on parts of your website or apps that might not get a lot of traffic to improve them. However, getting more traffic on your tests allows VWO to determine your conversion rates with more certainty allowing you to be more confident about your test results.
Actionable Results, Faster
VWO SmartStats was engineered keeping one key metric in mind: Speed. We have traded-off some accuracy for speed, not a lot, just a tiny bit, enough to get quicker results without impacting your bottom line. This frees up your time enabling you to test more. Also, on the off chance that you would want to be absolutely and completely sure, we calculate the maximum potential loss you'd be taking, and you can decide if the loss value matches your risk appetite.
Frequently Asked Questions
This is the conversion rate of the existing version of your website. You can use your analytics tool or VWO Goals to get this estimate. If your test is targeted to a segment, you should consider the same segments when calculating the conversion rate.
This is the improvement you want to achieve by running this test. Based on the hypothesis you are testing you can decide how much uplift you care about.
The duration will be estimated based on the amount of traffic that the variation with the lowest share will get. Once this variation has the required number of visitors, the test should reach statistical significance.
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VWO has been so helpful in our optimization efforts. Testing opportunities are endless and it has allowed us to easily identify, set up, and run multiple tests at a time.
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As the project manager for our experimentation process, I love how the functionality of VWO allows us to get up and going quickly but also gives us the flexibility to be more complex with our testing.
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