System and method of capturing, tracking, composing, analyzing and automating analog and digital interactions

1. A system, comprising:

a computer, comprising a processor and memory and operatively coupled to a display device, the computer configured to:

monitor at least two communication channels between one or more end user systems and one or more entity systems;

group interaction activities of the at least two communication channels based, at least in part, on one or more keywords of the interaction activities, wherein the grouped interaction activities correspond to customer cases;

generate a sentiment score associated with each of the interaction activities;

trigger an alert across the one or more grouped interaction activities in response to detecting one or more alert criteria;

display the grouped interaction activities, the sentiment score associated with each of the interaction activities and the alert on the display device;

identify a first communication channel of the at least two communication channels, wherein the first communication channel comprises at least one previous interaction activity;

identify a second communication channel of the at least two communication channels, wherein the second communication channel comprises at least one recent interaction activity;

determine the first communication channel is a higher priority communication channel than the second communication channel; and

assign a lower response priority to the grouped interaction activities.

2. The system of claim 1 , wherein the computer is further configured to:

generate an automated response to at least one of the one or more of the end user systems and the one or more entity systems based, at least in part, on an assigned sentiment score and a response priority.

3. The system of claim 1 , wherein the one or more alert criteria comprises a magnitude of change between a first sentiment score and a second sentiment score and the computer is further configured to:

determine the magnitude of change by comparing the first sentiment score comprising a sentiment score of one or more earlier interaction activities with the second sentiment score comprising a sentiment score of one or more subsequent interaction activities.

4. The system of claim 1 , wherein the computer is further configured to:

identify a source of the interaction activities of the at least two communication channels;

determine at least two topics of the interaction activities; and

group the interaction activities into at least two interaction threads based, at least in part, on the source of the interaction activities the least two topics, wherein a first interaction thread of the at least two interaction threads comprises interaction activities of the source and a first topic and a second interaction thread of the at least two interaction threads comprises interaction activities of the source and a second topic.

5. The system of claim 1 , wherein the computer is configured to further group interaction activities of the at least two communication channels based, at least in part, on a method of engagement.

6. The system of claim 2 , wherein the sentiment score comprises at least one of a subjective sentiment score and a numerical value sentiment score.

7. A computer-implemented method, comprising:

monitoring, by a computer, at least two communication channels between one or more end user systems and one or more entity systems;

grouping, by the computer, interaction activities of the at least two communication channels based, at least in part, on one or more keywords of the interaction activities, wherein the grouped interaction activities correspond to customer cases;

generating a sentiment score associated with each of the interaction activities;

triggering, by the computer, an alert across the one or more grouped interaction activities in response to detecting one or more alert criteria;

displaying, by a display device, the grouped interaction activities, the sentiment score associated with each of the interaction activities and the alert;

identifying, by the computer, a first communication channel of the at least two communication channels, wherein the first communication channel comprises at least one previous interaction activity;

identifying, by the computer, a second communication channel of the at least two communication channels, wherein the second communication channel comprises at least one recent interaction activity;

determining, by the computer, the first communication channel is a higher priority communication channel than the second communication channel; and

assigning, by the computer, a lower response priority to the grouped interaction activities.

8. The computer-implemented method of claim 7 , further comprising:

generating, by the computer, an automated response to at least one of the one or more of the end user systems and the one or more entity systems based, at least in part, on an assigned sentiment score and a response priority.

9. The computer-implemented method of claim 7 , wherein the one or more alert criteria comprises a magnitude of change between a first sentiment score and a second sentiment score, further comprising:

determining, by the computer, the magnitude of change by comparing the first sentiment score comprising a sentiment score of one or more earlier interaction activities with the second sentiment score comprising a sentiment score of one or more subsequent interaction activities.

10. The computer-implemented method of claim 7 , further comprising:

identifying, by the computer, a source of the interaction activities of the at least two communication channels;

determining, by the computer, at least two topics of the interaction activities; and

grouping, by the computer, the interaction activities into at least two interaction threads based, at least in part, on the source of the interaction activities the least two topics, wherein a first interaction thread of the at least two interaction threads comprises interaction activities of the source and a first topic and a second interaction thread of the at least two interaction threads comprises interaction activities of the source and a second topic.

11. The computer-implemented method of claim 7 wherein grouping, by the computer, interaction activities of the at least two communication channels based, at least in part, on one or more keywords of the interaction activities further comprises:

grouping, by the computer, interaction activities of the at least two communication channels based, at least in part, on a method of engagement.

12. The computer-implemented method of claim 8 , wherein the sentiment score comprises at least one of a subjective sentiment score and a numerical value sentiment score.

13. A non-transitory computer-readable storage medium embodied with software, the software when executed:

monitors at least two communication channels between one or more end user systems and one or more entity systems;

groups interaction activities of the at least two communication channels based, at least in part, on one or more keywords of the interaction activities, wherein the grouped interaction activities correspond to customer cases;

generates a sentiment score associated with each of the interaction activities;

triggers an alert across the one or more grouped interaction activities in response to detecting one or more alert criteria;

displays the grouped interaction activities, the sentiment score associated with each of the interaction activities and the alert;

identifies a first communication channel of the at least two communication channels, wherein the first communication channel comprises at least one previous interaction activity;

identifies a second communication channel of the at least two communication channels, wherein the second communication channel comprises at least one recent interaction activity;

determines the first communication channel is a higher priority communication channel than the second communication channel; and

assigns a lower response priority to the grouped interaction activities.

14. The non-transitory computer-readable storage medium of claim 13 , the software when executed further:

generates an automated response to at least one of the one or more of the end user systems and the one or more entity systems based, at least in part, on an assigned sentiment score and a response priority.

15. The non-transitory computer-readable storage medium of claim 13 wherein the one or more alert criteria comprises a magnitude of change between a first sentiment score and a second sentiment score, the software when executed further:

determines the magnitude of change by comparing the first sentiment score comprising a sentiment score of one or more earlier interaction activities with the second sentiment score comprising a sentiment score of one or more subsequent interaction activities.

16. The non-transitory computer-readable storage medium of claim 13 , the software when executed further:

identifies a source of the interaction activities of the at least two communication channels;

determines at least two topics of the interaction activities; and

groups the interaction activities into at least two interaction threads based, at least in part, on the source of the interaction activities the least two topics, wherein a first interaction thread of the at least two interaction threads comprises interaction activities of the source and a first topic and a second interaction thread of the at least two interaction threads comprises interaction activities of the source and a second topic.

17. The non-transitory computer-readable storage medium of claim 13 , the software when executed groups the interaction activities of the at least two communication channels based, at least in part, on one or more keywords of the interaction activities by further:

grouping interaction activities of the at least two communication channels based, at least in part, on a method of engagement.