Workforce Management

It would be great to have this view as our team is accustomed to viewing this way

I should be able to track Chat Average Handling Time (AHT) based on the agent’s actual interaction time, starting from their first response to a ticket until they either resolve it or make their final reply. This metric should include active response time and applicable wrap-up time, calculated as: Chat AHT = Total Handling Time / Number of Chats Handled

Most teams think of CSAT in terms of percentage, not an average of score reported. It would be great to include options for this metric to be in percentage format. This is especially true for teams that have a simple "thumbs up" or "thumps down" system.

It would be helpful to have a metric that tracks how often agents are late to shifts.

Ability to see shrinkage by agent and total average shrink. Additionally see average totals for the other columns on team performance

As a manager I absolutely love the Agent Activity report and how it breaks up activity based on agents' activity (i.e. online in zendesk in a ticket, online in zendesk not in a ticket, offline etc.). It would be really useful to have some aggregate view of all those diff states somewhere so that I could have a quick and easy view of how much time in total agents spend in each state.

In Zendesk - 'Solved' and 'Closed' tickets count as Cases Solved. We can also optionally set 'Pending' to count in this metric. But 'On Hold' is never counted. We should add additional configuration options so customers can tailor their metrics to match their operations.

Shrinkage metric to be available on the agent score card.

Or "discretionary” and “nondiscretionary" shrinkage

Request Add a metric for Actual Staffing (actual FTE present per interval) in the Support Volume view, displayed next to the existing Scheduled Staffing column. Why this helps This would allow teams to quickly compare Scheduled vs Actual staffing at the interval level to identify gaps caused by adherence, lateness, or unplanned absences, and better understand their impact on service level performance.