Google Ads to BigQuery: 2 Easy Methods

on Tutorial • September 15th, 2021 • Write for Hevo

Google Ads is one of the modern marketer’s favorite channels to grow the business. If you are someone who has even glanced at the Google Ads interface would know that Google provides a gazillion data points to optimize and run personalized ads. The huge amount of diverse data points available makes performance tracking a complex and time-consuming task.

Well, the complexity increases further when Businesses want to build a 360 degree understanding of how Google Ads fare in comparison to the other marketing initiatives (Facebook Ads, LinkedIn Ads, etc.). To enable a detailed, convoluted analysis like this, it becomes important to extract and load the data from all the different marketing platforms used by a company to a robust cloud-based Data Warehouse like Google BigQuery. This blog talks about the different approaches to use when loading data from Google Ads to BigQuery

Table of Contents

Introduction to Google Adwords

Google Ads is an advertising system that allows marketers and advertisers to bid on specific words that are related to their business and showcase clickable ads on Google’s search results or partner network. They provide a wide array of options in terms of the advertisement content, visuals, and personalization configuration so that businesses can target the right audience, at the right time with the right ad. Given the flexibility, robustness and reach this medium drives, Google Ads has emerged as one of the most popular advertising platforms for businesses. 

Introduction to Google BigQuery

Google Ads to BigQuery- Google BigQuery Logo
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Google BigQuery is a cloud-based Data Warehouse service introduced by Google in 2011. The Data Warehouse solution offers super-fast SQL query resolution – bringing down the query periods from hours (using a service like Hadoop) to just a few seconds. It takes off the complete burden of managing and monitoring a data warehouse infrastructure enabling companies to focus on the analytics aspect. 

Methods to Move Data from Google Ads to BigQuery

Method 1: Using BigQuery Data Transfer Service to Connect Google Ads to BigQuery

BigQuery offers an in-built data connector service for transferring data from Google Ads (and a few more Google products). The biggest drawback of this approach is that implementing this requires a Business, Enterprise, or Education G-suite account. Additionally, this would need you to deploy engineering resources.

Method 2: Using Hevo Data to Connect Google Ads to BigQuery

Using Hevo Data Using a fully integrated, ready-to-use data integration platform like Hevo would allow you to save time and tech resources on building and maintaining a data infrastructure. Hevo can reliably and consistently deliver recent data from free data sources like Google Ads, etc., in real-time.

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Methods to Connect Google Ads to BigQuery

Here are the methods you can use to establish a connection from Google Ads to BigQuery in a seamless fashion:

Method 1: Using BigQuery Data Transfer Service to Connect Google Ads to BigQuery

Before you begin this process, you would need to create a Google Cloud project in the console and enable BigQuery’s API. Also, you need to enable billing on your Google Cloud project. This is a mandatory step that needs to be executed once per project. In case you already have set up a project, you would only need to enable the BigQuery API. 

  1. On the BigQuery platform, hit the “Create a Dataset” button and fill out the Dataset ID and Location fields. This will create a dedicated space for storing your  Google Ads data.
  2. Next, enable BigQuery Data Transfer Service from the web UI. Note – you would need to have admin access to transfer and update the data. 
  3. Click on the “Add Transfer” button. Select “Google Ads” in the source and destination dataset. 
  4. BigQuery’s data connector allows you to set up refresh windows (the max offered is 30 days) and a schedule to export the Google Ads data.
  5. Now, enter your Google Ads Customer ID or Manager Account (MCC).
  6. Next, allow the ‘Read’ access to the Google Ads Customer ID. This is needed for the transfer configuration.
  7. It is generally a good practice to opt for email notification in case a loading failure occurs.

Despite this being a native integration with two products available from Google, there are a few limitations that make companies look out for other options. 

