If you’re a Google Analytics 4 (GA4) user and pushing your data into Looker Studio (formerly known as Google Data Studio), chances are you’ve been hit by GA4’s API quota limits. Naturally, this has been causing a lot of issues for marketing teams as Google’s Universal Analytics is set to be sunset by the end of June and we all switch over to GA4.
Fret not, to help you overcome GA4’s API limitations, we’ve put together this quick guide on what GA4 quotas are and what you can do to overcome the GA4 quota limits in Looker Studio.
So, last year GA4 introduced API limits to their product, which has had a significant impact on anyone using that data in Looker Studio dashboards.
According to Google they have “put limits and quotas on API requests to protect the system from receiving more data than it can handle, and to ensure an equitable distribution of the system resources.”
Looker Studio has connectors to many of its Google products which are “real-time” meaning that each time you request data from a datasource, it will fetch it from the source platform immediately because it's a live connection.
What this means is, if lots of people are viewing and editing the contents of the dashboards, that there is a high volume of requests that very quickly can exceed the limit Google has applied to their GA4 API and your data will stop loading in their widgets.
“If the quota of requesting a Google Analytics API is exceeded, the API returns an error code 403 or 429 and a message that the account has exceeded the quota.”
Google Analytics 4 Data API has several quotas with the limits differing depending on how whether you are a standard or 360 customer. The most important quotas in relation to their current impact on Looker Studio reports are below or you can access the full list here.
|
Quota Name |
Standard Limit |
Analytics 360 Limit |
|
Core Tokens Per Property Per Day |
25,000 |
250,000 |
|
Core Tokens Per Property Per Hour |
5,000 |
50,000 |
|
Core Tokens Per Project Per Property Per Hour |
1,750 |
17,500 |
|
Core Concurrent Requests Per Property |
10 |
50 |
“What first seemed to be a huge but temporary bug in Looker Studio turned out to be one of the single worst updates Google Analytics 4 has ever made, impacting almost every user and use case involving GA4 and Looker Studio!”
-Looker User
While frustrating, there are workarounds to dealing with GA4’s API limits.
One thing you can do is manually export your GA4 data into a spreadsheet and then import that into Looker, but this is inadvisable.
Another option is to rebuild your Looker studio reports with fewer elements and have fewer users able to access them. This will make it less likely that you will exceed GA4’s limits and it’s always good practice to reduce unnecessary clutter in your reports however this solution is unlikely to help any but the most basic reports (sometimes complexity is necessary) and besides, having to reformat or rebuild reports you are already working with is both time-consuming and will impact your data strategy.
If you don’t want to start tearing up stripping back your Looker Studio reports and also don’t quite fancy manually integrating all your data from spreadsheets, your best option is to take a look at an integrated data platform like Adverity that can easily help overcome GA4’s API limit.
Within Adverity, you can create Datastreams for any Connector and schedule data retrievals so that data is refreshed at whatever cadence you would like.
This means instead of pulling data from a live API you are in fact pushing data to Looker Studio on an automated schedule.
And on top of that, the data you retrieve via an Adverity connector can be harmonized and enriched to align your columns, rows, and headers to be consistent across sources as it passes through before it hits Looker Studio. This means you can start visualizing it straight away and skip the painful data prep part in Looker Studio.
Adverity, like all other customers of the GA4 API, has the same rate limits. However, all our connectors have built-in logic to handle API rate limits, quotas, and timeouts so that even large volumes of data can be processed.
Adverity also includes transparent reporting on connector performance so you can see how long each datastream takes to retrieve data. In the event of any failed retrievals, there’s an easy Activity feed to monitor the progress of each datastream so you can be confident you’ve processed and transferred all the data you need.