GEOGRAPHIC SEGMENTATION SYSTEMS AND METHODS

• US 20160112291A1
• Filed: 12/22/2015
• Published: 04/21/2016
• Est. Priority Date: 08/31/2011
• Status: Active Grant

• Current Assignee: Adobe Inc.
• Original Assignee: Adobe Systems Incorporated (Adobe Inc.)
• Inventors: Hansen, Ian M., Aurigemma, Pearce, Sandquist, Carl J., George, William Brandon, Smith, Kevin G.
• Granted Patent: US 9,860,148 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 50/10 Services
• CPC Class Codes: H04L 41/0618 based on the physical or logical position
• CPC Class Codes: H04L 43/062 related to network traffic
• CPC Class Codes: H04L 43/0882 Utilisation of link capacity
• CPC Class Codes: H04L 5/0069 Allocation based on distance or geographical location allocation based on terminal or device properties in general, H04W72/51
• CPC Class Codes: H04L 51/222 using geographical location information, e.g. messages transmitted or received in proximity of a certain spot or area
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal

Abstract

Methods and systems for segmenting traffic based on geography include assigning coordinate location data received with respect to members of a plurality of computing devices to analytics data associated with a plurality of requests for content received from respective ones of the plurality of computing devices. A geographical location of interest is defined. The defining the geographical location of interest includes designating a plurality of points defining boundaries of the geographical location of interest. Respective ones of a plurality of traffic segments are assigned to the plurality of requests for content based in part upon a comparison of the geographical location of interest to coordinate location data assigned to respective ones of the plurality of requests for content. Network traffic metrics are generated for ones of the plurality of traffic segments. The request traffic metrics describe request behavior associated with particular segments of the plurality of traffic segments.

Claims

1. A computer implemented method for tracking analytics data related to requests for content over a computer network and generating metrics using the tracked analytics data, the method performing operations comprising:

tracking analytics data for requests for content over a computer network, the analytics data for each request comprising a user identifier of a person or a user computing device that made the request, a time and date of the request, a description of the request, and a coordinate location of the user computing device when the request for content was made, the coordinate location recorded and transmitted by the user computing device; and

generating traffic metrics for each of one or more geographical locations of interest by segmenting the analytics data based on the coordinate location of the request.

2. The method of claim 1, further comprising identifying the person or the user computing device that made the request for content from the analytics data for requests for provision of content based on requests received from the user computing device.

3. The method of claim 1, wherein tracking analytics data further comprises tracking location visit patterns using multiple coordinate locations.

4. The method of claim 1, further comprising designating a plurality of points defining boundaries of the geographical location of interest comprising:

analyzing the requests for content to determine request densities in a plurality of location units,

identifying a set of location units with respective request densities within a selected range,

fitting a set of boundary points to boundaries of the set of location units, and

assigning the set of boundary points to define the boundaries of the geographical location of interest.

5. The method of claim 1, further comprising designating a plurality of points defining boundaries of the geographical location of interest comprising:

analyzing the requests for content to determine respective request densities in a plurality of location units,

presenting a map of the plurality of location units with indications of the respective request densities in the plurality of location units, responsive to selection of a location unit from the plurality of location units,

identifying a set of location units with respective request densities similar to the request density of the location unit,

fitting a set of boundary points to boundaries of the set of location units with respective request densities similar to the request density of the location unit, and

assigning the set of boundary points to define the boundaries of the geographical location of interest.

6. A computer-implemented monitoring device for tracking analytics data related to requests for content over a computer network and generating metrics using the tracked analytics data, the monitoring device comprising:

at least one processor; and

a memory comprising program instructions, wherein the program instructions are executable by the at least one processor to;

track analytics data for requests for content over a computer network, the analytics data for each request comprising a user identifier of a person or a user computing device that made the request, a time and date of the request, a description of the request, and a coordinate location of the user computing device when the request for content was made, the coordinate location recorded and transmitted by the user computing device; and

generate traffic metrics for each of one or more geographical locations of interest by segmenting the analytics data based on the coordinate location of the request.

7. The computer-implemented monitoring device of claim 6, wherein the program instructions are further executable to identify the person or the user computing device that made the request for content from the analytics data for requests for provision of content based on requests received from the user computing device.

8. The computer-implemented monitoring device of claim 6, wherein tracking analytics data further comprises tracking location visit patterns using multiple coordinate locations.

9. The computer-implemented monitoring device of claim 6, further comprising designating a plurality of points defining boundaries of the geographical location of interest comprising:

analyzing the requests for content to determine request densities in a plurality of location units,

identifying a set of location units with respective request densities within a selected range,

fitting a set of boundary points to boundaries of the set of location units, and

assigning the set of boundary points to define the boundaries of the geographical location of interest.

10. The computer-implemented monitoring device of claim 6, further comprising designating a plurality of points defining boundaries of the geographical location of interest comprising:

analyzing the requests for content to determine respective request densities in a plurality of location units,

presenting a map of the plurality of location units with indications of the respective request densities in the plurality of location units, responsive to selection of a location unit from the plurality of location units,

identifying a set of location units with respective request densities similar to the request density of the location unit,

fitting a set of boundary points to boundaries of the set of location units with respective request densities similar to the request density of the location unit, and

assigning the set of boundary points to define the boundaries of the geographical location of interest.

11. A non-transitory computer-readable storage medium storing computer-executable program instructions, wherein the program instructions are executable to:

track analytics data for requests for content over a computer network, the analytics data for each request comprising a user identifier of a person or a user computing device that made the request, a time and date of the request, a description of the request, and a coordinate location of the user computing device when the request for content was made, the coordinate location recorded and transmitted by the user computing device; and

generate traffic metrics for each of one or more geographical locations of interest by segmenting the analytics data based on the coordinate location of the request

12. The non-transitory computer-readable storage medium storing computer-executable program instructions of claim 11, wherein the program instructions are further executable to identify the person or the user computing device that made the request for content from the analytics data for requests for provision of content based on requests received from the user computing device.

13. The non-transitory computer-readable storage medium storing computer-executable program instructions of claim 11, wherein the program instructions executable to track analytics data further comprises program instructions executable to track location visit patterns using multiple coordinate locations.

14. The non-transitory computer-readable storage medium storing computer-executable program instructions of claim 11, wherein the program instructions are further executable to designate a plurality of points defining boundaries of the geographical location of interest comprising:

analyze the requests for content to determine request densities in a plurality of location units,

identify a set of location units with respective request densities within a selected range,

fit a set of boundary points to boundaries of the set of location units, and

assign the set of boundary points to define the boundaries of the geographical location of interest.

15. The non-transitory computer-readable storage medium storing computer-executable program instructions of claim 11, wherein the program instructions are further executable to designate a plurality of points defining boundaries of the geographical location of interest comprising:

analyze the requests for content to determine respective request densities in a plurality of location units,

present a map of the plurality of location units with indications of the respective request densities in the plurality of location units, responsive to selection of a location unit from the plurality of location units,

identify a set of location units with respective request densities similar to the request density of the location unit,

fit a set of boundary points to boundaries of the set of location units with respective request densities similar to the request density of the location unit, and

assign the set of boundary points to define the boundaries of the geographical location of interest.