Method for evaluating customer valve to guide loyalty and retention programs
First Claim
1. A method for evaluating customer value to guide loyalty and retention programs comprising:
- generating, by a processing system, a hazard function model based on attributes relating to a plurality of current customer accounts;
generating, by the processing system, a hazard function for a first existing customer, to determine probability of churn, based on the hazard function model and account data associated with the first existing customer and corresponding to the attributes;
calculating a gain in lifetime value for the first existing customer based on a change in the hazard function resulting from a retention effort; and
determining a focus for retention-based interactions with the first existing customer based on at least the hazard function, wherein determining the focus comprises clustering the hazard function for the first existing customer and hazard functions for a plurality of other existing customers so that the hazard functions are grouped together according to shape, each group representative of a customer set.
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Accused Products
Abstract
A method and apparatus for training a neural network to compute hazard functions for customers and analyzing hazard functions, both for an individual customer, and for set of customers to focus marketing techniques. The hazard function represents the likelihood of churn for a particular customer. The gain in lifetime value is also calculated for each customer which incorporates the present value of the customer with the future value of the customer if a new contract is entered. The overall shape of the hazard function, combined with the gain in lifetime value, specifies what marketing techniques are to be applied together with what additional incentives are to be offered to the customer in order prevent churn.
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Citations
67 Claims
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1. A method for evaluating customer value to guide loyalty and retention programs comprising:
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generating, by a processing system, a hazard function model based on attributes relating to a plurality of current customer accounts; generating, by the processing system, a hazard function for a first existing customer, to determine probability of churn, based on the hazard function model and account data associated with the first existing customer and corresponding to the attributes; calculating a gain in lifetime value for the first existing customer based on a change in the hazard function resulting from a retention effort; and determining a focus for retention-based interactions with the first existing customer based on at least the hazard function, wherein determining the focus comprises clustering the hazard function for the first existing customer and hazard functions for a plurality of other existing customers so that the hazard functions are grouped together according to shape, each group representative of a customer set. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 62)
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15. An apparatus for evaluating customer value to guide loyalty and retention programs comprising:
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a computer, comprising; a first calculating component for generating a hazard function model based on attributes relating to a plurality of current customer accounts; a generating component for generating a hazard function for a first existing customer, to determine probability of churn, based on the hazard function model and account data associated with the first existing customer and corresponding to the attributes; a second calculating component for calculating a gain in lifetime value for the first existing customer based on a change in the hazard function resulting from a retention effort; a determining component for determining a focus for retention-based interactions with the first existing customer based on at least the hazard function; and a clustering component for clustering the hazard function for the first existing customer and hazard functions for a plurality of other existing customers so that the hazard functions are grouped together according to shape, each group representative of a customer set; and a display device displaying at least one of the hazard function, the gain in lifetime value for the first existing customer, and the focus for retention-based interactions with the first existing customer. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 63)
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29. A computer-readable medium including instructions, executable by a processor, for performing a method for evaluating customer value to guide loyalty and retention programs, the method comprising:
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generating a hazard function model based on attributes relating to a plurality of current customer accounts; generating a hazard function for a first existing customer, to determine probability of churn, based on the hazard function model and account data associated with the first existing customer and corresponding to the attributes; calculating a gain in lifetime value for the first existing customer based on a change in the hazard function; and determining a focus for retention-based actions based on at least the hazard function, wherein determining the focus comprises clustering the hazard function for the first existing customer and hazard functions for a plurality of other existing customers so that the hazard functions are grouped together according to shape, each group representative of a customer set. - View Dependent Claims (30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 64)
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43. A system for evaluating customer value to guide loyalty and retention programs comprising:
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means for generating a hazard function model based on attributes relating to a plurality of current customer accounts; means for generating a hazard function for a first existing customer, to determine probability of churn, based on the hazard function model and account data associated with the first existing customer and corresponding to the attributes; means for calculating a gain in lifetime value for the first existing customer based on a change in the hazard function; means for determining a focus for retention-based actions based on at least the hazard function; means for clustering the hazard function for the first existing customer and hazard functions for a plurality of other existing customers so that the hazard functions are grouped together according to shape, each group representative of a customer set; and means for displaying at least one of the hazard function, the gain in lifetime value for the first existing customer, and the focus for retention-based actions. - View Dependent Claims (44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 65)
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57. A method for evaluating customer value to guide loyalty and retention programs comprising:
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generating, by a multilayer feed-forward neural network, a hazard function for a first existing customer, to determine probability of churn, based on account data associated with the first existing customer and corresponding to a set of attributes; calculating, for the first existing customer, a gain in lifetime value based on a change in the hazard function resulting from a retention effort; and determining a focus for a retention-based program based on at least the hazard function, wherein determining the focus comprises clustering the hazard function for the first existing customer and hazard functions for a plurality of other existing customers so that the hazard functions are grouped together according to shape, each group representative of a customer set. - View Dependent Claims (58, 66, 67)
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59. A method for evaluating customer value to guide loyalty and retention programs comprising:
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generating, by a processing system and for each of a plurality of customers, a hazard function to determine a probability of churn for each customer, the hazard function based on attributes relating to customer account information; identifying a temporal-based retention effort based on the hazard function for each of the plurality of customers; calculating, for each of the plurality of customers, an expected gain in value from the identified retention effort; and determining a focus for customer interaction based on the expected gain in value, wherein determining the focus comprises clustering the hazard function for each of the plurality of customers so that the hazard functions are grouped together according to shape, each group representative of a customer set. - View Dependent Claims (60, 61)
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Specification