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Methods and systems for customer churn prediction

  • US 10,580,020 B2
  • Filed: 07/28/2015
  • Issued: 03/03/2020
  • Est. Priority Date: 07/28/2015
  • Status: Active Grant
First Claim
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1. A method of operating a customer service system, the method comprising:

  • receiving, by a database server, customer data for a plurality of customers through a communication network from a user-computing device, the plurality of customers comprising a set of churner customers and a set of non-churner customers;

    fusing, by the database server, the customer data;

    storing, by the database server, the fused customer data;

    receiving, by the database server, a query from an application server through the communication network to extract the fused customer data, the application server comprising one or more processors;

    receiving, by the application server, the extracted customer data comprising a plurality of attributes through the communication network;

    defining, by the application server, a plurality of bins corresponding to the plurality of attributes using a density plot of numerical values of each attribute of the plurality of attributes;

    generating, by the application server, an incidence matrix, based on the plurality of attributes, comprising a plurality of rows and a plurality of columns, wherein each row of the plurality of rows represents a customer of the plurality of customers and the plurality of columns corresponds to the plurality of bins;

    creating, by the application server, a customer similarity graph comprising a plurality of customer nodes and a plurality of edges, wherein each edge represents a bin of the plurality of bins, at least one edge of the plurality of edges connects more than two customer nodes of the plurality of customer nodes, each of the plurality of customer nodes represents a customer, the plurality of customer nodes are located in graphical neighborhoods, the customer similarity graph is created based on the incidence matrix, and each edge of the plurality of edges is represented as an n-dimensional vector with binary entries;

    determining, by the application server, a similarity matrix representative of a similarity between each of the plurality of customers, represented by the plurality of customer nodes, based on the customer similarity graph;

    decomposing, by the application server, the similarity matrix into a first matrix and a second matrix;

    determining, by the application server, a third matrix based on the first matrix, the second matrix, and a scaling parameter, wherein the third matrix is a heat kernel matrix defining an effect of each of the plurality of customers on the other customers of the plurality of customers, and the scaling parameter represents a factor that defines a radius of a neighborhood to determine an influence of the customer propagated among the plurality of customers;

    receiving, by the application server, information comprising a first set of attributes from the plurality of attributes, the first set of attributes pertaining to a set of churner customers from the plurality of customers, who have left the service during a pre-defined time interval through the communication network from the user-computing device, and a second set of attributes from the plurality of attributes pertaining to a set of non-churner customers from the plurality of customers;

    determining, by the application server, a set of potential churn customers based on;

    the third matrix comprising the effect of the customer on the other customers in the radius of the neighborhood and the influence of the customer that propagated, andthe information comprising the first set of attributes pertaining to the set of churner customers;

    receiving, by the user-computing device from the application server through the communication network, the set of potential churn customers; and

    visualizing, through a graphical interface on the user-computing device, the set of potential churn customers on the customer similarity graph, the plurality of customer nodes comprising churner customer nodes, non-churner customer nodes, and potential churn customer nodes located in the graphical neighborhoods relative to the radius, the potential churn customers comprising a third set of attributes from the plurality of attributes, the third set of attributes pertaining to the set of potential churn customers and based on;

    the first set of attributes of the churner customers,the second set of attributes of the non-churner customers,the scaling parameter with respect to the potential churn customers relative the churner customers, andthe scaling parameter with respect to the potential churn customers relative to the non-churner customers,wherein the visualization configured to assist a user in retaining the set of potential churn customers.

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