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Data Manager API Audience Ingestion

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  • Apache-2.0
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From the author

Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).
— the description by Google

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a comprehensive guide for developers to manage audience members—including adding, removing, and clearing lists—within Google products like Google Ads and Display & Video 360 using the Data Manager API. It covers the end-to-end process from identifying the correct destination account and formatting user data to executing API requests and performing asynchronous diagnostics to verify ingestion success.

What it does

  • Guides the implementation of audience ingestion, removal, and replacement workflows.
  • Provides instructions for configuring destination accounts and headers.
  • Details the normalization and hashing of user identifiers using utility libraries.
  • Explains how to validate API request schemas without applying changes.
  • Outlines the process for polling and interpreting asynchronous request status and diagnostics.
  • Highlights critical implementation gotchas regarding field naming, consent, and encoding.

When to use it

  • When you need to upload, remove, or clear audience members for Customer Match or mobile device ID lists.
  • When integrating the Data Manager API into your application for audience management.
  • When troubleshooting ingestion failures or verifying the status of an asynchronous request.
  • When refactoring existing code from older Google APIs to the Data Manager API.

Advantages

  • Standardizes the approach for managing audience data across different Google destinations.
  • Reduces errors by providing clear guidance on required fields and data formatting.
  • Ensures robust error handling through diagnostic polling and status inspection.
  • Provides direct access to language-specific code samples and migration field mappings.

Usage examples

“How do I upload a list of hashed emails to a Google Ads Customer Match audience?”
The agent will guide you through initializing the IngestionServiceClient, formatting the emails using the utility library, constructing an IngestAudienceMembersRequest, and checking the request status.
“I need to remove all members from an existing DV360 audience. What is the process?”
The agent will provide the steps to construct a RemoveAllAudienceMembersRequest, specify the correct destination, and execute the removal via the Data Manager API.
“How can I check if my audience ingestion request was successful?”
The agent will explain how to use the returned request_id to poll the retrieve_request_status endpoint and interpret the resulting status and diagnostic fields.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/google/data-manager-api-audience-ingestion/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip data-manager-api-audience-ingestion.zip -d .agents/skills

Documentation by Google

Data Manager API Audience 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.

  • Audience Creation (if needed): If the user does not have an existing audience or needs to create a new one, use the Create an Audience reference. This step provides the product_destination_id needed for the ingestion or removal requests.

Step 1: Identify Use Case & Read Documentation
  • Determine Destination Account Type: [CRITICAL] If it's not clear where the data is being sent (e.g., Google Ads, Display & Video 360, etc.), STOP and CLARIFY with the user 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.

  • Read the implementation guide: Read the relevant guide for your destination and use case. Do this before answering questions or writing code because each destination has unique payload structures, consent rules, and required fields.

DestinationAudience TypeAccepted Data TypesUpload GuideRemove All/Replace All Guide
Google AdsCustomer Matchcomposite_data.user_data (contact info), mobile_data (device IDs), user_id_data (user IDs)Upload DataRemove All/Replace All
Display & Video 360 (DV360)Customer Matchcomposite_data.user_data (contact info), mobile_data (device IDs)Upload DataRemove All/Replace All
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
Display & Video 360
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.

  • [ ] Format User Data: If sending an IngestAudienceMembersRequest or RemoveAudienceMembersRequest, refer to Formatting User Data to properly normalize and hash user identifiers using the utility library.

  • [ ] Construct Payload: Build the appropriate request payload based on the operation:

    • Add: IngestAudienceMembersRequest

    • Remove: RemoveAudienceMembersRequest

    • Remove All: RemoveAllAudienceMembersRequest

  • [ ] Support Validation: Support sending the validate_only boolean option on the payload to allow developers to validate schemas without actually applying changes.

  • [ ] Send Request: Execute the appropriate method and record the returned request_id for later diagnostics:

    • Add: ingest_audience_members

    • Remove: remove_audience_members

    • Remove All: remove_all_audience_members

  • [ ] Check for Ingestion Warnings: If any non-required field had a validation failure, the response from ingest_audience_members 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 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 client.retrieve_request_status using the request_id. Skipping this step is a common user mistake.

Critical Gotchas

  • If sending hashed user identifiers in user_data for ingest_audience_members or remove_audience_members, you must set the encoding field on the IngestAudienceMembersRequest to HEX or BASE64.

  • If uploading to a Customer Match audience, the terms_of_service field is required on the IngestAudienceMembersRequest to indicate the user has accepted the policies.

  • Only set the address field on UserIdentifier if all required fields (postal_code, family_name, given_name, region_code) are present; incomplete address fields will cause the API request to fail.

  • product_destination_id must be a numeric string. It is NOT a resource name.

  • The enum values for ConsentStatus are CONSENT_GRANTED and CONSENT_DENIED. Do not use the values GRANTED and DENIED.

  • Field names on UserIdentifier are email_address and phone_number. Do not use the Google Ads API field names hashed_email and hashed_phone_number.

  • 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 request.

  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:

    • Audience Status: Check the status specific to your request:

      • Ingest: Check the data-type-specific status nested under audience_members_ingestion_status (e.g., composite_data_ingestion_status).

      • Remove Individual Members: Check the data-type-specific status nested under audience_members_removal_status (e.g., composite_data_removal_status).

      • Remove All Members: There are no nested status fields or record counts available to check for this request type.

      • Record Count: If applicable (ingest or remove individual members), check record_count (nested inside the data-type-specific status object) which includes both success and failure.

      • Identifier Counts: If applicable (ingest or remove individual members), check the data-type-specific count field nested inside the status object (e.g., data_type_counts if uploading or removing composite data, or mobile_id_count if uploading or removing mobile IDs). Refer to the Diagnostics Guide for other count fields.

      • Match Rate Range: For uploads of user_data and composite_data, check upload_match_rate_range nested inside the status object.

    • 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

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python, Needs Node.js

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Attribution and licence

Published by
Google
Publisher
Google (Official)
Source
google/skills · skills/ads/data-manager-api-audience-ingestion · commit 2194d3b
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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