Mobile device sighting location analytics and profiling system
The present disclosure describes systems and methods for providing enhanced location analysis and consumer insights using mobile sightings data. An approximate geographic location is useful to mobile service providers and advertisers who wish to provide targeted content to consumers based on their location. The location analysis described herein provides more depth and detail about the detected geographic location of the consumer and also insights into business locations visited by the user of the device, consumer/market segments and patterns of behavior (for an individual consumer and/or for aggregated group of consumers), retail trends and patterns, and other profile information. For example, a location profile analytics system as described herein can determine a probability that an approximate geographic location actually corresponds to a specific geographic location, such as a business location. The analysis performed by the location profile analytics system may be further refined based on a number of additional input parameters.
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:
receive an electronic message via a communication network, the electronic message comprising:
electronic location data identifying a location of a computing device of a user, wherein the location data identifies geographic coordinates and a range of accuracy for the geographic coordinates as determined by the computing device of the user, wherein the range of accuracy is represented by a radius identified in the location data, and
an identifier that identifies at least one of the user or the computing device of the user;
determine timing data indicating when the computing device was determined to be at the location, the timing data including at least one of a date or a time;
obtain entity information for a plurality of entities from an entity information data store based on the received electronic location data, the entity information including, for each of the plurality of entities, an entity name, an entity location, and times of operation for the entity indicating hours during which the entity is open for business at the entity location;
filter the plurality of entities based on the entity location for each of the plurality of entities and the radius identified in the location data representing the range of accuracy of the location data to generate a subset of entities located within the radius of the geographic coordinates;
obtain, from a profile data store, a user profile based on the received identifier;
determine, from the subset of entities and based on at least the timing data, the obtained user profile, and the times of operation for each entity of the subset of entities, which entity of the subset of entities the user likely visited at the at least one of the date or the time;
generate an electronic response to the electronic message based on the determined entity; and
transmit the electronic response to the user via the communication network, wherein the response causes presentation to the user, on a display screen of the computing device of the user, of information associated with the determined entity.
2. The system of claim 1 , wherein the profile for the determined entity indicates one or more a volume or a relative likelihood of user visits by time of day and day of week and a relative likelihood of users having a specified user profile attribute.
3. The system of claim 1 , wherein the user profile comprises at least attributes or categories that are indicative of a relative likelihood that the computing device of the user visits entities of a particular type at one or more of a particular time of day or day of week.
4. The system of claim 1 , wherein the one or more computer processors are further configured to execute the executable instructions to generate a probability that the user likely visited the determined entity.
5. The system of claim 4 , wherein the probability is generated based at least in part on the at least one of the date or the time.
6. The system of claim 1 , wherein the one or more computer processors are further configured to execute the executable instructions to update one or more of the profile for the determined entity or the user profile.
7. The system of claim 1 , wherein the filtering is further based on a traffic pattern or traffic trend associated with one or more of the plurality of entities.
8. A computer-implemented method comprising:
receiving, by a computing system having one or more hardware processors, an electronic message via a communication network, the electronic message comprising:
electronic location data identifying a location of a computing device of a user, wherein the location data identifies geographic coordinates and a range of accuracy for the geographic coordinates as determined by the computing device of the user, wherein the range of accuracy is represented by a radius identified in the location data, and
an identifier that identifies at least one of the user or the computing device of the user;
determining, by the computing system, timing data indicating when the computing device was determined to be at the location, the timing data including at least one of a date or a time;
obtaining, by the computing system, entity information for a plurality of entities from an entity information data store based on the received electronic location data, the entity information including, for each of the plurality of entities, an entity name, an entity location, and times of operation for the entity indicating hours during which the entity is open for business at the entity location;
filtering, by the computing system, the plurality of entities based on the entity location for each of the plurality of entities and the radius identified in the location data representing the range of accuracy of the location data to generate a subset of entities located within the radius of the geographic coordinates;
obtaining, by the computing system from a profile data store, a user profile based on the received identifier;
determining, by the computing system from the subset of entities and based on at least the timing data, the obtained user profile, and the times of operation for each entity of the subset of entities, which entity of the subset of entities the user likely visited at the at least one of the date or the time;
generating an electronic response to the electronic message based on the determined entity; and
transmitting the electronic response to the user via the communication network, wherein the response causes presentation to the user, on a display screen of the computing device of the user, of information associated with the determined entity.
9. The method of claim 8 , wherein the profile for the determined entity indicates one or more a volume or a relative likelihood of user visits by time of day and day of week.
10. The method of claim 8 , wherein the user profile comprises at least attributes or categories that are indicative of a relative likelihood that the computing device of the user visits entities of a particular type at one or more of a particular time of day or day of week.
11. The method of claim 10 , further comprising generating a probability that the user likely visited the determined entity.
12. The method of claim 11 , wherein the probability is generated based at least in part on the at least one of the date or the time.
13. The method of claim 8 , wherein the filtering is further based on a traffic pattern or traffic trend associated with one or more of the plurality of entities.
14. The method of claim 8 further comprising generating an entity profile for a business based on location data associated with each of a plurality of user devices.