MOBILITY DATA-BASED END USER FILTERING SYSTEM
An improved computing system can use mobility data corresponding to a particular mobile device to identify one or more geographic locations to which the mobile device traveled within a certain period of time. The computing system can use parcel data to identify parcels that are located at any one of the identified geographic locations. The computing system can further use the parcel data to identify a subset of the identified parcels that are listed for sale or rent. If the computing system identifies at least one parcel that the mobile device visited that is available on the market, this may indicate that the user who operates the mobile device may be shopping for a home. In response, the computing system can update information about the user to indicate that the user may be shopping for a home.
1 . A system for identifying an end user that exhibits a type of behavior, the system comprising:
memory that stores computer-executable instructions; and
a processor in communication with the memory, wherein the computer-executable instructions, when executed by the processor, cause the processor to:
obtain an identification of a first plurality of parcels managed by a service user;
determine, using mobility data, a first end user device that is associated with a first parcel in the first plurality of parcels;
determine, using the mobility data, a second plurality of parcels visited by the first end user device;
identify a subset of the second plurality of parcels that each comprise a characteristic that corresponds with the type of behavior; and
cause information related to a first end user of the first end user device to be updated based on the identification of the subset of the second plurality of parcels.
2 . The system of claim 1 , wherein the computer-executable instructions, when executed, further cause the processor to:
obtain supplemental data that identifies an action performed by the first end user that corresponds with the type of behavior; and
cause information related to a first end user of the first end user device to be updated based on the identification of the subset of the second plurality of parcels and reception of the supplemental data that identifies the action performed by the first end user that corresponds with the type of behavior.
3 . The system of claim 1 , wherein the computer-executable instructions, when executed, further cause the processor to provide at least one of the mobility data associated with the first end user device or parcel data as an input to a trained artificial intelligence model, wherein providing at least one of the mobility data associated with the first end user device or the parcel data as the input to the trained artificial intelligence model causes the trained artificial intelligence model to output a propensity score that represents a likelihood that the first end user is engaging in an action that corresponds with the type of behavior.
4 . The system of claim 3 , wherein the computer-executable instructions, when executed, further cause the processor to cause the information related to the first end user of the first end user device to be updated with the propensity score.
5 . The system of claim 1 , wherein the computer-executable instructions, when executed, further cause the processor to mask personally identifiable information comprised within the mobility data.
6 . The system of claim 1 , wherein the computer-executable instructions, when executed, further cause the processor to:
generate user interface data that, when processed by a user device, causes the user device to render and display a user interface, wherein the user interface depicts the information related to the first end user and a geographic map identifying a location of the first parcel; and
transmit the user interface data to the user device.
7 . The system of claim 6 , wherein the user interface further comprises a filter, wherein selection of the filter causes the user interface to display the information related to the first end user in response to a determination that the first end user satisfies a criterion of the filter.
8 . The system of claim 7 , wherein the filter comprises one of a geography filter, a new end user filter, a low-to-moderate (LMI) income filter, an end user behavior filter, a contact status filter, or a service user team member assignment filter.
9 . The system of claim 1 , wherein the computer-executable instructions, when executed, further cause the processor to cause the information related to the first end user to be updated periodically.
10 . The system of claim 1 , wherein the computer-executable instructions, when executed, further cause the processor to transmit the information related to the first end user in response to an application programming interface (API) call.
11 . The system of claim 1 , wherein the computer-executable instructions, when executed, further cause the processor to include the information related to the first end user in a customer relationship management (CRM) file owned by the service user.
12 . The system of claim 1 , wherein the computer-executable instructions, when executed, further cause the processor to cause the first end user device to display a digital advertisement that describes a service offered by the service user.
13 . The system of claim 12 , wherein the first end user is an existing customer of the service user.
14 . The system of claim 1 , wherein the computer-executable instructions, when executed, further cause the processor to:
determine that the first end user device traveled to a first geographic location based on the mobility data;
determine based on the mobility data that the first end user device spent more time at the first geographic location than any other geographic location during a first time period;
determine that the first parcel is located at the first geographic location; and
map the first end user device to the first parcel.
15 . The system of claim 1 , wherein the characteristic comprises an availability for purchase or rent.
16 . A computer-implemented method for identifying an end user that exhibits a type of behavior, the computer-implemented method comprising:
obtaining an identification of a first plurality of parcels managed by a service user;
determining, using mobility data, a first end user device that is associated with a first parcel in the first plurality of parcels;
determining, using the mobility data, a second plurality of parcels visited by the first end user device;
identifying a subset of the second plurality of parcels that each comprise a characteristic that corresponds with the type of behavior; and
causing information related to a first end user of the first end user device to be updated based on the identification of the subset of the second plurality of parcels.
17 . The computer-implemented method of claim 16 , further comprising providing at least one of the mobility data associated with the first end user device or parcel data as an input to a trained artificial intelligence model, wherein providing at least one of the mobility data associated with the first end user device or the parcel data as the input to the trained artificial intelligence model causes the trained artificial intelligence model to output a propensity score that represents a likelihood that the first end user is engaging in an action that corresponds with the type of behavior.
18 . The computer-implemented method of claim 16 , further comprising:
generating user interface data that, when processed by a user device, causes the user device to render and display a user interface, wherein the user interface depicts the information related to the first end user and a geographic map identifying a location of the first parcel; and
transmitting the user interface data to the user device.
19 . The computer-implemented method of claim 18 , wherein the user interface further comprises a filter, wherein selection of the filter causes the user interface to display the information related to the first end user in response to a determination that the first end user satisfies a criterion of the filter.
20 . A non-transitory, computer-readable medium comprising computer-executable instructions for identifying an end user that exhibits a type of behavior, wherein the computer-executable instructions, when executed by a computer system, cause the computer system to:
obtain an identification of a first plurality of parcels managed by a service user;
determine, using mobility data, a first end user device that is associated with a first parcel in the first plurality of parcels;
determine, using the mobility data, a second plurality of parcels visited by the first end user device;
identify a subset of the second plurality of parcels that each comprise a characteristic that corresponds with the type of behavior; and
cause information related to a first end user of the first end user device to be updated based on the identification of the subset of the second plurality of parcels.