1. Analyze customer satisfaction consistency across all tickets
| Ticket ID | Priority | Opened | Closed | Agent | CSAT |
| TKT-001 | High | 2026-09-01 | 2026-09-02 | Alex | 4.8 |
| TKT-002 | Low | 2026-09-01 | 2026-09-05 | Blake | 4.2 |
| TKT-003 | Medium | 2026-09-02 | 2026-09-04 | Alex | 4.9 |
| TKT-004 | High | 2026-09-03 | 2026-09-03 | Charlie | 3.5 |
| TKT-005 | Low | 2026-09-04 | 2026-09-08 | Blake | 4.1 |
| TKT-006 | High | 2026-09-05 | 2026-09-06 | Alex | 4.7 |
=VAR.S(F2:F7)Result: 0.286
VAR.S calculates how the CSAT scores (4.8, 4.2, 4.9, 3.5, 4.1, 4.7) deviate from their mean of 4.37. The variance of 0.286 indicates relatively tight clustering—customer satisfaction is consistent across tickets, with scores rarely straying far from the average.