Multi-dimensional segmentation for use in a customer interaction
First Claim
1. A computer-implemented method for segmenting data representing a plurality of customers, comprising the computer-implemented steps of:
- choosing, using a data type choosing module, at least four different data types stored in a data warehouse on a computer platform,wherein the at least four different data types comprise a first data type containing customer behavior data, a second data type containing customer value data, a third data type, and a fourth data type; and
wherein the third and fourth data types are chosen from a group comprising attitude, satisfaction, brand experience, brand attachment, brand utility, lifestyle, life-stage, and category involvement;
segmenting, using at least one software module, a subset of the plurality of customers by each of the at least four different data types to produce a corresponding plurality of segmentation results;
generating a multi-dimensional hypercube, for cross-segmenting the subset of the plurality of customers, and combining the at least four different data types by overlaying the plurality of segmentation results within the multi-dimensional hypercube;
profiling the plurality of segmentation results overlaid within the multi-dimensional hypercube, wherein profiling includes cross-segmenting the subset of the plurality of customers to produce a joint view of relationships among the at least four different data types, and to identify the relationships among the at least four data types;
associating the identified relationships to a superset of the plurality of customers; and
updating a customer record stored in the data warehouse on the computer platform for each of the superset of the plurality of customers to reflect the identified relationships.
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Accused Products
Abstract
A system and method for segmenting customer data that represents a plurality of customers for use in a customer interaction. The segmentation process groups customers with similar characteristics into segments. The segments may be used to classify customers according to a likelihood of the customers to accept a particular marketing offer. The segments may also be used as an analytic framework for customer portfolio management, product development, marketing strategy, and customer interaction capabilities. A multi-dimensional segmentation approach may be used to cross-segment a plurality of customers so that the customers included in the crossed segments can be profiled for more precise targeting of marketing offers. Customers may be segmented according to one or more data types stored in a data warehouse. The multi-dimensional segmentation approach may be applied to relationships between and among the data types to obtain a holistic view of what drives customer value. The segmentations may be driven by a business objective. This enables the segment analysis to be calibrated in the context of the stated business objective.
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Citations
29 Claims
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1. A computer-implemented method for segmenting data representing a plurality of customers, comprising the computer-implemented steps of:
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choosing, using a data type choosing module, at least four different data types stored in a data warehouse on a computer platform, wherein the at least four different data types comprise a first data type containing customer behavior data, a second data type containing customer value data, a third data type, and a fourth data type; and wherein the third and fourth data types are chosen from a group comprising attitude, satisfaction, brand experience, brand attachment, brand utility, lifestyle, life-stage, and category involvement; segmenting, using at least one software module, a subset of the plurality of customers by each of the at least four different data types to produce a corresponding plurality of segmentation results; generating a multi-dimensional hypercube, for cross-segmenting the subset of the plurality of customers, and combining the at least four different data types by overlaying the plurality of segmentation results within the multi-dimensional hypercube; profiling the plurality of segmentation results overlaid within the multi-dimensional hypercube, wherein profiling includes cross-segmenting the subset of the plurality of customers to produce a joint view of relationships among the at least four different data types, and to identify the relationships among the at least four data types; associating the identified relationships to a superset of the plurality of customers; and updating a customer record stored in the data warehouse on the computer platform for each of the superset of the plurality of customers to reflect the identified relationships. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer-implemented method for segmenting data representing a plurality of customers, the method comprising the computer-implemented steps of:
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choosing, using a characteristic choosing module, at least four different characteristics stored in a data warehouse on a computer platform, wherein the at least four different characteristics are chosen from a group comprising attitude, behavior, value, satisfaction, brand experience, brand attachment, brand utility, lifestyle, life-stage, and category involvement; segmenting, using at least one software module, a subset of the plurality of customers by each of the at least four different characteristics to produce a corresponding plurality of segmentation results; generating a matrix multi-dimensional hypercube for cross-segmenting the subset of the plurality of customers and combining the at least four different characteristics by overlaying the plurality of segmentation results within the multi-dimensional hypercube; profiling the plurality of segmentation results overlaid within the multi-dimensional hypercube, wherein profiling includes cross-segmenting the subset of the plurality of customers to produce a joint view of relationships among the at least four different characteristics and to identify the relationships among the at least four different characteristics; associating the identified relationships to a superset of the plurality of customers; and updating a customer record stored in the data warehouse on the computer platform for each of the superset of the plurality of customers to reflect the identified relationships. - View Dependent Claims (12, 13)
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14. A system for segmenting data representing a plurality of customers, comprising:
