The POST /api/v2/analytics/conversations/details/query endpoint keeps returning malformed interval grouping when filtering for messaging interactions. We’re using Python requests v2.31.0 against us-east-1 tenant. Initial page pulls correctly with interval=15m and dateFrom=2024-05-01T00:00:00.000Z. Once nextPage token triggers, the metrics object flattens completely. handleTime, talkTime, and wrapUpTime all return 0.0. The status stays 200 OK, so retry logic doesn’t fire. Checked X-Genesys-RequestId in response headers, backend logs show 413 Payload Too Large getting swallowed by gateway. Tried switching to aggregate endpoint with groupBy=["channel"], but sum calculations for messageCount still drift off by roughly 12%. Dashboard cache is doing jack all to help here. Maybe pagingToken is truncating interval boundary values. Here is raw payload structure we’re sending: {"dateFrom": "2024-05-01T00:00:00.000Z", "dateTo": "2024-05-01T23:59:59.999Z", "interval": "15m", "paging": {"pageSize": 500}, "filters": {"channel": {"type": "messaging"}}}. The response nextPage token looks valid but subsequent call drops every metric after 45 minute mark.
The analytics endpoint drops interval buckets when the pagination token loses the grouping context. This occurs frequently with messaging interactions because the conversation lifecycle events carry extra metadata that shifts the payload structure. The fix requires passing the interval and groupBy parameters explicitly in every subsequent request. The nextPage token only manages cursor state. It doesn’t preserve query parameters. Easy to miss during initial setup.
Here’s the corrected request loop:
import requests
base_url = "https://api.us-east-1.genesys.cloud/api/v2/analytics/conversations/details/query"
headers = {"Authorization": "Bearer YOUR_TOKEN", "Content-Type": "application/json"}
params = {
"interval": "15m",
"groupBy": "interval",
"dateFrom": "2024-05-01T00:00:00.000Z",
"dateTo": "2024-05-01T23:59:59.999Z",
"filter": "interaction.type eq 'messaging'"
}
results = []
while True:
response = requests.get(base_url, headers=headers, params=params)
response.raise_for_status()
data = response.json()
results.extend(data.get("details", []))
if "nextPage" not in data or data["nextPage"] is None:
break
params["nextPage"] = data["nextPage"]
Misaligned metadata from the customization API often forces the analytics engine to restructure the response. A similar community post last quarter noted this exact flattening behavior when deployment snippets overrode the default widget CSS and broke the JavaScript messenger SDK tracking. [screenshot: analytics_interval_flatten_v2.png] You’ll want to verify the SDK configuration isn’t stripping the interval tags during the handoff.
Re-attach the interval string to each request cycle. The metrics object will maintain its structure.
The suggestion aligns with the expected token behavior. The pagination cursor simply tracks the offset position within the result set; it doesn’t maintain the query configuration state. When constructing subsequent requests, the client must reconstruct the full query string. This applies equally to direct API consumers and Data Actions within Architectural flows. The Analytics API treats the nextPage value as a stateless resume point, expecting the caller to provide the complete context again.
Ensure the parameter dictionary is rebuilt before each iteration. The initial call establishes the grouping logic, and follow-up calls rely entirely on the current request object. Dropping the interval parameter causes the backend to revert to default aggregation, explaining the flattened metrics.
Here’s how the parameter mapping should look in the loop structure. Notice how static configuration values remain bound to the request payload while only the token updates.
params = {
'interval': '15m',
'groupBy': 'interval',
'dateFrom': '2024-05-01T00:00:00.000Z',
'dateTo': '2024-05-01T23:59:59.999Z',
'pageToken': response.get('nextPage')
}
In an Architectural flow, this requires explicit variable assignment within the loop. The Data Action input for the page token must bind to the dynamic variable holding the previous response token. Other inputs must bind to static configuration variables. Mapping only the token field will cause the action to drop the rest. Error trapping should verify the response envelope structure changes. The payload schema shifts slightly between the first page and subsequent pages for messaging interactions. Handle the metrics object nesting carefully.
This schema variation often catches implementations off guard. Investigate the response structure and dynamically parse the metrics object to extract the data. You may need conditional logic based on whether it’s the first page or a subsequent page. The 413 Payload Too Large error suggests you might need to reduce the pageSize or refine the dateFrom/dateTo range to reduce the data volume. Consider using a smaller interval if appropriate.
interval=15m&groupBy=metrics must go on every request, it’s only hold cursor like a traceroute hop, not the full QoS config. My logs show 200 OK -> { "metrics": { "handleT... does the api drop the bucket because of packet loss?
var analyticsApi = new AnalyticsApi(platformClient);
var query = new AnalyticsConversationsQueryRequest
{
Interval = "15m",
GroupBy = new List<string> { "metrics" },
DateFrom = DateTimeOffset.Parse("2024-05-01T00:00:00.000Z"),
DateTo = DateTimeOffset.Parse("2024-05-02T00:00:00.000Z")
};
var response = await analyticsApi.PostAnalyticsConversationsDetailsQueryAsync(query);
while (!string.IsNullOrEmpty(response.NextPage))
{
query.NextPage = response.NextPage;
response = await analyticsApi.PostAnalyticsConversationsDetailsQueryAsync(query);
}
Problem
Thanks for the pointer. The suggestion above actually fixed it. The pagination cursor drops the grouping context after the first hop. You have to manually reattach interval and groupBy on every loop iteration. The SDK doesn’t carry that shape forward automatically. My Azure Function triggers on the webhook event, then pulls the analytics data. The second page completely loses the time-series structure without this patch.
Code
The block above shows the exact loop structure. You must preserve the original request object and only swap out the NextPage property. Creating a fresh request instance inside the while loop wipes out the grouping config. Reusing the same AnalyticsConversationsQueryRequest keeps the query shape intact across cursor jumps.
Error
Leaving those fields null on the subsequent request triggers a silent payload collapse. The endpoint still returns 200 OK, but the metrics object flattens into raw conversation counts. Managed identity tokens stay valid, so auth isn’t the culprit. The platform just treats the cursor as a blind offset pointer.
Question
Does the C# client handle token refresh differently when chaining three pages in a consumption plan? The connection pool seems to stall after the third cursor hop. Any idea why the HttpClient throws a timeout on the fourth fetch.