Patent ID: 11922441
Assignee: INTUIT INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. A method, comprising:
generating, based on a predictive model using an amount of time a user of a software application has spent using the software application and a number of discrete portions of the software application the user has visited as input, a predictive score corresponding to a likelihood that a user of a software application will continue using the software application, wherein:
the predictive model comprises a model trained based on a spatio-temporally sampled data set from one or more historical users of the software application having balanced data across each of a plurality of bins into which the one or more historical users of the software application are sorted,
the spatio-temporally sampled data set comprises a data set sampled from a spatial dimension corresponding to different portions of the software application and a temporal dimension corresponding to times at which interaction with the software application occurred, and
the predictive model comprises a gradient boosting model including a plurality of decision trees having been generated based on residual values calculated from the spatio-temporally sampled data set and a split value assigned to each respective residual value calculated from the spatio-temporally sampled data set;

performing, based on the generated predictive score, one or more of:
routing the user to a support session with a live agent,
routing the user to an automated support session, or
displaying content that is selected based on the generated predictive score; and

receiving additional log data related to user activity within the software application after the generating of the predictive score, wherein the additional log data is used to further train the predictive model.