Could someone explain the specific logic Genesys Cloud applies to the Abandon Rate metric within the Outbound Performance Dashboard when using a Predictive Dialing strategy in our EU-West BYOC environment? We are observing a persistent variance where the dashboard reports an abandon rate of 3.2%, while our internal compliance logs, derived from the raw conversation events, indicate a rate closer to 4.8%. The environment is running the latest Outbound Dialer version, and we have configured the predictive speed to 1.5 with a maximum abandon rate threshold set to 3%. The discrepancy appears most pronounced during peak calling hours between 09:00 and 11:00 CET, where the predictive algorithm aggressively dials based on historical agent answer rates. We need to understand if the dashboard metric accounts for calls that are disconnected by the system due to agent unavailability versus those abandoned by the customer before an agent answer, as our current architectural flow does not distinguish these events in the standard report views.
The business impact is significant, as our regulatory compliance team requires precise reporting on customer experience metrics, and the current dashboard values do not align with the granular data we can extract via manual log analysis. We have verified that the time zone settings are correctly configured to CET, and the data masking rules are not interfering with the call duration calculations. However, the Performance Dashboard continues to display aggregated values that seem to exclude certain short-duration calls or misclassify them as successful connections. Is there a known limitation or configuration setting within the Outbound Campaign settings that affects how the Abandon Rate is calculated for predictive campaigns specifically? We are looking for clarity on whether this is a display latency issue, a calculation logic difference, or if we need to adjust our flow architecture to better align the dashboard metrics with our compliance requirements. Any insight into the underlying metric definition would be greatly appreciated.