[Gurdeep]

Hey there,

Rest assured you’re not alone in your dilemma. Although there doesn’t seem to be a specific .Net NuGet package for Google Analytics 4 out there, you can still manage to work with it from a different angle.

It’s noteworthy to delineate that a .Net package will likely be helpful only if you’re after server-side tracking via the measurement protocol. And from what Google has put forth, it’s not particularly tailored for that. I even wrestled with the challenge myself and ended up crafting a personal solution for cross-tracking some events.

Nevertheless, the main tracking isn’t as dependent on it. Instead, directing your attention to implementing GA4 in JavaScript might be the way to go. You’d be looking at using gtag, Google Tag Manager, or server-side Google Tag Manager.

Hope this gives you a start in the right direction. Best of luck with your project!

[Gurdeep]

Currently, as of 2022, Google Analytics 4 (GA4) does not have the same kind of filter functionality that Universal Analytics (UA) has, such as search-and-replace filters to modify data. You can’t directly create a filter in GA4 to append a certain string before the page view paths. However, you can use GA4’s advanced event modification capabilities to achieve similar results.

You’d need to utilize GA4’s “Modify events” feature. You could create a new event parameter, let’s call it “modified_url”, that combines the “/from-somehost” string with the URL, based on the condition of the host being “somehost.org”. Then, in your reports, you would use this new parameter to track the page views.

Remember that any changes you make would only apply to data going forward and not to historical data. It’s advisable to consult with a professional or do thorough research before making these changes as they could dramatically affect your data reporting.

[Gurdeep]

Regrettably, audience data including user_id or user_pseudo_id is not directly available in GA4 reports or via API at this time. GA4 doesn’t have the capability to export audience memberships by user_pseudo_id to BigQuery. This differs from Universal Analytics, where you could send custom dimensions to capture audience data. However, you may be able to approximate it by setting up custom events or user properties that align with the way your audiences are defined. Ensure to keep your site’s privacy policy and data compliance in mind when doing this. Google occasionally updates and adds to their features, so it may be possible to get this information in the future.

[Gurdeep]

Unfortunately, at this point in time, Google doesn’t provide a straightforward solution to import historic data from Universal Analytics to GA4. The “Import from Universal Analytics” button is actually for bringing in goal configuration and not historical data. Currently, even if you’ve linked GA4 with Universal Analytics, old data from Universal Analytics won’t get migrated to GA4 – they exist separately.

Google has pointed out that GA4 is designed with different architecture and data models in mind, hence, a direct import is not feasible. However, GA4 does offer Data Import feature where you can upload CSV files for data like products, refunds, user data and campaign data but not historical user behavior data.

Also, please be aware that despite setting up a new GA4 property, your Universal Analytics properties will continue to collect data independently, so you’re not losing any data during the transition, and you can still reference old data.

[Gurdeep]

The “91471” you’re seeing is likely not a city, but a ZIP/postal code, hence it’s appearing as a number. Google Analytics attributes traffic to the location of the internet service provider (ISP), not the actual physical location of the individual accessing your application. It’s highly likely that the ISP is based in Germany, even if your users are not. The “91471” may also could be related to an anonymization of user data that Google Analytics applied, in compliance with data privacy regulations, like GDPR in Europe. That being said, precautionary measures like multi-factor authentication and password changes are always a good idea when any suspicion is raised. It would also be beneficial to further investigate on your server logs for any irregular login behavior.