[Li]

Absolutely, here’s the crux of it: the GA4 Measurement Protocol is not the same as the UA Measurement Protocol. It only takes POST requests, with the request body formatted in JSON, and requires a Secret and Measurement ID.

It seems like you might be attempting to mirror GA4’s client-side behavior from your backend; unfortunately, that’s not something it supports. To report events from the server-side, you should be using the GA4 MP API, which is JSON-based and needs a secret and measurement id.

For more detailed information, the official Google docs provide some great guidelines on sending events from the server-side through GA4 Measurement Protocol. You can check it out at,Google DevGuides.

[Li]

At the core of your query, you’re seeking advice on how to automatically import refunds data into Google Analytics 4 using their API. Unfortunately, it seems you’re having trouble because Google Analytics 4 documentation around this is lacking. You’ve found a potential tool in the NPM package ‘@google-analytics/data’ that appears to extract reports from Google Analytics. However, you’re not sure how to use it to upload data. Though I don’t have the exact solution you need, using APIs generally involve making HTTP requests (GET, POST etc) to specific endpoints that server exposes. You could approach Google Analytics support or check out their user community to see if others have had the same issue. It may also be worthwhile researching other similar APIs to increase understanding. Keep experimenting and modifying your script before finalising it, employing trial and error in the process can often provide solutions. A good principle in these scenarios is to break down the problem and try to solve one piece at a time.

[Li]

Gotcha! You aimed to extract just the names of items from your dataLayer, and you were getting an array. But what you wanted was a text list separated by commas. The idea is to convert the array into a comma-separated string, right? If that’s the case, you were on the right track!

Your initial attempt put the entire ‘item_name’ object into your list. To correct this, you can revise your push command to grab only the item names i.e., products[i].item_name, and collect those into your itemlist array.

The code should look like this:

`
var itemslist = [];
var products = {{dl – ecommerce – item name}};
for(i=0; i < products.length; i++){
itemslist.push(products[i].item_name); // just the item name
}
return itemslist.join(','); // join the array into a string
`

So, by correcting the push command and also using the join method, you’ll be able to convert the array into a string where its elements are separated by commas. I hope that helps! Give it another shot!

[Li]

The error message you’re seeing suggests that the ‘google.rpc’ module is missing. This module is part of the ‘grpcio’ package. You’ve already included the ‘grpcio’ package in your code, but you’re still seeing the error, which suggests that ‘grpcio’ might not have been installed correctly.

When working with AWS Lambda, you have to ensure that all your dependencies are packaged within your Lambda deployment package, especially when using libraries that have C extensions, such as grpcio. These C extensions need to be compiled on an environment similar to the AWS Lambda environment, which can be tricky. In order to compile the grpcio library correctly, you could use a tool called Docker which allows you to create a similar environment to AWS Lambda for the compilation step.

One other important thing to note is that some packages like ‘grpcio’ have additional dependencies of their own. In this case, ‘grpcio’ depends on ‘protobuf’ which may contain the ‘google.rpc’ module you’re missing. Ensure you have the correct version of ‘protobuf’ installed in your environment as well.

If this does not work, it could be useful to create a new, clean virtual environment and install your packages there one by one to identify any possible conflicts or issues during installation that might be causing the error.

Either way, you may need to bundle these dependencies with your AWS lambda function in order for it to work correctly.

[Li]

Yes, your understanding is correct. In a .Net MAUI app, you’re intending to send usage statistics to Google Analytics, specifically data regarding screen visits. At the moment, you can transmit event data through the Plugin.Firebase package but are unclear if this function extends to ‘Pages and Screens’. You’ve also discovered that the data is categorized by page title and screen class, the latter you presume to supply. However, the issue arises on how to assign the screen name against ‘Not Set’.

[Li]

No worries, I see what you’re getting at. It can get a bit tricky trying to handle multiple dimensions at once with BigQuery. The idea is to sift both ‘page_path’ and ‘previous_page_path’ out of the data, right? Here’s how you might fix that “hiccup”:

When filtering based on a dimension, for instance, ‘page_path’, you can do an UNNEST and then a subquery. Check this out:

SELECT 
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'page_path') AS page_path,
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'previous_page_path') AS previous_page_path
FROM project.dataset.events_*

When you include the WHERE clause to filter for ‘page_path’ = “/”, you were on the right track, only you can’t directly access the alias in the WHERE clause. BigQuery wants you to jump through a hoop first. You should wrap the original query as a subquery, like so:

SELECT *
FROM (
  SELECT 
    (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'page_path') AS page_path,
    (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'previous_page_path') AS previous_page_path
  FROM project.dataset.events_*
) 
WHERE page_path = "/"

It’s basically nesting those dimensions in another SELECT. This way you sidestep the restriction and can filter based on both dimensions ‘page_path’ and ‘previous_page_path’. All about syntax fun, right? Hope this helps level up your data mojo!

[Li]

It seems like there’s a bit of a misunderstanding about how to effectively debug; despite its name, Debug View might not be the most efficient tool for you. It’s known that GA4’s interface has some bugs, so ideally you don’t want to rely on it when there are better options available. Most in the industry actually avoid using the debug view in GA4, as it was pulled directly from Firebase without being aptly modified for GA4. Seems like they dropped the ball a little on that one. For a more detailed answer on how to troubleshoot this problem, check out this link: All events duplicated in Google Analytics 4 Debugger