Configuring Google Analytics

Learn how to connect and export data from your Google Analytics properties with SyncRange.

Overview

Google Analytics provides valuable insights into your website's traffic and user behavior. By connecting your Analytics properties, you can export this data to Google Sheets for further analysis, reporting, and visualization.

Prerequisites

Before you can configure Google Analytics exports, make sure you have:

Adding Analytics Properties

To export data from Google Analytics, you first need to select which properties you want to connect:

  1. Access the Google Integration Dashboard

    From your account dashboard, navigate to Apps > Google Integration.

  2. Find the Analytics Section

    In the Google Integration dashboard, locate the Google Analytics section.

    Analytics Section

    The Analytics section in the Google Integration dashboard

  3. Add an Analytics Property

    Click the "Add Property" button to open the property selection dialog.

  4. Select a Property

    From the dropdown menu, select the Analytics property you want to connect. The list shows all properties you have access to in Google Analytics.

    Select Analytics Property

    The property selection dialog showing available Analytics properties

  5. Confirm Your Selection

    Click the "Add Property" button to connect the selected property to your account.

Note

You can only select properties that you have access to in Google Analytics. If you don't see your property, make sure you have the correct permissions and that you're using the same Google account.

Managing Connected Properties

After connecting Analytics properties, you can manage them from the Google Integration dashboard:

Viewing Connected Properties

All your connected Analytics properties are listed in the Analytics section of the Google Integration dashboard. For each property, you can see:

  • The property name
  • The Analytics account it belongs to
  • An option to remove the property from your account

Removing a Property

To remove an Analytics property from your account:

  1. Find the property in the Analytics section of the dashboard
  2. Click the "X" icon next to the property name
  3. Confirm the removal when prompted

Important

Removing a property will not affect your Google Analytics account, but any exporters using this property will stop working. You'll need to update those exporters to use a different property.

Creating Analytics Exports

Once you've connected your Analytics properties, you can create exports to send data to Google Sheets:

  1. Navigate to the Export Builder from your dashboard
  2. Click "Create New Export"
  3. Select "Google Analytics" as the data source
  4. Choose the Analytics property you want to export data from
  5. Select a Google Sheet as the destination
  6. Configure the export settings (see below)
  7. Set up a schedule for the export
  8. Click "Create Export" to save your configuration

For detailed instructions on creating exporters, see our Creating Data Exporters guide.

Analytics Export Settings

When configuring an Analytics export, you'll have several options to customize what data is exported:

Basic Settings

Configure the fundamental settings for your export:

  • Export Name: A descriptive name to identify your export
  • Date Range: How much historical data each export run includes. Presets include:
    • Today — current calendar day
    • Yesterday — previous calendar day only
    • Last 3, 7, 14, 28, 30, or 90 days — rolling windows ending today
    • Last 6 months — about the past 180 days
    • Last year — about the past 365 days
    • This month — first of the current month through today
    • Last month — full previous calendar month
    • This quarter — first day of the current calendar quarter through today
    • Maximum (2 years) — up to about two years ending today; very large windows are slower and still subject to your property’s GA4 data retention in Google Analytics

    On each run, rolling and calendar presets are recalculated from the current date. Exports created with the older 7-, 30-, or 90-day options behave as before. The old “Last day” menu option is removed; any export that still has that value stored is treated like Yesterday (previous calendar day only).

Dimension Tabs

Analytics exports are organized by dimensions, with each dimension creating a separate tab in your Google Sheet. The interface uses a tab-based layout where you can configure each dimension independently:

Analytics Dimension Tabs

The tab interface for configuring different dimensions

Common dimensions include:

  • Property Summary: Property-wide totals for the export date range, with period start and end columns
  • Date: Performance data broken down by day
  • Source, Medium, Campaign: Traffic and campaign breakdowns
  • Page path / Page title: Content performance
  • Country, Region, City: Geographic locations of your users
  • Device Category, Browser, Operating System: Technology breakdowns
  • Event name: Analytics event types (e.g., purchase, signup)

For each dimension tab, you can:

  • Enable/Disable: Choose whether to include this dimension in your export by selecting metrics
  • Set Data Handling: Choose whether to append new data or replace existing data
  • Select Metrics: Choose which performance metrics to include for this dimension

Property Summary does not use a GA4 breakdown dimension. It returns one row per export with property-wide totals for the configured date range. Period Start and Period End columns identify the window for each run (useful with append mode).

