Reverse brand sorting tools for interest-graph driven personalization

• US 10,019,730 B2
• Filed: 03/15/2013
• Issued: 07/10/2018
• Est. Priority Date: 08/15/2012
• Status: Expired due to Fees

• Current Assignee: Rally AG LLC (Teledisc Corporation)
• Original Assignee: AutoGraph Incorporated
• Inventors: Roundtree, Brian
• Primary Examiner(s): Vu, Kieu
• Assistant Examiner(s): Calderon, IV, Alvaro R
• Application Number:
  US13/843,270
• Publication Number:
  US 20140052527A1
• Time in Patent Office: 1,943 Days
• Field of Search: 715745, 715810, 709203, 705 12, 705 141- 1473, 705 261- 272, 705310, 705319, 235375
• CPC Class Codes: G06Q 30/0245 Surveys

Abstract

An input and processing system allows user input information such as user affinity to efficiently block content and request content as well as novel input of commands such as copy/paste on a small mobile device screen among other computing devices. A client/server is also made more efficient due to the enhanced gathering of information such as content feedback from users.

Yet another disclosure regards a system allowing leveraging of preexisting information to display content and select brands for user feedback.

Also disclosed are systems for increasing sales efficiency, and various GUI interfaces.

Claims

1. A non-transitory computer readable medium having instructions stored thereon that are executable by processor electronics configured to:

receive preexisiting data from a user device associated to a user profile of a user, wherein the preexisting data is comprised of user location data which comprises a number of times the user was inside a boundary associated to a brand device, wherein the user location data was determined on the user device by the steps of;

displaying on the user device a user interface permitting the selection of a plurality of different location boundary granularities;

receiving a user selected location boundary granularity, wherein a location boundary granularity represents a specific geographical boundary specification; and

in response to the selection of the location boundary granularity, determining user location data, wherein the user location data comprises location data with only location boundary granularities with the same specification or greater specification than the selected location boundary granularity;

determine a characteristic of the user and an associated characteristic statistical probability based on a brand affinity, which is calculated at least from the preexisting data, wherein the determination of the user characteristic comprises associating said brand affinity with a preexisting data characteristics tag and an associated statistical probability characteristics tag based at least upon one or more of marketing data or a taxonomy, wherein the associated statistical probability characteristics tag represents a statistical probability of the user having the characteristic represented by the pre-existing data characteristics tag;

associate to the user at least two marketing brand buckets comprised of a first and a second marketing brand bucket, in which association comprises matching the user characteristic to the first marketing brand bucket using one or more of marketing data or a taxonomy, wherein the at least two marketing brand buckets each comprise a plurality of brands associated to users of brands associated with the respective buckets as determined by marketing data;

select at least one brand to be presented to the user, wherein the at least one brand selected is associated to at least one brand characteristic tag that is matched with the determined characteristic of the user, and the brand characteristic tag is associated to a brand statistical probability characteristics tag, wherein the brand statistical probability characteristics tag represents a statistical probability of users of the brand having the brand characteristic represented by the brand characteristic tag, wherein the at least one brand is selected from the plurality of brands from the associated first and second marketing brand buckets in which the at least one brand is selected in response to a determination that the at least one brand has the highest probability to determine the determined user characteristic relative to other brands from the plurality of brands;

receive user feedback indicating whether the user has an affinity for said at least one brand; and

based on the received feedback, change a confidence level that the user has the determined user characteristic.

2. The non-transitory computer readable medium of claim 1, further comprising instructions to determine neutral user affinity feedback.

3. The non-transitory computer readable medium of claim 1, further comprising instructions for assigning a weight to a piece of said preexisting data based on marketing data.

4. The non-transitory computer readable medium of claim 1, further comprising instructions to receive user feedback input in response to when the user moves a touch point on a display screen in a predefined direction over said at least one brand.

5. The non-transitory computer readable medium of claim 1, further comprising instructions for storing the user feedback input as a brand affinity tag.

6. The non-transitory computer readable medium of claim 1, further comprising instructions to add the one or more determined characteristics to an interest graph.

7. The non-transitory computer readable medium of claim 1, further comprising instructions to protect the user'"'"'s privacy by creating a unique intermediary identifier configured to be used as an intermediary between the preexisting data and a user ID associated to the user.

