Google Analytics is a popular choice for tracking and analyzing user behavior. While Google Analytics provides a wealth of data, extracting and exporting this information for further analysis or reporting can often present challenges. This article explores five effective methods for exporting Google Analytics data at no cost. Whether you need to export Google Analytics data to CSV files, Google Sheets, BigQuery, or other formats, we will discuss various techniques to help you extract and use your Google Analytics data efficiently. Keep reading to discover how to export and utilize your Google Analytics data efficiently.

Introduction to Export Possibilities of Google Analytics 4 Data

Google Analytics 4 (GA4) allows users to export data from their properties through various methods. Exporting GA4 data allows for greater flexibility in accessing and utilizing the valuable insights from GA4. By exporting data from your GA4 property, you can harness its full potential and derive actionable strategies for your business or website. The export possibilities of GA4 data open up opportunities for in-depth analysis and informed decision-making. Whether you prefer to export data for further analysis in third-party tools or for archival purposes, GA4 offers a range of methods to suit your specific needs and preferences.

Benefits of exporting Google Analytics 4 data

Exporting data from Google Analytics 4 offers several benefits for businesses looking to improve their digital marketing strategies and online performance. Here are some key advantages:

• Integrating GA4 data with Other Tools: Exported data can be easily integrated with data from other tools and platforms for further analysis or visualization. This includes combining Google Analytics 4 data with CRM systems, data visualization tools, or business intelligence platforms to gain a comprehensive view of online performance.
• Data Backup and Security: Exporting Google Analytics 4 data provides businesses with a backup of valuable information, especially with GA4’s 14-month data retention settings. Businesses can retain historical GA4 data beyond this period with the data export option.
• Enhanced Data Sharing: Exported data can be shared with stakeholders, team members, or external partners, fostering collaboration and facilitating decision-making. By exporting data to accessible formats like CSV or Google Sheets, key insights can be easily shared and understood by all relevant parties.
• Advanced Data Processing: Exporting Google Analytics 4 data to platforms like BigQuery enables businesses to perform advanced data processing, such as data mining, machine learning, and predictive analytics. This allows businesses to uncover hidden patterns and insights that drive strategic decision-making.

Overall, exporting Google Analytics 4 data empowers businesses to unlock the full potential of their GA4 data, gain valuable insights, and make informed decisions to optimize digital marketing efforts and achieve business goals.

Method #1: Export Google Analytics 4 Data via GA4 Interface as CSV, EXCEL Files

This method is suitable for users who do not require real-time data updates and wish to export GA4 data for specific analysis purposes.

In Google Analytics 4, you can export GA4 data as a CSV/Excel file through its interface from the standard report or through GA4 explorations. Let’s explore these methods in detail below.

How to export GA4 data in Standard Reports

You can download GA4 data as a CSV file in GA4 standard reports. The steps for this process are as follows:

1. Click on the “Share this report” icon.
2. Choose “Download file.”
3. Select “Download CSV.”

How to export GA4 data in Explorations

You can also export your GA4 data as a CSV file using GA4 Explore. First, create your exploration report. Then, click the download button at the top right of the report and select CSV. Your data will be exported as a CSV file. If you’re unsure about how to create an exploration report, don’t worry. Please check our detailed article for guidance.

Method #2: Export Google Analytics 4 data to Google Sheets

You can export your GA4 data to Google Sheets manually or automatically. Let’s explore the details of these methods below.

How to export GA4 data to Google Sheets manually

You can export GA4 data manually through the GA4 interface using any of the default GA4 reports or a GA4 exploration report. It’s almost the same steps as downloading a CSV file. The steps for this process are as follows:

1. Click on the “Share this report” icon.
2. Choose “Download file.”
3. Select “Download Google Sheets.”

How to export GA4 data into Google Sheets automatically using Google Sheets Add-ons

To automatically export GA4 data into Google Sheets, you can use the GA4 Report Builder for Google Analytics Add-on created by Google or the GA4 Magic Reports Add-on, created by Michele Pisani. Both add-ons are free and offer similar functionalities for connecting to GA4, exporting GA4 data and scheduled refresh. However, the GA4 Magic Reports Add-on provides additional features, such as the ability to sort and filter data during the report creation setup, which is unavailable in the Google Sheets Connector Add-on. If you’d like to learn more, we have a detailed article on how to export GA4 data to Google Sheets.

