Systems and methods for integrated multi-factor multi-label analysis

A method, comprising:

• accessing a plurality of customer profiles corresponding to a plurality of customers;
• performing, via at least one machine learning network, a multi-factor multi-label analysis on each customer profile of the plurality of customer profiles, wherein each factor of the multi-factor multi-label analysis represents a characteristic of the customer associated with the customer profile, and wherein each label of the multi-factor multi-label analysis represents an action of a set of possible actions that can be performed to the customer associated with the customer profile, wherein the multi-factor multi-label analysis is performed at least in part by:
• separating, via a data separator module, data associated with the plurality of customer profiles into a plurality of subsets of data;
• and
• scaling, for each subset of data, portions of the data that correspond to numeric information such that relative magnitudes of the numeric information are substantially similar across the plurality of subsets of data;
• generating, based on the multi-factor multi-label analysis, a score for each customer profile of the plurality of customer profiles;
• determining, based on the generated score, one or more targeted actions for at least a subset of the customers of the plurality of customers;
• and
• performing the one or more targeted actions to the subset of the customers.

A system, comprising:

• a non-transitory memory storing instructions;
• and
• one or more processors configured to execute the instructions to cause the system to perform operations comprising:
• accessing a plurality of entity profiles corresponding to a plurality of entities;
• accessing a machine learning network that comprises an input layer, an output layer, and a plurality of analyzer layers arranged in a serial chain that is coupled between the input layer and the output layer, wherein an output of a given one of the analyzer layers is passed on to a subsequent one of the analyzer layers down the serial chain or to a bypass path that is connected to one or more different ones of the analyzer layers down the serial chain;
• performing, via the machine learning network, an analysis of the plurality of entity profiles, wherein the analysis is based on a plurality of characteristics of each entity of the plurality of entities, and wherein the analysis is further based on a set of possible actions that can be performed for each entity of the plurality of entities;
• calculating, based on the analysis, a score for each entity profile of the plurality of entity profiles;
• determining, based on the calculated score, one or more targeted actions for at least a subset of the entities of the plurality of entities;
• and
• executing the one or more targeted actions.

A non-transitory machine-readable medium having instructions stored thereon, the instructions executable to cause a machine to perform operations comprising:

• accessing a plurality of customer profiles corresponding to a plurality of customers of a service provider;
• analyzing, via a machine learning model, each customer profile of the plurality of customer profiles, wherein the analyzing comprises:
• separating, via a data separator module, data associated with the plurality of customer profiles into a different subsets of data;
• and
• scaling, for each subset of data, portions of the data that correspond to numeric information such that relative magnitudes of the numeric information are substantially similar across the different subsets of data;
• generating, based on the analyzing, a metric for each customer of the plurality of customers, wherein the metric indicates a suitability of one or more potential actions for each customer or an interest level of the customer with respect to the one or more potential actions;
• and
• executing, based on the generated metric, one or more targeted actions for at least a subset of the customers of the plurality of customers, wherein at least one of the one or more targeted actions comprises offering one or more services of the service provider to at least the subset of the customers.