8. The non-transitory computer readable medium of claim 1, further comprising the instructions for:

presenting the at least one brand for user feedback to a second user different than the user;

receive second user feedback indicating whether the second user determines that the user has an affinity for said at least one brand; and

based on the received feedback from the second user, change a confidence level that the user has the determined characteristic.

9. The non-transitory computer readable medium of claim 1, further comprising instructions for selecting the at least one brand from the plurality of brands from the first and second marketing buckets based at least on the at least one brand being associated to the brand statistical probability characteristics tag having a higher signal to noise ratio than brand statistical probability characteristics tags associated to the other the brands from the first and second marketing buckets.

10. A non-transitory computer readable medium for a user profile creation tool, having instructions stored thereon that are executable by processor electronics to:

receive preexisiting data from a user device associated to a user profile of a user, wherein the preexisting data is comprised of user location data which comprises a number of times the user was within a boundary area associated to a brand device, wherein the user location data was determined by the user device by;

displaying on the user device a user interface permitting the selection of a plurality of different location boundary resolutions;

receiving a user selected location boundary resolution, wherein a location boundary resolution represents a specific geographical specification; and

in response to the selection of the location boundary resolution, determining user location data, wherein the user location data comprises geographical area references having only the same geographical specifications or greater geographical specifications than the selected location boundary resolution;

determine meaning of the received preexisting data, wherein the determination comprises associating at least a portion of said preexisting data with a preexisting data characteristic tag, wherein the association of the portion of preexisting data with said pre-existing data characteristic tag is based on one or more of a taxonomy or a marketing data association;

based at least on said meaning, select at least one set of brands in which each brand in the set of brands is associated to a common characteristic, wherein the selection comprises associating the preexisting data characteristic tag to a characteristic tag associated to the set of brands;

select at least one brand from the set of brands for user presentation on the user device, wherein selection comprises;

selecting the at least one brand from the set of brands in which the at least one brand is determined to have a highest conclusive probability to determine the pre-existing data characteristic or the common characteristic relative to other brands from the set of brands; and

receive user feedback on said at least one brand from the user device.

11. A non-transitory computer readable medium having instructions stored thereon that are executable by processor electronics to:

display a user interface permitting user selection of a plurality of different location boundary resolutions;

receive a user selected location boundary resolution, wherein a location boundary resolution represents a specific geographical area specification;

in response to the selection of the location boundary resolution, determine user location data, wherein the user location data comprises location data having resolutions only to geographical area specifications having the same area size or greater than the selected location boundary resolution;

select a preexisting characteristics tag and an associated probability based on the user location data which comprises a frequency that a device associated to a user is within a geographical area associated to a brand device which is the same geographical area specification or greater area specification than the selected boundary resolution;

transmit to a remote computer, the preexisting characteristics tag and the associated probability, both of which are configured to be associated to a user profile;

in response to transmitting the preexisting characteristics tag and the associated probability, receive references to at least two brands selected from a plurality of brands for presentation to the user on a display screen, in which the at least two brands were selected by the remote computer by;

assigning the preexisting data characteristic tag to the user profile;

determining at least two preexisting data characteristic tags in the user profile that are each associated to a probability that each preexisting data characteristic tag is greater than fifty percent probability of a user associated to the user profile having the characteristic represented by the preexisting data characteristic tag; and

selecting the at least two brands from the plurality of brands in which the at least two brands are a combination of brands that when presented to the user, are determined to elicit user feedback that has the greatest probability to further determine the at least two preexisting data characteristic tags relative to the other brands comprising the plurality of brands;

detect a gesture regarding an affinity for at least one of the two brands;

in response to the detected user affinity gesture, transmit the affinity to the remote computer; and

receive content based on the transmitted affinity.

12. The non-transitory computer readable medium of claim 11, further comprising instructions for determining a user affinity for at least one of the at least two brands by detecting when the user moves a touch point on the display screen in a predefined direction over a representation of said at least one of the at least two brands.

13. The non-transitory computer readable medium of claim 12, further comprising instructions for detecting movement of a touch point on the display screen from input via a touch screen.

14. The non-transitory computer readable medium of claim 11, further comprising instructions to incorporate the affinity into an interest graph.

15. The non-transitory computer readable medium of claim 11, further comprising instructions for displaying a brand that the user has previously interacted with and a brand that the user has not previously interacted with.