Need some troubleshooting help with a data mismatch between the AI Bot analytics dashboard and the standard queue performance metrics in our EU-FR environment. The bot shows successful intent resolution, yet the downstream queue reports immediate abandonment for the same conversation IDs. How can I reconcile these conflicting metrics to validate the handoff logic?
The problem is likely that a timestamp gap between the bot’s intent resolution and the queue’s abandonment threshold, causing the metrics to diverge.
{
"filter": {
"type": "conversation",
"id": "{{conversationId}}"
},
"include": ["botMetrics", "queueMetrics"]
}
Check the transferTime field in the recording metadata to see if the handoff occurred after the queue’s timeout window closed.
Check your JMeter test plan’s correlation logic when validating these handoff metrics. The suggestion above regarding transferTime is spot on, but from a load testing perspective, the discrepancy often stems from how concurrent requests are sampled during the handoff window. If your script polls the conversationApi too frequently, you might be capturing the bot’s success state before the queue’s abandonment logic fully processes the timeout event.
Ensure your JMeter threads are configured with a Constant Throughput Timer to mimic realistic user behavior rather than hammering the API. You should also verify that the include parameter in your JSON payload matches the exact metric names returned by the Genesys Cloud analyticsApi.
- API rate limits during high-concurrency handoffs
- WebSocket connection stability during bot-to-agent transfers
- Queue timeout thresholds vs. bot resolution latency
- JMeter correlation variables for conversation IDs