[Evelyn]

Indeed, your understanding is almost spot on. For an efficient tracking in GA4, it’s better to include the item list data in the add_to_cart event. The reason being, it creates a chain that helps identify how users are interacting with the items and from where. This chain is useful in understanding user behavior as it links back to where the initial add_to_cart action occurred.

Also, exploring the GA4 Item Lists report to its full potential often requires the integration of add_to_cart, checkouts, and purchases data. This data helps in giving a holistic picture of how items are performing. Tracking the source of add_to_cart events on your end is advantageous, as it strengthens this chain of user behavior data.

Now regarding the inclusion of item list data in the add_to_cart event based on whether the list supports this action or not, remember the main aim is to capture as much information as possible about the user’s journey. So, if the item list supports add_to_cart action, it makes sense to include this data. Even if the list doesn’t directly support this action, if the user traffic arrived at the product page from this list, this data can still provide valuable insights.

There isn’t a concrete documentation available that talks specifically about passing this data along. However, plenty of articles and documents are available online that discuss GA4 implementation and its best practices in bits and pieces.

And, yes, your suggestion of linking each item in a purchase back to where the add_to_cart action originated from is valuable. It will bolster your understanding of user behavior and preferences, potentially allowing for more effective marketing and sales strategies.

[Evelyn]

The issue you’re experiencing with missing NULLs in columns in the downloaded JSON is due to how JSON handles NULL values. In JSON, if a field has a NULL value, it’s often simply not included in the output. As a result, when you download your BigQuery results as JSON, columns that only contain NULLs seem to disappear. As for the changing order of columns, JSON objects are an unordered collection of key-value pairs. Upon re-importing your JSON data, BigQuery determines the column order based on the order it encounters the keys in the JSON file. One workaround to maintain a steady column order could be to create a view in BigQuery with columns in a specified order and then upload your JSON data into that view. This problem has much to do with the way BigQuery deals with data imported from JSON files. To maintain the same structure, some users apply extensive preprocessing before uploading it to BigQuery or utilize an intermediate system that is able to better handle JSON data.