Limitations of using BigQuery Data Transfer Service to Connect Google Ads to BigQuery

  • BigQuery Data Transfer Service supports a maximum of 180 days per data backfill request. This means you would have to manually transfer any historical data.
  • Since the business teams that need this data are not very tech-savvy, using this approach would necessarily mean that a company would need to invest tech bandwidth to move data. This is an expensive affair. 
  • While transferring data, you need to remember that BigQuery doesn’t allow joining datasets saved in different location servers later. So, always create datasets in the same locations across your project. Hence, you need to be careful initially while setting up as there’s no option to change the location later. 
  • Say you want to convert the timestamp in the data from UTC to PST, such modifications are not supported on the BigQuery Transfer service. 
  • BigQuery transfer service can only bring data from Google products into BigQuery. In the future, in case you want to bring data from other sources such as Salesforce, Mailchimp, Intercom, and more, you would need to use another service.

Method 2: Using Hevo Data to Connect Google Ads to BigQuery

Google Ads to BigQuery-Hevo logo
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Hevo works out of the box with both Google Ads and BigQuery. This makes the data export from Google Ads to BigQuery a cakewalk for businesses. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.

With Hevo’s point-and-click interface, you can load data from Google Ads to BigQuery in just two steps: 

  • Step 1: Configure the Google Ads data source by providing required inputs like the Pipeline Name, Select Reports, and Select Accounts.
Google Ads to BigQuery: Configure Source
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Step 2: Configure the BigQuery destination where the data needs to be loaded by providing details like Destination Name, Dataset ID, Project ID, GCS Bucket, Enable Streaming Inserts, and Sanitize Table/Column Names.

Google Ads to BigQuery: Destination Settings
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Once this is done, your data will immediately start moving from Google Ads to BigQuery.

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The Hevo Advantage

  1. Low Time to Insights – Hevo is a no-code platform and can be set up in just a few clicks. This means you will have analysis-ready data in your BigQuery data warehouse in a matter of a few minutes. 
  2. Zero Data Loss – Hevo’s fault-tolerant architecture and advanced algorithms reliably and securely deliver data into BigQuery.
  3. Transformations: Hevo provides preload transformations through Python code. It also allows you to run transformation code for each event in the pipelines you set up. You need to edit the event object’s properties received in the transform method as a parameter to carry out the transformation. Hevo also offers drag and drop transformations like Date and Control Functions, JSON, and Event Manipulation to name a few. These can be configured and tested before putting them to use.
  4. Connectors: Hevo supports 100+ integrations to SaaS platforms such as Salesforce, files, databases, analytics, and BI tools. It supports various destinations including Salesforce CRM, Google BigQuery, Amazon Redshift, Firebolt, Snowflake Data Warehouses; Amazon S3 Data Lakes; and MySQL, MongoDB, TokuDB, DynamoDB, PostgreSQL databases to name a few.  
  5. Automatic Schema Handling – Hevo detects any schema changes that occur on Google Analytics as a source and automatically map, and update this on BigQuery without any manual interference needed.
  6. Alerts and Monitoring – Hevo monitors your data flow and user activity. Hevo will promptly notify you of any loading failures, schema changes, user activities, and more.
  7. Robust Data Transformations – Hevo comes with an inbuilt data transformation feature that allows you to modify data both before and after loading to BigQuery as per your use case.
  8. 24X7 Support – Hevo has a dedicated support team that is available to resolve queries at your beck and call. 

As a business that spends hefty amounts on Google Ads, getting accurate data and insights from your Google Ads accounts is crucial. Hevo ensures that the data in your BigQuery warehouse is always accurate, correct, and reliable. 

Conclusion

This blog talks about the different methods you can use to establish a connection from Google Ads to BigQuery in a seamless fashion: using BigQuery Data Transfer Service and a third-party tool, Hevo.

Apart from providing data integration in Google Ads for free, Hevo enables you to move data from a variety of data sources (Databases, Cloud Applications, SDKs, and more). These include products from both within and outside of the Google Suite.

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Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.

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