[Thomas]

This discrepancy might be because Google Analytics 4 and BigQuery handle calculations differently. GA4 might deduplicate users based on user_id and device_id while BigQuery’s raw data won’t do that automatically. There could also be some processed metrics in GA4 that BigQuery doesn’t have. Some sessions might not have made it due to data latency in exporting to BigQuery or other technical issues as well.

[Thomas]

When using event-scoped dimensions, as in your case with exp_bucket, Google Analytics 4 executes queries at the event level rather than user level. This difference would explain why your user-total and funnel step data appears as 0.

A possible solution could be to redefine your dimensions as user-scoped. This can be achieved by storing the exp_bucket value in a user property when the experiment event is fired. Then, you can use this user property as the dimension in your reports, which would be a workaround for your current issue with user totals returning as zero.

Another way to handle this is by redefining your data pull to accommodate a user-level analysis. That means changing your dimensions attribute to something like dimensions: [{ name: 'userPseudoId' }], and then grouping by the exp_bucket column in your results.

Remember that it’s important to use the appropriate scope (event or user) for your analysis as both have somewhat different use cases. User-scoped dimensions would be more suitable for cumulative data across all the user sessions, while event-scoped dimensions would be more appropriate for data related to individual sessions or page views.

Regarding the idea of creating “ab_test_lane_[1|2|3|4|5]”, consider the scale of your implementation. If you have enough lanes that mapping won’t be an issue and the experiment configurations don’t overlap, this could work. However, you’ll need to ensure that all future experiments are carefully mapped to the correct lane to avoid conflict, which could be a complex and error-prone task.

[Thomas]

Sure, what you’re doing on your site sounds pretty spot on from my perspective. On my site, customers can add or remove items from their cart both from category & search listings and the product details page. When a customer interacts with the category or search listing, I include the item_list_id and item_list_name, but I don’t do this on the product details page. Similarly, I don’t pass this information when a customer tweaks their cart contents, although I do fire off a view_cart event.

And don’t worry about storing the URL – Google Analytics has it covered. The platform knows the URL of every page that triggers an event, so it’s not something you need to worry about.

[Thomas]

Yo, it’s totally possible to have one unified GA4 setup for both your landing page and web app. But considering they’re both doing their own thing, splitting your web streams into two tracks might give you a clearer picture of what’s happening where. In the end, it’s all about what gives you the best insights for your biz. Peace.

[Thomas]

As of now, linking your Android and iOS apps directly to Google Analytics 4 (GA4) without Firebase appears to not be possible. Google has integrated Firebase into its data collection methodology for mobile apps, making it an integral part of the process. Firebase is essentially the SDK that links your app to GA4. This means that if you want to use GA4 for your mobile apps analytics, you’ll have to integrate your app with Firebase first. We recommend checking Google’s official documentation regularly for any updates regarding this.

[Thomas]

Setting up Google Analytics 4 for a multilingual site involves several steps. Start by signing into your Analytics account and setting up a new property for actual data. As you input the property details, ensure that you select the correct timezone and currency for accurate tracking. Once you’ve successfully created the property, you can proceed with creating the data streams. Since you are working with a multilingual site, it would be ideal to create a separate data stream for each language variant of your site.

To exclude known networks like office or local host, you would have to set up ‘IP filters’. Unfortunately, as of now, Google Analytics 4 does not support IP exclusion directly. However, you can set up a workaround by using Google Tag Manager in conjunction with GA4. In it, you’d set up a variable that obtains the visitor’s IP address, then you’ll set up a trigger that fires when the IP address matches those you’d like to exclude. You could then set your GA4 event tag not to fire when this trigger fires.

Please delegate this process to a qualified professional because it involves reading your visitors’ IP addresses, which may have legal implications depending on your jurisdiction.

Remember, GA4 is quite different from the previous versions regarding the setup and how data is processed. It’s extensively event-based, meaning you’d need to manually set up a lot of event tracking parameters that were automatically tracked by Universal Analytics before. Be sure to explore Google’s skill shop for courses on GA4 to help you get a deeper understanding of how to work with this new version.