ASSESSING VISITOR COMPOSITION, SUCH AS FOR AUTOMATICALLY IDENTIFYING A FREQUENCY OF VISITORS TO A LOCATION
A variety of techniques for assessing visitor composition to a location in conjunction with one or more events are disclosed. Traffic associated with the presence of a set of devices at a location is received. The devices can be segmented based on a status—including into “recent” visitors and “re-engaged visitors.” A determination can be made of which additional events a given device was present at. A determination can be made as to how much time passes after an event before a given device returns to a location. A determination can be made as to the number of times a device visits a location during the event.
1 . At least one non-transitory, computer-readable medium carrying instructions, which when executed by at least one data processor, performs operations, the operations comprising:
wirelessly receiving traffic data associated with the presence of a set of mobile devices at a location,
wherein at least some of the mobile devices in the set of mobile devices are associated with different users;
wherein the traffic data is received via a wireless receiver located in or near the location, and,
wherein the location is an enclosed location within a building;
determining, from the received traffic data, a frequency of the number of times that a given mobile device included in the set of devices was observed at the location; and
providing the frequency as output to infer behavior of users of the mobile devices relative to the location.
2 . The computer-readable medium of claim 1 wherein providing the output includes providing a graphical display of visit frequencies of multiple users during an event, and wherein the graphical display provides an understanding of types of customers entering the location during the event.
3 . The computer-readable medium of claim 1 wherein the location is a store, wherein wirelessly receiving includes receiving WiFi identification signals from mobile phones of users within or adjacent to the store.
4 . The computer-readable medium of claim 1 wherein providing the output includes providing an event frequency, wherein the event frequency is the ratio of particular mobile devices identified during an event across distinct segments of time, and wherein the output further includes a total number of devices recorded during the event.
5 . The computer-readable medium of claim 1 wherein providing the output includes providing a graphical display of visit frequencies of multiple users during an event, and wherein the graphical display provides a bar chart as an event frequency report that specifies beginning and end times of the event and permits a user to hover over each bar and cause to be displayed frequency values.
6 . A computer-implementable method, comprising:
wirelessly receiving traffic data associated with the presence of a set of mobile phones at a location,
wherein at least some of the mobile phones in the set of mobile phones are associated with different visitors, and
wherein the traffic data is received via a wireless receiver located in or near the location, and;
filtering the received traffic data to identify mobile phones associated with visitors to the location and mobile phones of employees or mobile phones of visitors at or near the location below a time threshold;
determining, from the received traffic data, a frequency of the number of times that a given mobile phone included in the set of phones was observed at the location; and
providing the frequency as output to infer behavior of visitors of the mobile phones relative to the location.
7 . The method of claim 6 wherein providing the output includes providing a graphical display of visit frequencies of multiple visitors during an event.
8 . The method of claim 6 wherein the location is a store, wherein wirelessly receiving includes receiving WiFi identification signals from mobile phones of visitors within or adjacent to the store.
9 . The method of claim 6 wherein providing the output includes providing an event frequency, wherein the event frequency is the ratio of particular mobile phones identified during an event across distinct segments of time.
10 . The method of claim 6 wherein providing the output includes providing a status with respect to first and second events at the location, and a visitor status breakdown at the first event and visitor status breakdown at the second event.
11 . The method of claim 6 wherein the filtering includes employing a decision tree of rules to filter out phones as being in the location for too short or too long of a selected duration.
12 . A system, comprising:
a sensor for receiving traffic data from a set of phones at a location;
processor, coupled to the sensor, and configured to:
receive the traffic data, wherein the traffic data is associated with the presence of the set of phones at the location;
determine, from the received traffic, a frequency of the number of times that a given device included in the set of devices was observed at the location; and
provide the frequency as output; and
a memory coupled to the processor and configured to provide the processor with instructions.
13 . The system of claim 12 wherein the sensor is a Bluetooth or WiFi access point at or near the location.
14 . The system of claim 12 wherein providing the output includes providing a graphical display of visit frequencies of multiple users during an event.
15 . The system of claim 12 wherein the location is a store, wherein wirelessly receiving includes receiving WiFi identification signals from mobile phones of users within or adjacent to the store.
16 . The system of claim 12 wherein providing the output includes providing an event frequency, wherein the event frequency is the ratio of particular mobile devices identified during an event across distinct segments of time.
17 . The system of claim 12 wherein the processor is further configured to implement data ingestors configured to handle concurrent traffic data ingestion and rewrite the traffic data into a normalized and canonical format, and wherein the processor employs parsers specific to sensor hardware manufacturers.
18 . The system of claim 12 wherein the processor is further configured to implement data ingestors to process the traffic data and store in the memory at least three of: a unique identifier or manufacturer identifier for the sensor, a flag indicating whether the sensor is an access point, a minimum signal strength for traffic data received from each phone, a sum of the signal strength squared, a first signal strength detected, a last signal strength detected, a maximum signal strength, a summation of signal strength, a sum of signal strength cubed, a timestamp of first frame received, or a timestamp of last frame received.