Same testing options, same results, 90% more conversions while you wait.

A/B Tests are fundamentally flawed.

1 of 3 possible outcomes of a conventional A/B test significantly hurts your conversion rate. changes the game of testing and maximizes conversions during the test. There is no longer any harm in testing "bad" ideas.

A/B Tests require massive amounts of traffic.

For the average website, a 10% increase in conversion rate takes a minimum of 100,000 visitors to reach a 95% confidence interval in a split test. But, the average website doesn't have that much traffic. It could take months to be confident in your changes. eliminates the need to worry about statistical significance. We use a "leaning" algorithm that tests more often when confidence is low, and stops testing all together when confidence reaches 99%.

A/B Tests don't take business variables into account.

High conversion rates aren't necessarily good for business. If your goal is lead generation, higher conversion rates are only good if the leads are higher quality too. gives you the option to run tests based on conversion rate alone or to use other business metrics to get results that drive business, not stats.

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