Now, let’s look at how to export GA4 data to the GA4 Report Builder for Google Analytics. The steps include installing the add-on, creating (configuring) a report, and then running the Report.

To install the GA4 Report Builder for Google Analytics Add-on on Google Sheets, follow these steps:

1. Open a new Google Sheets document.
2. Click on the Extensions tab on the spreadsheet, then select Add-ons and click on Get Add-ons to navigate to the Google Marketplace. Search for the GA4 Report Builder for Google Analytics Add-on,  click the Install button to install it.

To create a new report using the GA4 Report Builder for the Google Analytics Add-on, follow these steps:

1. Open a new Google Sheet file and go to the extensions menu.
2. Click on the add-on and select “Create New Report.”
3. In the new window that appears, enter the required details such as the GA4 Account name, property, date, dimensions, and metrics, and then click the “Create Report” button.

To run the report:

Navigate to the Add-on in the extensions tab and select the “run report” option. This will generate a new tab containing the data using the name of the report you entered in the previous step.

Once your report is created, you can analyze and visualize your data as needed and schedule the frequency of the reports.

Method #3: Exporting Google Analytics 4 data into BigQuery

BigQuery is a cloud data warehouse developed by Google. Simply, it’s a platform for storing data in a tabular format and querying it using SQL. To export your GA4 data to BigQuery, you need to integrate your GA4 account with BigQuery.

Integrating your GA4 account with BigQuery unlocks two significant benefits. First, it liberates your access to raw data, eliminating the constraints of the GA4 interface. This raw data access empowers you to develop machine-learning models or use the data for more accurate forecasting. Secondly, BigQuery’s real-time analytics capability overcomes GA4’s data freshness issues, enabling you to visualize and act on your data faster than relying solely on the GA4 interface.

Integrating BigQuery and GA4 is a cost-effective solution. While the integration itself is free, you will need to pay for BigQuery usage. The costs are determined by storage and analysis pricing. Storage costs are based on the amount of data stored in BigQuery, while analysis pricing covers the cost of processing queries, including SQL queries, user-defined functions, scripts, and certain data manipulation language (DML) and data definition language (DDL) statements that scan tables.

Google offers a free tier, allowing you to store up to 10GB of data every month for free, and the first 1TB of monthly query data processed is also free.

Now, let’s move on to the integration process. To integrate GA4 with BigQuery, please follow the steps below:

#1 Create a Google Cloud Platform account by clicking on the “Start Free” button.

#2 Create a new project on Google Cloud (name it your organisation or website) and enable billing in your project (optional, according to what you selected in the previous chapter of this article)

#3 Open the GA4 Admin page and click on “BigQuery links”, click on “Link” button

#4 Choose your Google Cloud (BigQuery) project (that was created in the second step), select Data Location and click “Next.”

#6 Configure data streams and events you want to store in BigQuery (data streams, frequency, etc.)

#7 Review the settings provided and click the “Submit” button.

After you link GA4 and BigQuery, you should wait at least 24 hours to see the first data. You can see the data faster by enabling the billing and using streaming integration mode.

To find your data, go to Cloud Console – > BigQuery -> SQL workspace.

Method #4: Exporting GA4 data using Google Analytics API

Exporting Google Analytics 4 (GA4) data using the Google Analytics API is a powerful method that allows businesses to access and retrieve data from their GA4 properties programmatically. The Google Analytics API provides a flexible and efficient way to extract data from GA4, enabling businesses to automate data retrieval processes, integrate GA4 data with other systems, and perform custom analysis and reporting. The API is widely utilized by third-party data transfer tools such as Supermetrics and FiveTran and visualization tools that directly connect with GA4.

