[Noah]

That little exclamation mark in Google Analytics 4 is a data warning indicator. It’s letting you know that there is a significant data discrepancy or issue within that specific report. This could be due to a number of reasons like tracking errors, big changes in website traffic, or issues with data collection. You should investigate further to identify the root of the problem.

[Noah]

It seems there’s a discrepancy between having the GA4 event “ids2_verify_email” show up when you’re testing it and not when it’s run live. This could be due to a few reasons. For instance, users might have JavaScript disabled and hence the Google Tag Manager code isn’t running on their end. It’s also possible that there’s an error in the custom JavaScript variable causing the event not to fire in certain situations. Often, issues like these can be traced back to specific browser or device types, so that might be worth investigating. Lastly, it can sometimes take up to 48 hours for certain events to show up in Google Analytics, although if it’s been a week, this probably isn’t the case. This is a complicated issue and would require more troubleshooting to figure out the exact cause.

[Noah]

Sure thing! While the v1 Beta API deprecates some of the features synonymous with the older Google Analytics API, including the ability to use ‘segments’, it does introduce some powerful new features that might help you out: Filters and Cohorts. The use of the ‘filters’ parameter can essentially recreate much of the ‘segment’ functionality. You can apply these filters to define subsets of your data by including or excluding data based on dimensions or metrics. You’d define filters within the ‘dimensionFilter’ and ‘metricFilter’ parameters of your ‘runReport’ request. Also, the new ‘cohortSpec’ feature can produce cohort analysis reports to help track the behavior of a group of users in your defined cohort over time. Finally, potentially key to your request, you could look into setting up ‘audiences’ in Google Analytics 4 properties, which work like a charm with the new API. You’d use the ‘audience’ feature in your ‘runReport’ request. Check out more in the Google Developers guide.

[Noah]

Connecting refund data back to the original order using the Measurement protocol in GA4 can indeed be tricky, especially considering that refunds often occur beyond the 3-day window. But, there’s a way around it. The timestamp_micros key is actually optional. So, if the 3-day window doesn’t work for you, you can just omit it. Your refund will then be tracked when the hit is pushed. It’s way better than not tracking it at all, right?

As for understanding which acquisition channels are generating the most refunds, a solution might be at hand with data import, even though it’s not part of the measurement protocol. According to Google, the Source and Medium dimensions of the refund data will mirror the campaign attribution and date used in the customer’s last session. So, even if these are different from the original transaction data, you’ll be able to track where the refunds are coming from.

For example, let’s say customer A makes a transaction from a google/cpc on day 1, and then has another session from google/organic on day 2. If you end up refunding the original transaction, the refund data would be attributed to google/organic (the most recent Source/Medium), and the date will be set to the day the refund was uploaded.

It’s a bit of a workaround, but it should help you get a handle on where most of your refunds are originating from.