Patent ID: 11948153
Assignee: MASSACHUSETTS MUTUAL LIFE INSURANCE COMPANY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 5:
6. A system, comprising:
a telephone calling device for placing outbound customer call-backs from a call center;
an interactive voice response unit;
non-transitory machine-readable memory comprising a customer relationship management database of an enterprise that stores advisor records of a plurality of advisors of the enterprise, the advisor records comprising advisor call history data of the plurality of advisors of the enterprise and product history data for a plurality of products of the enterprise;
a storage module that stores a logistic regression model of customer call-backs, wherein the logistic regression model is configured to utilize time series forecasting to determine a plurality of call-back metrics for each advisor record of the advisor records stored by the customer relationship management data base and to classify a current customer call-back into one of a first call-back group and a second call-back group, wherein the logistic regression model applies regularization to feature selection; and
a processor, configured to execute a call-back management module, wherein the processor in communication with the non-transitory machine-readable memory and the a logistic regression modeling module executes a set of instructions instructing the processor to:
train the logistic regression model using a dataset having a plurality of features corresponding to historical calls, the logistic regression model trained by applying regularization to feature selection in repeated iterations;
open a call-back record for an identified customer including call-back data comprising one or more of interactive voice response (IVR) data received from the identified customer via interaction with the interactive voice response unit and call associated information for a previous call interaction of the identified customer with one of the plurality of advisors of the enterprise;
execute the logistic regression model to generate (i) a call-back signal representative of a likelihood of repeated call-backs by the identified customer and (ii) an interaction signal representative of a likelihood that the identified customer will perform a predetermined interaction during a future call-back by applying to the call-back data in the call-back record for the identified customer in the logistic regression model configured to utilize time series forecasting to determine the plurality of call-back metrics for each advisor record of a plurality of advisor records stored by the customer relationship management database, the logistic regression model trained to generate the call-back signal and the interaction signal as output, wherein the plurality of advisor records include advisor call history data of the plurality of advisors of the enterprise and product history data for a plurality of products of the enterprise;
apply the logistic regression model to classify the identified customer into one of the first call-back group and the second call-back group; and
in the event the logistic regression model classifies the identified customer into the first call-back group, initiate a call back between the identified customer and a selected agent of the call center;
in the event the logistic regression model classifies the identified customer into the second call-back group, direct the telephone calling device to place outbound customer calls to automatically execute a subordinate call-back procedure.