Dynamic minimum detectable effect
Split has now launched dynamic minimum detectable effect where statistically significant results can be obtained based on the dynamic relationship between the observed effect size and observed sample size of experiment metrics. For example, Split will indicate the sample size required for the given effect size to be statistically significant. Alternatively, we will also indicate the effect size needed for the results to be statistically significant with a given number of samples.
Customers can now set how long an experiment should run before results can be reviewed. Split will produce a warning on the metrics impact dashboard if an experiment has not met the minimum period.