IP Library Granted Patent US 10,134,049
Granted Patent B2
US 10,134,049 · App. 14/549,010 · Granted Nov 20, 2018

Customer service based upon in-store field-of-view and analytics

Inventors: Robert Alan Koch (Norcross, GA); Ari Craine (Marietta, GA); James Carlton Bedingfield, Sr. (Gainesville, GA)
Assignee: AT&T Intellectual Property I, L.P.
G06Q30/0201G06Q30/016G06Q50/01H04L51/32
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Quick Facts
Patent No.
US 10,134,049
App. No.
14/549,010
Granted
Nov 20, 2018
Kind
B2
Abstract

Concepts and technologies disclosed herein are directed to aspects of customer service based upon in-store field-of-view and analytics. According to one aspect disclosed herein, a store analytics system can collect user information associated with a plurality of users located within an environment. The store analytics system also can collect user device information associated with a plurality of user devices associated with the plurality of users. The store analytics system also can collect estimated fields-of-view associated with the plurality of users. The store analytics system can analyze the user information, the user device information, and the estimated fields-of-view to identify at least one commonality shared among at least two of the plurality of users. The store analytics system can create a logical group. The logical group can include the at least two users of the plurality of users that share the commonality.

Claims (55)

1. A method comprising

collecting, by a store analytics system comprising a processor that executes a store analytics application, user information associated with a plurality of users located within a store premises, wherein the user information uniquely identifies each of the plurality of users as a customer of the store premises, and wherein the store premises comprises a plurality of aisles in which a plurality of items are located;

collecting, by the store analytics system, user device information associated with a plurality of user devices associated with the plurality of users, wherein the user device information uniquely identifies each of the plurality of user devices;

receiving, by the store analytics system, from a visual orientation system, estimated fields-of-view associated with the plurality of users, wherein each estimated field-of-view of the estimated fields-of-view is determined by the visual orientation system based upon an orientation of a user device of the plurality of user devices and a location of the user device of the plurality of user devices within the store premises, wherein the orientation of the user device is determined by the user device via an orientation sensor of the user device in response to the orientation sensor detecting that the user device has stopped within the store premises at a specific time, wherein the location of the user device is determined by the user device via a location component of the user device further in response to the orientation sensor detecting that the user device has stopped within the store premises at the specific time, and wherein each estimated field-of-view of the estimated fields-of-view identifies an aisle of the plurality of aisles and an item of the plurality of items in the aisle;

determining, by the store analytics system, based upon the user information, the user device information, and the estimated fields-of-view, a commonality shared among at least two users of the plurality of users, wherein the commonality comprises each user of the at least two users of the plurality of users having the item of the plurality of items in an estimated field-of-view with the at least two users; and

creating, by the store analytics system, a logical group, wherein the logical group comprises a group of customers of the store premises comprising the at least two users of the plurality of users that share the commonality.

2. The method of claim 1 , further comprising:

generating, by the store analytics system, an offer directed to the logical group, wherein the offer is associated with the item; and

sending, by the store analytics system, the offer to the logical group.

3. The method of claim 2 , wherein sending, by the store analytics system, the offer to the logical group comprises sending, by the store analytics system, the offer to each user device of the plurality of user devices that is associated with a member of the logical group.

4. The method of claim 2 , wherein sending, by the store analytics system, the offer to the logical group comprises sending, by the store analytics system, the offer to a signage for presentation of the offer to the logical group, wherein the signage displays a price for the item particular to the logical group.

5. The method of claim 1 , further comprising:

collecting, by the store analytics system, traffic pattern data associated with a traffic pattern of the logical group as members of the logical group move within the store premises;

generating, by the store analytics system, a notification message to instruct customer service personnel associated with the store premises to assist members of the logical group with the item; and

sending, by the store analytics system, the notification message to the customer service personnel.

6. The method of claim 1 , further comprising instructing, by the store analytics system, a remote agent to provide assistance to members of the logical group with regard to the item.

7. The method of claim 1 , further comprising:

generating, by the store analytics system, a message directed to a member of a social network platform, wherein the message instructs the member of the social network platform to provide assistance to the logical group with regard to the item; and

sending, by the store analytics system, the message to the member of the social network platform so that the member of the social network platform can provide assistance to the logical group with regard to the item.

