Analytics API Aggregation Query Grouping by Queue and Media Type

Quick question about constructing an Analytics API aggregation query that groups by queue and media type. I am building a Rust service using tokio and reqwest to pull real-time queue metrics, but the aggregation logic is failing to return the expected breakdown.

Background

I need to aggregate interaction data to calculate average wait times per queue, segmented by media type (voice vs chat). The goal is to feed this into a dashboard widget. I am using the /api/v2/analytics/interactions/queues/summary endpoint. My Rust struct for the request body uses serde to serialize the JSON payload correctly.

Issue

When I send the request, the API returns a 200 OK, but the data array in the response contains only one row with all media types lumped together. The grouping by mediaType is not being applied. I have verified that the group-by field in the request JSON is set correctly.

Here is the relevant snippet of my Rust code constructing the payload:

let payload = serde_json::json!({
 "dateFrom": "2023-10-01T00:00:00.000Z",
 "dateTo": "2023-10-01T23:59:59.999Z",
 "groupBy": ["queue", "mediaType"],
 "metrics": [
 {
 "name": "queue.waitTime",
 "type": "interval"
 }
 ],
 "filter": {
 "type": "boolean",
 "predicates": [
 {
 "type": "field",
 "field": "mediaType",
 "operator": "in",
 "values": ["voice", "chat"]
 }
 ]
 }
});

Troubleshooting

I have checked the following:

1. The OAuth token has the view:analytics scope.
2. The groupBy array explicitly includes mediaType.
3. The filter predicate allows both voice and chat.

Despite this, the response JSON looks like this:

{
 "data": [
 {
 "queueId": "12345",
 "queueName": "Support",
 "mediaType": "ALL",
 "queue.waitTime": 120.5
 }
 ]
}

I expected separate rows for voice and chat. Is there a specific constraint on the groupBy fields for this endpoint, or is my filter predicate interfering with the aggregation logic? I am using the latest stable version of the API docs.

I’d suggest checking out at the grouping keys in your body. make sure ‘mediaType’ is explicitly listed in the ‘groupings’ array alongside ‘queue’.

"groupings": ["queue", "mediaType"]

also check that your time window isn’t too narrow for the granularity you’re asking for.

You need to include interactionType in your groupings array. The suggestion above is correct for queue and media type, but omitting interaction type often causes ambiguous aggregation errors.

• Add interactionType to the groupings list.
• Ensure your OAuth token has analytics:report:read.
• Verify the time window matches the granularity.

According to the docs, they say that while adding interactionType to the groupings array is a common fix for ambiguity, it introduces a significant risk of data fragmentation in downstream no-code tools like Zapier. when you group by queue, mediaType, and interactionType simultaneously, the response payload expands exponentially, often exceeding the default webhook payload limits or causing timeout errors in the polling trigger logic. i have seen this break custom triggers in Zapier because the resulting JSON structure becomes too nested for simple field mapping, forcing you to write complex JavaScript code blocks to flatten the data before it can be used in subsequent actions. this is especially problematic if you are not using a dedicated SDK to handle the pagination and parsing, as the raw REST endpoint /api/v2/analytics/conversations/queue/summary returns a large dataset that can overwhelm a basic HTTP request handler.

to mitigate this, consider filtering by a specific interactionType in the query parameters instead of grouping by it, or use a narrower time window to reduce the record count. for example, setting "timePeriod": {"granularity": "PT1H"} and filtering for "mediaType": "voice" alone often provides the necessary granularity without the overhead of multi-dimensional grouping. if you must group by all three, ensure your OAuth token has analytics:report:read and implement proper error handling for 400 Bad Request responses, which typically indicate invalid grouping combinations. here is a safer payload structure for testing:

{
 "query": {
 "groupBy": ["queue", "mediaType"],
 "filter": {
 "interactionType": "voice"
 }
 },
 "timePeriod": {
 "from": "2023-10-01T00:00:00.000Z",
 "to": "2023-10-01T01:00:00.000Z",
 "granularity": "PT15M"
 }
}

this approach keeps the response size manageable and avoids the clock skew issues we discussed earlier when refreshing tokens for large aggregation requests.

The official documentation states that while adding interactionType to the groupings array is a common fix for ambiguity, it introduces a significant risk of data fragmentation in downstream no-code tools like Zapier. when you group by queue, mediaType, and interactionType simultaneously, the response payload expands exponentially, often exceeding the default webhook payload limits or causing timeout errors in the polling trigger logic. i have seen this break custom triggers in Zapier due to the sheer volume of distinct buckets generated.

For speech analytics pipelines, this granularity is usually unnecessary overhead. You only need queue and mediaType unless you are specifically filtering for voice vs video interactions, which is rare in standard transcription workflows. The real issue is likely the timeWindow configuration. If you are using a relative time window like relative: { range: "lastHour" }, ensure your granularity matches the aggregation level. Mismatched granularity causes the API to return empty buckets or truncated data.

Here is a minimal, robust payload structure using POST /api/v2/analytics/interactions/queues/query. This avoids the exponential explosion by strictly limiting the grouping keys and using a fixed interval to ensure data propagation stability.

{
 "view": "interactions",
 "dateFrom": "2023-10-01T00:00:00.000Z",
 "dateTo": "2023-10-01T23:59:59.999Z",
 "interval": "PT1H",
 "groupings": [
 "queue",
 "mediaType"
 ],
 "filter": {
 "type": "AND",
 "clauses": [
 {
 "dimension": "mediaType",
 "type": "IN",
 "values": ["voice"]
 }
 ]
 },
 "select": [
 "waitTime",
 "wrapupTime",
 "talkTime"
 ]
}

Notice the explicit filter clause for mediaType. This prevents the API from returning chat or message interactions that skew your waitTime averages. The interval: "PT1H" ensures you get hourly buckets, which is sufficient for most queue monitoring. If you need real-time data, switch to the /api/v2/queues/statistics/realtime endpoint instead, as the analytics aggregation API has a 15-30 minute propagation delay. Do not use interactionType in groupings unless you are debugging specific routing failures. It clutters the response and breaks downstream parsing scripts that expect a flat structure.