Method and apparatus for dynamic, real-time market segmentation

• US 7,177,851 B2
• Filed: 11/09/2001
• Issued: 02/13/2007
• Est. Priority Date: 11/10/2000
• Status: Expired due to Term

• Current Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Original Assignee: Affinnova, Inc. (RR Donnelley & Sons Company)
• Inventors: Afeyan, Noubar B., Austin, legal representative, McClellan, legal representative, Ficici, Sevan G., Malek, Kamal M., Austin, deceased, Bufton, Nigel J.
• Primary Examiner(s): STARKS, WILBERT L
• Application Number:
  US10/053,353
• Publication Number:
  US 20030088458A1
• Time in Patent Office: 1,922 Days
• Field of Search: 345/467 382/203 434/43 709/223 706/13,45 705/10,14,925
• US Class Current: 706/13
• CPC Class Codes: G06F 2111/06 Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
• CPC Class Codes: G06F 2111/08 Probabilistic or stochastic CAD
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G06N 3/126 Evolutionary algorithms, e.g. genetic algorithms or genetic programming
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 10/101 Collaborative creation, e.g. joint development of products or services
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

The invention involves generating and presenting, typically electronically, a number of design alternatives to persons who are participating in the design, selection, or market research exercise. The participants (referred to as “selectors”) transmit data indicative of their preferences among or between the presented design alternatives, and that data is used to derive a new generation of design alternatives or proposals. The new designs are generated through the use of a computer program exploiting a genetic or evolutionary computational technique. The process is repeated, typically for many iterations or cycles.

Claims

1. A method of determining the relative affinity of one or more consumers from a group of consumers for a form of a product, comprising:

a) presenting, over a computer network and to the group of consumers, a group of product forms, each of the product forms including a particular combination of attributes;

b) enabling members of the group of consumers to express a preference for a subset of the presented product forms;

c) capturing data indicative of the preferences expressed by members of the group of consumers;

d) inputting at least some of the captured data into a computer program to provide a derived group of product forms, at least one of the derived group of product forms including a new attribute or a new combination of attributes;

e) presenting, to the at least some of the group of consumers, the derived group of product forms; and

f) repeating steps b) through e) to collect data indicative of the relative affinity of one or more consumers from the at least some of the group of consumers for a form of the product, wherein the product comprises a mass produced good, a consumer good, a manufactured good, a service, advertising material, or packaging material.

2. The method of claim 1 wherein step d) includes generating a variety of product forms in the derived group of product forms to promote exploration of consumer preferences for product forms including various combinations of attributes.

3. The method of claim 1 wherein step d) includes generating the derived group of product forms to promote convergence to product forms that include attributes that match the preference of one of the consumers of the group of consumers.

4. The method of claim 1 wherein step d) includes generating the derived group of product forms to promote convergence to product forms that include attributes that match the preferences of more than one of the consumers of the group of consumers.

5. The method of claim 1 wherein step d) includes generating the derived group of product forms using a genetic or evolutionary computation technique.

6. The method of claim 1 wherein step d) includes the use of conjoint analysis.

7. The method of claim 1 wherein each of the attributes comprises a structural, functional, stylistic, or economic feature of the product.

8. The method of claim 1 wherein the product comprises apparel, footwear, a computer, a telephone, a chair, a seat, an automobile, a bicycle, a home, a building, a boat hull, or a billboard.

9. The method of claim 1 further comprising collecting demographic information from the group of consumers.

10. An automated method of identifying member candidates for a group of persons having a shared affinity, comprising:

a) presenting, over a computer network, a set of alternatives to a group of participants, each of the alternatives having a particular combination of attributes;

b) enabling the participants or a subset thereof to express a preference for a subset of the presented alternatives;

c) capturing data indicative of the preferences expressed by the participants or the subset thereof;

d) inputting data into a computer program to provide a derived set of alternatives including alternatives having a new attribute or a new combination of attributes, the derived set of alternatives being influenced by the captured data;

e) presenting to the participants or a subset thereof at least a portion of the derived alternatives; and

f) repeating steps b) through e) until one or more groups of persons having a shared affinity for one or more of the derived alternatives are identified, wherein each of the attributes comprises a structural, functional, stylistic, or economic feature of one of the alternatives.

11. A method of identifying one or more subgroups of people from a larger group of people, comprising:

a) presenting, over a computer network and to at least some of the larger group of people, a plurality of forms of a product;

b) obtaining, from each of at least some of the at least some of the larger group, information about that person'"'"'s preference for one or some of the plurality of presented product forms;

c) providing a plurality of derived forms of the product, based at least in part on at least some of the obtained information; and

d) repeating steps a), b), and c), using the plurality of derived product forms from step c), until one or more subgroups of people are identifiable, each of the one or more identifiable subgroups preferring at least one product form that is different than at least one product form preferred by the other subgroups, wherein the product comprises a mass produced good, a consumer good, a manufactured good, a service, advertising material, or packaging material.

12. The method of claim 11 wherein each of the plurality of presented product forms includes a particular combination of attributes, and wherein at least one of the plurality of derived product forms includes a particular combination of attributes that is different than the particular combination of attributes for at least one of the plurality of presented product forms.

13. The method of claim 12 wherein each of the attributes comprises a structural, functional, stylistic, or economic feature of the product.

14. The method of claim 11 wherein step b) includes obtaining the information over the computer network.

15. The method of claim 11 wherein step c) includes the use of a computer program to provide the plurality of derived product forms.

16. The method of claim 11 wherein step c) includes the use of an evolutionary algorithm to generate the plurality of derived product forms.

17. The method of claim 11 wherein step c) includes the use of a genetic algorithm to generate the plurality of derived product forms.

18. The method of claim 11 wherein step c) includes selecting the plurality of derived product forms.

19. The method of claim 11 wherein the product comprises apparel, footwear, a computer, a telephone, a chair, a seat, an automobile, a bicycle, a home, a building, a boat hull, or a billboard.

20. The method of claim 11 further comprising collecting demographic information from people.

21. A plurality of client computers for use in identifying member candidates for a group of persons having a shared affinity, each of at least some of the client computers configured to:

a) receive for presentation, to a participant from a group of participants, a set of alternatives, each of the alternatives having a particular combination of attributes;

b) enable the participant to express a preference for a subset of the presented alternatives;

c) capture data indicative of the preference expressed by the participant;

d) provide data to at least one remote server which provides back a derived set of alternatives including alternatives having a new attribute or a new combination of attributes, the derived set of alternatives being influenced by the captured data;

e) receive for presentation to the participant at least a portion of the derived alternatives; and

f) repeat functions b) through e) until one or more groups of persons having a shared affinity for one or more of the derived alternatives are identified by the remote server, wherein each of the attributes comprises a structural, functional, stylistic, or economic feature of one of the alternatives.