[Evelyn]

It sounds like the Analytics Debug View might not be interpreting your ‘items’ array correctly. This could be due to some formatting issue or an incorrect configuration setting in GA4. Check that your array syntax is compatible with Analytics’ expectations and your GA4 setup is properly configured to handle this data type.

[Evelyn]

To automatically fill in geographic details when you record the “page_view” event on your app using Python, you will need to make use of specific Python libraries. These libraries can capture data such as the IP address of the user and convert it into geographic details. So, in your Python script where you are currently capturing the ‘page_view’ event, you would also add in the commands to capture and record the IP details and geographic location. Make sure to check the privacy regulations relevant to your app’s use, as sometimes explicit user permission is required to capture such data. Once the geographic details are captured, the details should go to the intended endpoint along with the other details of the ‘page_view’ event. If details are not populating as desired, double-check your script for any errors or omissions. It is also suggested to test across different devices and locations for ensuring that geographic details are being captured accurately.

[Evelyn]

This issue seems to be a common concern amongst Google Analytics 4 and BigQuery users, and unfortunately, there doesn’t appear to be a definitive solution provided in the forums you’ve mentioned. It’s possible that there could be delays in creating the events_YYYYMMDD tables due to BigQuery’s data management processes, especially considering the large volume of data you’re dealing with. It’s also possible that there could be a technical issue, or perhaps a certain condition or configuration within your own GA4 or BigQuery setup that’s preventing or delaying the creation of these tables.

Without Google support, it’s challenging to diagnose and resolve this issue. You may want to consider reaching out directly to Google Cloud Support, or perhaps posting in more active and specialized communities, such as Google Group’s google-analytics-solutions group. Additionally, you may also want to review your GA4 and BigQuery settings and configurations just to ensure there’s no overlooked setting or requirement causing this issue. Lastly, if possible, try to monitor your BigQuery events for a few more days to see if the events_YYYYMMDD tables do eventually appear, and if they do, note the timeframe for learning purposes.

[Evelyn]

Sure, let me clarify that for you. Google Analytics 4 doesn’t really have a definitive hit limit like its previous version. So, even when you cross the 10M hit point in a month, Google continues to track and collect data without a cap.

As for ‘Explore sampling limits,’ it’s not as complicated as it sounds. When you’re pulling a report that involves over 10 million hits, Google applies what’s called ‘sampling’ to manage the volume. This means your report will be based on a subset (or a ‘sample’) of all those hits to make the data more manageable. If you prefer to get a report without sampling, you can adjust your parameters like reducing the date range to keep total events below the 10M mark. This way, your report still provides reliable insights while keeping within the limit.

[Evelyn]

The person is trying to add GA4 analytics to a Chrome Extension using the Measurement Protocol with gtag, but faced an issue where no event data was being sent to GA despite no errors showing up in the console. The initial attempt used constant values for the measurement ID and API secret in a fetch URL in the Service Worker.

After some adjustments to their code, they were able to solve the issue by directly inserting the values of the measurement ID and API secret into the fetch URL. Thus, the event data began successfully showing up in GA4. The changes showcased that the problem was related to how the constant values were being used in the fetch URL.