Cloud Engineering

Google Cloud Platform:

 

Hi my name is Scott Becker and I  have experience setting up Google BigQuery to gather data from multiple platforms, including GA4, Google Ads, and YouTube Analytics. My goal is to provide a single-pane-of-glass view of the data to make data-driven decisions. I will detail the steps I take to set up BigQuery, perform queries on the data, and export the results to Looker Studio to create a compelling dashboard.

The first step is to connect BigQuery to the data sources. I use the Google Analytics and Google Ads APIs to extract data from these platforms and load it into BigQuery.

For YouTube Analytics, I use the YouTube API to extract data on video performance. Once the data was loaded into BigQuery, I am able queries on the data, providing a more in-depth analysis of the metrics.

Next, I perform queries on the data to gain insights into the performance of my digital marketing campaigns. For example, I am able to combine data from Google Analytics and Google Ads to see which ads are driving the most traffic to the website, and which pages on the site are converting the most visitors into customers. I also use BigQuery to analyze the performance of individual video campaigns on YouTube, giving my clients valuable insights into their video marketing strategies.

One of the key benefits of BigQuery is that it allows for the extraction of large amounts of data quickly, providing insights in near real-time. This is particularly useful for my clients who need to make quick decisions based on their data.

To further enhance the insights I am able to provide to my clients, I export the results of my queries to Looker Studio. Looker Studio is a powerful data visualization tool that allows me to create compelling dashboards that display the metrics that matter most to my clients in a single, easy-to-understand view.

For each platform, I am able to select the dimensions that are most important for my clients. For Google Analytics, some of the dimensions I include are user location, device type, and pageviews. For Google Ads, I include metrics such as ad spend, clicks, and conversions. For YouTube Analytics, I include metrics such as views, watch time, and engagement.

By combining the data from multiple platforms, I am able to provide my clients with a more comprehensive view of their digital marketing performance. The dashboards I create in Looker Studio display a combined view of the key metrics, providing my clients with a clear understanding of the performance of their campaigns and the areas where improvements can be made.

Setting up Google BigQuery to gather data from Google Analytics, Google Ads, and YouTube Analytics provides my clients with valuable insights into their digital marketing performance. The ability to perform complex queries on the data, and export the results to Looker Studio to create compelling dashboards, allows me to provide a single-pane-of-glass view of the data, making it easier for my clients to make data-driven decisions.

 

What is Google Big Query and what are the advantages of using it for digital marketing?

Google Big Query is a cloud-based data warehouse and analytics platform that allows businesses to store, query, and analyze large volumes of data. It is designed to handle complex queries and support a wide range of data types, making it a powerful tool for digital marketing.

Some of the advantages of using Google Big Query for digital marketing include:

  1. Scalability: Google Big Query can easily scale up or down to meet the changing needs of your business, making it ideal for digital marketing where data volumes can fluctuate rapidly.
  2. Speed: Google Big Query is designed to handle large volumes of data and support complex queries, making it possible to quickly access and analyze the data you need for your digital marketing efforts.
  3. Integration: Google Big Query can easily integrate with other tools and systems, such as Google Analytics and Google Ads, to provide a more comprehensive view of your data and help inform your digital marketing decisions.
  4. Cost-effectiveness: Google Big Query is a pay-as-you-go service, which means you only pay for the resources you use. This can be more cost-effective than on-premises solutions that require upfront costs for hardware and software.

Google Big Query is a powerful tool for digital marketing that can help improve the performance, scalability, and cost-effectiveness of your data management and analysis efforts.

 

The Benefits of Using Cloud Data Warehouse

Please call / text 469-751-2933 or email support@xldigitalmedia.com for more information and to get a reasonable price quote based on the requested services. (Note – Prices may vary depending on the size of company, amount & frequency of services requested.)

 

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