One of the best features of GA4 is the ability to send the data to BigQuery. All it takes is a few clicks and your data will start to stream into BigQuery.
So why should you care? Here are the 9 reasons why you should turn this feature on.
- Unsampled Data - GA4 data to big query is unsampled, unlike the data that is available in the GA4 reporting interface. Which means you have a better quality of data in BigQuery.
- QA of GA4 Implementation - Having GA4 data in BigQuery makes it easier for you to validate your reporting and implementation. You can run SQL queries and do all sorts of counts and aggregations to see where your implementation is wrong. Since the stream data (if you chose that option) is available in almost real-time, you can also fix the issues right away rather than waiting a day for the data to show up in the GA4 interface.
- Better Reporting - As I mentioned above, you get access to unsampled data, which makes your reporting much better. In addition to that, you are not limited to what a drag-and-drop GA4 reporting interface can do. You can write any query you need to get exactly the report that you need.
- No more dealing with API limits - Free Looker Studio + GA4 connector enforces API limits, which means your reports will break once you hit the free limits. With BigQuery, you don't have to worry about those limits. Just point Looker Studio to BigQuery and you will have a better-functioning reporting system.
- Richer Data Set - Since you have raw hit level data available in BigQuery, you can combine it with other data sources such as CRM, Email, Ads, etc. as well as 3rd party data such as weather to get a much better data set for analysis.
- Deeper Insights - Since you can integrate various data sets, run any queries you want, and slice the data any way you want, you get much deeper insights than what the GA4 interface can provide. It can do better segmentation. For example, GA4 can tell you which source/medium is bringing you traffic and conversions but it won't be able to tell you that people who converted from Google Ads are the same people who have purchased multiple times in the past and have smaller spend per transaction but tend to buy 2 particular categories of products together. It can't tell you that the same people then spend more money in winter as compared to summer. BigQuery can if you just know how to ask the right question and build the right query.
- Better Targeting - Now won't you be able to better target your customers and prospects if you had deeper insights? You can do timely emails (winter v/s summer) to a targeted group of customers (people who buy more) with other products or categories of products. You can make better Ads and do better targeting.
- Data is retained forever - GA4 data can store up to 14 months of data (2 months by default) but BigQuery will retain your data for as long as you want.
- Cardinality - this is going to cause your stakeholders to lose faith in GA4 data. Cardinality occurs when you have too many rows in the underlying table that populates the report. Standard reports and exploration have different table limits so you can potentially get a different result for using the same dimensions and metrics. It also introduces another dimension called “other”, whenever it hits the row limit. How will you explain this to your stakeholders? If the same metrics and dimensions provide different results in a standard report and Explore or adding a new dimension produces entirely different results then which one is correct? How will you know? The reports generated using BigQuery don’t have the same limits and issues.
Learn on your own - Want to learn more about BigQuery, GA4, Segmentation, Analysts, etc.? Join Optizent Academy at https://academy.optizent.com/courses/membership/ .
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