Analytics API 422 Unprocessable Entity on Custom Report Definition Migration from Zendesk

General Discussion
1

Struggling to understand why the Genesys Cloud Analytics API is rejecting our custom report definitions with a 422 Unprocessable Entity error during the migration phase. We are moving from Zendesk Explore to Genesys Cloud Analytics, and the mapping of ticket-based metrics to interaction-based metrics is causing significant friction. Zendesk’s flat structure for ticket status and priority does not translate cleanly to GC’s hierarchical routing and interaction attributes, leading to schema validation failures.

Here are the steps to reproduce the issue:

  1. Create a custom report definition in Zendesk Explore that includes ticket creation time, agent handle time, and resolution status.
  2. Map these fields to Genesys Cloud’s interaction metrics: created_timestamp, agent_hold_duration, and disposition_code.
  3. Use the Genesys Cloud Analytics API endpoint POST /api/v2/analytics/report/definitions to upload the JSON payload.
  4. Observe the 422 error response with the message: “Invalid metric type for interaction report. Expected ‘count’ or ‘sum’, got ‘average’.”

The error seems to stem from the way Zendesk’s average handle time (AHT) is calculated compared to GC’s interaction-level metrics. Zendesk provides AHT as a pre-calculated field, while GC requires aggregating raw interaction durations. Our migration script is attempting to map Zendesk’s AHT directly to GC’s agent_hold_duration metric, which is invalid because GC expects a count or sum operation for this field.

We are using the Genesys Cloud Java SDK version 10.2.0 and the API version v2. The environment is eu-west-1, and we are migrating from Zendesk Suite to Genesys Cloud CX. The issue persists even after adjusting the metric type to sum, as the aggregation logic does not match Zendesk’s calculations.

Could someone provide guidance on how to properly map Zendesk’s AHT and ticket status metrics to Genesys Cloud’s interaction-based reporting structure? We need a reliable way to replicate Zendesk’s reporting capabilities in GC without manual post-processing. Any examples of successful Zendesk-to-GC report migrations would be greatly appreciated.

2

According to the docs, they say that custom report definitions must align strictly with the underlying interaction schema, not legacy ticket structures.

Mapping Zendesk flat attributes to Genesys hierarchical routing requires explicit transformation logic.

Check the specific attribute paths in your JSON payload against the Analytics API schema reference.

3 
resource "genesyscloud_routing_queue" "example" {
 name = "Migrated Queue"
 # Ensure interaction attributes match GC schema
}

resource "genesyscloud_analytics_customreport" "zendesk_migration" {
 name = "Zendesk Interaction Report"
 report_type = "INTERACTION"
 
 data_filters {
 # Map flat Zendesk status to GC interaction state
 filter_type = "EQUALS"
 field = "interaction.state"
 value = "completed"
 }
 
 columns {
 # Use GC native attributes, not legacy ticket fields
 id = "interaction.id"
 name = "Interaction ID"
 type = "STRING"
 }
}

I usually solve this by discarding the Zendesk schema entirely and rebuilding the report definition using native Genesys Cloud interaction attributes. The 422 error occurs because the API strictly validates against the interaction schema. Flat ticket data does not map to hierarchical routing attributes without explicit transformation.

Define the data_filters and columns using Genesys Cloud fields like interaction.state or routing.queue.id. Do not attempt to push legacy ticket IDs directly into the analytics definition. Use Terraform to enforce the correct schema during deployment. This ensures the report definition aligns with the underlying data model. The migration script should transform the data before ingestion, not during report definition.

4

The root of the issue is likely a mismatch between the attribute type definition in your Outbound Campaign configuration and the payload structure sent via the API. Genesys Cloud is strict about schema validation. Try adding a constant timer to your JMeter thread group before hitting the Analytics endpoint to see if rate limiting is masking the actual 422 error. Check the interaction schema reference for exact path requirements.