Multilayer correlation profiling engines
A profiling engine is disclosed. The profiling engine collects information from a variety of sources in real time and stores the information in a profile. The profile may have a number of layers, each layer having a number of categories. The profile is made available for use by applications and services.
1. A method, comprising:
examining, using a computer executing a customer efficiency service, a personal profile of a client to determine that an application is accessed on a device associated with the client using three different screens, wherein the personal profile is based upon information, and wherein the information defines
content accessed by the client,
a protocol associated with services accessed by the client,
a location at which the client accesses the services, and
a time of day at which the client accesses the services; and
providing, using the customer efficiency service, a recommendation to use only one of the three different screens to access the application,
wherein the recommendation results in an improved client efficiency,
wherein the personal profile defines a signaling layer for saving an event, data, and metadata, and
wherein the event, the data, and the metadata correspond to protocols used to access one of the application and a service on a network using the device.
2. The method of claim 1 , wherein the personal profile is saved in a data repository.
3. The method of claim 2 , wherein the data repository is located on the network.
4. The method of claim 1 , wherein the signaling layer comprises a plurality of categories, the plurality of categories comprising a voice category, a download category, a messaging category, and a browse category.
5. The method of claim 4 , wherein the download category comprises data transferred from the network to the device.
6. The method of claim 1 , wherein the personal profile is compiled using a personal profiling engine that collects the information.
7. The method of claim 1 , wherein the personal profile is compiled using a community personal profiling engine that collects the information.
8. The method of claim 1 , wherein the personal profile further comprises an interrelation layer.
9. The method of claim 1 , wherein the personal profile further comprises a supersegmentation layer.
10. A system, comprising:
a data repository; and
a computer comprising a processor that executes a customer efficiency service that, when executed by the processor, causes the processor to perform operations comprising:
examining a personal profile of a client to determine that an application is accessed on a device associated with the client using three different screens, wherein the personal profile is based upon information, and wherein the information defines
content accessed by the client,
a protocol associated with services accessed by the client,
a location at which the client accesses the services, and
a time of day at which the client accesses the services; and
providing a recommendation to the client, the recommendation comprising a recommendation to use only one of the three different screens to access the application,
wherein the recommendation results in an improved client efficiency,
wherein the personal profile includes a signaling layer for saving an event, data, and metadata, and
wherein the event, the data, and the metadata correspond to protocols used to access one of the application and a service on a network using the device.
11. The system of claim 10 , further comprising a personal profiling engine that collects the information and creates the personal profile based upon the information.
12. The system of claim 10 , further comprising a community profiling engine that collects the information and creates the personal profile based upon the information.
13. The system of claim 10 , wherein the signaling layer comprises a plurality of categories including a voice category, a download category, a messaging category, and a browse category.
14. A method, comprising:
obtaining, at a computer executing a customer efficiency service, a personal profile associated with a client to determine that an application is accessed on a device associated with the client using three different screens, wherein the personal profile is based upon information, and wherein the information defines
content accessed by the client,
a protocol associated with services accessed by the client,
a location at which the client accesses the services, and
a time of day at which the client accesses the services, wherein the personal profile is stored at a data repository;
examining, by the computer, the personal profile; and
improving a client efficiency by providing, by the customer efficiency service, a recommendation to the client, the recommendation comprising a recommendation to use only one of the three different screens to access the application,
wherein the personal profile defines a signaling layer for saving an event, data, and metadata, and
wherein the event, the data, and the metadata correspond to protocols used to access the application using the device.
15. The method of claim 14 , wherein the data repository is located on a network.
16. The method of claim 14 , wherein the signaling layer comprises a plurality of categories, the plurality of categories comprising a voice category, a download category, a messaging category, and a browse category.
17. The method of claim 16 , wherein the download category comprises data transferred from a network to the device.
18. The method of claim 14 , wherein the personal profile is compiled using a personal profiling engine that collects the information.
19. The method of claim 14 , wherein the personal profile is compiled using a community profiling engine that collects the information.
20. The method of claim 14 , wherein the personal profile further comprises an interrelation layer and a supersegmentation layer.