8. A store analytics system comprising:

a processor; and

memory that stores computer-executable instructions that, when executed by the processor, cause the processor to perform operations comprising

collecting user information associated with a plurality of users located within a store premises, wherein the user information uniquely identifies each of the plurality of users as a customer of the store premises, and wherein the store premises comprises a plurality of aisles in which a plurality of items are located,

collecting user device information associated with a plurality of user devices associated with the plurality of users, wherein the user device information uniquely identifies each of the plurality of user devices,

receiving, from a visual orientation system, estimated fields-of-view associated with the plurality of users, wherein each estimated field-of-view of the estimated fields-of-view is determined by the visual orientation system based upon an orientation of a user device of the plurality of user devices and a location of the user device of the plurality of user devices within the store premises, wherein the orientation of the user device is determined by the user device via an orientation sensor of the user device in response to the orientation sensor detecting that the user device has stopped within the store premises at a specific time, wherein the location of the user device is determined by the user device via a location component of the user device further in response to the orientation sensor detecting that the user device has stopped within the store premises at the specific time, and wherein each estimated field-of-view of the estimated fields-of-view identifies an aisle of the plurality of aisles and an item of the plurality of items in the aisle,

determining, based upon the user information, the user device information, and the estimated fields-of-view, a commonality shared among at least two users of the plurality of users, wherein the commonality comprises each user of the at least two users of the plurality of users having the item of the plurality of items in an estimated field-of-view with the at least two users, and

creating a logical group, wherein the logical group comprises a group of customers of the store premises comprising the at least two users of the plurality of users that share the commonality.

9. The store analytics system of claim 8 , wherein the operations further comprise:

generating an offer directed to the logical group, wherein the offer is associated with the item; and

sending the offer to the logical group.

10. The store analytics system of claim 9 , wherein sending the offer to the logical group comprises sending the offer to each user device of the plurality of user devices that is associated with a member of the logical group.

11. The store analytics system of claim 9 , wherein sending the offer to the logical group comprises sending the offer to a signage for presentation of the offer to the logical group, wherein the signage displays a price for the item particular to the logical group.

12. The store analytics system of claim 8 , wherein the operations further comprise:

collecting traffic pattern data associated with a traffic pattern of the logical group as members of the logical group move within the store premises;

generating a notification message to instruct customer service personnel associated with the store premises to assist members of the logical group with the item; and

sending the notification message to the customer service personnel.

13. The store analytics system of claim 8 , wherein the operations further comprise instructing a remote agent to provide assistance to members of the logical group with regard to the item.

14. The store analytics system of claim 8 , wherein the operations further comprise:

generating a message directed to a member of a social network platform, wherein the message instructs the member of the social network platform to provide assistance to the logical group with regard to the item; and

sending the message to the member of the social network platform so that the member of the social network platform can provide assistance to the logical group with regard to the item.

15. A computer-readable storage medium having computer-executable instructions that, when executed by a processor of a store analytics system, cause the store analytics system to perform operations comprising:

collecting user information associated with a plurality of users located within a store premises, wherein the user information uniquely identifies each of the plurality of users as a customer of the store premises, and wherein the store premises comprises a plurality of aisles in which a plurality of items are located;

collecting user device information associated with a plurality of user devices associated with the plurality of users, wherein the user device information uniquely identifies each of the plurality of user devices;

receiving, from a visual orientation system, estimated fields-of-view associated with the plurality of users, wherein each estimated field-of-view of the estimated fields-of-view is determined by the visual orientation system based upon an orientation of a user device of the plurality of user devices and a location of the user device of the plurality of user devices within the store premises, wherein the orientation of the user device is determined by the user device via an orientation sensor of the user device in response to the orientation sensor detecting that the user device has stopped within the store premises at a specific time, wherein the location of the user device is determined by the user device via a location component of the user device further in response to the orientation sensor detecting that the user device has stopped within the store premises at the specific time, and wherein each estimated field-of-view of the estimated fields-of-view identifies an aisle of the plurality of aisles and an item of the plurality of items in the aisle;

determining, based upon the user information, the user device information, and the estimated fields-of-view, a commonality shared among at least two users of the plurality of users, wherein the commonality comprises each user of the at least two users of the plurality of users having the item of the plurality of items in an estimated field-of-view with the at least two users; and

creating a logical group, wherein the logical group comprises a group of customers of the store premises comprising the at least two users of the plurality of users that share the commonality.

16. The computer-readable storage medium of claim 15 , wherein the operations further comprise:

generating an offer directed to the logical group, wherein the offer is associated with the item; and

sending the offer to the logical group.

17. The computer-readable storage medium of claim 16 , wherein sending the offer to the logical group comprises sending the offer to each user device of the plurality of user devices that is associated with a member of the logical group.

18. The computer-readable storage medium of claim 16 , wherein sending the offer to the logical group comprises sending the offer to a signage for presentation of the offer to the logical group, wherein the signage displays a price for the item that is particular to the logical group.

19. The computer-readable storage medium of claim 15 , wherein the operations further comprise instructing a remote agent to provide assistance to members of the logical group with regard to the item.

20. The computer-readable storage medium of claim 15 , wherein the operations further comprise:

generating a message directed to a member of a social network platform, wherein the message instructs the member of the social network platform to provide assistance to the logical group with regard to the item; and

sending the message to the member of the social network platform so that the member of the social network platform can provide assistance to the logical group with regard to the item.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 20, 2014
From: KOCH, ROBERT ALAN; CRAINE, ARI; BEDINGFIELD, JAMES CARLTON, SR
To: AT&T INTELLECTUAL PROPERTY I, L.P.
Reel/Frame 034221/0655 →
Continuity (1)
Related Publication 20160148218A1 · May 26, 2016