AI Analytics Dashboard
Full transparency into every AI decision. Track approval rates, confidence scores, and accuracy metrics. Watch your AI get smarter over time—and prove it with data.
Key Metrics
Approval Rate
Percentage of AI actions approved by you or auto-approved based on confidence thresholds
94% means 94 out of 100 AI actions were approved
Confidence Score
AI's self-assessed certainty for each decision, ranging from 0 to 1
0.89 average means the AI is typically 89% confident
Accuracy
How often approved AI actions led to positive outcomes
96% means 96% of actions achieved their intended result
Actions Processed
Total number of AI actions taken in the selected time period
127 today means the AI handled 127 customer interactions
Knowledge Quality Metrics
Track the health and effectiveness of your knowledge base:
Evidence Coverage
Percentage of AI responses that include citations from your knowledge base
95% means 95 out of 100 answers cite a source
Stale Source Alerts
Number of knowledge sources flagged as outdated and needing review
3 stale sources means 3 items are over 90 days old
Gap Acceptance Rate
Percentage of AI-suggested knowledge gaps that you added to the knowledge base
78% means you added 78 out of 100 suggested topics
Citation Accuracy
How often the cited source correctly answers the customer's question
97% means 97 out of 100 citations were relevant
Understanding Confidence Scores
Every AI action includes a confidence score that reflects how certain the AI is about its decision:
AI is very certain. These actions can typically be auto-approved.
AI is reasonably sure. May warrant a quick review.
AI is somewhat uncertain. Review recommended before approval.
AI flagged this for human review. Always requires manual approval.
Decision History
The decision history shows every AI action with full context:
Action Description - What the AI did (e.g., "Replied to Sarah about availability")
Confidence Score - How certain the AI was about this action
Status - Whether it was approved, auto-approved, pending, or rejected
Timestamp - When the action occurred
Linked Context - Customer, booking, or conversation associated with the action
Decision Statuses
AI action met confidence threshold and was executed automatically
You or a team member reviewed and approved the AI action
AI action is waiting for human review before execution
You rejected the AI's proposed action and took over manually
Improving AI Performance
Your AI learns from every interaction. Here's how to help it improve:
Review pending actions promptly
The faster you approve or reject, the faster the AI learns your preferences.
Add knowledge when AI hesitates
Low confidence often means missing information. Add to your knowledge base.
Adjust autonomy levels gradually
As approval rates improve, consider increasing AI autonomy for efficiency.
Check weekly trends
Monitor the learning rate metric to ensure consistent improvement.
Configuring Auto-Approval
Set thresholds for when AI can act without waiting for approval:
Confidence Threshold - Actions above this score are auto-approved (default: 0.90)
Action Type Rules - Different thresholds for messages, bookings, reminders
Risk Level Override - High-risk actions always require approval regardless of confidence
Troubleshooting Low Approval Rates
If your approval rate drops below 90%, consider these fixes:
Problem: AI suggests wrong services
Solution: Update your knowledge base with service details and common customer requests
Problem: AI responds with incorrect information
Solution: Add FAQs and correct information to the knowledge base
Problem: AI doesn't understand customer intent
Solution: Review rejected actions and add examples to help the AI learn patterns
Problem: Too many actions requiring approval
Solution: Consider raising autonomy level if approval rate is consistently high
Learning Rate Explained
The learning rate shows how quickly your AI is improving:
This means your AI's performance metrics (approval rate, accuracy, confidence) are improving by an average of 2.3% each week. A positive learning rate indicates the AI is successfully adapting to your business patterns.
Pro Tips
- • Check your analytics dashboard at least weekly to spot trends
- • Export reports for team meetings or business reviews
- • Compare performance across different action types
- • Use insights to optimize your knowledge base content