Framework for supporting a call center

• US 10,326,883 B2
• Filed: 07/31/2018
• Issued: 06/18/2019
• Est. Priority Date: 06/26/2017
• Status: Active Grant

• Current Assignee: Splunk Inc. (Cisco Systems, Inc.)
• Original Assignee: Splunk Inc. (Cisco Systems, Inc.)
• Inventors: Molander, Troy Elliot, McIntyre, Steven Shaun, Burnett, Ricky Gene
• Primary Examiner(s): Nguyen, Khai N.
• Application Number:
  US16/051,322
• Publication Number:
  US 20180375999A1
• Time in Patent Office: 322 Days
• Field of Search: 37921001, 37926501, 37926502, 37926503, 37926504, 37926505, 37926506, 37926507, 37926508, 37926509, 3792651, 37926511, 37926512, 37926513, 37926514, 37926601, 37926602, 37926603, 37926604, 37926605, 37926606, 37926607, 37926608, 37926609, 3792661
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: H04M 2201/42 Graphical user interfaces
• CPC Class Codes: H04M 2203/402 Agent or workforce management
• CPC Class Codes: H04M 2203/556 Statistical analysis and interpretation
• CPC Class Codes: H04M 3/5133 Operator terminal details
• CPC Class Codes: H04M 3/5175 Call or contact centers supervision arrangements
• CPC Class Codes: H04M 3/5238 with waiting time or load prediction arrangements

Abstract

One or more embodiments related to a method that includes querying a data store for current interaction data between call center personnel and customers. The call center personnel are grouped into call center groups. The method further includes determining, for at least some call center groups, a current interaction metric specific to the call center group. The current interaction method is provided for each of the at least some call center groups.

Claims

1. A method, comprising:

acquiring raw machine data at a data intake and query system operably coupled to a call center that includes one or more call center devices, the raw machine data comprising current interaction data;

storing the raw machine data in a data store;

querying, by a processor, the data store for the current interaction data between a plurality of call center personnel and a plurality of customers, the plurality of call center personnel grouped into a plurality of call center groups, wherein querying the data store comprises searching the data store for the current interaction data;

determining, for a call center group of the plurality of call center groups, a current interaction metric specific to the call center group using the current interaction data; and

providing the current interaction metric for the call center group.

2. The method of claim 1, wherein the current interaction metric is a target for a number of agents.

3. The method of claim 1, wherein the current interaction metric is determined individually for each call center group of a subset of the plurality of call center groups, the subset of the plurality of call center groups comprising the call center group.

4. The method of claim 1, wherein providing the current interaction metric comprises:

querying a metric interface hierarchy to obtain a subhierarchy having an ordered set of nodes; and

generating a graphical user interface by adding a plurality of visualizations from each node of the subhierarchy according to the ordered set of nodes and a general layout.

5. The method of claim 1, wherein determining the current interaction metric comprises implementing ErlangC.

6. The method of claim 1, wherein determining the current interaction metric comprises performing Ramanujan factorial approximation in an implementation of ErlangC.

7. The method of claim 1, further comprising:

calculating a probability of a customer not waiting in the call center group using an exponential function approximation and an error portion, wherein the error portion is a truncated summation.

8. The method of claim 1, further comprising:

determining a target for a number of agents for the call center group of the plurality of call center groups by;

selecting a first number of agents;

obtaining a first estimated metric matching the first number of agents;

comparing the first estimated metric with a threshold to obtain a difference;

incrementing the first number of agents based on a percentage of the difference to obtain a second number of agents; and

selecting the second number of agents as the target for the number of agents when a second estimated metric obtained for the second number of agents satisfies the threshold.

9. The method of claim 1, wherein querying the data store comprises accessing a plurality of events in a field-searchable data store, the plurality of events comprising the raw machine data associated with a timestamp, the raw machine data representing activities of a plurality of call center devices and the plurality of customers.

