Export Google Analytics 4 Data to Google Sheets: 4 Methods

How do you export GA4 data to Google Sheets?

Four routes move Google Analytics 4 data into Google Sheets. Download a report from GA4 as a file and import it manually. Connect a third-party add-on like Supermetrics or Windsor.ai that pulls from GA4 and writes to Google Sheets. Write a script against GA4's Data API. Or route your data through BigQuery first.

• Manual export. Download a report from GA4 as a file, then import it into Google Sheets. Free, but you repeat the task every time you need fresh numbers.
• Connector add-on. Supermetrics and Windsor.ai both list Google Analytics 4 as a source and Google Sheets as a destination, as of September 6, 2026, with a scheduled refresh.
• Data API script. GA4's Data API lets a script query a property directly, with documentation at developers.google.com, checked August 12, 2026.
• BigQuery export. GA4 exports raw event data to BigQuery daily. This route matters once your team needs history beyond GA4's 14-month retention window.

Pick the right route based on how often the sheet needs to update, how much history matters, and whether your team can script. The same tradeoff applies across most marketing analytics, including the closely related question of exporting Facebook Ads data to Google Sheets.

What do you need before you start?

Before you export, gather what you need: access to the GA4 property, a Google account for Sheets, clear metrics and date range choices, and—for the connector, API, or BigQuery route—a paid subscription, API access, or a linked export. Getting these right the first time saves you from rebuilding later.

• Access to the GA4 property you want to report on
• A Google account for Google Sheets
• Clarity on which metrics, dimensions, and date range you need
• For the connector route: a payment method, since Supermetrics and Windsor.ai require paid plans above their limited free or trial tiers
• For the Data API route: a way to authenticate your script against the property, plus read access
• For the BigQuery route: a linked BigQuery export
• Consistent event and parameter naming, plus UTM tagging on campaigns, makes it far easier to join Sheets data with other channels later

Method 1: Export GA4 data manually

The manual route costs nothing. Download a report from GA4 as a file, then import that file into a new or existing Google Sheet. It works for a one-off pull or an occasional report. Expect to repeat the download-and-import steps every time you want fresh data.

1. Set the metrics, dimensions, and date range you need inside GA4's reporting view.
2. Download the report as a file.
3. Open Google Sheets and import that file into a new or existing sheet.
4. Re-map column headers if needed so downstream formulas and charts keep working.
5. Repeat the same steps whenever the numbers need updating.

Use this route for a single report, a one-time audit, or a dashboard you update monthly. Re-downloading the same report every week is a signal to move to Method 2.

Method 2: Use a connector add-on like Supermetrics or Windsor.ai

A connector add-on like Supermetrics or Windsor.ai connects to your GA4 property and writes data straight into Google Sheets on a schedule. Both list Google Analytics 4 as a source and Google Sheets as a destination. Setup means picking the vendor, authorizing the property, and choosing a refresh frequency.

Both are third-party add-ons, not a Google-built feature. Pricing and refresh frequency separate entry plans from higher ones, all as of September 6, 2026:

• Supermetrics Starter: $55/month ($44/month billed yearly), weekly data refreshes (Google Sheets only)
• Supermetrics Growth: $222/month ($177/month billed yearly), daily data refreshes (Google Sheets only)
• Windsor.ai Free: $0/month, daily sync
• Windsor.ai Basic: $23/month ($19/month billed annually), daily scheduled sync
• Windsor.ai Standard: $118/month ($99/month billed annually), daily or hourly scheduled sync

1. 1

   Sign up for a plan

   Choose Supermetrics or Windsor.ai. Supermetrics offers a 14-day free trial with no credit card needed; Windsor.ai offers a 30-day trial that converts to a Forever Free plan, also with no credit card needed, both as of September 6, 2026.

2. 2

   Connect GA4 as the data source

   Both tools list Google Analytics 4 as a data source. Authorize the connector against your property so it can read the underlying data.

3. 3

   Choose Google Sheets as the destination

   Point the connector at a new or existing Google Sheet—Google Sheets is a supported destination on both platforms.

4. 4

   Pick fields, property, and date range

   Select the metrics, dimensions, and time range to pull, within the data-source and account limits of your plan tier.

