Period: Last 7 Days (Nov 22 - Nov 29, 2025)
Generated: 2025-11-29
512
6
60
479
1,189
68
13
Total Tickets Created: 441
Total Tickets Solved: 334
| Date | Created | Solved |
|---|---|---|
| 23 Nov 25 | 51 | 47 |
| 24 Nov 25 | 80 | 67 |
| 25 Nov 25 | 63 | 48 |
| 26 Nov 25 | 69 | 50 |
| 27 Nov 25 | 77 | 51 |
| 28 Nov 25 | 93 | 67 |
| 29 Nov 25 | 8 | 4 |
| Channel | Created | Solved |
|---|---|---|
| Messaging | 51 | 246 |
| 40 | 194 | |
| Web | 8 | 39 |
Total Agents: 6
Total Solved Tickets: 512
Average Satisfaction Score: 60.1%
| Agent Name | Solved Tickets | First Reply Time (hrs) | Resolution Time (hrs) | Satisfaction Score (%) | One-Touch Tickets (%) |
|---|---|---|---|---|---|
| Neo | 232 | 0.18 | 1.01 | 50.0% | 73.3% |
| Jason | 109 | 0.08 | 13.98 | 77.8% | 28.4% |
| Esther | 90 | 0.08 | 0.84 | 50.0% | 40.0% |
| John | 61 | 0.20 | 9.48 | 62.5% | 55.7% |
| Lilly | 16 | 0.07 | 17.25 | N/A | 6.2% |
| Cristina | 4 | 0.15 | 7.36 | N/A | 0.0% |
Total Solved Tickets: 479
Total Agent Replies: 1,189
Average Daily Solved: 68.4
Average Daily Replies: 169.9
| Date | Solved Tickets | Agent Replies | Avg Replies per Ticket |
|---|---|---|---|
| 23 Nov 25 | 55 | 65 | 1.18 |
| 24 Nov 25 | 61 | 146 | 2.39 |
| 25 Nov 25 | 97 | 180 | 1.86 |
| 26 Nov 25 | 108 | 370 | 3.43 |
| 27 Nov 25 | 50 | 94 | 1.88 |
| 28 Nov 25 | 100 | 321 | 3.21 |
| 29 Nov 25 | 8 | 13 | 1.62 |
Average Satisfaction Score: 60.1%
Agents with Satisfaction Data: 4
⚠️ Bad Satisfaction Tickets: 13
• Top Performer: Neo solved 232 tickets with 50.0% satisfaction. Consider sharing best practices with the team.
• Support Needed: Neo, Esther have satisfaction scores below 60%. Schedule coaching sessions to improve customer interactions.
• Efficiency Opportunity: Several agents have low one-touch ticket rates. Focus on first-contact resolution training to reduce ticket volume.
• Volume Management: Average 68.4 tickets solved per day. Monitor capacity and ensure adequate staffing for peak periods.
• Quality Focus: 13 tickets received bad satisfaction ratings. Review these cases to identify common issues and improve resolution quality.
• Weekly Action Items:
• 1. Review individual agent performance with each team member
• 2. Identify and address any recurring customer issues
• 3. Optimize workload distribution based on agent strengths
• 4. Schedule training sessions for agents below performance targets
• 5. Celebrate top performers to maintain team morale