METHOD FOR CUSTOMER-CHOICE-BASED BUNDLING OF PRODUCT OPTIONS

• US 20090055244A1
• Filed: 03/21/2008
• Published: 02/26/2009
• Est. Priority Date: 05/04/2006
• Status: Active Grant

• Current Assignee: Claudia Reisz
• Original Assignee: Claudia Reisz
• Inventors: REISZ, Claudia
• Granted Patent: US 8,332,407 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0268 at point-of-sale [POS]

Abstract

A method and system for customer-choice-based bundling of product options collects data from previous orders about customer component choices, computes a pairwise distance between any pair of components that capture how much the probability of a choice pair P(a.b) deviates from the expected probability under the null hypothesis of independence P(a)*P(b), and clusters the components. The methodology can be implemented as instructions implemented in a computer readable medium. In this way, the need for a method to permit bundles of product options to be configured through the use of business processes reflecting choices based on the preferences of customers rather than the preferences of product designers is fulfilled.

Claims

1. A method for customer-choice-based bundling of product options, comprising the steps of:

using a computer to define one or a plurality of groups of product components exhibiting strong customer-choice interdependencies by

collecting customer choice data relating to a plurality of product components,

grouping said product components as elements in one or a plurality of sets of product components by computing distances between choice pairs of said product components and, based on said distances, determining the extent to which the probability of a choice pair P(a.b) deviates from the expected probability under a null hypothesis of independence P(a)*P(b), and

determining one or a plurality of bundles of product components by the application of said clustering approach; and

generating as output one or a plurality of lists of clustered product components comprising said one or a plurality of bundles of product components.

2. The method of claim 1, wherein the computer is connected to a network.

3. The method of claim 2, wherein the network is the Internet.

4. The method of claim 2, wherein said customer choice data is obtained from a database connected to said network.

5. A system for customer-choice-based bundling of product options, comprising:

a computer defining one or a plurality of groups of product components exhibiting strong customer-choice interdependencies by

collecting customer choice data relating to a plurality of product components,

grouping said product components as elements in one or a plurality of sets of product components by computing distances between choice pairs of said product components and, based on said distances, determining the extent to which the probability of a choice pair P(a.b) deviates from the expected probability under a null hypothesis of independence P(a)*P(b), and

determining one or a plurality of bundles of product components by the application of said clustering approach; and

generating as output one or a plurality of lists of clustered product components comprising said one or a plurality of bundles of product components.

6. The system of claim 5, wherein the computer is connected to a network.

7. The system of claim 6, wherein the network is the Internet.

8. The system of claim 6, wherein said customer choice data is obtained from a database connected to said network.

9. A computer-readable medium for customer-choice-based bundling of product options, on which is provided:

instructions for using a computer to define one or a plurality of groups of product components exhibiting strong customer-choice interdependencies by

collecting customer choice data relating to a plurality of product components,

grouping said product components as elements in one or a plurality of sets of product components by computing distances between choice pairs of said product components and, based on said distances, determining the extent to which the probability of a choice pair P(a.b) deviates from the expected probability under a null hypothesis of independence P(a)*P(b), and

determining one or a plurality of bundles of product components by the application of said clustering approach; and

generating as output one or a plurality of lists of clustered product components comprising said one or a plurality of bundles of product components.

10. The machine-readable medium of claim 9, wherein the computer is connected to a network.

11. The machine-readable medium of claim 10, wherein the network is the Internet.

12. The machine-readable medium of claim 11, wherein said customer choice data is obtained from a database connected to said network.