[Casey]

Based on Joel’s observation, there seems to be a discrepancy in the “Active users today” data when transitioning from Universal Analytics (UA) to Google Analytics 4 (GA4). The metrics for the current active users are off between the two platforms, but the main issue lies in the count for active users today. The figures being reported on GA4 are not aligning with those on UA, even to the point where GA4 is reporting a daily user count that’s lower than the last 15 minutes. Despite following a straightforward process to request the report, the same anomalies are observed in the analytics site. It raises a question if GA4 is experiencing a delay or backlog in processing today’s data in the report compared to UA.

[Casey]

It could be one of two things – either something on your site’s checkout page has changed and the ‘purchase’ event code got misplaced somewhere in the process, or it could be a bug with Google’s algorithms. I suggest doing a thorough audit of the ‘purchase’ event code on your site. If stuff still isn’t clearing up, you might want to contact Google Support.

[Casey]

Unfortunately, as of now, Google’s GA4 API does not directly support fetching Google Ads related metrics similar to how you can see it in their dashboard. This deficiency has been noted by other users as well, and it is suggested to keep an eye on updates from the GA4 API documentation for any future inclusion of these metrics. Another potential workaround could be to link your Google Ads and GA4 and then use Google Ads API to fetch the costs, but the process could be cumbersome and may not always deliver the expected results. I would recommend reaching out to Fivetran or Google support for further clarification on this issue.

[Casey]

Google Analytics 4 (GA4) does have the Measurement Protocol similar to Universal Analytics but with a more flexible approach. Their version, called the GA4 Measurement Protocol, allows developers to make HTTP requests to send raw user interaction data directly to Google Analytics servers. This can encompass various data types, including email click data or open data. However, it might require a more technical implementation compared to the Universal Analytics version. Google may expand its functionalities in the future, but as of now, it does not offer a directly comparable feature to the email tracking option you’re referring to in Universal Analytic. It’s always a good idea to stay updated with Google’s documentation or in contact with their support for any future updates.

[Casey]

Sure, I can break that down a little bit more.
Setting debug_mode to true essentially helps you see more detailed data in GA4’s debug_view. It’s like turning on a flashlight in a dark room — it helps you see all the details you wouldn’t normally see. And, this information would also show up on the Realtime Report in GA4.

But, the tricky part here is that it doesn’t directly help with excluding specific users. For that, you would need to create a unique trigger and remove it from every GA4 trigger in use. Now, this isn’t a quick fix. It’s gonna take some time and effort. Plus, at the moment, this is the only workaround until Google hopefully comes up with an easier way to do it!

[Casey]

It’s hard to provide specific code without knowing the format your data is in, however, the general way to accomplish this in any language would be to check each nested list for a ‘video_complete’ value.

In Python for instance, a basic way to do this would be to iterate over your list of lists using a for loop. Inside the loop, you would use an if statement to check the first element of each nested list. If the first element is ‘video_complete’, you would temporarily store this nested list in a variable, then remove it from the main list using the ‘remove’ method. After the for loop completed, you’d then use the ‘append’ method to add the stored ‘video_complete’ list to the end of the main list.

Doing something similar in your language of choice will move the row with ‘video_complete’ to be at the very bottom of your nested list. However, it is important to note that this is a very basic brute force method and not optimal for large lists. For a more efficient approach, you may want to consider sorting your data when querying it from the database or using more advanced algorithms and libraries.