US 2022/0067769 A1Published application

Training a machine learning algorithm to create survey questions

AssigneeDell Products L. P.

InventorsKarthik Ranganathan, Sathish Kumar Bikumala

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Abstract

In some examples, a server may determine that a case, created to address an issue of a computing device, is closed and perform an analysis of steps in a process used to close the case. The analysis may determine a length of time of each step and determine that a time to close the case or complete a particular step was at least a predetermined amount faster than average. The server may use machine learning to create a survey question to determine a technique used to close the case or complete the particular step faster than average and to determine one or more incentives to provide a technician that closed the case. An answer from the technician to the survey question may include the technique used to close the case or complete the particular step faster than average. The technique may be shared with other technicians.

Claims19

Dependent claims

A method comprising:

determining, by a server associated with a technical support group, that a case created to address an issue associated with a computing device is closed;
performing, by the server, an analysis of a process used to close the case, the analysis comprising determining a length of time corresponding to individual steps in the process used to close the case;
determining, using a machine learning algorithm executed by the server and based at least in part on the analysis, that the case was closed faster than an average case time to close similar cases;
generating, using the machine learning algorithm, a custom survey including a question to determine a technique used to close the case faster than the average case time;
determining, using the machine learning algorithm, one or more incentives to provide to a technique to respond to the custom survey;
providing, by the server, the custom survey to a technician that closed the case faster than the average case time;
identifying, by the server, the one or more incentives to the technician;
receiving, by the server, an answer corresponding to question, the answer including the technique used to close the case faster than the average case time;
and
providing, by the server, the technique used to close the case faster than the average case time to one or more additional technicians.

7 more elements

A server comprising:

one or more processors;
and
one or more non-transitory computer readable media storing instructions executable by the one or more processors to perform operations comprising:
determining that a case created to address an issue associated with a computing device is closed;
performing an analysis of a process used to close the case, the analysis comprising determining a length of time corresponding to individual steps in the process used to close the case;
determining, based at least in part on the analysis, that the case was closed faster than an average case time to close similar cases;
generating a custom survey including a question to determine a technique used to close the case faster than the average case time;
determining, using the machine learning algorithm, one or more incentives to provide to a technique to respond to the custom survey;
providing the custom survey to a technician that closed the case faster than the average case time;
identifying the one or more incentives to the technician;
receiving an answer corresponding to question, the answer including the technique used to close the case faster than the average case time;
and
providing the technique used to close the case faster than the average case time to one or more additional technicians.

10 more elements

One or more non-transitory computer-readable media storing instructions executable by one or more processors to perform operations comprising:

determining that a case created to address an issue associated with a computing device is closed;
performing an analysis of a process used to close the case, the analysis comprising determining a length of time corresponding to individual steps in the process used to close the case;
determining, based at least in part on the analysis, that the case was closed faster than an average case time to close similar cases;
generating a custom survey including a question to determine a technique used to close the case faster than the average case time;
determining, using the machine learning algorithm, one or more incentives to provide to a technique to respond to the custom survey;
providing the custom survey to a technician that closed the case faster than the average case time;
identifying the one or more incentives to the technician;
receiving an answer corresponding to question, the answer including the technique used to close the case faster than the average case time;
and
providing the technique used to close the case faster than the average case time to one or more additional technicians.

7 more elements

Dependencies are inferred from the claim text.