Call center analysis

• US 10,069,972 B1
• Filed: 06/26/2017
• Issued: 09/04/2018
• 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 Elliott, McIntyre, Steven Shaun, Burnett, Ricky Gene
• Primary Examiner(s): Nguyen, Khai N
• Application Number:
  US15/633,697
• Time in Patent Office: 435 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 a query at a processor that is part of a data intake and query system operably coupled to a call center that includes one or more call center agents who interact with customers through one or more call center devices, wherein the query comprises one or more query commands;

querying, by the processor and through use of at least a portion of the acquired query, a data store for 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 the current interaction data includes data from at least one customer of the plurality of customers interacting with two or more different types of call center devices;

determining, for a call center group of the plurality of call center groups, a current interaction metric specific to the call center group, wherein the current interaction metric is at least partly based on 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, the metric interface hierarchy comprising a plurality of nodes, each node of the plurality of nodes defining a visualization for an interaction metric corresponding to the node; 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 of the graphical user interface.

5. The method of claim 1, wherein determining the current interaction metric comprises implementing ErlangC to determine a probability that a new customer is added to a wait queue.

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 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 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, wherein acquiring the query comprises:

generating the 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, wherein acquiring the query comprises:

receiving the 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. The method of claim 1, wherein the query that comprises one or more query commands includes a first query command processed by a search query phase processor and a second query command processed by a call center query phase processor.

15. The method of claim 1, wherein the two or more different types of call center devices interact with the plurality of customers via at least two communication channels to generate heterogeneous machine data.

16. The method of claim 1, wherein the two or more different types of call center devices include automated response devices and phones.

17. A system comprising:

memory comprising instructions; and

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

acquiring a query that is part of a data intake and query system operably coupled to a call center that includes one or more call center agents who interact with customers through one or more call center devices wherein the query comprises one or more query commands;

querying, through use of at least a portion of the acquired query, a data store for 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 the current interaction data includes data from at least one customer of the plurality of customers interacting with two or more different types of call center devices;

determining, for a call center group of the plurality of call center groups, a current interaction metric specific to the call center group, wherein the current interaction metric is at least partly based on the current interaction data; and

providing the current interaction metric for the call center group.

18. The system of claim 17, wherein providing the current interaction metric comprises:

querying a metric interface hierarchy to obtain a subhierarchy having an ordered set of nodes, the metric interface hierarchy comprising a plurality of nodes, each node of the plurality of nodes defining a visualization for an interaction metric corresponding to the node; 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 of the graphical user interface.

19. The system of claim 17, 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 truncated summation.

20. The system of claim 17, 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.

21. The system of claim 17, wherein querying the data store comprises 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 activities of a plurality of call center devices and the plurality of customers.

22. The system of claim 17, wherein acquiring the query comprises:

generating the 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.

23. The system of claim 17, wherein acquiring the query comprises:

receiving the 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.

24. The system of claim 17, 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.

25. 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 a query at the one or more processors that is part of a data intake and query system operably coupled to a cal center that includes one or more call center agents who interact with customers through one or more call center devices, wherein the query comprises one or more query commands;

querying, by the one or more processors and through use of at least a portion of the acquired query, a data store for 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 the current interaction data includes data from at least one customer of the plurality of customers interacting with two or more different types of call center devices;

determining, for a call center group of the plurality of call center groups, a current interaction metric specific to the call center group, wherein the current interaction metric is at least partly based on the current interaction data; and

providing the current interaction metric for the call center group.

26. The non-transitory computer readable medium of claim 25, wherein providing the current interaction metric comprises:

querying a metric interface hierarchy to obtain a subhierarchy having an ordered set of nodes, the metric interface hierarchy comprising a plurality of nodes, each node of the plurality of nodes defining a visualization for an interaction metric corresponding to the node; 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 of the graphical user interface.

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

28. The non-transitory computer readable medium of claim 25, wherein querying the data store comprises 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 activities of a plurality of call center devices and the plurality of customers.

29. The non-transitory computer readable medium of claim 25, wherein acquiring the query comprises:

generating the 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 25, wherein acquiring the query comprises:

receiving the 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.