Connect Google Ads to BigQuery

Quickly integrate Google Ads with BigQuery using Windsor.ai’s ELT connectors to centralize your data and generate automated reports.

Use these insights to fine-tune your strategy and optimize your advertising budgets, eliminating wasteful spending and increasing your returns on investment.

Forget CSVs. Stop copy/paste. Connect data in 2 minutes. No code required.

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Windsor.ai is your proven Google Ads to Google BigQuery connector

Analyze ad performance at scale with Google Ads to BigQuery integration

Windsor.ai extracts, transforms, and loads Google Ads data into BigQuery, offering advanced analytics and data modeling tools to manage your ad data efficiently. This integration delivers the following benefits:

Data centralization

Data centralization

You can use Windsor.ai to sync your Google Ads data with other business data in BigQuery, creating a single source of truth. This centralization streamlines data management and ensures anytime, anywhere access to all your information.

Automated data transfer

Automated data transfer

Our no-code connectors automatically import Google Ads data into BigQuery, eliminating manual input and saving you hours of work. With real-time updates, you can always access the latest ad performance data and make timely, data-driven optimizations.

Advanced data modeling

Advanced data modeling

Google BigQuery enables structured and scalable access to your ad data, allowing you to generate consistent, actionable reports across campaigns. Use these insights to refine ad targeting, adjust bid strategies, and optimize your budgets for better ROIs.

Robust analytics and reporting tools

Robust analytics and reporting tools

Leverage BigQuery’s built-in analytics and reporting tools to gain deeper insights into your Google Ads results. With Windsor.ai’s integration, you can easily run custom queries, visualize data, and automate reports to uncover trends and identify growth opportunities.

Using Windsor.ai connector to import data from Google Ads into BigQuery

While most methods for syncing Google Ads data with BigQuery can be complex, costly, and often require specialized technical knowledge, Windsor.ai simplifies this process with a codeless, user-friendly ELT connector.

In just a few clicks, you can import your Google Ads data directly into BigQuery, eliminating the need for manual data preparation, formatting, and transfers.

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Join over 3,000 businesses that trust Windsor.ai to streamline Google Ads to BigQuery integration
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How to connect Google Ads to BigQuery in Windsor.ai

Make sure you have the following prerequisites before setting up the connector:

  • Google Ads account with API access and API credentials
  • Google Cloud Platform (GCP) account with BigQuery enabled
  • Active Windsor.ai account
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How to connect Google Ads to BigQuery manually

Manually integrating Google Ads with BigQuery involves multiple steps, including API setup, data extraction, transformation, and loading. While this approach requires technical expertise, it provides full control over the data pipeline.

Windsor.ai offers a seamless alternative by automating the entire process, eliminating the need for manual scripts, ensuring real-time data synchronization, and reducing errors.

However, if you prefer a manual integration, follow this step-by-step guide to extract Google Ads data via the Google Ads API and load it into Google BigQuery.

Prerequisites

Before proceeding with the manual integration, ensure you have the following:

  • A Google Ads account with API access enabled.
  • Google Ads API credentials (Developer Token, Client ID, Client Secret, and Refresh Token).
  • A Google Cloud Platform (GCP) account with BigQuery enabled.
  • A Service Account with the necessary permissions for BigQuery.

Step 1. Set up Google Ads API

1. Enable Google Ads API access:

2. Create API credentials:

  • Go to Google Cloud Console → APIs & Services → Credentials.
  • Create an OAuth 2.0 Client ID for API authentication.
  • Generate a Refresh Token to access the Google Ads API using the created credentials via the cloud.

3. Get required credentials:

  • Developer Token from Google Ads API Console.
  • Client ID and Client Secret from Google Cloud Console.
  • Refresh Token from Google OAuth Authentication.
  • Google Ads Customer ID for data extraction from Google Ads account.

Step 2. Extract Google Ads data

Use the Google Ads API to fetch campaign data. The API query language Google Ads Query Language (GAQL) allows you to retrieve relevant insights.

1. First, get the Access Token needed to authorize the Google Ads API request. You can get it using the following API call.

curl \
–data “grant_type=refresh_token” \
–data “client_id=CLIENT_ID” \
–data “client_secret=CLIENT_SECRET” \
–data “refresh_token=REFRESH_TOKEN” \
https://www.googleapis.com/oauth2/v3/token

2. You can extract Google Ads data by using Google Ads API. You can edit the query to get what data you want from the API.

curl -i -X POST https://googleads.googleapis.com/v18/customers/CUSTOMER_ID/googleAds:searchStream \ -H “Content-Type: application/json” \ -H “Authorization: Bearer ACCESS_TOKEN” \ -H “developer-token: DEVELOPER_TOKEN” \ -H “login-customer-id: LOGIN_CUSTOMER_ID” \ –data-binary ‘{ “query”: “SELECT campaign.id, campaign.name, metrics.impressions, metrics.clicks, metrics.conversions FROM campaign WHERE segments.date DURING LAST_30_DAYS” }’

You’ve set up Google Ads API and got your campaign data. Now, let’s get this data in the BigQuery table.

Step 3. Set up Google BigQuery

1. Enable BigQuery API:

  • Go to the Google Cloud Console.
  • Select your project or create a new one.
  • Navigate to APIs & Services -> Library.
  • Search for BigQuery API and click Enable.

2. Create a BigQuery Dataset and Table:

  • Go to the BigQuery Console.
  • Click on your project in the left panel.
  • Click Create Dataset and provide a name.
  • Click Create Table inside the dataset.
  • Define the schema based on your data structure.

3. Create a Service Account for BigQuery:

  • Navigate to IAM & Admin -> Service Accounts.
  • Click Create Service Account.
  • Assign BigQuery Admin role.
  • Click Create Key and select JSON format.
  • Download the key file for authentication.

Step 4. Load data into BigQuery

1. You can upload the data to the BigQuery table using the BigQuery API URL.

Here is a sample API URL that is called via the curl command. Replace {PROJECT_ID}{DATASET_ID}, and {TABLE_ID} with your actual BigQuery details and “google_ads_data.json” file with your ads data file.

curl -i -X POST https://googleads.googleapis.com/v18/customers/CUSTOMER_ID/googleAds:searchStream \ -H “Content-Type: application/json” \ -H “Authorization: Bearer ACCESS_TOKEN” \ -H “developer-token: DEVELOPER_TOKEN” \ -H “login-customer-id: LOGIN_CUSTOMER_ID” \ –data-binary ‘{ “query”: “SELECT campaign.id, campaign.name, metrics.impressions, metrics.clicks, metrics.conversions FROM campaign WHERE segments.date DURING LAST_30_DAYS” }’

2. You can go to your GCP console and query the data from your BigQuery table to verify that Google Ads data is present.

Cheers, you’ve sent your Google Ads data to Google BigQuery!

FAQs

What is Google Ads?

Google Ads is a leading online advertising platform that allows businesses to create and display advertisements across Google’s network, including search results, high-traffic websites, and apps. The platform operates primarily on a pay-per-click (PPC) model, where advertisers bid for ad placements and pay only when users click on their ads.

Google Ads also provides comprehensive targeting options, allowing advertisers to reach their audience based on factors like location, keywords, demographics, and user behavior. Additionally, the platform integrates seamlessly with other Google services, such as Google My Business and Google Analytics, giving you a more detailed look into the performance of your ad campaigns.

Popular Google Ads integrations

Import your Google Ads data into any destination using Windsor.ai.

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Tired of manual Google Ads data exports? Get started with Windsor.ai today to automate your reporting

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