Conversational Analytics
Conversational Analytics dashboard provides insights into Virtual Agent conversational data.
Install Trend
View Install Data
| Date | Install Count | Change |
|---|---|---|
| 2026-10-27 | 0 | - |
| 182 days of no change | ||
| 2026-04-27 | 902 | -902 |
| 143 days of no change | ||
| 2025-12-04 | 901 | +1 |
| 2025-12-03 | 900 | +1 |
| 3 days of no change | ||
| 2025-11-29 | 899 | +1 |
| 2025-11-28 | 898 | +1 |
| 6 days of no change | ||
| 2025-11-21 | 897 | +1 |
| 1 days of no change | ||
| 2025-11-19 | 895 | +2 |
| 4 days of no change | ||
| 2025-11-14 | 894 | +1 |
| 6 days of no change | ||
| 2025-11-07 | 893 | +1 |
| 2025-11-06 | 892 | +1 |
| 1 days of no change | ||
| 2025-11-04 | 891 | +1 |
| 2025-11-03 | 889 | +2 |
| 4 days of no change | ||
| 2025-10-29 | 888 | +1 |
| 2025-10-28 | 887 | +1 |
| 1 days of no change | ||
| 2025-10-26 | 886 | +1 |
| 2 days of no change | ||
| 2025-10-23 | 885 | +1 |
| 2 days of no change | ||
| 2025-10-20 | 884 | +1 |
| 1 days of no change | ||
| 2025-10-18 | 883 | +1 |
| 2 days of no change | ||
| 2025-10-15 | 882 | +1 |
| 2025-10-14 | 879 | +3 |
| 2025-10-13 | 877 | +2 |
| 3 days of no change | ||
| 2025-10-09 | 875 | +2 |
| 2025-10-08 | 873 | +2 |
| 2025-10-07 | 872 | +1 |
| 2025-10-06 | 868 | +4 |
| 2 days of no change | ||
| 2025-10-03 | 866 | +2 |
| 8 days of no change | ||
| 2025-09-24 | 865 | +1 |
| 2025-09-23 | 864 | +1 |
| 2 days of no change | ||
| 2025-09-20 | 863 | +1 |
| 1 days of no change | ||
| 2025-09-18 | 861 | +2 |
| 2025-09-17 | 860 | +1 |
| 1 days of no change | ||
| 2025-09-15 | 859 | +1 |
| 4 days of no change | ||
| 2025-09-10 | 858 | +1 |
| 2025-09-09 | 857 | +1 |
| 3 days of no change | ||
| 2025-09-05 | 856 | +1 |
| 2 days of no change | ||
| 2025-09-02 | 855 | +1 |
| 2025-09-01 | 854 | +1 |
| 2 days of no change | ||
| 2025-08-29 | 853 | +1 |
| 2025-08-28 | 852 | +1 |
| 1 days of no change | ||
| 2025-08-26 | 851 | +1 |
| 7 days of no change | ||
| 2025-08-18 | 850 | +1 |
| 1 days of no change | ||
| 2025-08-16 | 849 | +1 |
| 2 days of no change | ||
| 2025-08-13 | 848 | +1 |
| 2025-08-12 | 847 | +1 |
| 5 days of no change | ||
| 2025-08-06 | 846 | +1 |
| 2025-08-05 | 844 | +2 |
| 2025-08-04 | 843 | +1 |
| 1 days of no change | ||
| 2025-08-02 | 842 | +1 |
| 1 days of no change | ||
| 2025-07-31 | 841 | +1 |
| 2025-07-30 | 840 | +1 |
| 2025-07-29 | 839 | +1 |
| 1 days of no change | ||
| 2025-07-27 | 838 | +1 |
| 2 days of no change | ||
| 2025-07-24 | 837 | +1 |
| 2025-07-23 | 836 | +1 |
| 2025-07-22 | 835 | +1 |
| 2 days of no change | ||
| 2025-07-19 | 833 | +2 |
| 4 days of no change | ||
| 2025-07-14 | 832 | +1 |
| 4 days of no change | ||
| 2025-07-09 | 831 | +1 |
| 6 days of no change | ||
| 2025-07-02 | 828 | +3 |
| 2025-07-01 | 825 | +3 |
| 1 days of no change | ||
| 2025-06-29 | 824 | +1 |
| 2025-06-28 | 823 | +1 |
| 2025-06-27 | 822 | +1 |
| 1 days of no change | ||
| 2025-06-25 | 820 | +2 |
| 2025-06-24 | 819 | +1 |
| 2025-06-23 | 818 | +1 |
| 1 days of no change | ||
| 2025-06-21 | 817 | +1 |
| 2025-06-20 | 816 | +1 |
| 2025-06-19 | 815 | +1 |
| 1 days of no change | ||
| 2025-06-17 | 813 | +2 |
| 2025-06-16 | 811 | +2 |
| 2025-06-15 | 810 | +1 |
| 1 days of no change | ||
| 2025-06-13 | 809 | +1 |
| 2025-06-12 | 808 | +1 |
