CRO makes big promises. But the way people get to those 300% lifts in conversions is by being organized.
Here’s the most common problem I see when it comes to conversion rate optimization (CRO): Not putting enough energy into conducting the proper initial research into what to test.
A type of hypothesis testing where multiple variables are tested simultaneously to determine how the variables and combinations of variables influence the output. If several different variables (factors) are believed to influence the results or output of a test, multivariate testing can be used to test all of these factors…
A term used to describe test methods or algorithms that continuously shift traffic in reaction to the real-time performance of the test.
We lied to you. For years, we, as providers of an A/B testing tool, told you it was easy. We made a visual editor and pretty graphs and gave you wins on engagement or a lower bounce rate, but we did not really contribute to your bottom line.
Most A/B test and conversion optimization ideas have their beginnings in web analytics reports. And there are countless types of reports that can provide inspiration for meaningful A/B testing. But still, it is extremely hard to come up with a successful test hypothesis using only quantitative data.
If you’re reading this post, you already know how CRO (“conversion rate optimization”) can help you increase revenues and create better customer experiences. The problem now is: how do you decide what to test?
Confidence Interval: A range of values calculated such that there is a known probability that the true mean of a parameter lies within it.
Confidence Level: The percentage of time that a statistical result would be correct if you took numerous random samples.