Providing Recommendations Through Predictive Analytics
A recommendation engine analyzes metrics on an active support ticket to provide recommended solutions, technicians and offers. The recommendation can communicate with a predictive analysis engine to identify solutions, technicians, or offers that are highly correlated with the input parameters. In some embodiments, instructions can be provided to a client device for measuring a metric that is used as an input parameter of the predictive analysis engine. The customer or the technician can follow the instructions to measure the metric.
1 . A computer-implemented method, comprising:
receiving, from a client device, an issue report configured to report a problem experienced with a sales item;
identifying, by a processor, a metric associated with the sales item that is missing in the issue report;
transmitting, by the processor, a measurement request to the client device to retrieve the metric;
receiving, by the processor, the metric from the client device;
performing, by the processor, a query on a predictive analysis engine to generate a ranked list of solutions that are applicable to the issue, the query including the metric;
selecting, by the processor, a recommended solution from the ranked list; and
transmitting, by the processor, the recommended solution to the client device.
2 . The computer-implemented method of claim 1 , wherein identifying the metric comprises:
identifying, by the processor, a plurality of metrics utilized by the predictive algorithm to generate the ranked list; and
determining, by the processor, that the metric is missing in the issue report.
3 . The computer-implemented method of claim 1 , wherein the measurement request includes at least one user instruction to retrieve the metric using the client device.
4 . The computer-implemented method of claim 3 , wherein the metric is measured using a sensor on the client device.
5 . The computer-implemented method of claim 1 , wherein the recommended solution is an on-site visit from a technician.
6 . The computer-implemented method of claim 5 , further comprising:
transmitting, by the processor, another measurement request to another client device, the another client device being operated by the technician;
receiving, by the processor, another metric from the another client device;
performing, by the processor, another query on the predictive analysis engine to generate another ranked list of solutions that are applicable to the issue, the query including the metric and the another metric;
selecting, by the processor, another recommended solution from the another ranked list; and
transmitting, by the processor, the another recommended solution to the another client device.
7 . The computer-implemented method of claim 5 , further comprising:
performing, by the processor, another query on the predictive analysis engine to generate another ranked list of technicians available to service the problem;
selecting, by the processor, a technician from the another ranked list; and
scheduling, by the processor, the technician to the on-site visit.
8 . A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions for:
receiving, from a client device, an issue report configured to report a problem experienced with a sales item;
identifying a metric associated with the sales item that is missing in the issue report;
transmitting a measurement request to the client device to retrieve the metric;
receiving the metric from the client device;
performing a query on a predictive analysis engine to generate a ranked list of solutions that are applicable to the issue, the query including the metric;
selecting a recommended solution from the ranked list; and
transmitting the recommended solution to the client device.
9 . The non-transitory computer readable storage medium of claim 8 , wherein identifying the metric comprises:
identifying a plurality of metrics utilized by the predictive algorithm to generate the ranked list; and
determining that the metric is missing in the issue report.
10 . The non-transitory computer readable storage medium of claim 8 , wherein the measurement request includes at least one user instruction to retrieve the metric using the client device.
11 . The non-transitory computer readable storage medium of claim 10 , wherein the metric is measured using a sensor on the client device.
12 . The non-transitory computer readable storage medium of claim 8 , wherein the recommended solution is an on-site visit from a technician.
13 . The non-transitory computer readable storage medium of claim 12 , further comprising:
transmitting another measurement request to another client device, the another client device being operated by the technician;
receiving another metric from the another client device; and
performing another query on the predictive analysis engine to generate another ranked list of solutions that are applicable to the issue, the query including the metric and the another metric;
selecting another recommended solution from the another ranked list; and
transmitting the another recommended solution to the another client device.
14 . The non-transitory computer readable storage medium of claim 12 , further comprising:
performing another query on the predictive analysis engine to generate another ranked list of technicians available to service the problem;
selecting a technician from the another ranked list; and
scheduling the technician to the on-site visit.
15 . A computer implemented system, comprising:
one or more computer processors; and
a non-transitory computer-readable storage medium comprising instructions, that when executed, control the one or more computer processors to be configured for:
receiving, from a client device, an issue report configured to report a problem experienced with a sales item;
identifying a metric associated with the sales item that is missing in the issue report;
transmitting a measurement request to the client device to retrieve the metric;
receiving the metric from the client device;
performing a query on a predictive analysis engine to generate a ranked list of solutions that are applicable to the issue, the query including the metric;
selecting a recommended solution from the ranked list; and
transmitting the recommended solution to the client device.
16 . The computer implemented system of claim 15 , wherein identifying the metric comprises:
identifying a plurality of metrics utilized by the predictive algorithm to generate the ranked list; and
determining that the metric is missing in the issue report.
17 . The computer implemented system of claim 15 , wherein the measurement request includes at least one user instruction to retrieve the metric using the client device.
18 . The computer implemented system of claim 15 , wherein the recommended solution is an on-site visit from a technician.
19 . The computer implemented system of claim 18 , further comprising:
transmitting another measurement request to another client device, the another client device being operated by the technician;
receiving another metric from the another client device; and
performing another query on the predictive analysis engine to generate another ranked list of solutions that are applicable to the issue, the query including the metric and the another metric;
selecting another recommended solution from the another ranked list; and
transmitting the another recommended solution to the another client device.
20 . The computer implemented system of claim 18 , further comprising:
performing, by the processor, another query on the predictive analysis engine to generate another ranked list of technicians available to service the problem;
selecting, by the processor, a technician from the another ranked list; and
scheduling, by the processor, the technician to the on-site visit.