data-manager-api-event-ingestion

name	data-manager-api-event-ingestion
description	Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads, click conversions, Google Analytics web or app events, or any other event ingestion use case supported by the Data Manager API. Don't use for uploading audience members (use the data-manager-api-audience-ingestion skill).
metadata	{"version":1.1,"category":"GoogleAds"}

Data Manager API Event Ingestion

Implementation Workflow

Prerequisites

• Authentication & Library Installation: If you need to set up access to the Data Manager API or install the client and utility libraries, refer to the data-manager-api-setup skill.

Step 1: Identify Use Case & Read Documentation

• Determine Destination Account Type: [CRITICAL] If it's not explicitly stated, STOP and CLARIFY with the user where the data is being sent (e.g., Google Ads, Floodlight, Google Analytics) BEFORE generating any code. Do not assume Google Ads by default. This maps to the account_type field of the operating_account in the Destination, and also determines valid event identifiers and requirements.
• Read Documentation: [CRITICAL] Follow the Send events guide to implement the integration, as steps for configuring and sending the request may vary between destinations.

Step 2: Retrieve Code Sample

[!IMPORTANT] If writing or updating an ingestion script, ALWAYS retrieve the relevant code sample to use as a reference:

Language	Sample
Python	ingest_events.py
Java	IngestEvents.java
PHP	ingest_events.php
Node	ingest_events.ts
.NET	IngestEvents.cs

Step 3: Retrieve Migration Guides

[!IMPORTANT] If refactoring code to upgrade from another Google API, ALWAYS extract the full contents of the relevant field mapping guide.

Google Ads

• Google Ads API Offline Conversions: Google Ads Offline Conversions Migration Field Mappings
• Google Ads API Store Sales: Google Ads Store Sales Migration Field Mappings

Google Analytics

• Measurement Protocol (Google Analytics): Google Analytics Measurement Protocol Migration Field Mappings

Campaign Manager 360 (CM360)

• Campaign Manager 360 API Offline Conversions: Campaign Manager 360 Offline Conversions Migration Field Mappings

Step 4: Implementation

Implement the ingestion logic using the following checkpoints:

• Initialize Client: Instantiate the Data Manager client (IngestionServiceClient).
• Define Destinations: Build the Destination object using the product_destination_id and the appropriate account configurations: operating_account (target account receiving data), login_account (if authenticating using a manager account or a data partner account), and linked_account (if you're a data partner accessing the account via a partner link to a manager account). STRONGLY RECOMMENDED: Refer to the Configure destinations and headers guide for more details on configuring destinations.
• Prepare Event Data: Use the utility library helpers to format and normalize user identifiers correctly.
• Construct Payload: Build the request payload (IngestEventsRequest) containing the destinations, event records, and consent permissions.
• Support Validation: Support sending the validate_only boolean option on the IngestEventsRequest to allow developers to validate schemas without actually uploading data.
• Send Request: Execute ingest_events and record the returned request_id for later diagnostics.
• Check for Ingestion Warnings: If any non-required field had a validation failure, the response from ingest_events will also include field_warnings, a list of FieldWarning objects detailing the issues.
• Retrieve Request Status: Check the status of the ingestion request using diagnostics. Since request processing is asynchronous, a successful ingestion response (HTTP 200 OK returning a request_id) only indicates the payload was received. To check if the records actually succeeded, partially succeeded, or failed to process, query the client.retrieve_request_status endpoint using the . Skipping this step is a common user mistake.

Formatting

• Fetch the Format user data guide and use that as the source of truth for formatting and normalization rules.

• Use the utility library to format, hash, and encrypt user data (emails, phone numbers, addresses).

  Python Example:

  from google.ads.datamanager_util import Formatter
  from google.ads.datamanager_util.format import Encoding
  
  formatter: Formatter = Formatter()
  
  processed_email: str = formatter.process_email_address(
      email, Encoding.HEX
  )
  

Critical Gotchas

• Format product_destination_id as a numeric string. It is NOT a resource name path.
• Format event_timestamp strictly in RFC 3339 format. Use the SDK's typed timestamp object instead of a raw string where available.
• Nest click identifiers (gclid, gbraid, wbraid) inside the ad_identifiers block, not directly on the base event payload.
• The enum values for ConsentStatus are CONSENT_GRANTED and CONSENT_DENIED. Do not use the values GRANTED and DENIED.
• Note that consent can be set globally on the IngestEventsRequest or on individual Events.
• Verify that UserIdentifier uses email_address and phone_number. Do not use the Google Ads API fields hashed_email and hashed_phone_number.
• Ensure the currency field on the event is named currency, not currency_code.
• Do not call the diagnostics endpoint (retrieve_request_status) if validate_only is set to true.

Error Handling & Troubleshooting

Inspecting Error Payloads & Ingestion Warnings

[!IMPORTANT] Refer to Understand API Errors for a detailed guide on how to understand the structure of errors and warnings returned by the API.

Retrieving Request Status (Diagnostics)

Periodically poll for status using exponential backoff, starting at least 30 minutes after sending the IngestEventsRequest.

1. Call client.retrieve_request_status using RetrieveRequestStatusRequest(request_id=...).
2. Loop through request_status_per_destination in the response to inspect each target's request_status.
3. If processing is complete and request_status is SUCCESS, PARTIAL_SUCCESS, or FAILED, inspect diagnostic values:
   • Event Record Counts: Check events_ingestion_status.record_count (includes both success and failure).
   • Error Details: If status is FAILED or PARTIAL_SUCCESS, inspect each error's reason and record_count under error_info.error_counts.
   • Warning Details: Inspect each warning's reason and record_count under warning_info.warning_counts (even if the destination status is SUCCESS).

API Reference

• REST API Reference
• Diagnostics Guide