Gabriel
Forum Replies Created
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No worried at all! It’s pretty simple to do this. Just like Universal Analytics, Google Analytics 4 (or GA4) also allows you to set fields in Google Tag Manager. In the configuration tag for GA4, you’d see a familiar option “Fields to Set”. It’s totally the same process – you just pick the parameter name that you have in mind (either a unique one or a set name that Google already uses), then just pass your variable in as the value.
The only extra step you have to take here is to create a custom parameter. But hey, it’s not rocket science. Go into the Configuration menu in GA4, and you’ll find the option to create the custom parameter. Once you’ve done that, you’re all set! Your created parameter can now be utilized in your reports. Easy peasy, right?
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It sounds like the issue you’re facing could be due to differences in data processing between GA4 and BigQuery, like maybe filtering bots and spam, or adjusting for unique users. You may want to ensure that you’re using the same parameters for your GA4 queries as your BigQuery ones. Also, let’s try looking into the exact metrics and dimensions you’re querying on both platforms, as there may be differences that are causing the discrepancy. Keep at it, and don’t hesitate to ask more questions!
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The discrepancy you’re experiencing between the Looker report and your Google BigQuery results could be due to a number of reasons. A likely factor could be how the ‘views’ are defined in each platform (Looker vs Google BigQuery). There may be differing criteria for defining a ‘view’, thus contributing to a difference in counts. For instance, unique views could be counted in one platform while total views, including multiple views by the same visitors, could be counted in the other. Also, there could be a mismatch in the date filtering between the platforms or the data may not have been updated synchronously on both platforms, causing an apparent discrepancy. It could also be a result of Looker using a different query or join-condition to compute the total views. It might be helpful to directly compare the Looker query with your BigQuery query to identify potential differences.
Moreover, the data you’re querying with BigQuery could potentially be an unclean dataset, and might require some preprocessing to match the criteria applied in your Looker-Studio report. This could include removing duplicate entries, filtering out irrelevant data, or transforming the data into a suitable format. Finally, it could be a simple error in your BigQuery syntax leading to incorrect results being returned. A thorough review of the code and comparison with Looker’s query could help identify and fix the issue.
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In Google Analytics 4 (GA4), the concept of “Goals” from Universal Analytics (UA) has been replaced with “Conversions.” Therefore, you may not find the old ‘goalCompletionAll’ or similar goal metrics in GA4. Instead, what you need to look for are “Events” that you mark as “Conversions.” You can decide which actions on your site (like purchases, form submissions, etc.) should be marked as Conversions, and then track those in GA4 accordingly.
As for pulling the data in SSIS, first ensure your GA4 property is properly set up and collecting the data you need. Make sure any designated conversion events are correctly being tracked. Once this is done, you should be able to extract the data using the same or similar SSIS procedures you used with UA. However, please note, the structure of the data may be different given the move to event-based tracking. This might require adjusting your SSIS package to correctly pull in and interpret the data.
