Correlating geographic positions of mobile devices with confirmed point-of-sale device transactions

1. A method, comprising:

accessing a plurality of events in a field-searchable data store, the plurality of events comprising raw machine data associated with a timestamp, the raw machine data representing a plurality of interactions between a mobile device and at least one network device at a locale;

determining, based on the plurality of interactions, at least one geographic position of the mobile device;

calculating a metric for the locale using the at least one geographic position;

obtaining a plurality of completed sales transactions from a point of sale (POS) device at the locale;

determining, using the plurality of events and based on the at least one geographic position being within a predetermined threshold of the POS device for at least a predetermined amount of time, that at least one completed sales transaction is performed;

correlating the at least one completed sales transaction with the plurality of completed sales transactions from the POS device to obtain at least one confirmed transaction; and

determining, in response to the correlating, an impact on the metric by a promotion comprising a discount used in the at least one confirmed transaction.

2. The method of claim 1 ,

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

3. The method of claim 1 , further comprising:

obtaining, in response to the correlating, at least one correlation comprising a first correlation of a first geographic position and a first time interval;

identifying the first correlation as an anomaly; and

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

4. The method of claim 1 ,

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

5. The method of claim 1 , further comprising:

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.

6. The method of claim 1 , further comprising:

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.

7. The method of claim 1 , further comprising:

obtaining sensor data from at least one sensor at the locale; and

correlating the at least one geographic position and at least one time interval determined from the plurality of interactions with the sensor data.

8. The method of claim 1 , further comprising:

obtaining sensor data from at least one sensor at the locale; and

correlating the at least one geographic position and at least one time interval determined from the plurality of interactions with the sensor data, wherein the metric is a spike in a size of walk-by traffic at the locale.

9. The method of claim 1 , wherein the at least one network device comprises a wireless access point.

10. The method of claim 1 , wherein the plurality of interactions comprises a request from the mobile device to connect to a network at the locale via the at least one network device.

11. A computer system, comprising:

a field-searchable data store comprising a plurality of events comprising raw machine data associated with a timestamp, the raw machine data representing a plurality of interactions between a mobile device and at least one network device at a locale; and

circuitry configured to:

access the plurality of events;

determine, based on the plurality of interactions, at least one geographic position of the mobile device;

calculate a metric for the locale using the at least one geographic position;

obtain a plurality of completed sales transactions from a point of sale (POS) device at the locale;

determine, using the plurality of events and based on the at least one geographic position being within a predetermined threshold of the POS device for at least a predetermined amount of time, that at least one completed sales transaction is performed;

correlate the at least one completed sales transaction with the plurality of completed sales transactions from the POS device to obtain at least one confirmed transaction; and

determine, in response to the correlating, an impact on the metric by a promotion comprising a discount used in the at least one confirmed transaction.

12. The system of claim 11 , wherein the circuitry is further configured to:

obtain, in response to the correlating, at least one correlation, the at least one correlation comprising a first correlation of a first geographic position and a first time interval;

identify the first correlation as an anomaly; and

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

13. The system of claim 11 , wherein the circuitry is further configured to:

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.

14. The system of claim 11 , wherein the circuitry is further configured to:

obtain sensor data from at least one sensor at the locale; and

correlate the at least one geographic position and at least one time interval determined from the plurality of interactions with the sensor data.

15. The system of claim 11 , wherein the at least one network device comprises a wireless access point.

16. The system of claim 11 , wherein the plurality of interactions comprises a request from the mobile device to connect to a network at the locale via the at least one network device.

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

access a plurality of events in a field-searchable data store, the plurality of events comprising raw machine data associated with a timestamp, the raw machine data representing a plurality of interactions between a mobile device and at least one network device at a locale;

determine, based on the plurality of interactions, at least one geographic position of the mobile device;

calculate a metric for the locale using the at least one geographic position;

obtain a plurality of completed sales transactions from a point of sale (POS) device at the locale;

determine, using the plurality of events and based on the at least one geographic position being within a predetermined threshold of the POS device for at least a predetermined amount of time, that at least one completed sales transaction is performed;

correlate the at least one completed sales transaction with the plurality of completed sales transactions from the POS device to obtain at least one confirmed transaction; and

determine, in response to the correlating, an impact on the metric by a promotion comprising a discount used in the at least one confirmed transaction.

18. The non-transitory computer-readable medium of claim 17 , wherein the instructions, upon execution, further cause the computer system to:

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.

19. The non-transitory computer-readable medium of claim 17 , wherein the instructions, upon execution, further cause the computer system to:

obtain sensor data from at least one sensor at the locale; and

correlate the at least one geographic position and at least one time interval determined from the plurality of interactions with the sensor data.

20. The non-transitory computer-readable medium of claim 17 , wherein the at least one network device comprises a wireless access point.