ow to test changes in conversion, bounce, and exit rates
Posted: Wed Jan 29, 2025 4:33 am
from the only ones. You can also test for statistically significant differences between segments (e.g. organic vs. paid search visits) or time periods (e.g. April 2013 vs. April 2014).
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It’s important to note, however, that this correlation does not imply causation. When we run split tests, we know that we can attribute any changes in results to the elements that differentiate the pages – after all, special care is taken to ensure that the pages are otherwise identical. If you’re comparing groups like organic versus paid search visitors, any number of other factors could be at play – organic search may have a lot of nighttime visits, for example, and conversion rates among nighttime visitors are quite high. Significance tests help establish whether there’s a cause for the change, but they can’t tell you what that cause is.
3. H
When we look at “metrics,” we’re really looking at averages of binary variables — someone either completed the target action or they didn’t. If we have a sample of 10 people with a conversion south africa consumer email list rate of 40%, we’re really looking at a table like this:
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We'll need this table, along with the mean, to calculate the standard deviation , a key component of statistical significance. However, the fact that each value in the table is either zero or one makes our job easier — we can avoid copying a huge list of numbers by using an A/B test confidence calculator, based on the mean and sample size. This is a tool from KissMetrics .
298-3.jpg
It’s important to note, however, that this correlation does not imply causation. When we run split tests, we know that we can attribute any changes in results to the elements that differentiate the pages – after all, special care is taken to ensure that the pages are otherwise identical. If you’re comparing groups like organic versus paid search visitors, any number of other factors could be at play – organic search may have a lot of nighttime visits, for example, and conversion rates among nighttime visitors are quite high. Significance tests help establish whether there’s a cause for the change, but they can’t tell you what that cause is.
3. H
When we look at “metrics,” we’re really looking at averages of binary variables — someone either completed the target action or they didn’t. If we have a sample of 10 people with a conversion south africa consumer email list rate of 40%, we’re really looking at a table like this:
298-4.jpg
We'll need this table, along with the mean, to calculate the standard deviation , a key component of statistical significance. However, the fact that each value in the table is either zero or one makes our job easier — we can avoid copying a huge list of numbers by using an A/B test confidence calculator, based on the mean and sample size. This is a tool from KissMetrics .