Release Notes

December 7, 2018

Management Console

  • 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.
  • Review periods
    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.

Read more about this release in our blog

Subscribe to Updates

RSS Feed Atom Feed

Latest Releases

  • June 12, 2019

    Management Console Event Property Capture With this new release, you can now use event properties as filters to create more granular metrics and gain insights from a subset of users in your sample. Properties provide additional context around the events your customers generate. Event properties are attributes of a particular event and reflect the state…

  • June 4, 2019

    Integrations Enhancements Jira Integration Authentication Update Atlassian has recently updated their security requirements to enforce usage of API Tokens on all integrations. This release changes our authentication method on our Jira integration to now support API tokens instead of passwords.

  • May 20, 2019

    Support for Dynamic Configurations.

  • April 2, 2019

    Access metric impact trends, metric dispersion, and the sample population used for the metric value in your experiment.

  • March 5, 2019

    Split is now a supported Segment destination.