[William]

Yes, it’s possible that there may be a conflict or a bug causing your website to be laggy and unresponsive. Given that it’s only affecting people using Chrome on Apple M1 or M2 chips and seems linked to your GA4 tag, it might be an issue related specifically to that combination of circumstances. It could be the GA4 tag scripts are causing extra load on this hardware and software combination, leading to unresponsiveness. Perhaps a script isn’t well-optimized for Apple’s processors or there’s an issue with memory allocation. It might be worth reaching out to Google’s support, detailing these specifics to help diagnose the issue.

[William]

The issue likely lies in how your custom event parameter is interpreted by GA4 – it’s possible that “event_params.app_version” isn’t defined as a dimension in GA4. You might need to manually configure it in GA4 as a custom dimension first before using it in the JAVA library. Try defining app_version as a custom dimension in your GA4 dashboard, relaunch your app, then you should be able to access it as expected.

[William]

You need to use dimensionFilter again, rather than metricFilter, to filter by the “userId”. The “userId” is a dimension (a characteristic of your users), not a metric (a measurement of their behavior). Also, make sure the fieldName value is correct for your user ID.

[William]

Sure, your users’ identifiers should stay consistent, as they are tied to the device and browser, not location. In GA4 and UA, you might be able to create a specific filter by comparing users’ first visit location with their current location. This is a bit tricky but definitely doable. Reach out if you need more help!

[William]

From your query, it appears you’re not seeing the ‘store code’ when a button is clicked in your GA4 data. You’ve already set up the Google Tag Manager but GA4 is not reflecting some information. Implementing extra JavaScript code as you’ve shared indeed can provide a solution. However, I understand that you’d rather have a solution from within the GTM. Unfortunately, without detailed information or error messages, it’s challenging to provide a precise solution. It’s crucial to revise the setup and possibly seek local troubleshooting. A common pitfall could be that a data layer variable defined for the ‘store code’ is not correctly set up or that value is empty/not captured for the clicks. Please ensure the data layer variable for ‘store code’ exists and is accurately capturing data.

[William]

The issue seems to stem from the new dependency com.mparticle:android-googleanalyticsfirebasega4-kit:5+ that you’ve added. However, these error messages could be just warnings, indicating that these specific libraries were not found. This might be the case if you do not have these libraries (Flurry, Google Analytics V3,V4, and so on) as dependencies in your project. If your app is functioning correctly, these messages may not be a cause for concern. However, if you are running into issues with your app’s functionality, you might need to look into these dependencies.

For instance, the message Apptimize: Apptimize did not detect Flurry. If you are using Flurry, then the most likely cause is ProGuard. Please consult the Apptimize docs for how to adjust your ProGuard configuration. indicates that the Apptimize library did not find the Flurry library in your project. If you’re not using Flurry, you can safely ignore this message. But if you are using Flurry and Apptimize can’t see it, then you need to inspect your ProGuard configuration because it may not be properly configured to keep the Flurry classes from being obfuscated.

The ProGuard configuration you’ve provided seems to be set up correctly and in line with the guidelines provided by mParticle on their GitHub page. If you’ve already tried tweaking the dependency versions and explored the ProGuard rules, then reaching out to support is a justifiable step. It would help if you got the exact dependency tree and their specified versions.

[William]

Google Analytics 4 should ideally be able to read data irrespective of whether dataLayer.unshift() or dataLayer.push() is used, as it is designed to process arrays and objects in the data layer. However, the order in which events are processed could be impacted. Push() adds the data to the end of the dataLayer, whereas unshift() adds the data to the beginning. This could potentially lead to issues if other scripts or tags depend on the order of the data in the dataLayer. Therefore, while it may appear to work initially, it might still lead to unexpected behaviors down the line.

[William]

Certainly! It’s not uncommon to face a hiccup or two when migrating from Universal Analytics to GA4, especially with the measurement protocol currently being slightly limited. This just means that you won’t be able to send over all the types and amount of data you used to, at least for now.

Got some feedback about this? Great – the Google Analytics team could use it. You can quickly share your thoughts via this [support form](https://developers.google.com/analytics/devguides/support). Your voice matters and who knows? It might just tip the balance to speed up the process. It’s all a part of the ride, so enjoy the journey as we navigate through these evolving technologies together.