Adaptive Commerce Systems and Methods

• US 20070073553A1
• Filed: 11/13/2006
• Published: 03/29/2007
• Est. Priority Date: 05/20/2004
• Status: Active Grant

• Current Assignee: Manyworlds Incorporated
• Original Assignee: Manyworlds Incorporated
• Inventors: Moneypenny, Naomi, Flinn, Steven
• Granted Patent: US 7,904,341 B2
• Time in Patent Office: Days
• US Class Current: 705/1.100
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

A system and method for adaptive commerce is disclosed. Adaptive commerce enables recommendations of products or services based on usage behaviors and commercial contextual information. Commercial contextual information may include the business environment of the recommendation recipient, purchase histories, and product or service attributes. Bundles of products and/or services, or specific product or service configurations may be recommended. Corresponding prices may be determined in accordance with behavioral inferences and commercial contextual information.

Claims

1. An adaptive commerce system, comprising:

a content aspect comprising information;

a structural aspect comprising the content aspect and associated relationships;

a usage aspect, comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users;

a commerce contextualization function; and

a function to generate an adaptive recommendation of one or more products and services based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories and at least one item of commerce contextualization information.

2. The system of claim 1, wherein the commerce contextualization function comprises:

a commerce context function, the commerce context function being selected from a group consisting of a customer context function, a purchase history function, and a product or service attribute function.

3. The system of claim 1, further comprising:

a price discovery function.

4. The system of claim 1, further comprising:

a product or service bundling function.

5. The system of claim 1, wherein a function to generate an adaptive recommendation of one or more products and services based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories and at least one item of commerce contextualization information comprises:

a function to generate a recommended bundle comprising at least a first product or service and a second product or service.

6. The system of claim 1, wherein a function to generate an adaptive recommendation of one or more products or services based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories and at least one item of commerce contextualization information comprises:

a function to generate a recommended product or service configuration.

7. The system of claim 1, wherein a function to generate an adaptive recommendation of one or more products or services based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories and at least one item of commerce contextualization information comprises:

a function to generate a price corresponding to the one or more recommended products and services.

8. An adaptive commercial solutions system, comprising:

a usage aspect, comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users;

a product or service bundling function;

a price discovery function; and

a function to generate an adaptive solutions recommendation based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories.

9. The system of claim 8, wherein a price discovery function comprises:

a pricing function, the pricing function being selected from a group consisting of a price elasticity function, a pricing experimental design function, and a collective price formation process function.

10. The system of claim 8, further comprising:

supplier contextual information.

11. The system of claim 8, wherein a function to generate an adaptive solutions recommendation based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories comprises:

a recommended bundle comprising at least a first product or service and a second product or service, and a price corresponding to the bundle.

12. The system of claim 8, wherein a function to generate an adaptive solutions recommendation based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories comprises:

a recommended product or service configuration and a corresponding price.

13. An adaptive commerce method, comprising:

capturing usage behaviors, wherein the usage behaviors are associated with one or more users; and

generating an adaptive commercial recommendation based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories and at least one item of commerce contextualization information.

14. The method of claim 13, wherein generating an adaptive commercial recommendation based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories and at least one item of commerce contextualization information comprises:

applying supplier contextual information.

15. The method of claim 13, wherein generating an adaptive commercial recommendation based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories and at least one item of commerce contextualization information comprises:

generating a recommended product or service.

16. The method of claim 15, wherein generating a recommended product or service comprises:

generating a price corresponding to the recommended product or service.

17. The method of claim 13, wherein generating an adaptive commercial recommendation based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories and at least one item of commerce contextualization information comprises:

generating a recommended bundle comprising at least a first product or service and a second product or service.

18. The method of claim 17, further comprising:

generating a price corresponding to the recommended bundle.

19. The method of claim 13, wherein generating an adaptive commercial recommendation based, at least in part, on a plurality of usage behaviors associated with the one or more users corresponding to a plurality of usage behavior categories and at least one item of commerce contextualization information comprises:

generating a recommended product or service configuration.

20. The method of claim 19, further comprising:

generating a price corresponding to the recommended product or service configuration.