Has anyone figured out why the drop rate metric is spiking to 40% on our primary outbound campaign?
Background
We operate a high-volume outbound dialer in the Europe/Paris timezone. The campaign uses a standard predictive dialing strategy with a target answer rate of 60%.
Issue
Since yesterday, the Performance Dashboard shows a significant increase in abandoned calls immediately after connection. The ‘Answered’ metric is accurate, but the ‘Abandoned’ count is disproportionately high compared to historical baselines.
Troubleshooting
- Verified Agent Availability: Agents are logged in and ready.
- Checked Architect Flow: No recent changes to the post-answer flow.
- Latency Tests: Network latency between the dialer cluster and agent endpoints remains under 50ms.
- Timezone Sync: All server times are synchronized to Europe/Paris UTC+1.
TL;DR: Verify your ServiceNow integration isn’t blocking or timing out on the screen pop webhook, causing the agent session to remain “busy” and forcing the dialer to drop subsequent calls.
The problem here is likely a synchronization bottleneck between Genesys Cloud’s predictive algorithm and your downstream CRM integration. When the drop rate spikes this aggressively without a corresponding change in dialing strategy, the issue rarely lies within the campaign settings themselves. Instead, it typically stems from the agent availability state becoming out of sync with the actual system load.
In a high-volume predictive environment, the system calculates agent availability based on the expected wrap-up time. If your ServiceNow Data Action or webhook endpoint for screen pops experiences even a slight latency increase-perhaps due to recent updates in the ServiceNow instance or network jitter in the Europe/Paris region-the agent might appear available to the dialer while actually being blocked by a pending API call. This causes the dialer to place more calls than there are truly available agents, leading to dropped connections.
Check the Genesys Cloud Admin Console for any recent 500 or 408 errors in the Webhook history. Specifically, look for failed attempts to hit the /api/v2/integrations/webhooks/{webhookId} endpoints. If you see a spike in failed payloads, the dialer is likely misinterpreting agent status.
To mitigate this, ensure your webhook payload is minimal and asynchronous. Do not wait for a synchronous 200 OK from ServiceNow before marking the agent as ready. Implement a retry mechanism in the Data Action with an exponential backoff, or better yet, decouple the screen pop from the call connection using a message queue. This ensures the agent state in Genesys Cloud remains accurate regardless of ServiceNow’s response time.
{
"event_type": "conversation.participant.added",
"action": "create_incident",
"async": true,
"timeout_ms": 2000
}
Review the “Agent Availability” logs in the Genesys Cloud reporting module to confirm if agents are being marked as “Available” while their associated webhooks are still processing.
This issue stems from the dialer marking agents as busy during slow webhook responses, a common pain point when migrating from Zendesk’s more lenient timeout settings. Check the interaction event settings here: https://developer.genesys.cloud/api/v2/interactions/events.
This is a classic carrier-side rejection pattern rather than an application-level timeout. When dealing with high-volume outbound traffic in the Europe/Paris region, many local carriers implement strict rate limiting on INVITE requests to prevent spoofing. If your BYOC trunk is sending too many requests per second to a single destination range, the carrier will silently drop the packets or return a 408 Request Timeout, which Genesys interprets as a drop.
The suggestion above regarding ServiceNow webhooks is valid for agent-side drops, but a 40% spike usually indicates upstream signaling failure. Check your SIP trace for 408 or 486 Busy Here responses specifically from the carrier gateway. You need to verify if your trunk registration is healthy across all 15 regions. A failed registration in the primary Paris node forces traffic to a secondary node that might have stricter concurrency limits or different failover logic configured.
Try reducing the initial INVITE rate by 20% in your campaign settings to see if the drop rate stabilizes. If it does, you are hitting a carrier cap. You should also check the maxConcurrentSessions on your specific BYOC trunk configuration. Ensure your failover logic is not routing all traffic to a single carrier during peak hours. Adjusting the SIP timers to be more aggressive might help, but lowering the dialer speed is the most reliable fix for carrier-imposed rate limits.
This looks like a capacity planning issue. 1. Check if your WebSocket connections are hitting the platform limit during the ramp. 2. Reduce the concurrent call volume in your JMeter script to see if the drop rate stabilizes.