[Brett]

Funny, I had the same question too! After some consideration, I personally decided to go with Option 2. To me, ‘view_item_list’ seems to suggest a product listing page or a section of recommended products. The only downside I see is it might overstate the views for the main product. But then again, it’s all a matter of how you interpret the data, isn’t it?

[Brett]

It seems like you’re trying to capture Google Analytics events from the network logs of a website, but you’re running into a problem where the events don’t appear when you automate the process with Chrome, despite appearing when you track them manually. You’ve already turned on your network and performance logs, which was a good initial step. The issue might be related to the settings or it could require more advanced modifications. The code you shared takes a look at the performance logs, scanning for messages that contain both “https://analytics.google.com/g/collect” and the specific Google Analytics event. If the event isn’t found, it returns false. One possible solution could be to double-check whether the events should in fact be part of the performance logs, as well as to validate if the URL and event string you’re using are absolutely correct.

[Brett]

For the remove_from_cart event in GA4, you should only include the item that was removed from the cart in the items array, not what’s left. I know it’s a bit confusing, but I hope that clears it up for you!

[Brett]

The differences in data you’re noticing between Google Analytics 4 (GA4) and Universal Analytics (UA) could indeed be due to data sampling. Sampling is a method Google uses to generate quicker reports. For large data sets, it only processes a portion of the data (sample) instead of the entire data set. One way to minimize the effect of sampling is to reduce the size of the data you are requesting in each API call. In your code, you are currently requesting to pull 100,000 rows per call. This could potentially cause sampling, as Google may decide to sample reports with large amounts of data to reduce processing time. Try reducing the limit value in your request to a lower number and see if that reduces the discrepancy between GA4 and UA data. Remember to adjust your offset accordingly, to ensure you are collecting the entire data set across multiple API calls.