What data can move from Google BigQuery to Google Ads?

The exact coverage depends on Google BigQuery connector support, account permissions, selected records and fields, retained history, identity rules, consent, and the Google Ads mapping confirmed for the workflow.

How often can Google BigQuery data update in Google Ads?

The cadence is agreed during setup and depends on source API limits, provider latency, destination limits, data volume, and whether the workflow needs event-driven, scheduled, batch, or historical delivery.

Does Vendo control what Google Ads does with the data?

No. Vendo prepares and delivers the configured data. Google Ads retains control of its own analysis, campaigns, audiences, messages, storage, consent, and destination behavior.

Google BigQuery

Vendo

Google Ads

Google BigQuery → Vendo → Google Ads

Integration guide

Connect Google BigQuery to Google Ads

Connect Google BigQuery to Google Ads through Vendo. Use governed Google BigQuery outcomes to prepare conversion signals and eligible audiences for Google Ads. Your team confirms the supported data, identifiers, consent, history, schedule, and destination behavior before production use.

Book a Discovery Call Google BigQuery details Google Ads details

Problem and fit

Use Google BigQuery and Google Ads as one connected workflow.

This workflow is useful when your team needs supported data from Google BigQuery to be available alongside or inside Google Ads. The connection still needs an agreed schema, stable identifiers, permissions, consent rules, and a clear policy for late, duplicate, rejected, and historical records.

Before you connect

What Google BigQuery and Google Ads data the workflow uses

Which mappings, identifiers, permissions, and consent rules need to be confirmed

Which problems the connection may help solve

Which limits must be tested before production use

Vendo handles the connection between both tools.

1. Connect Google BigQuery and Google Ads

Authorize both tools with the account access and permissions required for the agreed workflow.

2. Map Google BigQuery data

Choose supported Google BigQuery records and fields, then map them to the documented Google Ads schema, identity, and consent requirements.

3. Validate the Google Ads workflow

Test representative records, review unmatched, duplicate, late, and rejected data, and confirm the destination behavior before production use.

Move the right context between both platforms.

Supported Google BigQuery data such as Page Viewed, Order Completed, Product Purchased, User Profiles (Identify)

Mapped Google Ads events, profiles, audiences, or tables supported by the destination workflow

Stable identifiers, consent fields, and deduplication keys required by the agreed mapping

Historical and incremental data within source API, retention, and destination limits

Put the connection to work.

Send Google BigQuery conversion signals to Google Ads

Map approved server-side outcomes and available click identifiers to the destination conversion contract.

Activate Google BigQuery audiences in Google Ads

Build governed customer groups and sync only eligible identifiers under the agreed consent and refresh rules.

Improve campaign measurement

Compare destination responses, rejected records, attribution windows, and reporting differences before optimizing campaigns.

Go deeper on the workflow.

Google BigQuery details

Open page

Google Ads details

Open page

Use cases hub

Open page

Attribution methodology

Open page

Signal recovery methodology

Open page

Value-based bidding methodology

Open page

FAQ

Frequently Asked Questions

Request Access

Check whether Vendo fits your current setup.

Bring the tools you use and one recurring data problem. We will explain what Vendo can handle, what setup is required, and any current limits.

Book a Discovery Call