Analytics Dashboard
A good dashboard turns raw data into actionable decisions. Here is how to set up support analytics that your entire team can use.
Dashboard Structure
Organize your dashboard into four sections:
Section 1: Real-Time Overview At-a-glance current state:
- Active conversations right now
- AI vs. human handling breakdown
- Current queue depth
- Average response time (last hour)
Section 2: Daily Performance Rolling 24-hour metrics:
- Conversations handled (AI vs. human)
- Resolution rate
- Average CSAT score
- Top 5 topics by volume
Section 3: Weekly Trends Week-over-week comparisons:
- Resolution rate trend
- Cost per resolution trend
- Ticket volume trend
- Content gap rate trend
Section 4: Business Impact Monthly business metrics:
- Total cost savings vs. human-only support
- Customer retention impact
- Agent productivity gains
- ROI calculation
Setting Up in Corebee
Navigate to Analytics > Dashboard and configure:
- Choose your date range defaults (today, 7 days, 30 days)
- Select metrics for each widget
- Set comparison periods for trend analysis
- Configure automated email reports for stakeholders
Key Visualizations
Resolution Funnel Shows how conversations flow: Total received > AI attempted > AI resolved > Escalated > Agent resolved
Topic Heatmap Visual grid showing conversation volume by topic and time of day. Helps with staffing and content planning.
CSAT Distribution Histogram of satisfaction scores, split by AI vs. human handling. Quickly spot if one channel underperforms.
Stakeholder Views
Different audiences need different dashboards:
Executives — Monthly business impact, ROI, cost savings Support Managers — Daily operational metrics, agent performance, queue health Content Team — Knowledge base effectiveness, content gaps, article performance Product Team — Feature-related support volume, bug reports, feature requests
Alerts and Notifications
Configure alerts for anomalies:
- Resolution rate drops below threshold
- CSAT falls below target
- Queue depth exceeds capacity
- New topic spike detected
Exporting Data
Export options for deeper analysis:
- CSV export for spreadsheet analysis
- API access for custom dashboards
- Scheduled email reports (daily, weekly, monthly)
Next up: Using A/B testing to optimize your AI support performance.