Systems and methods of a tracking analytics platform
In one embodiment, an analytics tracking system is disclosed that comprises an interface in electronic communication with one or more consumer devices configured to enable a corresponding consumer to access the interface via a mobile application. The system further comprises a consumer data store comprising data regarding at least one consumer, a movement data store comprising data regarding locations and/or movement of the at least one consumer, and an online behavior data (OBD) data store comprising data associated with browsing and/or application data histories of the at least one consumer. The system further comprises a dynamic analysis system configured to analyze data from the consumer data store, the movement data store, and the OBD data store to generate at least one of custom information for the at least one consumer or identify a location for presentation of information to the at least one consumer.
1 . A system comprising:
a non-transitory data store configured to store executable instructions; and
one or more computer processors configured to execute the executable instructions to:
access or receive consumer data regarding at least one consumer;
generate aggregated online behavior data by aggregating first online behavior data associated with the at least one consumer with online behavior data associated with thousands of other consumers;
update the aggregated online behavior data to exclude or filter out personally identifying information;
associate the aggregated online behavior data with a first population segment of a plurality of segments, wherein the first population segment is associated with a first vertical;
analyze the consumer data and the aggregated online behavior data associated with the first population segment to generate customer behavior data;
generate first predictive behavioral data based on the aggregated online behavior data associated with the first population segment and the customer behavior data;
generate a report of the first predictive behavioral data based on the aggregated online behavior data associated with the first population segment and the customer behavior data; and
generate and electronically provide, to a remote device, a data package comprising the report.
2 . The system of claim 1 , wherein the one or more computer processors are further configured to execute the executable instructions to receive data associated with locations or movement of the at least one consumer.
3 . The system of claim 1 , wherein the first online behavior data comprises data associated with browsing and/or application data histories of the at least one consumer.
4 . The system of claim 1 , wherein the generation of the first predictive behavioral data is based at least in part on one or more behavioral categories associated with the aggregated online behavior data.
5 . The system of claim 1 , wherein behavioral categories for the online behavior data includes one or more of: shopping, sports, hobbies and interests, health and fitness, careers, society, or food and drink.
6 . The system of claim 1 , wherein the first vertical is a health-oriented vertical.
7 . The system of claim 1 , wherein the online behavior data comprises web site data and mobile application data.
8 . The system of claim 1 , wherein the customer behavior data comprises at least one of: custom information for the at least one consumer, or a location for presentation of information to the at least one consumer.
9 . A computer-implemented method, as implemented by one or more computing devices configured with specific executable instructions to at least:
access or receive consumer data regarding at least one consumer;
generate aggregated online behavior data by aggregating first online behavior data associated with the at least one consumer with online behavior data associated with thousands of other consumers;
update the aggregated online behavior data to exclude or filter out personally identifying information;
associate the aggregated online behavior data with a first population segment of a plurality of segments, wherein the first population segment is associated with a first vertical;
analyze the consumer data and the aggregated online behavior data associated with the first population segment to generate customer behavior data;
generate first predictive behavioral data based on the aggregated online behavior data associated with the first population segment and the customer behavior data;
generate a report of the first predictive behavioral data based on the aggregated online behavior data associated with the first population segment and the customer behavior data; and
generate and electronically provide, to a remote device, a data package comprising the report.
10 . The computer-implemented method of claim 9 , wherein the one or more computing devices are further configured with specific executable instructions to receive data associated with locations or movement of the at least one consumer.
11 . The computer-implemented method of claim 9 , wherein the first online behavior data comprises data associated with browsing and/or application data histories of the at least one consumer.
12 . The computer-implemented method of claim 9 , wherein the generation of the first predictive behavioral data is based at least in part on one or more behavioral categories associated with the aggregated online behavior data.
13 . The computer-implemented method of claim 9 , wherein behavioral categories for the online behavior data includes one or more of: shopping, sports, hobbies and interests, health and fitness, careers, society, or food and drink.
14 . The computer-implemented method of claim 9 , wherein the first vertical is a health-oriented vertical.
15 . The computer-implemented method of claim 9 , wherein the online behavior data comprises web site data and mobile application data.
16 . The computer-implemented method of claim 9 , wherein the customer behavior data comprises at least one of: custom information for the at least one consumer, or a location for presentation of information to the at least one consumer.
17 . A non-transitory computer storage medium storing computer-executable instructions that, when executed by a processor, cause the processor to at least:
access or receive consumer data regarding at least one consumer;
generate aggregated online behavior data by aggregating first online behavior data associated with the at least one consumer with online behavior data associated with thousands of other consumers;
update the aggregated online behavior data to exclude or filter out personally identifying information;
associate the aggregated online behavior data with a first population segment of a plurality of segments, wherein the first population segment is associated with a first vertical;
analyze the consumer data and the aggregated online behavior data associated with the first population segment to generate customer behavior data;
generate first predictive behavioral data based on the aggregated online behavior data associated with the first population segment and the customer behavior data;
generate a report of the first predictive behavioral data based on the aggregated online behavior data associated with the first population segment and the customer behavior data; and
generate and electronically provide, to a remote device, a data package comprising the report.
18 . The non-transitory computer storage medium of claim 17 , wherein the computer-executable instructions, when executed by the processor, further cause the processor to receive data associated with locations or movement of the at least one consumer.
19 . The non-transitory computer storage medium of claim 17 , wherein the first online behavior data comprises data associated with browsing and/or application data histories of the at least one consumer.
20 . The non-transitory computer storage medium of claim 17 , wherein the customer behavior data comprises at least one of: custom information for the at least one consumer, or a location for presentation of information to the at least one consumer.