Prediction
Beta
Prediction shows how some action events can “predict” the probability which users will move from a source cohort to a target cohort. This statistics-heavy correlation analysis feature masterfully identifies key user actions in the app.
Default view shows All Events’ prediction. For each event, you can see for each N days after the action was taken, what’s the “Correlation” value which predicts users moving from Source Cohort to Target Cohort.
The frequency (the number of times) an action was taken matters a lot in prediction. Thus only the frequency of highest predictive value is displayed in each cell where the “n in (>n)” indicates that frequency.
Details of each cell: a correlation table with detailed statistics and the different predictive value for each frequency of the Action Event.
Pearson correlation is the geometric mean of how predictive X is of Y and how predictive Y is of X. In this case, X is performing at least the threshold number of events and Y is being retained.
This table displays the following raw user counts, starting clockwise from the upper left: True Positive, False Positive, True Negative, False Negative.
The detailed statistics are a series of ratios that can be helpful in interpreting the correlation score. They can all be generated directly from the user counts in the correlation table.
Pearson correlation is the geometric mean of how predictive X is of Y and how predictive Y is of X. In this case, X is performing at least the threshold number of events and Y is being retained.
Proportion of users performing at least the threshold number of events who were also retained.
Proportion of users performing less than the threshold number of events who were not retained.
Proportion of retained users who performed at least the threshold number of events.
Proportion of not retained users who performed less than the threshold number of events.
Proportion of users performing at least the threshold number of events.
You can toggle to see specific statistics on the detailed view.