Data aggregation for user interaction enhancement
A contact center system correlates one or more past user interactions to a current user interaction with the contact center system. The current user interaction may in some cases use a different communication modality (e.g., chat, voice, video, SMS, email, or social) than a past user interaction. The contact center system may automatically alert a supervisor agent when the system detects that a certain user warrants more attention. Real-time assistance may be provided to an agent of the contact center system based on aggregated data from a user's history of user interactions across modalities.
1. A method comprising:
correlating a past user interaction with a contact center system to a current user interaction with the contact center system to associate the past user interaction and the current user interaction with a user;
aggregating data of the past user interaction with data of the current user interaction to obtain aggregated interaction data for the user associated with the past user interaction and with the current user interaction;
generating a message based on the aggregated interaction data; and
presenting the message in a user interface.
2. The method of claim 1 , wherein the past user interaction and the current user interaction use different modalities for communication.
3. The method of claim 1 , wherein the past user interaction is a chat session, and the current user interaction is a phone call.
4. The method of claim 1 , wherein the data of the past user interaction includes a first duration of the past user interaction, the data of the current user interaction includes a second duration of the current user interaction, and aggregating the data of the past user interaction with the data of the current user interaction includes determining an aggregated duration based on the first duration and the second duration.
5. The method of claim 1 , wherein the data of the past user interaction includes a first sentiment score determined based on a transcript of the past user interaction using a machine learning model, the data of the current user interaction includes a second sentiment score determined based on a transcript of the current user interaction using a machine learning model, and aggregating the data of the past user interaction with the data of the current user interaction comprises determining an aggregated sentiment score based on the first sentiment score and the second sentiment score.
6. The method of claim 1 , comprising:
prioritizing, based on the aggregated interaction data, the current user interaction in one or more queues of user interactions in the contact center system.
7. The method of claim 1 , wherein the message includes prompts for assisting an agent of the contact center system to complete the current user interaction.
8. The method of claim 7 , wherein the agent is a first agent, the user interface is a first user interface, and comprising:
determining a status indicator for the current user interaction based on the aggregated interaction data;
automatically triggering, based on the status indicator, an alert message for a second agent of the contact center system; and
presenting the alert message in a second user interface.
9. A system comprising:
a processor, and
a memory, wherein the memory stores instructions executable by the processor to:
correlate a past user interaction with a contact center system to a current user interaction with the contact center system to associate the past user interaction and the current user interaction with a user;
aggregate data of the past user interaction with data of the current user interaction to obtain aggregated interaction data for the user associated with the past user interaction and with the current user interaction; and
generate a message based on the aggregated interaction data.
10. The system of claim 9 , wherein the past user interaction and the current user interaction use different modalities for communication.
11. The system of claim 9 , wherein the past user interaction is a chat session, and the current user interaction is a phone call.
12. The system of claim 9 , wherein the data of the past user interaction includes a first duration of the past user interaction, the data of the current user interaction includes a second duration of the current user interaction, and aggregating the data of the past user interaction with the data of the current user interaction includes determining an aggregated duration based on the first duration and the second duration.
13. The system of claim 9 , wherein the data of the past user interaction includes a first sentiment score determined based on a transcript of the past user interaction using a machine learning model, the data of the current user interaction includes a second sentiment score determined based on a transcript of the current user interaction using a machine learning model, and aggregating the data of the past user interaction with the data of the current user interaction comprises determining an aggregated sentiment score based on the first sentiment score and the second sentiment score.
14. The system of claim 9 , wherein the memory stores instructions executable by the processor to:
prioritize, based on the aggregated interaction data, the current user interaction in one or more queues of user interactions in the contact center system.
15. The system of claim 9 , wherein the message includes prompts for assisting an agent of the contact center system to complete the current user interaction.
16. The system of claim 15 , wherein the agent is a first agent, the user interface is a first user interface, and the memory stores instructions executable by the processor to:
determine a status indicator for the current user interaction based on the aggregated interaction data;
automatically trigger, based on the status indicator, an alert message for a second agent of the contact center system; and
present the alert message in a second user interface.
17. A non-transitory computer-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising:
correlating a past user interaction with a contact center system to a current user interaction with the contact center system to associate the past user interaction and the current user interaction with a user;
aggregating a first duration of the past user interaction with a second duration of the current user interaction to obtain aggregated duration for the user associated with the past user interaction and with the current user interaction;
generating a message based on the aggregated duration; and
presenting the message in a user interface.
18. The non-transitory computer-readable storage medium of claim 17 , wherein the past user interaction and the current user interaction use different modalities for communication.
19. The non-transitory computer-readable storage medium of claim 17 , wherein the past user interaction is a chat session, and the current user interaction is a phone call.
20. The non-transitory computer-readable storage medium of claim 17 , comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising:
prioritizing, based on the aggregated duration, the current user interaction in one or more queues of user interactions in the contact center system.