Widget experiments and A/B testing

in personizely, you can create a/b tests and multivariate tests these allow you to create different versions of a widget and track which one of them performs better you can create up to five variations of a widget and give each of them a specific share the a/b test distribution is being done using javascript's math random() function when creating an experiment, you can select the primary metric that you want to track this is going to be the default metric selected in the experiment report you can also enable a control group visitors who fall into the control group won't see the widget but a view is going to be attributed if at least one of the triggers from the other variations has fired, so if your variation has a time trigger set to 15 seconds, the control group view will only be attributed once 15 seconds pass, even if the visitor is in the control group when the control group is enabled, the goal conversion rate (goal cvr) for this group is calculated based on reach rather than conversions note that having multiple variations with different triggers, as well as a control group, can skew the number of views, so you might need more traffic/views to get any sensible results for your experiments things that are specific to each variation steps and design all the visual and interactivity settings of the widget are variation specific and will only affect the variation you are currently editing this allows for creating totally different versions of the widget, both visually and conceptually triggers you can use a different set of triggers for each variation to test which triggers perform better for your widgets hide triggers you can choose different close triggers for each variation to test which close triggers perform better for your widgets