Feedback: Review User Reaction on the Chatbot Responses
A user feedback mechanism for SUVA gathers users feedback on chatbot responses for both traditional and LLM-powered chatbots. This feedback helps admins evaluate the quality of responses generated by the chatbot and whether or not those responses helped the users. The Feedback report lets admins view all user feedback on the bot-generated responses.
The Feedback report consists of four columns: 1. User Query, 2. Story Name, 3. Reaction, and 4. Preview Response.
The report can be filtered using Filter by Intent. You can select intent(s) for which you want to see the feedback list. You can further sort the list using the Date Range and Select Location filters .
You can view the total number of thumbs-up and thumbs-down responses in the Total Responses Feedback.
The details of each column and what they represent are as follows:
User Query
This column lists the user queries which triggered a bot response on which the users left feedback (thumbs up or thumbs down)..
Story Name
It enlists the name of the story as there could be more than one story under a storyboard.
Reaction
You can see the user feedback (thumbs up or thumbs down) for the user query. The column is sortable; you can view user queries with the 1) Thumbs up reaction, 2) Thumbs down reaction, and 3. Both (Thumbs up and Thumbs down) reactions.
Preview response
This column shows a message icon. The icons highlighted in gray represent bot responses that didn't attract any clicks and the bot responses that attracted a click are highlighted in blue. You can click the preview response icon to view the bot responses on which users left a feedback.
Next Best Action
The feedback report is vital for enhancing the chatbot's performance and user experience.
A positive user feedback will help you be sure that your chatbot was successful in helping users with their queries.
However, a negative feedback can help you identify and understand user needs, find content gaps. Thus, you can improve your content experience and quality by better structuring your content and ultimately engage and retain users effectively. By incorporating user feedback into iterative development processes, chatbots can continually evolve to better serve their users and provide more accurate, helpful, and satisfying interactions.