| 1 days of no change | ||
| 2025-06-10 | 806 | +2 |
| 4 days of no change | ||
| 2025-06-05 | 805 | +1 |
| 2025-06-04 | 803 | +2 |
| 1 days of no change | ||
| 2025-06-02 | 802 | +1 |
| 3 days of no change | ||
| 2025-05-29 | 800 | +2 |
| 1 days of no change | ||
| 2025-05-27 | 799 | +1 |
| 3 days of no change | ||
| 2025-05-23 | 798 | +1 |
| 2025-05-22 | 797 | +1 |
| 2 days of no change | ||
| 2025-05-19 | 796 | +1 |
| 1 days of no change | ||
| 2025-05-17 | 795 | +1 |
| 1 days of no change | ||
| 2025-05-15 | 794 | +1 |
| 1 days of no change | ||
| 2025-05-13 | 793 | +1 |
| 2025-05-12 | 791 | +2 |
| 1 days of no change | ||
| 2025-05-10 | 790 | +1 |
| 2025-05-09 | 788 | +2 |
| 2025-05-08 | 785 | +3 |
| 2025-05-07 | 784 | +1 |
| 2025-05-06 | 782 | +2 |
| 2025-05-05 | 781 | +1 |
| 2025-05-04 | 780 | +1 |
| 1 days of no change | ||
| 2025-05-02 | 778 | +2 |
| 1 days of no change | ||
| 2025-04-30 | 776 | +2 |
| 2025-04-29 | 773 | +3 |
| 2025-04-28 | 772 | +1 |
| 2 days of no change | ||
| 2025-04-25 | 770 | +2 |
| 2025-04-24 | 768 | +2 |
| 1 days of no change | ||
| 2025-04-22 | 765 | +3 |
| 3 days of no change | ||
| 2025-04-18 | 763 | +2 |
| 1 days of no change | ||
| 2025-04-16 | 762 | +1 |
| 1 days of no change | ||
| 2025-04-14 | 761 | +1 |
| 3 days of no change | ||
| 2025-04-10 | 760 | +1 |
| 2 days of no change | ||
| 2025-04-07 | 758 | +2 |
| 2025-04-06 | 756 | +2 |
| 2 days of no change | ||
| 2025-04-03 | 755 | +1 |
| 2 days of no change | ||
| 2025-03-31 | 754 | +1 |
| 5 days of no change | ||
| 2025-03-25 | 753 | +1 |
| 1 days of no change | ||
| 2025-03-23 | 752 | +1 |
| 4 days of no change | ||
| 2025-03-18 | 751 | +1 |
| 2025-03-17 | 748 | +3 |
| 1 days of no change | ||
| 2025-03-15 | 747 | +1 |
| 4 days of no change | ||
| 2025-03-10 | 746 | +1 |
| 2025-03-09 | 745 | +1 |
| 1 days of no change | ||
| 2025-03-07 | 744 | +1 |
| 2025-03-06 | 743 | +1 |
| 2025-03-05 | 742 | +1 |
| 5 days of no change | ||
| 2025-02-27 | 740 | +2 |
| 2025-02-26 | 739 | +1 |
| 2025-02-25 | 737 | +2 |
| 4 days of no change | ||
| 2025-02-20 | 736 | +1 |
| 9 days of no change | ||
| 2025-02-10 | 734 | +2 |
| 3 days of no change | ||
| 2025-02-06 | 733 | +1 |
| 1 days of no change | ||
| 2025-02-04 | 732 | +1 |
| 2025-02-03 | 731 | +1 |
| 2 days of no change | ||
| 2025-01-31 | 730 | +1 |
| 2025-01-30 | 729 | +1 |
| 12 days of no change | ||
| 2025-01-17 | 726 | +3 |
| 6 days of no change | ||
| 2025-01-10 | 723 | +3 |
| 7 days of no change | ||
| 2025-01-02 | 721 | +2 |
| 63 days of no change | ||
| 2024-10-30 | 694 | +27 |
About
The Conversational Analytics dashboard improves Virtual Agent interactions with users by providing insights into conversational data. The dashboard also identifies underperforming topics, drives deflection, and discovers where users often transfer to live agents. The dashboard refines active topics and ultimately increases the deflection rate of Virtual Agent.
Key Features
- User insights and data history of user conversations.
- Conversation details: discover metadata about each Virtual Agent interaction, including user, chat duration, chat transcript, and which node a user progressed in a topic.
- Filter editors to filter the data and save/load the filters.
- Deflection indicators to realize the value of Virtual Agent.