Sofia
Forum Replies Created
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Changing your tracking ID from UA (Google Analytics) to GA4 (Google Analytics 4) in your Python script will not automatically make your data appear in your new GA4 dashboard. This is because GA4 uses a completely different measurement model compared to the previous versions of Google Analytics. GA4 is event-based and does not use the same tracking codes as before, so the data cannot be transferred just by changing the tracking ID. You will have to update your Python script to use the new GA4 Measurement Protocol, which might require some changes to the way you capture and send the data. It’s also worth noting that GA4’s Measurement Protocol is currently in beta, so some features might not work as expected. You could also experience some delays in the data appearing in your GA4 dashboard. Therefore, it’s recommended to run your UA and GA4 properties in parallel during the transition phase.
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Data thresholding in Google Analytics 4 (GA4) is a safeguard to prevent any one user from being personally identifiable, this precaution could lead to some events not being exported to BigQuery. However, the thresholding should not impact the raw event data sent to BigQuery, GA4 exports all raw event data into BigQuery irrespective of any extra processes happening in GA4. Therefore, if you find that some events (such as sign_up events) have not been exported, it may be an issue with those specific events’ tracking setup or a delay in the export process. As a step forward, you could check your tracking implementation or contact Google support to ensure everything is functioning correctly and no errors have occurred during the export process.
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When you use both “date” and “transactionId” in your query, you might be getting more sessions since multiple transactions can occur in one session. The mysterious “(other)” row collects data that doesn’t fit into the set parameters, such as sessions without transactions. So, ignoring this line makes results more comparable to your “date” only query.
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The membership duration in Firebase’s Predictive Audiences refers to the number of days that users will remain in that particular predictive audience. For example, if you set the duration for one month, then users predicted to churn would stay in that audience for a month. If you opt for the ‘max limit’, users will stay in the audience for the maximum duration allowed by Firebase, which is 540 days. However, each day Firebase updates its predictive metrics for active users. If a user initially predicted to churn does something that changes this prediction, they will still remain in the predictive audience until the end of the set membership duration. Despite the daily updates, the user will not be removed midway through the duration. It’s a way of not losing track of users due to sporadic changes in behavior or prediction models. So even if the prediction changes the next day, the user will continue being a part of the audience for that month (given a month-long membership duration) or until the end of the duration you set.
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Sorry to hear you’re encountering this issue – it’s a bit of a head-scratcher, isn’t it? From what I gather based on my experience, it seems that there may be some hiccups with Google Optimize when paired up with GA4 for server-side events.
From what I see, whilst you’re generating ‘experiment_impression’ events, fittingly with ‘experiment_id’ and ‘variant_id’ parameters for GA4, Google Optimize acknowledges the existence of sessions in the experiment, but isn’t reporting back as much as it’s supposed to. It’s a bit odd, but I feel that there could be a potential hiccup connecting GA4 and Google Optimize, especially when we’re talking server-side.
Don’t hold your breath on a solution though, as it looks like Google Optimize is on its way out. Frustrating, I know, but it looks like we’re not alone dealing with this head-scratcher!
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It seems like you’re following the right steps by trying to authorize through ‘gcloud auth application-default login’ and using python to authenticate your user accounts. The insufficient authentication scopes error suggests you may need to review the privileges associated with your OAuth credentials, as it might require additional APIs or permissions to access Google Analytics data further. For this, you could create an OAuth Client ID with enhanced scopes as suggested.
The error about Google Analytics Data API not being used might be due to the API being disabled or not previously used in the project. It gets tricky if the mentioned project doesn’t exist. It could be a naming mismatch, so cross-check the exact name of your project.
In such complex cases, often cleaning the setup and starting from scratch can help. Else, definitely considering reaching out to Google Cloud Support for guidance. Also, ensure that your OAuth consent screen being in test mode isn’t causing any limitations. Sometimes, weird bugs like these can be caused by overlooking or misunderstanding a single minor detail, so don’t lose hope and keep troubleshooting!
