Multidimensional personal behavioral tomography

• US 9,087,335 B2
• Filed: 09/29/2006
• Issued: 07/21/2015
• Est. Priority Date: 09/29/2006
• Status: Active Grant

• Current Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Original Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Inventors: Rane, Rajendra, Juang, David, Alvarez, Eduardo J., Fusillo, Iwao
• Primary Examiner(s): Miller, Alan S
• Application Number:
  US11/529,730
• Publication Number:
  US 20080091508A1
• Time in Patent Office: 3,217 Days
• Field of Search: 705 711- 742, 705 141- 144, 705/15, 705/16, 705/26.1, 705/30, 705/35, 705/319, 706 1- 15, 706/45, 709201-238, 725 1- 37
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

A method and computer program product for identifying attributes of customers and potential customers, allowing marketing to be directed at such consumers. Information is received regarding each of a number of consumers. This information can include demographic information, data regarding spending habits, and information as to how such attributes may have changed over time. Once attributes have been determined, and any changes over time to such attributes have been determined, a correlation of the attributes is performed. Such combined attributes are denoted as composite dimensions. Given the composite dimensions, as well as attributes that may not have been correlated with any other attributes, consumers are plotted in the resulting multi-dimensional space. Sets of consumers that appear to be grouped in this multi-dimensional space are then identified. Common attributes of this consumer group are identified. Unique attributes of a given consumer in such a group are also identified.

Claims

1. A method comprising:

determining, by a computer based system configured for grouping consumers, consumer attributes based on received consumer data,

wherein said received consumer data comprises demographic data of a consumer;

determining, by said computer based system, change attributes based on said received consumer data,

wherein said change attributes comprise trends,

wherein said change attributes comprise extent of change and rates of change of said consumer attributes;

organizing said consumer attributes and said change attributes, by said computer based system, according to correlations of said consumer attributes and change attributes, to create a set of composite dimensions,

wherein said composite dimensions are established based on a positive correlation between said consumer attributes and said change attributes;

plotting, by said computer based system, consumers relative to said set of composite dimensions on a multi-dimensional space;

grouping consumers, by said computer based system, according to location within said multidimensional space to create a consumer group;

identifying, by said computer based system, common attributes of said consumer group; and

identifying, by said computer based system, unique attributes of said consumer in said consumer group.

2. The method of claim 1, further comprising:

directing, by said computer based system, marketing tactics at said consumer on a basis of one or more common attributes of said consumer group associated with said consumer.

3. The method of claim 1, further comprising:

directing, by said computer based system, marketing tactics at said consumer on additional basis of one or more unique attributes of said consumer.

4. The method of claim 3, wherein said marketing tactics comprise targeted spending incentives.

5. The method of claim 3, wherein said marketing tactics comprise targeted advertising.

6. The method of claim 1, wherein said received consumer data comprises spend data of said consumer.

7. The method claim 6, wherein said spend data is aggregated by time interval.

8. The method of claim 6, wherein said spend data is aggregated by merchant industry.

9. The method of claim 1, wherein the received consumer data is from a consumer survey.

10. A non-transitory computer-readable storage medium having stored thereon a plurality of instructions, when executed by a processor configured for grouping consumers, are configured to cause said processor to perform operations comprising:

determining, by said processor, consumer attributes based on received consumer data,

wherein said received consumer data comprises demographic data of a consumer;

determining, by said processor, change attributes based on said received consumer data,

wherein said change attributes comprise trends,

wherein said change attributes comprise extent of change and rates of change of said consumer attributes;

organizing said consumer attributes and said change attributes, by said processor, according to correlations of said consumer attributes and change attributes, to create a set of composite dimensions,

wherein said composite dimensions are established based on a positive correlation between said consumer attributes and said change attributes;

plotting, by said processor, consumers relative to said set of composite dimensions on a multi-dimensional space;

grouping consumers, by said processor, according to location within said multidimensional space to create a consumer group;

identifying, by said processor, common attributes of said consumer group; and

identifying, by said processor, unique attributes of said consumer in said consumer group.

11. The medium of claim 10, wherein said received consumer data comprises spend data of said consumer.

12. The medium of claim 11, wherein said spend data is aggregated by time interval.

13. The medium of claim 11, wherein said spend data is aggregated by merchant industry.

14. A computer based system, comprising:

a computer network communicating with a memory;

said memory communicating with a processor configured for grouping consumers; and

said processor, when executing a computer program is configured to;

determine, by said processor, consumer attributes based on received consumer data,

wherein said received consumer data comprises demographic data of a consumer;

determine, by said processor, change attributes based on said received consumer data,

wherein said change attributes comprise trends,

wherein said change attributes comprise extent of change and rates of change of said consumer attributes;

organize said consumer attributes and said change attributes, by said processor, according to correlations of said consumer attributes and change attributes, to create a set of composite dimensions,

wherein said composite dimensions are established based on a positive correlation between said consumer attributes and said change attributes;

plot, by said processor, consumers relative to said set of composite dimensions on a multi-dimensional space;

group consumers, by said processor, according to location within said multidimensional space to create a consumer group;

identify, by said processor, common attributes of said consumer group; and

identify, by said processor, unique attributes of said consumer in said consumer group.

15. The computer based system of claim 14, wherein said received consumer data comprises spend data of said consumer.