Adaptive commerce systems and methods

• US RE43,768 E1
• Filed: 10/24/2011
• Issued: 10/23/2012
• Est. Priority Date: 05/20/2004
• Status: Active Grant

• Current Assignee: Manyworlds Incorporated
• Original Assignee: Manyworlds Incorporated
• Inventors: Flinn, Steven Dennis, Moneypenny, Naomi Felina
• Primary Examiner(s): Zurita, James
• Application Number:
  US13/279,871
• Time in Patent Office: 365 Days
• Field of Search: 705/26.7, 705/26.63, 705/37
• US Class Current: 705/26.7
• 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 usage function implemented on a processor-based computing device comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users of a computer-implemented system;

a production cost; and

a computer-implemented function to generate an adaptive recommendation of one or more products 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 the production cost.

2. The system of claim 1, further comprising:

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 attribute function.

3. The system of claim 1, further comprising:

a price discovery function.

4. The system of claim 1, further comprising:

a product bundling function.

5. The system of claim 1, wherein a computer-implemented function to generate an adaptive recommendation of one or more products 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 the production cost comprises:

a bundle-recommending function comprising at least a first product and a second product.

6. The system of claim 1, wherein a computer-implemented function to generate an adaptive recommendation of one or more products 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 the production cost comprises:

a product configuration-generating function.

7. The system of claim 1, wherein a computer-implemented function to generate an adaptive recommendation of one or more products 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 the production cost comprises:

a price-generating function wherein the price generated by the price-generating function corresponds to the one or more recommended products.

8. An adaptive commercial solutions system, comprising:

a usage function implemented on a processor-based computing device comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users;

a product-bundling function;

a price discovery function; and

a computer-implemented function to generate an adaptive solutions recommendation comprising a plurality of products 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 a production cost.

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 computer-implemented function to generate an adaptive solutions recommendation comprising a plurality of products 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 and a second product, and a price corresponding to the bundle.

12. The system of claim 8, wherein a computer-implemented function to generate an adaptive solutions recommendation comprising a plurality of products 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 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 interacting with a processor-based computing device; 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 a production cost.

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 a production cost 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 a production cost comprises:

generating a recommendation of a product.

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

generating a price corresponding to the recommended product.

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 a production cost comprises:

generating a recommendation of a bundle comprising at least a first product and a second product.

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 a production cost comprises:

generating a recommendation of a product configuration.

20. The method of claim 19, further comprising:

generating a price corresponding to the recommended product configuration.