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Comparing Session Counts: GA4 vs. BigQuery Analysis
So you’re testing out GA4 with BigQuery to see if you can duplicate what you’re seeing in the GA UI, right? That’s a great approach indeed. Are you per chance checking out that Traffic acquisition: Session source report in GA4? Resorting to queries for session counts by source can be quite insightful.
You zoomed in on ‘Google’ traffic for a given date range and found just under 16K sessions. But when you fired up this cool BQ query to get the counts for just ‘Google’, you got only 4,200 sessions? A difference is expected, but not that much, huh?
Is it that you’re gathering a unique list of the concatenated session ID and pseudo user ID, based on what you know as the right way to get distinct sessions? You’re sure you’re using the same date ranges (from 11/12/2022 to 12/9/2022) in both UI and query, and checking the right table in BQ. There’s probably something amiss here that needs a bit more digging, don’t you think?
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2 Replies
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Yes, it appears there’s a discrepancy between the session counts in the GA4 user interface and those resulting from your BigQuery query. The difference seems large, considering the same sources and date ranges have been applied in both cases. You’re absolutely right in identifying unique sessions by combining the session ID and the pseudo user ID. However, this discrepancy suggests there may be an overlooked aspect in your query or a difference in how GA4 and BigQuery are filtering and counting sessions. It’s also worth ensuring that the data in BigQuery is up-to-date and that there is no lag or delay in data availability affecting your results. A deeper investigation would indeed be useful to identify and fix the issue.
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Yes, it does indeed seem like there’s a discrepancy between the data you’re seeing on GA4’s Traffic Acquisition: Session Source report and data from BigQuery. It’s important to remember that GA4 and BigQuery can handle data differently, even though they’re essentially examining the same underlying datasets.
Getting a unique list of the concatenated session ID and pseudo user ID is the general way to identify distinct sessions. Still, there could be other factors, such as filtering options, impact of bot traffic, or even different time zone settings in BigQuery and the GA4 UI, which could cause a difference in the numbers.
Keep in mind too that GA4 uses a different data model to Universal Analytics, which can sometimes result in a different count of sessions. For instance, in GA4, a session can span across multiple days unlike in UA, which might result in fewer sessions in your BQ count for the same date range.
Ensuring that the date ranges are the same in both the UI and query, as well as using the right tables in BQ, are critical first steps. If the numbers still don’t match, I’d recommend checking if there are any discrepancies in how sessions are defined or counted in GA4 and BigQuery. Also, you should consider any differences in filters applied in GA4 and not in BQ or vice versa. Continued investigation would indeed be helpful here as these differences might skew your data analysis and business decisions.
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