How to Export All Rows in Google Analytics

It’s a frustratingly common story: you build the perfect report in Google Analytics, finally zeroing in on the exact dimensions and metrics you need, only to hit the export button and receive just a fraction of your data. This is because Google Analytics limits the number of rows you can export directly from its user interface, often giving you a "sampled" view that doesn't tell the whole story. This article will show you exactly how to bypass this limitation and export all your data rows from Google Analytics using a few different methods, from easy fixes within GA4 to more powerful, automated solutions.

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Why Does Google Analytics Limit Data Exports?

Before diving into the "how," it helps to quickly understand the "why." Google Analytics processes an astronomical amount of data. To make reports load quickly in your browser, especially complex ones with multiple dimensions, GA often relies on a technique called data sampling.

Instead of analyzing every single session to generate your report, it looks at a representative subset - a sample - of the data and then extrapolates the results. Think of it like a political poll: surveyors ask a few thousand people who they’re voting for instead of asking every single person in the country. It’s faster and usually gives a good estimate, but it's not the complete, exact picture.

When you're dealing with a week's worth of data, your reports are likely 100% unsampled. But when you look at a full year of data and start adding secondary dimensions or filters, sampling will almost certainly kick in. You'll often see a green checkmark icon at the top of your report indicating the percentage of sessions used to create it.

This sampling, combined with hard export limits (typically 5,000 rows for standard reports downloaded as a CSV from the main GA interface), is why your exported files feel incomplete. GA is trying to balance performance with precision, but when you need precision for deep analysis, you need a way to get the full, unsampled dataset.

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Method 1: Use GA4 Explore Reports for Larger, Unsampled Exports

If you just need a little more data than the standard reports provide and want to stay within the Google Analytics interface, GA4's "Explore" section is your best first stop. Explorations are a more powerful, flexible type of analysis than standard reports and often provide access to unsampled data.

While the standard GA4 reports have stricter limits, a free-form exploration allows you to export up to 50,000 rows daily for standard GA4 properties (and even more for GA360). This is often more than enough for many common analysis tasks.

How to Export Data from an Explore Report:

1. In the left-hand navigation of Google Analytics 4, click on Explore.
2. Start a new exploration, typically using the Free-form template.
3. In the "Variables" column on the left, click the "+" icon to import the Dimensions (e.g., Page path and screen class, Session source / medium) and Metrics (e.g., Sessions, Total users, Conversions) you need for your report.
4. Drag the dimensions you imported into the "Rows" section and the metrics into the "Values" section of the "Tab Settings" column.
5. As you build, your table will populate in the main window. Make sure the data looks correct.
6. In the top right corner of the screen, you’ll see several icons. Click the download icon (an arrow pointing down into a tray).
7. Choose your preferred format: Google Sheets, TSV, or CSV.

This downloaded file will contain the unsampled data for your query, up to the 50,000-row limit. For many marketers, this is the quickest and easiest way to pull a more complete dataset for analysis in a spreadsheet tool like Excel or Google Sheets without dealing with add-ons or APIs.

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Method 2: Connect Google Analytics to Google Sheets with the Add-on

When 50,000 rows still aren't enough or you want to automate your reporting on a schedule, the next best step is the official Google Analytics Spreadsheet Add-on. This free tool lets you query the Google Analytics API directly from a Google Sheet, bypassing the user interface and its sampling limitations entirely.

It's a bit more technical to set up your first report, but once you get the hang of it, you can create powerful, automated data pulls directly into a spreadsheet.

How to Use the Google Analytics Spreadsheet Add-On:

1. Open a new Google Sheet.
2. In the top menu, go to Extensions > Add-ons > Get add-ons.
3. Search for "Google Analytics" and install the official add-on from Google.
4. Once installed, go to Extensions > Google Analytics > Create new report.
5. A sidebar will appear on the right. Give your report a name, then select the Google Analytics account, property, and view (for UA) or data stream (for GA4) you want to pull data from. Be aware that the setup and metric names differ between Universal Analytics and GA4, so be sure you're using the correct API syntax.
6. In the "Configure a new report" section, you'll specify your metrics and dimensions. For example:
7. Click the Create Report button. This will create a new tab in your spreadsheet called "Report Configuration" that contains all the parameters for your report.
8. Finally, go back to Extensions > Google Analytics > Run reports.

The add-on will now query the GAReporting API and pull your unsampled data into a new tab in your spreadsheet. The real power here is that you can set a schedule (e.g., run every day at 6 am) to keep your data fresh without you having to lift a finger. This also effectively solves the row limit problem, though you may need to adjust your date ranges to stay within daily API quotas if you're pulling enormous amounts of data.

Method 3: Go Pro with the GA4 to BigQuery Integration

For businesses with large amounts of data or those that need to combine analytics data with information from other systems (like a CRM or payment processor), there is no better solution than the native Google Analytics to BigQuery integration. This approach is the ultimate way to access all your raw, unsampled, event-level data.

BigQuery is Google's cloud data warehouse. Setting this up means GA will send a complete copy of all a site's raw data directly to your private warehouse. From there, you are no longer constrained by any of GA's limits. Fair warning: This method is more advanced and requires some comfort with the Google Cloud ecosystem and potentially SQL to query your data.

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How to Set Up the BigQuery Export:

1. Go to the Admin section of your Google Analytics 4 property (you need Admin-level permissions).
2. In the "Property" column, find Product Links and click on BigQuery Links.
3. Click the blue Link button. From here, you’ll choose a BigQuery project. If you don't have one, you’ll be guided through setting one up (it's part of the free tier of a Google Cloud account).
4. Follow the steps to configure your data stream, choosing which data to export and how frequently ("Daily" or "Streaming" for near real-time data).
5. Once configured, GA4 will start exporting your raw data to BigQuery every day.

The beauty of this is that the export itself is free for standard GA4 properties up to one million events per day. You only pay for BigQuery's data storage and querying, which are very cheap and have generous free tiers. Once your data is in BigQuery, you can use Looker Studio dashboards, connect it to advanced BI tools like Tableau or Power BI, or write SQL queries to perform any analysis you can imagine.

Final Thoughts

Making decisions based on sampled or incomplete data can lead you down the wrong path. By mastering these export methods, you can move beyond Google Analytics' interface limits and ensure you’re always working with the full, accurate picture of your business's performance. The right method depends on your needs, from a quick unsampled export from Explore reports to a fully automated pipeline with BigQuery.

Even with these methods, managing reporting can still feel like a manual chore, whether you're building queries in spreadsheets or writing SQL. At Graphed, we automate this entire process. We connect directly to your Google Analytics account, pull your raw, unsampled data into our platform, and let you create real-time reports and dashboards just by asking questions in plain English. This lets you skip the spreadsheet wrangling and technical setup so you can get straight to making data-driven decisions for your business.