INTELLIGENT PERFORMANCE-BASED PRODUCT RECOMMENDATION

• US 20100262556A1
• Filed: 06/22/2010
• Published: 10/14/2010
• Est. Priority Date: 10/18/2000
• Status: Active Grant

• Current Assignee: Johnson & Johnson Consumer Companies Incorporated (Johnson & Johnson)
• Original Assignee: Johnson & Johnson Consumer Companies Incorporated (Johnson & Johnson)
• Inventors: Kollias, Nikiforos, Bloom, Jeffrey Adam, Shaya, Steven A., Singarayar, John Anthony, Matheson, Neal
• Granted Patent: US 8,666,844 B2
• Time in Patent Office: Days
• US Class Current: 705/347
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 30/0641 Shopping interfaces

Abstract

Systems and methods of utilizing communications networks and multivariate analysis to predict or recommend optimal products from a predefined population of commercially available products are disclosed. The recommendations are based on intelligence contained in processing elements and subjective and/or objective product information received from consumers or input to the systems as part of their initial setup. The output of the systems comprise sets of products that they predict the consumer will prefer and/or perform well for the problem or concern identified by the consumer. The performance and preference predictions are a function of consumer problems and product responsiveness patterns. Objective product information is generally obtained with diagnostic instruments. Data measured with the diagnostic instruments may be communicated to the data processing portions of the invention via the Internet. The outputs of the data processing portion of the system may be presented to consumers via the Internet as well.

Claims

1. A method for improving product recommendation quality, the method comprising:

generating a plurality of individualized product recommendations for a given concern with an intelligent performance-based product recommendation engine;

receiving feedback from a plurality of consumers on use of products to treat the concern; and

re-training the product recommendation engine based on the feedback received.

2. The method of claim 1, wherein the receiving feedback step comprises receiving product preference data.

3. The method of claim 1, wherein the receiving feedback step comprises receiving product performance data.

4. The method of claim 3, wherein the receiving product performance data step further comprises receiving target substrate condition data.

5. The method of claim 3, wherein the receiving feedback step further comprises receiving subjective product performance data.

6. The method of claim 3, wherein the receiving feedback step further comprises receiving objective product performance data.

7. The method of claim 6, wherein the receiving objective product performance data step comprises receiving diagnostic data.

8. The method of claim 1, wherein the re-training step comprises adjusting values of a plurality of product attributes in a neural network, the neural network comprising a portion of the product recommendation engine.

9. The method of claim 1, wherein the re-training step comprises adjusting values of a plurality of connection weights in a neural network, the neural network comprising a portion of the product recommendation engine.

10. The method of claim 1, wherein the re-training step comprises identifying relevant consumer segments based on the feedback and grouping the consumers into the segments.

11. The method of claim 1, wherein the re-training step comprises revising a set of collaborative neighborhood configurations in a collaborative filter, the collaborative filter comprising a portion of the product recommendation engine.

12. The method of claim 1, wherein the re-training step comprises adding a personal profile information filter to a set of collaborative neighborhood configurations in a collaborative filter, the collaborative filter comprising a portion of the product recommendation engine.

13. A system for generating individual product recommendations, the system comprising:

a database containing product information and consumer information; and

an intelligent performance-based product recommendation engine in communication with the database,

wherein the individualized product recommendations are generated by the product recommendation engine in response to a request, the product recommendation engine drawing on data contained in the request and the information in the database to generate the product recommendations.

14. The system of claim 13, wherein the product recommendation engine comprises a content-based filter.

15. The system of claim 13, wherein the product recommendation engine comprises a neural network.

16. The system of claim 15, wherein the neural network contains a plurality of attributes for each of a plurality of products within a plurality of product categories.

17. The system of claim 15, wherein the neural network receives as inputs a plurality of consumer characterization variables for the consumer and product performance data for a population of consumers.

18. The system of claim 15, wherein the neural network receives as inputs a plurality of consumer characterization variables for the consumer and product preference data for a population of consumers.

19. The system of claim 13, wherein the product recommendation engine comprises a collaborative filter, the collaborative filter defining a set of other consumers similar to the consumer associated with the request.

20. The system of claim 13, wherein the product recommendation engine comprises a cascaded collaborative and content-based filter.

21. The system of claim 13, further comprising an information interface communicably connected to the product recommendation engine.

22. The system of claim 21, wherein the communicable connection comprises a computer network.

23. The system of claim 21, wherein the communicable connection comprises a telecommunications network.

24. The system of claim 21, wherein the communicable connection comprises the Internet.

25. The system of claim 21, wherein the information interface comprises a personal computer.

26. The system of claim 21, wherein the information interface comprises a diagnostic device.

27. The system of claim 21, wherein the information interface comprises a camera.

28. The system of claim 21, wherein the information interface comprises a kiosk.

29. The system of claim 21, wherein the product recommendations are limited to products available for purchase in a vicinity of the information interface.

30. The system of claim 21, wherein the information interface is located at a professional service provider'"'"'s office.

31. The system of claim 21, wherein the information interface is located at a consumer'"'"'s home.

32. The system of claim 13, wherein the request comprises an identification of a target substrate and a particular consumer, the consumer information stored in the database comprising a characterizations record for the particular consumer.

33. The system of claim 13, wherein the request is generated by the consumer.

34. The system of claim 13, wherein the request is generated by a professional service provider.

35. The system of claim 33, wherein the record further comprises an importance of the concern.

36. The system of claim 33, wherein the record further comprises a severity of the concern.

37. The system of claim 33, wherein the record further comprises product preference information.

38. The system of claim 33, wherein the record further comprises historical product preference information.

39. The system of claim 33, wherein the record further comprises historical product performance information.

40. The system of claim 33, wherein the record further comprises personal profile information.

41. The system of claim 13, wherein the product recommendations comprise a first list of products and a scored predicted performance utility for each listed product.

42. The system of claim 13, wherein the product recommendations comprise a first list of top-N products and a scored predicted performance utility for each listed product.

43. The system of claim 13, wherein the product recommendations comprise a first list of products and a scored predicted preference utility for each listed product.

44. The system of claim 13, wherein the product recommendations comprise a first list of top-N products and a scored predicted product preference utility for each listed product.

45. The system of claim 13, wherein the product recommendations comprise a first list of products and a purchase price for each listed product.

46. The system of claim 13, further comprising generating ancillary information output with the product recommendation engine in response to the request.

47. The system of claim 13, wherein ongoing feedback regarding the use of products is received by the system, portions of the feedback being stored in the product information and consumer information databases.

48. The system of claim 47, wherein the feedback comprises product performance data.

49. The system of claim 47, wherein the feedback comprises product preference data.

50. The system of claim 47, wherein the feedback comprises subjective feedback.

51. The system of claim 47, wherein the feedback comprises objective feedback.

52. The system of claim 47, wherein the product recommendation engine is periodically re-trained based on the feedback.

53. The system of claim 52, wherein the re-training improves a quality of the product recommendations.

54. The system of claim 52, wherein the product recommendation engine comprises a collaborative filter having a plurality of collaborative neighborhoods and the re-training comprises revising the collaborative neighborhoods based on performance response patterns of the consumers.

55. The system of claim 13, further comprising a professional interface communicably connected to the product recommendation engine.

56. The system of claim 55, wherein the communicable connection comprises the Internet.

57. The system of claim 55, wherein the professional interface comprises a personal computer.

58. The system of claim 55, wherein the professional interface comprises a diagnostic device.

59. The system of claim 58, wherein the device comprises a camera.