Bot analytics api missing trunk data in apac

Is it possible to get detailed bot interaction metrics broken down by specific byoc trunk id using the analytics api? we are seeing a weird discrepancy in our reporting for the singapore region. the architect flow routes inbound calls to our virtual agents based on the originating trunk, which is critical for our carrier-specific failover logic. however, when querying the /api/v2/analytics/conversations/summary endpoint, the trunk_id field is either null or returns a generic platform id instead of the actual byoc trunk identifier. this makes it impossible to correlate bot deflection rates with carrier performance issues we are tracking. we have 15 trunks active in apac and need to isolate which carriers are causing higher bot escalation rates due to sip registration jitter. the api response shows the conversation id and participant details correctly, but the infrastructure metadata seems stripped. is there a specific query parameter or a different endpoint required to pull this granular trunk-level data for bot sessions? currently using the v2 sdk and the data looks fine in the ui but not in the api payload.

Make sure you are explicitly including the trunk_id field in your request body under the groupBy array. The Genesys Cloud analytics engine does not return trunk-level granularity by default, especially for BYOC configurations where metadata handling differs from native SIP trunks. For APAC regions, there is often a slight lag in metadata propagation due to edge synchronization intervals.

The issue likely stems from how the virtual agent flow captures the trunk context. If the flow does not explicitly set a custom attribute or pass the trunk identifier into the conversation metadata before the analytics summary runs, the API returns null. Verify that your Data Action or Flow step captures the TrunkId from the initial inbound event. Additionally, check if the BYOC trunk is correctly tagged in the Genesys Cloud configuration. If the trunk ID is missing at the source, the analytics API cannot aggregate it.

• BYOC trunk metadata propagation
• Analytics API groupBy parameters
• Virtual Agent flow context variables
• ServiceNow webhook payload mapping

How I usually solve this is by verifying that the trunk metadata is explicitly mapped within the flow architecture before it reaches the analytics engine. The discrepancy often arises because the virtual agent interaction does not automatically inherit the SIP trunk identifiers from the initial inbound leg unless the flow is configured to pass these attributes through the interaction context.

The suggestion above regarding the groupBy array is correct, but it assumes the data is already populated in the conversation object. If the trunk_id is null in the API response, the issue is likely upstream in the flow design rather than the query itself.

To ensure the metrics are accurate for your carrier-specific failover logic, check the following:

• Flow Configuration: Ensure the “Set Interaction Attributes” block is used immediately after the initial greeting or transfer to the virtual agent. Map the trunk.id system attribute to a custom interaction attribute.
• Analytics Definition: When building the query, ensure the groupBy includes the custom attribute you just created, not just the raw trunk_id, as the system attribute may not persist across channel transitions in APAC edge nodes.
• Data Latency: Acknowledge that BYOC metadata can have a propagation delay of up to 15 minutes. Running the query immediately after a spike test may yield incomplete data.

Here is an example of how the query body should be structured to capture this correctly:

{
 "dateRange": {
 "from": "2023-10-01T00:00:00Z",
 "to": "2023-10-02T00:00:00Z"
 },
 "groupBy": ["customAttributes.trunkOrigin"],
 "selection": ["interactionCount", "avgDuration"]
}

This approach ensures that the reporting aligns with the actual routing logic defined in the architect flows, providing the granularity needed for your business metrics.

Take a look at at how the analytics engine handles metadata propagation during high-concurrency events in the APAC region. The discrepancy often stems from the virtual agent flow not explicitly inheriting SIP trunk identifiers from the initial inbound leg. If the flow doesn’t pass these attributes through the interaction context, the trunk_id field remains null or defaults to a generic platform ID.

To verify if this is a data ingestion issue rather than an API query problem, try isolating the metadata attachment latency from the export throughput metrics. A common fix is to ensure the trunk metadata is explicitly mapped within the flow architecture before it reaches the analytics engine.

Here is a sample JMeter config snippet to test the throughput of the analytics query under load:

<configElement name="ThroughputController">
 <stringProp name="TestPlan.comments">Bot Analytics Throughput Test</stringProp>
 <boolProp name="TestPlan.tearDownOnShutdown">true</boolProp>
 <elementProperty name="Controller">
 <stringProp name="TestPlan.comments">Limit to 50 req/sec</stringProp>
 <doubleProp name="ThroughputController.throughput">50.0</doubleProp>
 </elementProperty>
</configElement>

Run this against the /api/v2/analytics/conversations/summary endpoint with the groupBy array explicitly including trunk_id. If the 422 errors persist or the trunk data remains missing, it suggests a bottleneck in the analytics engine’s ability to process narrow time windows with custom metadata.

The suggestion above regarding the groupBy array is correct, but it assumes the data is present in the first place. If the flow isn’t configured to capture the trunk ID, no amount of grouping will fix the null values. Check the virtual agent flow configuration to ensure the trunk attributes are being passed through the interaction context.

Have you tried injecting the trunk identifier directly into the conversation attributes before the analytics engine processes the summary? As a chat widget developer, I know how critical context preservation is, but this applies to voice flows too. The suggestion above about groupBy is correct, but if the flow doesn’t explicitly set the attribute, the analytics engine has nothing to group. You need to ensure the virtual agent flow captures the sip.trunkId from the incoming leg and maps it to a custom attribute or ensures it persists in the interaction context. Without this explicit mapping, the metadata often gets stripped during the handoff to the bot, resulting in null values in the APAC region due to how edge nodes handle initial SIP headers.

Here is a sample Architect flow configuration snippet to ensure the trunk ID is captured and passed correctly. You should add a “Set Attribute” action immediately after the “Start” node or the “Answer Call” node. This forces the platform to retain the trunk metadata for downstream analytics.

{
 "actions": [
 {
 "id": "set-trunk-attr",
 "type": "SetAttribute",
 "key": "custom.trunkId",
 "value": "{{ sip.trunkId }}"
 }
 ]
}

After setting this attribute, your analytics query should group by custom.trunkId instead of relying on the potentially volatile trunk_id field. This approach bypasses the metadata propagation lag mentioned earlier because you are explicitly storing the value in the conversation context before the analytics summary is generated. This method has worked reliably for us when debugging carrier-specific routing issues in high-latency regions.