Correlation of mobile device positions determined using wireless access points with data sources

1. A method, comprising:

receiving, via a network connection, an event log from at least one wireless access point in a plurality of network devices at a locale,

wherein the event log lists a plurality of network interactions between a plurality of mobile devices and the at least one wireless access point in order for the plurality of mobile devices to access a wireless network, the plurality of network interactions each corresponding to a single event of a plurality of events in the event log;

storing the event log at a data intake and query system;

processing, by the data intake and query system, a query for a subset of the plurality of events corresponding to a mobile device of the plurality of mobile devices;

determining, by a processor and based on the plurality of network interactions, at least one geographic position and at least one corresponding time interval of the mobile device at the at least one geographic position based on a time difference between a time of a first event and a time of a second event as recorded in the event log;

obtaining external data comprising a plurality of sales transactions, the plurality of sales transactions obtained from a point of sale (POS) device at the locale;

correlating, by the processor, the at least one geographic position and the at least one corresponding time interval with the external data to obtain a metric;

determining, in response to the correlating, an impact on the metric by a promotion used in the plurality of sales transactions;

predicting, using the impact on the metric, a value of the metric in a periodic time interval using a trend in previous values of the metric in the periodic time interval; and

adjusting, in response to predicting the value of the metric, an operating parameter of the locale.

2. The method of claim 1 ,

wherein the metric is a walk-by conversion rate at the locale.

3. The method of claim 1 ,

wherein the external data further comprises sensor data obtained from at least one sensor at the locale, and

wherein the metric is a spike in a size of walk-by traffic at the locale.

4. The method of claim 1 ,

wherein the external data further comprises sensor data obtained from at least one sensor at the locale, and

wherein the metric is a wait time in a line at a register at the locale.

5. The method of claim 1 , wherein correlating the at least one geographic position and the at least one corresponding time interval generates at least one correlation, the at least one correlation comprising a first correlation of a first geographic position and a first time interval, the method further comprising:

identifying the first correlation as an anomaly; and

excluding, in response to identifying the first correlation as the anomaly, the first correlation from the at least one correlation.

6. The method of claim 1 , wherein the external data further comprises user data obtained from an application of the mobile device, the method further comprising:

identifying, using the user data, a purchasing preference for a product, wherein the product is being sold at a geographic position at the locale within a threshold of the at least one geographic position; and

transmitting a promotion for the product to the mobile device.

7. The method of claim 1 , wherein the external data further comprises user data obtained from an application of the mobile device, the method further comprising:

identifying, using the user data, a purchasing preference for a first product having an attribute; and

transmitting a promotion for a second product having the attribute to the mobile device.

8. The method of claim 1 , wherein the external data further comprises user data obtained from an application of the mobile device and inventory data obtained from an inventory system, the method further comprising:

identifying, using the inventory data, a product with expiring inventory;

identifying, using the user data, a purchasing preference for the product; and

transmitting a promotion for the product to the mobile device.

9. The method of claim 1 ,

wherein at least the subset of the plurality of events each include a mobile device identifier of the mobile device, a timestamp, and an interaction type,

wherein the timestamp records a time of a corresponding network interaction between the mobile device and the at least one wireless access point, and

wherein, for the first event, the interaction type is an initial access request, wherein, for the second event, the interaction type is a termination access request.

10. The method of claim 1 , wherein determining the at least one geographic position of the mobile device is further performed using triangularization based on measuring a radial distance of the plurality of network devices to the mobile device as recorded in the plurality of events.

11. A computer system, comprising:

a first data source comprising a plurality of events comprising a plurality of network interactions between a mobile device and at least one wireless access point on a network at a locale; and

a processor comprising circuitry configured to:

receive, via a network connection, an event log from the at least one wireless access point in a plurality of network devices at the locale,

wherein the event log lists the plurality of network interactions between the mobile device and the at least one wireless access point in order for the mobile device to access a wireless network, the plurality of network interactions each corresponding to a single event of the plurality of events in the event log;

store the event log at a data intake and query system;

process, by the data intake and query system, a query for a subset of the plurality of events corresponding to the mobile device of a plurality of mobile devices;

determine, by the processor and based on the plurality of network interactions, at least one geographic position and at least one corresponding time interval of the mobile device at the at least one geographic position based on a time difference between a time of a first event and a time of a second event as recorded in the event log;

obtain external data comprising a plurality of sales transactions, the plurality of sales transactions obtained from a point of sale (POS) device at the locale;

correlate, by the processor, the at least one geographic position and the at least one corresponding time interval with the external data to obtain a metric;

determine, in response to the correlating, an impact on the metric by a promotion used in the plurality of sales transactions;

predict, using the impact on the metric, a value of the metric in a periodic time interval using a trend in previous values of the metric in the periodic time interval; and

adjust, in response to predicting the value of the metric, an operating parameter of the locale.

