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

Claim 13:
14. A system, comprising:
a memory having executable instructions stored thereon; and
a processor configured to execute the executable instructions to cause the system to:
generate a spatially sampled data set for a set of users of a software application including, for each respective user of the set of users, an amount of time the respective user has spent using the software application, a number of discrete portions of the software application the respective user has visited, and an indication of whether the respective user has completed a defined task in the software application, wherein:
in order to generate the spatially sampled data set, the processor is configured to cause the system to:
divide the set of users of the software application into a plurality of bins, each bin corresponding to a unique range of numbers of discrete portions of the software application visited by users in the bin;
select all users from a bin of the plurality of bins having a smallest number of users; and
select a subset of users for each of the plurality of bins other than the bin having the smallest number of users, and

the spatially sampled data set comprises a data set smaller than a historical activity data set from which the spatially sampled data set is generated, the historical data set including a spatial dimension corresponding to discrete portions of the software application and a temporal dimension corresponding to times at which interaction with the software application occurred;
generate a spatio-temporally sampled data set from the spatially sampled data set including, for each respective user in the spatially sampled data set, a plurality of candidate timestamps bounded by the amount of time the respective user has spent using the software application, wherein in order to generate the spatio-temporally sampled data set, the processor is configured to cause the system to:
identify, from users in the spatially sampled data set, a maximum timestamp indicating a longest amount of time a user in the spatially sampled data set has used the software application; and
select, for each respective user in the spatially sampled data set, candidate timestamps in each window of a plurality of windows, each window being defined based on the maximum timestamp and a multiple of a defined interval;

train a predictive model for predicting a likelihood that a user will continue using the software application based on the spatio-temporally sampled data set given an input of a timestamp and a spatial data point within the software application, wherein in order to train the predictive model, the processor is configured to cause the system to train a gradient boosting model including a plurality of decision trees 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, wherein:
the trained predictive model is used to generate a predictive score based on respective spatio-temporally sampled data; and
the generated predictive score is used to perform one or more of:
routing the user to a support session with a live agent, or
routing the user to an automated support session; and

further train the predictive model based on additional log data related to user activity within the software application after the generating of the predictive score.