EFFICIENT PROCESSING OF TRIE DATA STRUCTURES TO SUPPORT CUSTOMER JOURNEY VISUALIZATIONS

1 . A method for providing efficient trie data structure processing, the method comprising:

splitting, by a computing system and based on organization identifiers and sequence identifiers, a data frame indicative of a set of events associated with customer interactions with automated agents of a contact center to produce a set of multiple partitions;

producing, by the computing system, a set of multiple trie data structures, including generating a trie data structure for each partition, wherein each trie data structure represents aggregate counts of a corresponding subset of event sequences associated with a corresponding organization;

merging, by the computing system, multiple trie data structures of the set of trie data structures to produce a combined organization trie data structure; and

storing, by the computing system, the combined organization trie data structure to enable generation of a visualization of the combined organization trie data structure.

2 . The method of claim 1 , further comprising:

assigning, by the computing system, each partition to a separate execution unit for concurrent processing.

3 . The method of claim 1 , further comprising:

performing, by the computing system, analytics on the combined organization trie data structure including filtering the combined organization trie data structure as a function of a path category indicative of a type of event that occurred during the customer interactions with the automated agents of the contact center.

4 . The method of claim 1 , wherein merging the multiple trie data structures comprises:

identifying a set of unique organization identifiers associated with the multiple trie data structures;

repartitioning the data frame based on the organization identifiers; and

merging trie data structures that are associated with a shared organization identifier.

5 . The method of claim 1 , wherein merging the multiple trie data structures comprises:

initializing an empty base trie data structure;

reading multiple trie data structures of the set from storage as subtrie data structures; and

merging each subtrie data structure into the base trie data structure.

6 . The method of claim 5 , wherein merging each subtrie data structure into the base trie data structure comprises, for each subtrie data structure:

sorting node paths by distance from a root in ascending order; and

combining a subtrie node with a base trie node in response to a determination that a node path exists in the base trie data structure or adding the subtrie node to the base trie data structure as a new node in response to a determination that the node path does not exist in the base trie data structure.

7 . The method of claim 1 , further comprising:

tracking, by the computing system, merged nodes of the combined organization trie data structure using a node map; and

calculating, by the computing system, an edge count for a selected node represented in the node map, including querying the node map to identify the set of merged nodes and summing individual counts associated with the merged nodes.

8 . The method of claim 1 , further comprising:

identifying, by the computing system, a selected node of the combined organization trie data structure for a drilled-down view in the visualization;

identifying, by the computing system, a child node set of one or more child nodes of the selected node; and

deleting, by the computing system, the child node set from the visualization.

9 . The method of claim 8 , further comprising:

identifying a parent node set of one or more parent nodes of the selected node;

identifying a set of one or more child nodes of the parent node set;

subtracting counts of the identified child nodes from counts of corresponding parent nodes in the parent node set to provide an accurate representation of count data pertaining to the drilled-down view; and

deleting the identified child nodes of the parent node set in the drilled-down view.

10 . A system for providing efficient trie data structure processing, the system comprising:

at least one processor; and

at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to:

split, based on organization identifiers and sequence identifiers, a data frame indicative of a set of events associated with customer interactions with automated agents of a contact center to produce a set of multiple partitions;

produce a set of multiple trie data structures, including generating a trie data structure for each partition, wherein each trie data structure represents aggregate counts of a corresponding subset of event sequences associated with a corresponding organization;

merge multiple trie data structures of the set of trie data structures to produce a combined organization trie data structure; and

store the combined organization trie data structure to enable generation of a visualization of the combined organization trie data structure.

11 . The system of claim 10 , wherein the plurality of instructions further causes the system to assign each partition to a separate execution unit for concurrent processing.

12 . The system of claim 10 , wherein the plurality of instructions further causes the system to perform analytics on the combined organization trie data structure including filtering the combined organization trie data structure as a function of a path category indicative of a type of event that occurred during the customer interactions with the automated agents of the contact center.

13 . The system of claim 10 , wherein to merge the multiple trie data structures comprises to:

identify a set of unique organization identifiers associated with the multiple trie data structures;

repartition the data frame based on the organization identifiers; and

merge trie data structures that are associated with a shared organization identifier.

14 . The system of claim 10 , wherein to merge the multiple trie data structures comprises to:

initialize an empty base trie data structure;

read multiple trie data structures of the set from storage as subtrie data structures; and

merge each subtrie data structure into the base trie data structure.

15 . The system of claim 14 , wherein to merge each subtrie data structure into the base trie data structure comprises, for each subtrie data structure, to:

sort node paths by distance from a root in ascending order; and

combine a subtrie node with a base trie node in response to a determination that a node path exists in the base trie data structure or add the subtrie node to the base trie data structure as a new node in response to a determination that the node path does not exist in the base trie data structure.

16 . The system of claim 10 , wherein the plurality of instructions further causes the system to:

track merged nodes of the combined organization trie data structure using a node map; and

calculate an edge count for a selected node represented in the node map, including querying the node map to identify the set of merged nodes and summing individual counts associated with the merged nodes.

17 . The system of claim 10 , wherein the plurality of instructions further causes the system to:

identify a selected node of the combined organization trie data structure for a drilled-down view in the visualization;

identify a child node set of one or more child nodes of the selected node; and

delete the child node set from the visualization.

18 . The system of claim 10 , wherein the plurality of instructions further causes the system to:

identify a parent node set of one or more parent nodes of the selected node;

identify a set of one or more child nodes of the parent node set;

subtract counts of the identified child nodes from counts of corresponding parent nodes in the parent node set to provide an accurate representation of count data pertaining to the drilled-down view; and

delete the identified child nodes of the parent node set in the drilled-down view.

19 . One or more non-transitory machine-readable storage media comprising a plurality of instructions stored thereon that, in response to execution by a computing system, causes the computing system to:

split, based on organization identifiers and sequence identifiers, a data frame indicative of a set of events associated with customer interactions with automated agents of a contact center to produce a set of multiple partitions;

produce a set of multiple trie data structures, including generating a trie data structure for each partition, wherein each trie data structure represents aggregate counts of a corresponding subset of event sequences associated with a corresponding organization;

merge multiple trie data structures of the set of trie data structures to produce a combined organization trie data structure; and

store the combined organization trie data structure to enable generation of a visualization of the combined organization trie data structure.

20 . The one or more non-transitory machine-readable storage media of claim 19 , wherein the plurality of instructions further causes the computing system to assign each partition to a separate execution unit for concurrent processing.