Can't correct respondent funnel and distribution data? | XM Community
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There seems to be a huge flaw in the functionality of the respondent funnel as there is no way to correct inaccurate data if there was mistake on the initial distribution data. This is means we have no way to create accurate dashboards that involve distribution data. 

I’m hoping someone can help as we use the response funnel data to create response rates which are very important to many our of survey clients. We accidentally left out an embedded data field in one of our contact upload and so it was missing from the distribution data when we did the send. 

Now we have no way of correcting is because Qualtrics says all distribution data is point in time and can’t be changed. But if the data exist in the back end of the platform in the respondent funnel data table then there has to be way to edit it. 

Has anyone had this issue and found any way to correct this? 

No, definitely a flaw. Another flaw - it’s only available for reporting for 13 months of history and then it disappears. So if you want to compare response rates year-over-year, tough luck.

We are working on getting this data synched to our data lake so we can do historical distribution reporting outside of Qualtrics.

Best workaround that we have found is to add filters to remove what yo do not want to see. Not a solution but more of a workaround...

Yes, this is an issue with the respondent funnel. It is pretty much an untouchable datasource that requires a lot of escalations to try and have their engineers delete or change any of the data.

It sounds like the issue is that you sent your distributions with data that was either wrong or changed over time. One potential way to get around this would be to store your transaction data in a separate data source like an Imported Data Project, and then join the respondent funnel dataset to that IDP. You would just want the transaction’s unique identifier set up as a respondent funnel field, and then use that unique identifier to join to the IDP which brings in the rest of the data about that transaction. This requires using the data modeler for your dashboard dataset.

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