How to Export More Than 5000 Rows in Google Analytics

Hitting the 5,000-row export limit in Google Analytics is a classic rite of passage for anyone trying to do serious analysis. You set up the perfect report, see that it contains tens of thousands of rows of valuable data, click "Export," and receive a file that's frustratingly incomplete. This article will show you three effective methods, from simple to advanced, to get all the data you need out of Google Analytics 4, well beyond that 5,000-row ceiling.

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Why Does GA4 Limit Report Exports to 5,000 Rows?

Before diving into the workarounds, it's helpful to understand why this limit exists. The standard reports you see in the Google Analytics interface are designed for quick, on-the-fly analysis. Processing and displaying massive tables of data in a web browser is resource-intensive. To ensure a smooth and fast user experience for everyone, Google limits the amount of data that can be viewed and exported directly from these standard reports.

Another key factor is data sampling. When you request a large or complex report in the GA4 interface, Google sometimes uses a representative subset of your data to estimate the results quickly. The 5,000-row limit on exports is intertwined with this system. To get access to 100% of your unsampled data, you need to use more powerful tools designed to handle larger datasets. Let's look at how to do that.

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Method 1: Manual Filtering and "Chunking" Your Data

This is the most straightforward method, requiring no additional tools or technical setup. The strategy is to break down your large report into smaller "chunks" that are each under the 5,000-row limit. You can then export these chunks individually and stitch them together in a spreadsheet program like Google Sheets or Microsoft Excel.

Imagine you have a "Pages and screens" report with 15,000 unique URLs (rows) that you want to export. Here's how you could do it using this chunking method.

Step-by-Step Instructions:

1. Navigate to Your Report: Open Google Analytics and go to the report you need, for example, Reports → Engagement → Pages and screens. Set your desired date range.
2. Apply an Initial Filter: At the top of the report, click "Add filter." You'll build a filter to isolate your first chunk of data. For a large set of pages, you could use a dimension that splits the data logically, like Device category.
3. Export the First Chunk: In the upper right corner of the report, click the "Share this report" icon (a box with an arrow) and select "Download File" → "Download CSV". Name it something clear, like pages_desktop.csv.
4. Filter and Export the Next Chunks: Go back to your report and edit the filter.
5. Combine the Files: Open a new Google Sheet or Excel workbook. Import or copy-paste the data from each of your CSV files into a single master sheet. You now have a complete report with all 15,000 rows.

You can get creative with your filters. If filtering by device isn't enough, you can filter by Country, a medium (e.g., organic, CPC), or even use "contains" logic on the page path itself (e.g., Page path containing "/blog/" for one export, and another excluding that path for the next).

• Pros: No extra tools or technical skills are needed. It's conceptually simple and uses the familiar GA interface.
• Cons: Extremely manual and time-consuming for very large datasets. It's easy to make a mistake with your filters, leading to data that is either duplicated or missing entirely. This method is not scalable for regular reporting needs.

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Method 2: Using the Google Analytics Add-on for Google Sheets

If you find yourself manually chunking data more than once, it's time to graduate to a more efficient and automated method. The official Google Analytics add-on for Google Sheets is a fantastic tool that allows you to pull data directly from the GA API into a spreadsheet, bypassing the interface's export limit.

This method has a slight learning curve but will save you countless hours in the long run.

Step-by-Step Instructions:

1. Install the Add-on: Open a new Google Sheet. In the menu, navigate to Extensions → Add-ons → Get add-ons. Search for "Google Analytics" and install the official add-on offered by Google. You'll need to grant it permission to access your Google account.
2. Create a New Report: Once installed, go to Extensions → Google Analytics → Create a new report. A configuration sidebar will appear on the right side of your sheet.
3. Configure Your Report:
4. Set the Row Limit: Critically, the report configuration isn't created directly in the sidebar. When you click "Create Report," the add-on populates a special tab named "Report Configuration." Go to this tab. You'll see your chosen settings laid out in cells. Find the "Limit" field — it's likely set to "1000" by default. Change this number to a higher value, like 100000, to pull up to 100,000 rows.
5. Run the Report: Go back to the menu and select Extensions → Google Analytics → Run reports. The add-on will now query the Google Analytics API with your settings. After a few moments (depending on the size of your query), it will dump all the data into a new sheet named after your report.

The best part? You can schedule these reports to run automatically every day, week, or month, ensuring your data is always fresh without any manual rerunning.

• Pros: Highly efficient and scalable. Allows for scheduled, automated data pulls. Lets you pull up to 100,000 rows per report. The data lands directly in a spreadsheet, ready for analysis or visualization.
• Cons: Requires initial setup and configuration. You need to know the specific names of the dimensions and metrics you want, though the add-on helps you find them.

Method 3: Connecting GA4 to BigQuery for Unlimited Data

For those who need access to raw, unsampled, event-level data without any practical row limits, the ultimate solution is the native integration between Google Analytics 4 and BigQuery. BigQuery is Google's cloud data warehouse, built to handle massive datasets. The GA4-to-BigQuery connection is a direct pipeline for your analytics data, and for most businesses, it's completely free to set up and use within the generous free tier.

This method is the most technically advanced but it future-proofs your analytics capabilities entirely.

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General Workflow:

1. Link GA4 to BigQuery: First, you need a Google Cloud Platform project with BigQuery enabled. Inside your Google Analytics account, go to the Admin panel. Under the Property column, click on Product Links → BigQuery Links. Follow the prompts to link your GA4 property to your BigQuery project. You can choose to export new data daily or in a continuous stream.
2. Wait for Data to Populate: After you've created the link, GA4 will begin exporting your raw data to BigQuery. It can take up to 24 hours for the first daily batch export to appear. You'll see new tables created in BigQuery each day, named events_YYYYMMDD.
3. Query Your Data with SQL: This is where the power lies. Instead of using a graphical interface with dropdown menus, you interact with your data by writing SQL (Structured Query Language) queries. Don't let this scare you! For basic reporting, you only need to learn a few simple commands.
4. Export the Results: After running your query, BigQuery will display the results in a table right in your browser. From there, you can easily save or export the results as a CSV file, send them to Google Sheets, or connect them to a BI tool like Looker Studio. There is no 5,000-row limit here, you can export millions of rows if your query returns them.

• Pros: Provides access to complete, raw, unsampled data. There are no practical row limits beyond the capabilities of your spreadsheet or analysis tool. It's the most powerful and flexible method for deep-dive analysis and understanding user-level behavior.
• Cons: Has the steepest learning curve, requiring at least a basic understanding of SQL. Can incur costs if your data storage and querying needs exceed BigQuery's generous free tier.

Final Thoughts

Getting around Google Analytics' 5,000-row export limit is entirely possible, and the method you choose depends on your needs. For a one-off task, manually filtering and combining files might be enough. For more regular reporting, the Google Sheets add-on is a game-changer. And for complete data freedom, the BigQuery integration is the professional standard.

These manual exports, queries, and spreadsheets are often a Band-Aid for a larger issue: getting clear insights from your data shouldn't be so difficult. We built Graphed to erase this exact friction. Instead of exporting CSVs or learning SQL to answer questions, you can connect your Google Analytics account once and simply ask for what you need in plain English — like "show me my top 500 pages by sessions last quarter as a table" or "create a dashboard of my marketing funnel performance." Our tool handles the querying and visualization instantly, giving you back time to focus on strategy, not data wrangling.