Prerequisites

1. A Google account with Viewer access at the Property and View levels for your GA4 property
   
   
   

Adding Google Analytics 4 as a Data Source

1. Log out of all Google accounts except the one you want to connect.
2. In your Power My Analytics Hub, navigate to Sources.
3. Click + Add new source and select Google Analytics 4 from the gallery.
4. Sign in to your Google account when prompted.
5. Grant Power My Analytics the required permissions (Edit Google Analytics management entities and View and Manage your Google Analytics Data) for your Google account.
   
   

Power My Analytics' connector will never edit, create, or delete anything in your Google Analytics 4 account. Google does not provide a read-only option for permissions.

Creating a Looker Studio Report

1. In your Power My Analytics Hub, go to Reports > Looker Studio
2. Select Google Analytics 4 under Create Looker Studio Report (this will open the official Looker Studio application in a new window)
3. Google Looker Studio Configuration:
1. Step 1:
1. Name your data source (e.g., "Google Analytics 4 - My Website")
2. Select your Power My Analytics hub from the dropdown
3. Optional: Leave "Use report template for new reports" checked to use the PMA demo template
4. Click Next
2. Step 2:
1. User Account: Select your Google Analytics 4 account for real data or "Sample Account" for demo data
2. Click Next
3. Step 3:
1. Choose "Account" and "Currency" for your reports
2. Optional: Allow "Account" modification in reports
3. Click Connect (top right)
4. Step 4:
1. Click Create Report (top right)
   

Key Reports and Fields

1. Report Metrics: Users, New Users, Average engagement time, Total Revenue, Sessions
2. User Metrics: New Users by First User Default Channel Grouping, Engaged Sessions, Engagement Rate, Average Engagement Time, Event Count, Conversions, Total Revenue
3. Traffic Metrics: Users by Session default channel grouping, Total Users, Sessions, Engaged Sessions, Average engagement time, Engaged sessions per user, Events per session, Engagement Rate, Event Count, Conversions, Total Revenue
4. Event Metrics: Event Count, Total Users, Event Count Per User, Total Revenue
5. Conversion Metrics: Conversions, Total Users, Total Revenue
6. Pages and Screens Metrics: Screen Page Views, Active Users, Views per User, Average engagement time, Event Count, Conversions, Total Revenue
7. Landing Page Metrics: Sessions, Total Users, New Users, Average engagement time (sec), Conversions, Total Revenue
8. Ecommerce Metrics: Cart To View Rate, Items Added To Cart, Item Purchase Quantity, Item Revenue
9. Purchase Journey Metrics: Sessions, Item Views, Add To Carts, Checkouts, Total Purchasers
10. Publisher Ad Metrics: Publisher Ad Impressions, Ad Unit Exposure, Publisher Ad Clicks, Total Ad Revenue
11. Promotion Metrics: Item Promotion Views, Item Promotion Clicks, Item Promotion Click Through Rate, Items Added To Cart, Item Purchase Quantity, Item Revenue
12. Demographic Metrics: Total Users, New Users, Engaged Sessions, Engagement Rate, Engaged sessions per user, Average engagement time, Event Count, Conversions, Total Revenue
13. Tech Metrics: Total Users, New Users, Engaged Sessions, Engagement Rate, Engaged sessions per user, Average engagement time, Event Count, Conversions, Total Revenue
14. Custom Channel Groups
15. Custom Fields
    

For a complete list of available fields, refer to the Schema Explorer.

Checkout Journey Funnel Reporting

For information on reporting checkout journey funnels using your GA4 data in Looker Studio reports, please see Create a GA4 Checkout Journey Funnel with Filters.

Data Alignment and Channel Grouping Dimensions

Our GA4 connector offers two distinct dimensions with similar names that can be used for reporting sessions: Session Default Channel Grouping and Default Channel Grouping. Session Default Channel Grouping is the dimension used by PMA’s GA4 demo template under the Traffic Acquisitions report:

This table reports data equivalent to the Google Analytics 4 UI page “Traffic acquisition: Session primary channel group (Default Channel Group)”:

However, if the Default Channel Grouping dimension is used instead of Session Default Channel Grouping, the values reported will no longer match those of the GA4 UI’s traffic acquisition report:

Limitations and Important Considerations

1. Backfilling: Power My Analytics caches some GA4 data breakdowns to improve performance, but not all fields are cached. Nightly backfills occur for tables containing cached fields or subsets of cached fields within a table.
2. Metric discrepancies: Some metrics may show higher values in Power My Analytics compared to the GA4 UI, including:
1. Views and other page/screen metrics
2. User engagement metrics
3. Event counts in certain combinations
3. Adding new custom fields: If you add custom fields to an existing GA4 data source, you must reconnect the source in Looker Studio for the new fields to appear.
   
4. Custom dimension and custom metric name conflicts: When both a custom dimension and custom metric are created in GA4 with identical field names, Power My Analytics will only include the custom dimension in the list of available fields. If a custom metric has a name identical to an existing custom dimension, the custom metric will not appear in the available fields.
   
1. Workaround: If one of your custom metrics in GA4 has the same name as a custom dimension, rename one of the fields in your GA4 property so that the fields have unique names.
5. Unique metrics: Sessions and other unique metrics cannot be summed up daily to equal their values when reported over more than 1 day. Because of the challenge in reporting unique metrics, if a report does not include "Date" as a field, we will fetch the report live from GA4's API rather than retrieving cached data from the PMA data warehouse.
   
6. Audience reporting: The API will not report audiences with fewer than 10 users.
   
   

Unavailable Data

1. Realtime data