12. The system of claim 11 , wherein correlating the at least one geographic position and the at least one corresponding time interval generates at least one correlation, the at least one correlation comprising a first correlation of a first geographic position and a first time interval, wherein the circuitry is further configured to:

identify the first correlation as an anomaly; and

exclude, in response to identifying the first correlation as the anomaly, the first correlation from the at least one correlation.

13. The system of claim 11 , wherein the external data further comprises user data obtained from an application of the mobile device, wherein the circuitry is further configured to:

identify, using the user data, a purchasing preference for a product, wherein the product is being sold at a geographic position at the locale within a threshold of the at least one geographic position; and

transmit a promotion for the product to the mobile device.

14. The system of claim 11 , wherein the external data further comprises user data obtained from an application of the mobile device and inventory data obtained from an inventory system, wherein the circuitry is further configured to:

identify, using the inventory data, a product with expiring inventory;

identify, using the user data, a purchasing preference for the product; and

transmit a promotion for the product to the mobile device.

15. The system of claim 11 ,

wherein at least the subset of the plurality of events each include a mobile device identifier of the mobile device, a timestamp, and an interaction type,

wherein the timestamp records a time of a corresponding network interaction between the mobile device and the at least one wireless access point, and

wherein, for the first event, the interaction type is an initial access request, wherein, for the second event, the interaction type is a termination access request.

16. The system of claim 11 , wherein determining the at least one geographic position of the mobile device is further performed using triangularization based on measuring a radial distance of the plurality of network devices to the mobile device as recorded in the plurality of events.

17. A non-transitory computer-readable medium comprising instructions, execution of which in a computer system causes the computer system to perform operations comprising:

receiving, via a network connection, an event log from at least one wireless access point in a plurality of network devices at a locale,

wherein the event log lists a plurality of network interactions between a plurality of mobile devices and the at least one wireless access point in order for the plurality of mobile devices to access a wireless network, the plurality of network interactions each corresponding to a single event of a plurality of events in the event log;

storing the event log at a data intake and query system;

processing, by the data intake and query system, a query for a subset of the plurality of events corresponding to a mobile device of the plurality of mobile devices;

determining, by a processor and based on the plurality of network interactions, at least one geographic position and at least one corresponding time interval of the mobile device at the at least one geographic position based on a time difference between a time of a first event and a time of a second event as recorded in the event log;

obtaining external data comprising a plurality of sales transactions, the plurality of sales transactions obtained from a point of sale (POS) device at the locale;

correlating, by the processor, the at least one geographic position and the at least one corresponding time interval with the external data to obtain a metric;

determining, in response to the correlating, an impact on the metric by a promotion used in the plurality of sales transactions;

predicting, using the impact on the metric, a value of the metric in a periodic time interval using a trend in previous values of the metric in the periodic time interval; and

adjusting, in response to predicting the value of the metric, an operating parameter of the locale.

18. The non-transitory computer-readable medium of claim 17 , wherein the external data further comprises user data obtained from an application of the mobile device, wherein the operations further comprise:

identifying, using the user data, a purchasing preference for a product, wherein the product is being sold at a geographic position at the locale within a threshold of the at least one geographic position; and

transmitting a promotion for the product to the mobile device.

19. The non-transitory computer-readable medium of claim 17 , wherein the external data further comprises user data obtained from an application of the mobile device and inventory data obtained from an inventory system, wherein the operations further comprise:

identifying, using the inventory data, a product with expiring inventory;

identifying, using the user data, a purchasing preference for the product; and

transmit a promotion for the product to the mobile device.

20. The non-transitory computer readable medium of claim 17 ,

wherein at least the subset of the plurality of events each include a mobile device identifier of the mobile device, a timestamp, and an interaction type,

wherein the timestamp records a time of a corresponding network interaction between the mobile device and the at least one wireless access point, and

wherein, for the first event, the interaction type is an initial access request, wherein, for the second event, the interaction type is a termination access request.

21. The non-transitory computer readable medium of claim 17 , wherein determining the at least one geographic position of the mobile device is further performed using triangularization based on measuring a radial distance of the plurality of network devices to the mobile device as recorded in the plurality of events.