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The Discrepancy Between Google Analytics 4 API and User Interface Data
Hey there, I’ve been working on automating data collection from a Google Analytics 4 property, and something a little bit odd is happening. You know how when you pull data directly there’s normally no trouble? Well, I’ve been getting some discrepancies when I compare it to the on-site data.
As an example, if I take a peek at some fields (see this image) for February and March, I get 188,213 total sessions from the API data, but checking the Google Analytics user interface itself turns up 189,042. Bit weird, right?
Here’s what’s even more strange: if I simplify the API query and just pull the sessions from February and March, the numbers add up perfectly – I get exactly 189,042. So it appears that adding some dimensions to the query is throwing off the results, and I can’t figure out why!
Can anyone offer an explanation? It’s so important to me that the data is reliable, and it’s kind of hard to trust it when it’s not consistent. Cheers for any help you lot can provide! Check out the image below for better understanding.
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2 Replies
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You might be experiencing a data sampling issue. When you add more dimensions to your API query, Google Analytics sometimes uses a smaller subset of data to give you the result (especially when dealing with vast amounts of data). That might make the result a bit different from the full picture you get when you pull just the session numbers. Worth looking into!
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The data discrepancy you’re experiencing may be due to “data sampling” in Google Analytics. When you add more dimensions to your query, the required computations become complex and Google Analytics reverts to using a sample of data rather than the full dataset to speed up operations. This results in slightly varying data when compared to the full, unsampled data seen directly on the Google Analytics interface.
Alternatively, there could be differences due to the way the API and the Google Analytics interface handle certain metrics, particularly multi-session metrics, for individuals who have had more than one session within the defined period. The discrepancy arises from the difference between a user-centric view and a session-centric view. Some sessions might not contain the data associated with the dimensions you’re pulling, which would make the session not be counted when you pull in the dimensions.
It’s helpful to note that minor discrepancies are expected when dealing with large data sets and complex queries. If precise accuracy is essential, you may need to adjust your API queries or consider a different approach. It’s always a good idea to understand and allow for potential sources of error in your data analysis.
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