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a data type choosing module that chooses at least four different data types stored in a data warehouse on a computer platform, wherein the at least four different data types comprise a first data type containing behavior data, a second data type containing value data, a third data type, and a fourth data type; and wherein the third and fourth data types are chosen from a group comprising attitude, satisfaction, brand experience, brand attachment, brand utility, lifestyle, life-stage, and category involvement; a data type segmenting module that segments a subset of the plurality of customers by each of the at least four different data types to produce a corresponding plurality of segmentation results; and a multi-dimensional hypercube generating module that generates a multi-dimensional hypercube for cross-segmenting the subset of a plurality of customers by the at least four different data types and that combines the at least four different data types by overlaying the plurality of segmentation results within the multi-dimensional hypercube; a profiling module that profiles the segmentation results overlaid within the multi-dimensional hypercube by cross-segmenting the subset of the plurality of customers to produce a joint view of relationships among the at least four different data types, and to identify the relationships among the at least four different data types; an associating module that associates the identified relationships to a superset of the plurality of customers; and an updating module that updates a customer record stored in the data warehouse on the computer platform for each of the superset of the plurality of customers to reflect the identified relationships. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A system for segmenting data representing a plurality of customers, the system comprising:
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a characteristic choosing module that chooses at least four different characteristics stored in a data warehouse on a computer platform, wherein the at least four different characteristics are chosen from a group comprising attitude, behavior, value, satisfaction, brand experience, brand attachment, brand utility, lifestyle, life-stage, and category involvement; a characteristic segmenting module that segments a subset of the plurality of customers by each of the at least four different characteristics to produce a corresponding plurality of segmentation results; a multi-dimensional hypercube generating module that generates a multi-dimensional hypercube for cross-segmenting the subset of a plurality of customers and that combines the at least four different characteristics by overlaying the plurality of segmentation results within the multi-dimensional hypercube; a profiling module that profiles the plurality of segmentation results overlaid within the multi-dimensional hypercube by cross-segmenting the subset of the plurality of customers to produce a joint view of relationships among the at least four different characteristics and to identify the relationships among the at least four different characteristics; associating the identified relationships to a superset of the plurality of customers; and an updating module that updates a customer record stored in the data warehouse on the computer platform for each of the superset of the plurality of customers to reflect the identified relationships. - View Dependent Claims (26, 27)
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28. A computer program product comprising a computer-readable medium having computer-executable instructions that control a computer to perform a method for segmenting data representing a plurality of customers, the method comprising the computer-implemented steps of:
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choosing, using a data type choosing module, at least four different data types stored in a data warehouse on a computer platform, wherein the at least four different data types comprise a first data type containing customer behavior data, a second data type containing customer value data, a third data type, and a fourth data type; and wherein the third and fourth data types are chosen from a group comprising attitude, satisfaction, brand experience, brand attachment, brand utility, lifestyle, life-stage, and category involvement; segmenting, using at least one software module, a subset of the plurality of customers by each of the at least four different data types to produce a corresponding plurality of segmentation results; generating, using the at least one software module, a multi-dimensional hypercube for cross-segmenting the subset of the plurality of customers and combining the at least four different data types by overlaying the plurality of segmentation results within the multi-dimensional hypercube; profiling the plurality of segmentation results within the multi-dimensional hypercube, wherein profiling includes cross-segmenting the subset of the plurality of customers to produce a joint view of relationships among the at least four different data types and to identify relationships among the at least four different data types; associating the identified relationships to a superset of the plurality of customers; and updating a customer record stored in the data warehouse on the computer platform for each of the superset of the plurality of customers to reflect the identified relationships.
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29. A computer program product comprising a computer-readable medium having computer-executable instructions that control a computer to perform a method for segmenting data representing a plurality of customers, the method comprising:
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choosing, using a characteristic choosing module, at least four different characteristics stored in a data warehouse on a computer platform, wherein the at least four different characteristics are chosen from a group comprising attitude, behavior, value, satisfaction, brand experience, brand attachment, brand utility, lifestyle, life-stage, and category involvement; segmenting, using a segmenting module, a subset of the plurality of customers by each of the at least four different characteristics to produce a corresponding plurality of segmentation results; and generating, using a generating module, a multi-dimensional hypercube for cross-segmenting the subset of a plurality of customers and combining the at least four different characteristics by overlaying the plurality of segmentation results within the multi-dimensional hypercube; profiling, using a profiling module, the plurality of segmentation results within the multi-dimensional hypercube by cross-segmenting the subset of the plurality of customers to produce a joint view of relationships among the at least four different characteristics and to identify the relationships among the at least four different characteristics; associating, using an association module, the identified relationships to a superset of the plurality of customers; and updating, using an updating module, a customer record stored in the data warehouse on the computer platform for each of the superset of the plurality of customers to reflect the identified relationships.
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Specification