Google Cloud BigQuery (REST) and Google Ads Integration

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Google Cloud BigQuery (REST)

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Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Cloud BigQuery (REST) and Google Ads

Create a New Scenario to Connect Google Cloud BigQuery (REST) and Google Ads

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud BigQuery (REST), triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery (REST) or Google Ads will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or Google Ads, and select the appropriate trigger to start the scenario.

Add the Google Cloud BigQuery (REST) Node

Select the Google Cloud BigQuery (REST) node from the app selection panel on the right.

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Configure the Google Cloud BigQuery (REST)

Click on the Google Cloud BigQuery (REST) node to configure it. You can modify the Google Cloud BigQuery (REST) URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Run node once

Add the Google Ads Node

Next, click the plus (+) icon on the Google Cloud BigQuery (REST) node, select Google Ads from the list of available apps, and choose the action you need from the list of nodes within Google Ads.

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Authenticate Google Ads

Now, click the Google Ads node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Ads settings. Authentication allows you to use Google Ads through Latenode.

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Configure the Google Cloud BigQuery (REST) and Google Ads Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Run node once

Set Up the Google Cloud BigQuery (REST) and Google Ads Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Google Cloud BigQuery (REST), Google Ads, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud BigQuery (REST) and Google Ads integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Google Ads (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Google Cloud BigQuery (REST) and Google Ads

Google Cloud BigQuery + Google Ads + Google Sheets: Analyzes Google Ads spend data from BigQuery. The analyzed data is then used to generate a report using Google Ads, which is subsequently added to a Google Sheet for tracking performance.

Google Cloud BigQuery + Google Ads + Slack: Analyzes Google Ads campaign performance using BigQuery. If a campaign is underperforming based on the analysis, a notification is sent to a designated Slack channel.

Google Cloud BigQuery (REST) and Google Ads integration alternatives

About Google Cloud BigQuery (REST)

Automate BigQuery data workflows in Latenode. Query and analyze massive datasets directly within your automation scenarios, bypassing manual SQL. Schedule queries, transform results with JavaScript, and pipe data to other apps. Scale your data processing without complex coding or expensive per-operation fees. Perfect for reporting, analytics, and data warehousing automation.

About Google Ads

Use Google Ads in Latenode to automate campaign management and reporting. Pull ad performance data, adjust bids based on real-time events, or trigger alerts for budget changes. Combine with other apps to build custom marketing workflows. Latenode's flexibility avoids rigid, pre-built integrations and costly per-step pricing.

See how Latenode works

FAQ Google Cloud BigQuery (REST) and Google Ads

How can I connect my Google Cloud BigQuery (REST) account to Google Ads using Latenode?

To connect your Google Cloud BigQuery (REST) account to Google Ads on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Google Cloud BigQuery (REST) and click on "Connect".
  • Authenticate your Google Cloud BigQuery (REST) and Google Ads accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automate ad performance reporting using BigQuery data?

Yes, you can! Latenode lets you automate reports by analyzing BigQuery data and updating Google Ads, saving time and improving campaign optimization with scheduled workflows.

What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Google Ads?

Integrating Google Cloud BigQuery (REST) with Google Ads allows you to perform various tasks, including:

  • Automatically updating Google Ads campaigns based on BigQuery data analysis.
  • Creating custom audiences in Google Ads using BigQuery customer data.
  • Analyzing ad spend and performance data stored in BigQuery.
  • Generating reports on ad campaign ROI using combined data sources.
  • Triggering Google Ads actions based on real-time BigQuery data insights.

HowdoesLatenodehandlelargeBigQuerydatasetsforGoogleAdsautomation?

Latenode efficiently handles large datasets via optimized data processing, ensuring seamless automation even with extensive BigQuery data for Google Ads.

Are there any limitations to the Google Cloud BigQuery (REST) and Google Ads integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Complex queries in BigQuery might require optimized configurations for optimal performance.
  • Real-time data updates are subject to Google Ads API rate limits.
  • Some advanced BigQuery data types might require transformation for use in Google Ads.

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