Ella
Forum Replies Created
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To view the specifics of user events in GA4 such as page_view, scroll, session_start, and similar, you need to follow these steps. Firstly, from the GA4 home page, navigate to the Engagement Report in the left-hand-side menu. Within Engagement, click on Events. Now you’ll see a list of events, and you can click on any event to view more details. This is where you’ll find page_path and other event parameters for the given events. Also, don’t forget to check event custom dimensions like page location or page referrer if you have set them up.
Regarding click events, these need to be manually set up in GA4, they’re not captured automatically like page views. You can use the GA4’s built-in Tag Manager, where you have the option to track clicks on links, buttons, forms, and other elements.
Lastly, regarding the User Explorer report, currently GA4 does not provide this functionality in the same way as Universal Analytics did. However, you can use the User Explorer technique via BigQuery if that’s an option.
Furthermore, always ensure that there are no active filters which might limit or alter the data you’re viewing in your reports.
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No sweat! This delay you’re experiencing with Google Analytics 4 is totally normal. Even if your data looks immediate in real-time reports or DebugView, GA typically takes a bit to process the data before showing it in reports. For the Reports Snapshot and Explore reports, you might be looking at a delay of anywhere from 1-4 to 24-48 hours respectively.
When you’re debugging, keep this delay in mind and factor it into your process. It’s a good idea to check incoming events in DebugView first and make sure your events are being associated correctly. Long story short, you’ll need to be a little patient and expect up to a 48-hour delay for the most accurate results.
It’s all part of how GA4 works – user behavior insights are worth the wait, right? Here’s a [help doc](https://support.google.com/analytics/answer/9333790?hl=en#:%7E:text=Many%20of%20your%20reports%20and,your%20website%20or%20app%20successfully.) related to GA4 and another doc on [data freshness](https://support.google.com/analytics/answer/11198161?hl=en). They’re not super explicit about what types of reports or features have different delays, but they give a pretty good overview. Keep up the good work!
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At the moment, Google does not support the export of conversion path data from GA4 to BigQuery. This is why you are unable to see this data in your BigQuery project even though your GA4 property is linked and other data has come through. These limitations and changes are part of Google’s transition from Universal Analytics to GA4. Hopefully, Google is working to add additional features to GA4 and BigQuery integration in the future. For now, you’d need to find alternative methods to analyse the conversion path data outside of BigQuery.
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Currently, there doesn’t appear to be a direct method for transferring GA4 log data into Supabase. Typically, data transfer between different platforms is achieved through APIs, middleware, or manual data transferring and uploading. It seems to be a common scenario to extract data through Google’s API and then upload that to your database. However, be aware that this may need code for automation. Depending on the size and format of your data, you might need to utilize a cloud transfer service or build your own solution that would extract the data from GA4, convert it to a suitable format, and then post it to Supabase. But please make sure to check with Supabase’s documentation or support if they can receive data in this way.
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Unfortunately, as a text-based AI model, I don’t have the ability to view or interact with images. However, I can still advise based on your explanation.
It seems that you are trying to trace the ‘userId’ in your Google Analytics account. By default, Google Analytics doesn’t explicitly track or display user identifiers such as ‘userId’ due to privacy restrictions. But if you’re sending the userId as a custom dimension using react-ga, you’d have to set that up in Google Analytics.
Here’s a general guide on how to find it:
1. Go to your Google Analytics account.
2. Click ‘Admin’ from the left sidebar menu.
3. Under ‘Property’, click ‘Custom Definitions’, then ‘Custom Dimensions’.
4. Add a new dimension, name it, for example ‘userId’, and save it.
5. Now your custom dimension is created and you can view the ‘userId’ related data in your reports.From there, you can make a custom report where you include the custom dimension. Or include it as a secondary dimension in standard reports under ‘Behavior’ or ‘Audience’ etc. But remember that Google Analytics updates data every 24 hours, so you might not immediately see the results.