Here are some key steps involved in exporting GA4 data using the Google Analytics API:

• Authentication: Before accessing GA4 data through the API, businesses need to set up authentication to authorize access to their GA4 properties. This typically involves creating a project in the Google Cloud Console, enabling the Google Analytics API, and generating API credentials such as API keys or OAuth tokens.

• Querying Data: Businesses can use the Google Analytics API to query and retrieve specific data metrics and dimensions from their GA4 properties. Using any of the Data API methods, the API allows businesses to specify parameters such as the date range, metrics (e.g., sessions, pageviews), dimensions (e.g., traffic source, device category), and filters to tailor the data retrieval process to their specific needs within an API call.

One of the key advantages of using the Google Analytics API for exporting GA4 data is the ability to automate data retrieval processes and schedule regular data exports. Businesses can set up automated scripts or workflows to fetch data at specific intervals, generate reports, and deliver insights to stakeholders on a recurring basis. This Google documentation outlines the full steps required in using the API. 

Method #5: How to export Google Analytics data into other destinations

Exporting Google Analytics data to other destinations can be achieved through various methods. Two effective approaches include:

1. Exporting to Google BigQuery and Using Google Cloud Functions/Airbyte: Businesses can export raw GA4 data to Google BigQuery as described above, and then utilize Google Cloud Functions or Airbyte to transfer this data to other destinations such as PostgreSQL, MongoDB, and more. By leveraging these tools, businesses can streamline the process of moving and transforming data, enabling seamless integration with different databases and systems.

2. Deploying Airbyte on Google Cloud: Another option is to deploy Airbyte, an open-source data integration platform, on Google Cloud. This allows businesses to load GA4 data directly into any desired destination without requiring intermediate steps. Running Airbyte on Google Cloud costs around $70 monthly for a virtual machine instance. However, you can reduce this cost to $5-10 per month by scheduling virtual machine runs instead of keeping them active for the entire month. This approach provides a cost-effective solution for data integration and migration needs.

By utilizing these methods, businesses can efficiently export Google Analytics data into other destinations, enabling them to leverage the insights and analytics provided by GA4 across various platforms and systems. Whether it’s for advanced data analysis, reporting, or integration with other tools, these approaches offer flexibility and scalability in managing and utilizing GA4 data effectively.

Do you need extra help exporting your Google Analytics data? 

It is essential to use the most suitable method for exporting your GA4 data and optimizing the process. Not sure of the most appropriate method for your business? We can assist you in selecting the best method and streamline the process. At Vakulski-Group, we specialize in providing comprehensive support for GA4. Our services include GA4 implementation, customization, and in-depth data analysis.

Our success stories are a testament to our capabilities. We’ve successfully resolved data export issues for numerous clients, transforming their processes and unlocking meaningful insights from their Google Analytics data. One such example is our work with SavvyDealer. We helped them optimize their clients’ data export processes and derive valuable insights from their Google Analytics data. Our competitive cost for data export and integration services makes us the ideal partner for you, offering both quality and affordability.

Contact us today to learn how we can help you effectively export, analyze, and utilize your Google Analytics data to drive business success.

Final Words on How to Export Google Analytics 4 Data

In conclusion, by leveraging the methods discussed in this article to export data from Google Analytics 4, such as exporting to CSV/Excel, Google Sheets, BigQuery, API, and other options, businesses can effectively access and analyze their data in diverse formats to derive valuable insights. Exporting this data allows businesses to merge GA4 data with data from other sources like backend systems, Google Ads, and Google Search Console. This comprehensive approach gives businesses a complete view of their performance and customer behavior, helping them better understand user interactions and identify trends and patterns that may not be obvious when analyzing data separately. Businesses should choose the most suitable method based on their specific requirements and objectives to fully leverage their GA4 data export and analysis.

Frequently Asked Questions