As I mentioned in my earlier post about the drawbacks with the entity-attribute-value data model used in Firebase Analytics and Google Analytics app plus web, it is hard to know what events and associated attributes and data types are logged without proper documentation. Another way to get an overview is to actually query the table. Below you find an example of how to do it.
SELECT event_name, ARRAY_AGG(struct(name, value)) as attribute FROM( SELECT event_name, param....
Google recently released Google Analytics App + Web which essentially is something like Firebase Analytics for web (or Google Analytics version 2 if you want to). This is exciting for many reasons, two of them are:
Google is finally moving away from a user-session-pageview based model to one built on users and events It supports BigQuery export also for standard users That is awesome. These two are actually two of the primary reasons why I built datahem....
I recently implemented firebase analytics tracking in MatHem’s native apps and in that process I discovered that the documentation about tracking e-commerce is very limited compared to how to implement it in Google Analytics. Also, the events and parameters in the documentation didn’t fit our needs for analyzing e-commerce interactions. Hence, I thought I would share our implementation of Firebase Analytics.
First, Firebase Analytics has a completely different data model than Google Analytics....
Are you planning to use Firebase Analytics in a WebView on Android or iOS? Beware if you want to log doubles (price for example) as event parameters.
Google is sunsetting the Analytics Services SDKs coming fall and promote the transition to tracking your apps with the Firebase SDKs. Firebase Analytics is awesome (BigQuery Export, User and Event based, etc.). However, there is an issue I’m certain many analysts will face when implementing Firebase Analytics in a WebView....