10. The method of claim 1, further comprising:

generating a query, the query comprising;

a first pipeline command for a plurality of statistics from the data store,

a second pipeline command to evaluate the plurality of statistics and obtain a plurality of evaluation results, and

a third pipeline command to determine the current interaction metric from the plurality of evaluation results.

11. The method of claim 1, further comprising:

receiving a query;

partitioning the query into a plurality of pipeline commands;

transmitting a first pipeline command of the plurality of pipeline commands to a first query phase processor, the first query phase processor obtaining a plurality of statistics from the data store using at least one indexer;

transmitting a second pipeline command of the plurality of pipeline commands to a second query phase processor, the second query phase processor evaluating the plurality of statistics to obtain a plurality of evaluation results; and

transmitting a third pipeline command of the plurality of pipeline commands to a third query phase processor, the third query phase processor determining the current interaction metric from the plurality of evaluation results.

12. The method of claim 1, further comprising:

obtaining a third party data describing an environment affecting at least some of the plurality of customers;

predicting an effect on the call center based on the environment affecting at least some of the plurality of customers; and

determining a future interaction metric for the call center using the current interaction data and the effect on the call center.

13. The method of claim 1, further comprising:

determining an expected volume of calls for a time period,

wherein the current interaction data describes a performance of the call center within the time period to a current point in time;

predicting, based at least in part on the current interaction data and the expected volume of calls, a future volume of calls to the call center for a remainder of the time period, the remainder of the time period being after the current point in time; and

determining the current interaction metric using the future volume of calls.

14. A system comprising:

memory comprising instructions; and

a computer processor for executing the instructions that cause the computer processor to perform operations comprising;

acquiring raw machine data at a data intake and query system operably coupled to a call center that includes one or more call center devices, the raw machine data comprising current interaction data;

storing the raw machine data in a data store;

querying a data store for the current interaction data between a plurality of call center personnel and a plurality of customers, the plurality of call center personnel grouped into a plurality of call center groups, wherein querying the data store comprises searching the data store for the current interaction data;

determining, for a call center group of the plurality of call center groups, a current interaction metric specific to the call center group using the current interaction data; and

providing the current interaction metric for the call center group.

15. The system of claim 14, wherein providing the current interaction metric comprises:

querying a metric interface hierarchy to obtain a subhierarchy having an ordered set of nodes; and

generating a graphical user interface by adding a plurality of visualizations from each node of the subhierarchy according to the ordered set of nodes and a general layout.

16. The system of claim 14, wherein determining the current interaction metric comprises performing Ramanujan factorial approximation in an implementation of ErlangC.

17. The system of claim 14, wherein the operations further comprise:

calculating a probability of a customer not waiting in the call center group using an exponential function approximation and an error portion, wherein the error portion is a truncated summation.

18. The system of claim 14, wherein the operations further comprise:

determining a target for a number of agents for the call center group of the plurality of call center groups by;

selecting a first number of agents;

obtaining a first estimated metric matching the first number of agents;

comparing the first estimated metric with a threshold to obtain a difference;

incrementing the first number of agents based on a percentage of the difference to obtain a second number of agents; and

selecting the second number of agents as the target for the number of agents when a second estimated metric obtained for the second number of agents satisfies the threshold.

19. The system of claim 14, wherein querying the data store comprises accessing a plurality of events in a field-searchable data store, the plurality of events comprising the raw machine data associated with a timestamp, the raw machine data representing activities of a plurality of call center devices and the plurality of customers.

20. The system of claim 14, wherein the operations further comprise:

generating a query, the query comprising;

a first pipeline command for a plurality of statistics from the data store,

a second pipeline command to evaluate the plurality of statistics and obtain a plurality of evaluation results, and

a third pipeline command to determine the current interaction metric from the plurality of evaluation results.

