Detect whether any hold or extended wait occurred during the interaction.
The evaluation focuses on whether hold occurred during the interaction.
This is one of those behaviors that separates good agents from great ones, and it is nearly impossible to track at scale through manual QA. A supervisor might catch it on a handful of monitored calls, but the pattern only becomes visible when you can see it across hundreds or thousands of interactions.
Tracking hold occurred over time reveals coaching opportunities that are specific and actionable. Instead of telling an agent to "do better," supervisors can point to concrete moments in real conversations where the behavior was present or missing.
Compass analyzes the full context of the conversation to determine whether hold occurred occurred. This is not keyword matching or phrase detection. The evaluation considers meaning, sequence, and conversational dynamics to distinguish genuine instances from surface-level similarities.
The evaluation is calibrated to account for ambiguity. When the evidence is not strong enough to make a confident determination, the signal surfaces as unclear rather than being forced into a binary present-or-absent result. This means teams can trust the signal when it does fire.
QA teams use this signal to focus their review time on the interactions that matter most. Instead of random sampling, they can prioritize calls where this behavior was absent or inconsistent, making every review hour more productive.
Supervisors track the signal over time to identify trends. A gradual decline in an agent or team often points to burnout, a process change that is creating friction, or a knowledge gap that coaching can address.
Operations leaders connect this signal to broader outcomes like customer satisfaction, repeat contacts, and retention. The correlation between consistent agent behaviors and business results becomes visible when you can measure it across every interaction.
This signal is part of Chordia’s Quality Monitoring capabilities.
