5 advantages of using BigQuery alongside GA4

You can export all event data from GA4 properties to BigQuery free of charge, up to a limit of 1M hits/day (free version of GA4).

⚠️ Data access is not retroactive, so you need to open an instance before you can collect data in BigQuery.

In BigQuery, you can import external data from other sources, such as CRM data, and combine it with your Google Analytics data, using SQL-like syntax to query the data for advanced reporting beyond sampling and quota limits.

This lets you create audience segments, explore personalized traffic attribution, and build simple machine learning models for reporting and audiences.

Integrate other data sources

BigQuery is compatible with many other platforms, such as advertising, CRM and affiliate platforms. This means you can import various types of data into BigQuery, turning it into a veritable data lake. This means you can combine GA4 data with other data sources to get a complete view of your business and make informed strategic decisions.

Create audience segments

With the integration of GA4 and BigQuery, you can create sophisticated, personalized audience segments. By combining online behavior data from GA4 with other data sources in BigQuery, you can target very specific audiences. These segments can be used for targeted marketing campaigns, improving customer engagement and increasing campaign ROI.

Explore customized attribution models

Using GA4 and BigQuery together, you can explore personalized attribution models, essential for understanding the customer journey. With BigQuery, you can analyze in depth the effectiveness of different channels and touchpoints, identifying which contribute most to conversion. This enables more precise attribution of sales and conversions, helping to optimize marketing and advertising strategies.

Exploiting Machine Learning models (BQML)

BigQuery ML (BQML) lets you create and run machine learning models directly within BigQuery. This integration facilitates predictive analysis and behavioral segmentation, without requiring advanced data science skills. So you can predict consumer trends, identify the most valuable customer segments, and optimize marketing campaigns based on predictions generated by BQML.

Other benefits of GoogleBigQuery

Benefit from faster processing times

Google BigQuery is designed to process large amounts of data quickly, making it particularly useful for executing advanced SQL queries. Its speed of execution makes it possible to extract information quickly, even from large datasets.

No infrastructure to manage

BigQuery lets you store and query unlimited amounts of data, without having to set up your own servers. The tool itself manages its infrastructure needs. This allows users to concentrate on data analysis and processing.

Flexible pricing

BigQuery is a big data storage and processing service offered by Google Cloud Platform. It can store and analyze large quantities of data, making it an ideal solution for creating a data warehouse.

Google BigQuery offers a flexible pricing structure based on data usage. Costs depend on several factors, including:

• the amount of data stored ;

• the amount of data processed ;

• and the type of queries executed (inserting continuous data into BigQuery is free, but reading continuous data is charged according to the number of GB read).

Google offers a free monthly allowance of 10 GB of data storage, as well as 1 TB of data processing per month. So, for the majority of small and medium-sized businesses, BigQuery is free to use. So you have everything to gain by implementing this solution.

Avoiding GA4 API quota limits on Google Looker Studio

On November 10, 2022, Google modified its API limits by implementing "quotas"These were implemented via a connector between GA4 and Looker Studio, Google's graphical dashboard and reporting tool. What initially appeared to be a temporary problem in Looker Studio turned out to be the result of changes made in Google Analytics 4 with the use of connection APIs. As a result, all Looker Studio dashboards using connectors such as the GA4 API, but also others such as Supermetrics, for example, are seeing their dashboards affected with data display and loading problems.

By exporting raw analytics data from GA4 to BigQuery, you solve the problem of limited queries. The export is done directly, making all your data available and guaranteeing fast loading of reports.