For other dimensions, GA4 exports range totals by default (one row per breakdown value). Enable time breakdown to split results into daily, ISO weekly, or monthly rows. Page path, page title, and event name with time breakdown enabled can produce very large exports; use shorter date ranges when needed.

User metrics

GA4 user counts depend on how data is broken down. Match the tab and grain to the analysis you need:

  • Property Summary: Active Users and Total Users are deduplicated across the export’s full date range.
  • Date: User metrics are calculated per day. They are not additive across rows—a user who visits on multiple days appears in each day’s count.
  • Other dimensions (range totals): User metrics are deduplicated per breakdown value over the export window (for example, per country or source). Totals across rows may double-count users who appear in more than one segment.

Active Users counts users with at least one engaged session and generally matches the “Users” metric in the GA4 reporting interface. Total Users counts everyone who triggered any event in the period. Period totals always reflect the date range set on the export.

Metrics Selection

For each dimension, you can select which metrics to include in your export:

Analytics Metrics Selection

The metrics selection interface for a dimension

Available metrics include (availability may vary slightly by dimension; incompatible combinations are skipped during export):

  • Total Users: Unique users who triggered any event in the period
  • Active Users: Unique users with at least one engaged session; aligns with GA4 UI “Users” in most reports
  • Sessions: Total number of sessions
  • Page Views: Total screen and page views
  • Event count: Number of events (not available with Source, Medium, or Campaign tabs)
  • Bounce Rate: Percentage of non-engaged sessions
  • Engagement Rate: Percentage of engaged sessions
  • Engagement Duration: Total user engagement time in seconds (Property Summary, Date, and Event name tabs only)
  • Engaged Sessions: Sessions that lasted longer than 10 seconds, had a conversion, or had at least two page views
  • Revenue: Total revenue from ecommerce and other monetization events
  • Transactions: Number of purchase events
  • Conversions: Number of conversion events
  • Date Exported: Timestamp when SyncRange ran the export

You can use the "Select All" and "Deselect All" buttons to quickly manage your metric selections.

Data Handling

For each dimension tab, you can choose how to handle the exported data:

  • Replace (default): Each export run will clear existing data and replace it with new data
  • Append: Each export run will add new data rows without removing existing data

The append option is particularly useful for building historical datasets. When enabled, each export adds new rows to the destination and leaves existing rows. When disabled, the destination is fully refreshed and existing data is removed.

Understanding Tab Badges

Each dimension tab displays a badge showing how many metrics are currently selected. A zero indicates that the dimension will not be included in the export.

Best Practices

  • Match tabs to the question: Use Property Summary for property-wide period totals; use Date for daily trends; use other dimensions for segment breakdowns
  • Focus on key metrics: Select only the metrics that are most relevant to your analysis to keep exports manageable
  • Use multiple dimensions: Create exports with different dimensions to analyze your data from various angles
  • Regular scheduling: Set up daily or weekly exports to build a comprehensive historical dataset
  • Combine with other data: Use Google Sheets or BigQuery to join Analytics data with Search Console, Ads, or other sources

Troubleshooting

Property Not Appearing

If your Analytics property doesn't appear in the selection list:

  • Verify you're using the same Google account that has access to the property in Google Analytics
  • Check that you have at least Read & Analyze permissions for the property
  • Ensure the property is properly set up in Google Analytics

No Data in Exports

If your exports aren't showing any data:

  • Check that your website has traffic during the selected date range
  • Verify that your Analytics tracking code is properly implemented on your website
  • Ensure you've selected at least one metric for each dimension
  • Remember that new websites may have limited data in Analytics

User metrics differ from GA4

If user counts in your destination do not match GA4 reports:

  • Check whether daily user metrics from the Date tab are being aggregated across multiple days
  • Confirm the export date range matches the period you are comparing in GA4
  • Compare Active Users to GA4 “Users” and Total Users to GA4 “Total users” as appropriate
  • Allow for small differences on recent dates while GA4 finishes processing

Sampling issues

If you notice inconsistencies in your exported data:

  • Be aware that Google Analytics may sample data for reports with large amounts of data
  • Try reducing the date range or the number of dimensions/metrics to minimize sampling
  • Consider using shorter, more frequent exports rather than large date ranges

Related Documentation

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