5. 5

   Set the refresh schedule

   Supermetrics Starter refreshes Google Sheets weekly and Growth refreshes daily; Windsor.ai syncs daily on Free and Basic and daily or hourly from Standard, all as of September 6, 2026.

6. 6

   Review the sheet

   Confirm the pulled rows and headers match what your charts or formulas expect before relying on the automatic refresh.

This pattern mirrors what you'll see with connecting Google Ads to Looker Studio: pick a vendor, authorize the account, choose a destination, set a schedule.

Method 3: Pull GA4 data with the Data API

GA4's Data API lets a script query metrics and dimensions from a property directly and write the results into Google Sheets via the Sheets API, on whatever cadence you set. Use this route if your team has developer resources and wants full control over fields, cadence, and history without opening the GA4 interface.

1. Authenticate a script against the GA4 property so it can read data programmatically.
2. Call the Data API for the metrics and dimensions your report needs.
3. Set the date range and any filters inside the script itself.
4. Write the returned rows into Google Sheets via the Sheets API, or through an intermediate script.
5. Schedule the script to re-run on whatever cadence your team needs.

Method 4: Use BigQuery export

GA4 can export raw event data to BigQuery daily. From there, a script or connector can move it into Google Sheets. The standard version caps the daily export at 1 million events and keeps only 14 months of history in the GA4 interface itself. The BigQuery route is how you preserve data that GA4's own reports will eventually drop.

GA4's standard version caps data retention in the interface at 14 months, and the daily BigQuery export at 1 million events. GA4 360 raises retention to up to 50 months and the export ceiling to billions of events, per Google's documentation checked August 12, 2026.

GA4 360 carries no published price on Google's own page—the only listed action is to talk to sales, per documentation checked August 12, 2026.

Which export method should you choose?

Pick the manual route for a single report, a connector add-on for a recurring sheet that needs a scheduled refresh, the Data API for full programmatic control, and the BigQuery route when history beyond GA4's 14-month standard retention matters most.

• Compare price, refresh frequency, and key limits side by side before committing to a paid connector.
• Supermetrics Enterprise and Windsor.ai Enterprise carry pricing on request, as of September 6, 2026.
• Refresh frequency is the clearest differentiator between tiers on both connector platforms.

Every figure above comes from each vendor's own pricing page on the date shown. For a wider shortlist before committing, see Supermetrics alternatives and Windsor.ai alternatives.

What mistakes make GA4 numbers not match your Google Sheet?

Mismatches almost always trace back to one of four causes: sampling in Explorations reports, GA4's retention window dropping older data, a date range or time zone mismatch between the export and the GA4 interface, or GA4 withholding rows through data thresholding.

• Sampling. Explorations reports can sample results once a query crosses GA4's event threshold for your tier. The standard version caps sampling at 10 million events per query, per Google's documentation checked August 12, 2026. Standard reports outside Explorations, and BigQuery's raw event export, are the two ways to avoid it.
• Retention. A sheet built from data that has aged past GA4's 14-month standard retention window won't match a fresh pull. GA4 has already dropped that data from the interface.
• Date range and time zone. Confirm the export and the GA4 interface are reading the same window and the same property time zone before comparing numbers.
• Thresholding. GA4 can withhold or blank out rows with very small user counts for privacy reasons. This shows up as gaps rather than a clean mismatch.

How do you automate reporting beyond a single spreadsheet?

A spreadsheet works until GA4 has to sit next to ad spend, CRM, or other channel data in one report. At that point, a marketing analytics platform that blends sources automatically becomes faster than maintaining more sheet tabs, more connector subscriptions, and more formulas.

• Every method above produces one channel's data in one sheet. Combining GA4 with ad platforms or CRM data means either more connector tasks or more script logic.
• AdMetric is an AI marketing automation and analytics platform built for small and mid-size businesses that need channels blended without stitching together a spreadsheet by hand.
• The same tradeoff applies to end-to-end marketing analytics and to teams building closed-loop reporting from GA4 through to revenue.

Frequently asked questions about exporting GA4 data to Google Sheets

Here are the questions that come up most when teams move GA4 numbers into Google Sheets: cost, automation, retention, sampling, and connector pricing.