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data-manager-api-event-ingestion

Synced v1.0.0 License: Apache-2.0 Source: google/skills/skills/ads/data-manager-api-event-ingestion Commit: 99c871e Latest included change:

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).

Summary

Purpose
It helps developers build and troubleshoot event-ingestion integrations for Google Ads, Google Analytics, and Floodlight using the Data Manager API.
When to use
Use it to implement or migrate an event-ingestion workflow, format its data and destinations, validate a request, or diagnose ingestion status, errors, and warnings.
Outputs
It provides destination-specific implementation steps, sample and migration-guide references, data-formatting and payload guidance, and request-status troubleshooting.
Upstream changes (8, latest included 2026-09-24)
fd762f9 feat: update event ingestion skill to reference new detailed use case guides The skill now directs implementations to destination- and use-case-specific event guides, adds intent-based troubleshooting and migration guidance, and updates its version to 1.2.0.
329fa26 Standardize version formatting in Ads skills metadata The skill metadata version was standardized from 1.1 to "1.1.0".
126ed1e feat: add guidance on implementing remove and removeall workflows to audience skill feat: add step for ingestion warnings to both ingestion skills feat: add reference for creating new user lists to audience skill The skill adds guidance for `field_warnings`, updates request-ID wording to `request_id`, and expands its troubleshooting guidance to cover warnings.
703f8d2 Move ads skills from per-product subdirectories to top-level skills/ads/ directory. The skill file moved from `skills/ads/data-manager-api/data-manager-api-event-ingestion/SKILL.md` to `skills/ads/data-manager-api-event-ingestion/SKILL.md` without content changes.
e1ac3d0 feat: Introduce a new data-manager-api-setup skill for getting started, auth setup, and client/utility library installation feat: Add guidance to ingestion skills for retrieving diagnostics and using the validate_only flag The skill now delegates authentication and library setup to `data-manager-api-setup`, and adds `validate_only` and asynchronous request-status diagnostics guidance.
dac3453 Fixes to instructions for utility library installation The skill description now targets developers, and its utility-library instructions correct version-source references and the Python dependency pin syntax.
c75b500 Restructure the YAML frontmatter in all SKILL.md files to nest the 'category' field under the 'metadata:' block. The 'category' field is used to organize the skills in the README.md The skill's `category` field was moved under `metadata`, and spacing around front matter and code blocks was adjusted.
b13a5a1 Add new skills for Google Advertising and Measurement. The new skill defines an event-ingestion workflow covering destination selection, setup, client installation, code samples, migration guides, payload construction, formatting, common pitfalls, and error handling.
npx skills add "lettucebo/Skills#v2.2.0@data-manager-api-event-ingestion" --full-depth

⚠ Available after v2.2.0 is published

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 can't be determined from the user's context, consider clarifying which destination events are being ingested to before generating any code. This maps to the account_type field of the operating_account in the Destination, and also determines valid event identifiers and requirements.
  • Identify User Intent:
    • Implementing ingestion code: Follow the relevant implementation guide for the destination and use case in the Implementation guide column below. This is critical to ensure field requirements are met and destinations are correctly configured.
    • Checking request status or inspecting errors: Refer to the Error Handling & Troubleshooting section below.
    • Migrating from another Google API: Refer to Step 3: Retrieve Migration Guides below to extract the full contents of the relevant field mapping guide.
Destination (operating_account.account_type) Use case Implementation guide
Google Ads (GOOGLE_ADS) Offline conversions, enhanced conversions for leads Send events
Google Ads (GOOGLE_ADS) Multi-source conversions supplementing the Google tag Send events
Google Ads (GOOGLE_ADS) Store sales conversions Send events
Google Analytics (GOOGLE_ANALYTICS_PROPERTY) Recommended and custom GA4 events Send events
Google Analytics (GOOGLE_ANALYTICS_PROPERTY) Multi-source events with a transaction ID Send events
Floodlight (FLOODLIGHT_CONFIG) Floodlight offline conversions Send events
Floodlight (FLOODLIGHT_CONFIG) Multi-source conversions supplementing the Google or Floodlight tag Send events

If the request doesn't match any row, fetch the Events overview to find the right guide rather than guessing.

Step 2: Retrieve Code Sample

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

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 Analytics

Floodlight

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 request_id. 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

History

v1.0.0 mapping-added 99c871e