I will try to check later on my own reportings if I can find something similar,
But I just wanted to also mention some things for you to consider:
1) You mentioned removing callbacks as they are reflect as "inbound/outbound". I don't think you should remove them, as callbacks are originally an inbound call that just transforms into a callback.
2) Something else to check, maybe some of your interactions are being routed back to the queue, and this might cause the "Offer" metric to count it twice? (I haven't checked, but maybe take a look at this)... So if that's the case you could simply have some interactions counting twice, so that's why the number of Offer is higher than the total number of interactions that you see on your export.
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Marcello Jabur
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Original Message:
Sent: 06-02-2026 22:24
From: Robert Brown
Subject: Variance in figures in 'Queue Performance' and in total interactions when exported
Thanks for the responses. To clarify I am comparing figures from 'Queue Performance' in the analytics workspace.

Then if I click through to see the individual interactions by clicking on queue name>Interactions then export to excel I get a total of 363 interactions. If I then filter the raw data to remove outbound (as we do have agents calling out from this queue) I get 235. If I remove callbacks, which reflect as inbound/outbound, I get 209.
I am struggling to get my export of calls to match the total. I even got copilot to run over the data and asked it to apply different filters to find a combination that would match the 226 and it couldnt. I can try drilling down to different timeframes to see if it can help pinpoint where the issue may be but curious if anyone else has any ideas.
Thanks again for any insights.
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Robert Brown
Member Advocate
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Original Message:
Sent: 06-02-2026 20:27
From: Marcello Jabur
Subject: Variance in figures in 'Queue Performance' and in total interactions when exported
Hey Robert, if you could give more details and examples (Which metrics exactly are not matching, etc.), maybe someone will be able to see something that you are not seeing.
Also, have you tried investigating by just looking at a smaller sample? Looking at the whole day (350 interactions, assuming that's the number for the whole day) might be a little hard to see which interactions are not matching, etc. But if you try to check for just 1 hour, or maybe a 30 minutes interval, the difference might only be for 1 or 2 interactions, and then you can check 1 by 1 to try to identify which interaction is missing on the source that has a lower number, etc.
Edit: Also, something else to keep in mind.. Are both sources using the same timezone? Make sure that the data exported is using the same one you use on the Genesys interface, otherwise you could see some interactions being counted towards the wrong day without noticing, etc.
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Marcello Jabur
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