RECOGNIZING AND CREDITING OFFLINE REALIZATION OF ONLINE BEHAVIOR

• US 20090132366A1
• Filed: 06/11/2008
• Published: 05/21/2009
• Est. Priority Date: 11/15/2007
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Lam, Lawrence, Ward, Bradley W., Sacheti, Arun
• Application Number:
  US12/137,487
• Publication Number:
  US 20090132366A1
• Time in Patent Office: Days
• US Class Current: 705/14.360
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0236 Incentive or reward received by requiring registration or ID from user
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising
• CPC Class Codes: G06Q 40/12 Accounting

Abstract

The subject disclosure relates to an improved electronic commerce and advertising platform that aggregates transaction data from merchants and consumers. A set of enhanced scenarios built on the platform span both the online and offline transactional and advertising universe to the benefit of all participants of the electronic commerce and advertising platform. In one embodiment, an online recommendation for a product or service represented in a user'"'"'s transaction history is received by a set of recipients. A recipient then purchases the product or service in an offline transactional environment (e.g., in a store), and the recommendation is credited for the offline realization for the online recommendation.

Claims

1. A method for a service of an electronic commerce platform that aggregates offline and online user transaction data from users, including:

accessing a transaction history representing a set of products or services consumed by a user;

publishing online, to a group of users of which the user is a member, at least one recommended product or service selected from the set;

determining at least one other user of the group subsequently interacted with the at least one recommended product or service according to an offline interaction in an offline setting; and

automatically correlating the offline interaction to the publishing online.

2. The method of claim 1, further comprising:

automatically crediting an account of the user with a reward for the user in response to the correlating if the offline interaction is threshold correlated to the publishing online.

3. The method of claim 1, wherein the correlating includes automatically correlating the offline interaction to the publishing online to determine if sufficient correlation exists between the publishing online and the offline interaction to recognize a conversion.

4. The method of claim 1, wherein the determining includes determining at least one other user of the group subsequently purchased the at least one recommended product or service in the offline setting.

5. The method of claim 1, further comprising:

receiving at least one selection of the at least one recommended product or service from the user.

6. The method of claim 1, wherein the publishing includes automatically publishing the at least one recommended product or service selected from the set based on a predetermined rule.

7. The method of claim 1, further comprising:

receiving a designation of the group of users from alternate choices of groups of users from the user.

8. The method of claim 1, wherein the accessing includes accessing a transaction history online representing a set of products or services consumed by the user in both online and offline settings.

9. The method of claim 1, further comprising:

filtering the products of the transaction history to form the set of products and services based on an analysis of user profiles of the group.

10. An electronic commerce platform, comprising:

a data exchange for aggregating user transaction data from online and offline transactions conducted by a group of users;

a recommendation service that recommends an item from a user'"'"'s purchase history to other users of a group of users including the user; and

a benefit payout component that recognizes an offline purchase of the item by one of the other users of the group after the item is recommended via the recommendation service.

11. The electronic commerce platform of claim 10, wherein the benefit payout component automatically awards a benefit to the user based on the recognizing of the offline purchase of the item.

12. The electronic commerce platform of claim 10, wherein the benefit payout component automatically credits an account of the user based on the recognizing of the offline purchase of the item.

13. The electronic commerce platform of claim 10, wherein the recommendation service recommends the item automatically based on at least one recommendation rule preconfigured by the user.

14. The electronic commerce platform of claim 10, wherein the recommendation service recommends the item automatically based on a solicitation for recommendations from at least one other user of the group.

15. A method for interfacing with a service of an electronic commerce platform that aggregates offline and online user transaction data for users, including:

displaying a set of offline and online transactions conducted by a user representing a set of products or services consumed by the user;

receiving a selection of at least one product or service from the set to recommend to a group of other users of the platform, advertising the at least one product or service to the group of other users;

determining at least one other user of the group subsequently interacted with the at least one recommended product or service according to an offline interaction in an offline setting; and

automatically correlating the offline interaction to the advertising.

16. The method of claim 15, wherein the advertising includes at least one of automatically generating an advertisement based on a description of the at least one product or service, generating an advertisement from user input about the at least one product or service, or retrieving pre-existing advertisement content associated with the at least one product or service.

17. The method of claim 15, further comprising:

receiving a selection of the communications channel for use with the advertising step to customize the way the group of other users receive an advertisement of the at least one product or service.

18. The method of claim 15, further comprising:

receiving a selection of the group from a set of groups including explicitly defined groups based on user input and implicitly defined groups based on an analysis of user profiles of the group of other users.

19. The method of claim 15, further comprising:

automatically crediting an account of the user with a reward for the user in response to the correlating if the offline interaction is determined to be threshold correlated to the advertising.

20. The method of claim 15, further comprising:

filtering the products of the transaction history to form the set of products and services for potential recommendation according to the advertising.