👍👎 User Feedback System
Learn how users can provide feedback on their call experiences and how this feedback helps improve your AI assistant.
Overview
The user feedback system allows callers to rate their experience and provide detailed feedback about how well your AI assistant handled their call. This feedback helps identify areas for improvement and automatically creates knowledge base gaps when needed.
📝 How Feedback Works
FAQ Suggestion Feedback
When users interact with FAQ suggestions during or after calls, they can:
- Rate with Thumbs Up/Down: Quick feedback on whether the FAQ was helpful
- Provide Detailed Comments: Add specific feedback about what went wrong
- Select Feedback Categories: Choose from predefined categories to help you understand the issue better
Feedback Categories
When users provide negative feedback, they can categorize their experience:
🗣️ Conversational Flow: Issues with how the conversation progressed
- Example: "The assistant kept interrupting me" or "The conversation felt unnatural"
❌ Wrong Answers: When the assistant provided incorrect information
- Example: "The assistant gave me the wrong office hours" or "Incorrect contact details"
🧠 Lack of Knowledge: When the assistant didn't have enough information
- Example: "The assistant couldn't answer my question about new services"
- Note: This automatically creates knowledge base gaps for your team to address
🔊 Voice Quality: Issues with how the assistant sounds
- Example: "The voice was too fast" or "Hard to understand the pronunciation"
🤖 Smart Feedback Analysis
Automatic Knowledge Gap Detection
When users provide feedback, our intelligent AI system analyzes it using multiple methods to accurately identify knowledge-related issues:
Three-Tiered Detection System:
- Direct Feedback Analysis: When users select "Lack of Knowledge" as their feedback category, the system verifies the feedback truly relates to a knowledge gap before creating one
- Comment Analysis: When users provide written comments without selecting a category, AI analyzes the content to determine if it indicates missing knowledge
- Call Pattern Recognition: The system monitors call success patterns and automatically identifies gaps when calls fail due to missing information
Note: All feedback is thoroughly analyzed by AI before creating knowledge base gaps, ensuring only relevant and actionable gaps are tracked. This prevents unnecessary gaps from cluttering your dashboard.
How It Works:
- User provides feedback (with or without category selection)
- System collects all feedback details for complete context
- AI analyzes the feedback using intelligent detection algorithms
- Only feedback that genuinely indicates missing knowledge creates a gap
- Gaps are categorized by type (CUSTOMER for user feedback, SYSTEM for automated detection)
- You receive a notification about the new knowledge base gap
- You can review and address the gap in your Knowledge Base section
📊 Using Feedback Data
In Analytics
- Track feedback trends over time
- See which categories get the most negative feedback
- Monitor knowledge gap creation patterns
- Identify specific contacts who frequently provide feedback
In Knowledge Base Gaps
- Review gaps created from user feedback
- See which feedback led to each gap
- Track how addressing gaps improves user satisfaction
💡 Best Practices
For Analyzing Feedback:
- Review feedback regularly to identify common issues
- Pay attention to knowledge gaps - they show you exactly what information to add
- Track trends to see if improvements are working
- Use contact filtering to understand specific user needs
For Improving Based on Feedback:
- Address knowledge gaps promptly by adding missing information to your knowledge base
- Update conversation flows if users report flow issues
- Review voice settings if users mention voice quality problems
- Train your assistant with better responses for frequently misunderstood questions
🔔 Notifications
You'll receive notifications when:
- New knowledge base gaps are created from user feedback
- Patterns in negative feedback are detected
- Specific feedback categories reach concerning levels
Remember: User feedback is a valuable tool for continuously improving your AI assistant. The more you act on this feedback, the better your assistant becomes at serving your callers!
If you need help interpreting feedback or making improvements, please contact your administrator or support team.