GA4 Looker Studio data API quotas and how to overcome the challenges

Since the 21st November, many Looker Studio users have been met with a range of error messages which are linked to the new GA4 Data API update. This update has introduced a number of tight querying quotas to users of Looker Studio with dashboards built using the GA4 native connector.   We cover what has changed, how the new quotas work, and some methods to potentially overcome these quotas.

What happened? 

On the 10th November Looker Studio announced a change to how it deals with the GA4 Data API limits for concurrent requests which are called “quotas” when using the GA4 Looker Studio connector.  Quotas in the GA4 Data API have always existed, the major change here is that Looker Studio users no longer get the benefit of avoiding these quotas when using the Looker Studio native connector. Errors began showing up in dashboards, and what many users assumed to be a Looker Studio bug turned out to be the result of the GA4 Data API quota limits to Looker Studio.

What are the Google Analytics data API quotas?

When extracting data from GA4, any tool (Looker Studio or otherwise) will need to send a request to the GA4 Data API. Until very recently the native GA4 Looker Studio Connector did not enforce the quota limits on the data API, but now a new set of querying quotas have been introduced. There are two main quotas impacted by this change, these are: Core Hourly and Daily Tokens and Core Concurrent Requests.

Core Tokens 

These are tokens related to the data being pulled into each report per hour and day. Tokens are consumed every time users change filters, edit date ranges or even when refreshing data in a Looker Studio dashboard. Standard GA4 users are allocated 1,250 hourly tokens, and a total of 25,000 daily tokens. The number of tokens used per request is based on the complexity and size of the request made. For example, visualisations which use blended data will incur double the tokens of a visualisation with a single source.

Core Concurrent Requests Per Property

These are tokens related to the necessary API calls used to pull data into each element of the Looker Studio dashboard. Concurrent requests are measured by the number of requests being simultaneously executed and can be highlighted in Looker studio when the blue loading bar displays above the navigation bar of the report.

Users are allocated 10 API Calls concurrently; this means that on a dashboard page with 10 graphs you will be meeting the quota limits for concurrent requests. This will also be the case if two users access a dashboard page with 5 graphs at the same time, so these limits are fairly easy to meet.

There are different quota limits for the free GA4 and GA4360 accounts, with 360 users having access to 5 to 10 times higher quotas than the free counterparts, depending on the quota or token type.

A list of all quota limits is documented here.

The new quota limits are significantly lower than Universal Analytics, where the UA API would allow for 10,000 requests per day per view, with up to 100,000 rows per request.

How will the new quotas affect Looker Studio?

This change has meant that almost all Looker Studio users which utilise the native GA4 connector are likely to have issues visualising their data. Once the property quota has been exceeded charts will break and users will need to wait for the quota to be refreshed before the next API call can be executed (quotas are refreshed hourly or daily, depending on the quota exceeded). 

Although Google has announced work is underway to improve the quotas system and increase transparency on token consumption by report components, it is still vital to find a long term solution to the quotas in general.

What are some ways of overcoming the limitations of quotas?

GA4 Explorations

GA4 Explorations are a new module added to GA4 (Also available to 360 users in UA) where users can create custom reports based on GA4 data. Exploration reports allow for more advanced techniques that go beyond standard reports. However, Explorations are far less versatile than Looker studio dashboards in terms of functionality and allow for a maximum of three months' of look back data.

Google sheets add-ons for GA4 

Adformatic offers a really useful tool to connect GA4 to Google Sheets in order to query your data. This add-on allows users to pull data from the GA4 API and schedule data pulls daily to avoid quota restraints. This data can then be linked to Looker Studio to build your dashboards, avoiding the use of the GA4 data API. This is however a short term solution, as using spreadsheets to substitute data warehousing tools is not sustainable, especially if you need to export large amounts of data.

Partner connectors

Partner connectors can also be useful in mitigating the issues brought on by the Looker Studio quotas, although all options provided below are paid services.  Tools such as  Analytics Canvas and PowerMyAnalytics are warehoused partner connectors which query data from the GA4 API only once, and store the data within their own data warehouse as opposed to querying APIs. 

Supermetrics can also be a potential workaround for this. Although the tool works as a live connector, Supermetrics have several layers of cache which are able to either successfully query cached data or limit simultaneous requests to reduce the risk of exceeding quotas. 

BigQuery 

BigQuery is Google’s data warehousing tool, and a good contender for a more longer term solution for dealing with Google’s quota changes. BigQuery has a native connector to Looker Studio, and the service offers a free monthly 10GB data storage limit and a 1TB querying limit, which users will need to utilise in order to use the Big Query Looker Studio connector.

Some of the potential drawbacks of using BigQuery as a solution is that it can incur costs if not used wisely. Exporting GA4 data into BigQuery is free and easy but it is possible to incur costs. Once the free limits have been exceeded BigQuery will start charging, and depending on the usage of the tool, costs can increase quickly.

Implementing BigQuery can also be a long winded process if users are not familiar with the tool. To extract data out of BigQuery you will need to use SQL language. Tables that would very quickly be created using Looker studio can require advanced knowledge to reconstruct in BigQuery in order to keep querying costs low. 

How can we help?

The move to a quota based usage of GA4 in Looker studio has and will have a considerable impact on your GA4 dashboards, but there are several ways to mitigate this challenge. Equimedia has the expertise to assist you to implement all potential workarounds so please get in touch if you would like to discuss any of these options.