21. The system of claim 14, wherein the operations further comprise:

receiving a query;

partitioning the query into a plurality of pipeline commands;

transmitting a first pipeline command of the plurality of pipeline commands to a first query phase processor, the first query phase processor obtaining a plurality of statistics from the data store using at least one indexer;

transmitting a second pipeline command of the plurality of pipeline commands to a second query phase processor, the second query phase processor evaluating the plurality of statistics to obtain a plurality of evaluation results; and

transmitting a third pipeline command of the plurality of pipeline commands to a third query phase processor, the third query phase processor determining the current interaction metric from the plurality of evaluation results.

22. The system of claim 14, wherein the operations further comprise:

determining an expected volume of calls for a time period,

wherein the current interaction data describes a performance of the call center within the time period to a current point in time;

predicting, based at least in part on the current interaction data and the expected volume of calls, a future volume of calls to the call center for a remainder of the time period, the remainder of the time period being after the current point in time; and

determining the current interaction metric using the future volume of calls.

23. A non-transitory computer-readable storage medium storing computer-readable program code which, when executed by one or more processors, cause the one or more processors to perform operations, comprising:

acquiring raw machine data at a data intake and query system operably coupled to a call center that includes one or more call center devices, the raw machine data comprising current interaction data;

storing the raw machine data in a data store;

querying the data store for the current interaction data between a plurality of call center personnel and a plurality of customers, the plurality of call center personnel grouped into a plurality of call center groups, wherein querying the data store comprises searching the data store for the current interaction data;

determining, for a call center group of the plurality of call center groups, a current interaction metric specific to the call center group using the current interaction data; and

providing the current interaction metric for the call center group.

24. The non-transitory computer readable medium of claim 23, wherein providing the current interaction metric comprises:

querying a metric interface hierarchy to obtain a subhierarchy having an ordered set of nodes; and

generating a graphical user interface by adding a plurality of visualizations from each node of the subhierarchy according to the ordered set of nodes and a general layout.

25. The non-transitory computer readable medium of claim 23, wherein determining the current interaction metric comprises performing Ramanujan factorial approximation in an implementation of ErlangC.

26. The non-transitory computer readable medium of claim 23, wherein the operations further comprise:

calculating a probability of a customer not waiting in the call center group using an exponential function approximation and an error portion, wherein the error portion is a truncated summation.

27. The non-transitory computer readable medium of claim 23, wherein the operations further comprise:

determining a target for a number of agents for the call center group of the plurality of call center groups by;

selecting a first number of agents;

obtaining a first estimated metric matching the first number of agents;

comparing the first estimated metric with a threshold to obtain a difference;

incrementing the first number of agents based on a percentage of the difference to obtain a second number of agents; and

selecting the second number of agents as the target for the number of agents when a second estimated metric obtained for the second number of agents satisfies the threshold.

28. The non-transitory computer readable medium of claim 23, wherein querying the data store comprises accessing a plurality of events in a field-searchable data store, the plurality of events comprising the raw machine data associated with a timestamp, the raw machine data representing activities of a plurality of call center devices and the plurality of customers.

29. The non-transitory computer readable medium of claim 23, wherein the operations further comprise:

generating a query, the query comprising;

a first pipeline command for a plurality of statistics from the data store,

a second pipeline command to evaluate the plurality of statistics and obtain a plurality of evaluation results, and

a third pipeline command to determine the current interaction metric from the plurality of evaluation results.

30. The non-transitory computer readable medium of claim 23, wherein the operations further comprise:

receiving a query;

partitioning the query into a plurality of pipeline commands;

transmitting a first pipeline command of the plurality of pipeline commands to a first query phase processor, the first query phase processor obtaining a plurality of statistics from the data store using at least one indexer;

transmitting a second pipeline command of the plurality of pipeline commands to a second query phase processor, the second query phase processor evaluating the plurality of statistics to obtain a plurality of evaluation results; and

transmitting a third pipeline command of the plurality of pipeline commands to a third query phase processor, the third query phase processor determining the current interaction metric from the plurality of evaluation results.