USER INTENT TRACKING STREAMS

• US 20150112754A1
• Filed: 10/17/2013
• Published: 04/23/2015
• Est. Priority Date: 10/17/2013
• Status: Active Application

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Godsey, Sandra Lynn, Romero, Steven, Akin, Jeremiah Jose
• Application Number:
  US14/056,762
• Publication Number:
  US 20150112754A1
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

Systems, methods and media are proposed for user intent tracking streams. One example embodiment relates to a system that comprises an identification module to identify a plurality of aspects of contextual or personal information relating to a user, and an analysis module to analyze the plurality of aspects of contextual or personal information to identify user intent or a likelihood relating to a pre-determined action. The system further comprises a correlation module to correlate the user intent or likelihood with at least a sub-set of the analyzed aspects of contextual or personal information to identify an intent tracking stream for the user, the intent tracking stream based on the correlated sub-set, and a tracking module to track the intent tracking stream as a user identifier or a predictor of the pre-determined action.

Claims

1. An intent tracking system comprising:

an identification module to identify a plurality of aspects of contextual or personal information relating to a user;

an analysis module to analyze the plurality of aspects of contextual or personal information to identify a user intent or a likelihood relating to a pre-determined action or event;

a correlation module to correlate the user intent or likelihood with at least a sub-set of the analyzed aspects of contextual or personal information to identify an intent tracking stream for the user, the intent tracking stream based on the correlated sub-set; and

a tracking module to track the intent tracking stream as a user identifier or a predictor of the pre-determined action or event, and wherein each of the modules executes on one or more computer processors.

2. The system of claim 1, wherein the tracking module is further to track the intent tracking stream in a marketplace environment and take an action based on the identified intent tracking stream.

3. The system of claim 2, further comprising a targeting module to present real-time targeted information, relevant to a pre-determined action, to a user based on the identified intent tracking stream.

4. The system of claim 1, further comprising an aggregation module to identify the intent tracking stream based on aspects of contextual or personal information identified across a multiplicity of devices, sessions, interfaces or communication channels.

5. The system of claim 4, wherein the aggregation module is further to aggregate a plurality of aspects of contextual or personal information across a multiplicity of users to identify an intent tracking stream as a collective user identifier or a predictor of the pre-determined action, or event.

6. A method comprising:

identifying a plurality of aspects of contextual or personal information relating to a user;

analyzing the plurality of aspects of contextual or personal information to identify a user intent or a likelihood relating to a pre-determined action or event;

correlating the user intent or likelihood with at least a sub-set of the analyzed aspects of contextual or personal information to identify an intent tracking stream for the user, the intent tracking stream based on the correlated sub-set; and

tracking the intent tracking stream as a user identifier or a predictor of the pre-determined action or event.

7. The method of claim 6, further comprising tracking the intent tracking stream in a marketplace environment and taking an action based on the identified intent tracking stream.

8. The method of claim 7, wherein the action taken includes presenting real-time targeted information, relevant to a pre-determined action, to a user.

9. The method of claim 6, wherein the intent tracking stream is based on aspects of contextual or personal information identified across a multiplicity of devices, sessions, interfaces or communication channels.

10. The method of claim 6, further comprising aggregating the plurality of aspects of contextual or personal information across a multiplicity of users to identify an intent tracking stream as a collective user identifier or a predictor of the pre-determined action or event.

11. A machine readable medium, including instructions, which when performed by a machine, causes the machine to perform the operations of:

identifying a plurality of aspects of contextual or personal information relating to a user;

analyzing the plurality of aspects of contextual or personal information to identify a user intent or a likelihood relating to a pre-determined action or event;

correlating the user intent or likelihood with at least a sub-set of the analyzed aspects of contextual or personal information to identify an intent tracking stream for the user, the intent tracking stream based on the correlated sub-set; and

tracking the intent tracking stream as a user identifier or a predictor of the pre-determined action or event.

12. The machine readable medium of claim 11, wherein the operations further comprise tracking the intent tracking stream in a marketplace environment and taking an action based on the identified intent tracking stream.

13. The machine readable medium of claim 12, wherein the action taken includes presenting or restricting real-time targeted information, relevant to a pre-determined action, to a user.

14. The machine readable medium of claim 11, wherein the intent tracking stream is based on aspects of contextual or personal information identified across a multiplicity of devices, sessions, interfaces or communication channels.

15. The medium of claim 11, wherein the operations further comprise aggregating the plurality of aspects of contextual or personal information across a multiplicity of users to identify an intent tracking stream as a collective user identifier or a predictor of the pre-determined action or event.