Understanding Differing Ticket Counts between DatasetsAnswered
I'm currently working on reviewing data from our past year. Simple start is comparing our volume to the previous year. The problem I'm running into is the difference in number presented between the Tickets dataset and the Ticket Updates dataset.
Over in the Tickets dataset, I create a simple query with the following:
Columns: Ticket created - Month
Rows: Ticket created - Year (filtered for only 2019 and 2020)
Over in the Ticket updates dataset, I create another simple query with the following:
Metrics: COUNT(Tickets created)
Columns: Update - Month
Rows: Update - Year
The first thing that popped out was the fact that the Ticket Updates dataset query showed a 3x difference in tickets created for a particular month than the Tickets dataset. Other months also show smaller differences as well (typically less than 10 tickets).
(Note: We moved to Zendesk in the middle of 2019 which may account for the insane difference in the Ticket Updates dataset.)
To troubleshoot, I added the metric COUNT(Tickets solved) to the Ticket Updates dataset query. Sure enough, that brought the inaccurate number more inline with the Tickets dataset count. (There are still minor differences in other counts between the two datasets too.)
But now if you compare the Solved number presented by the Ticket Updates dataset, they don't match (sometimes by nearly 40x) the numbers presented in the Tickets dataset with the following query:
Metrics: COUNT(Solved tickets)
Columns: Ticket solved - Month
Rows: Ticket solved - Year (filtered for only 2019 and 2020)
The reason I've used the Ticket Updates dataset in the past is because I want to show both Created and Solved in charts. But seeing the difference in numbers has me concern as to which is giving the correct numbers I should be looking at, especially once I start adding in other criteria to compare counts.
Could someone help explain why there is a (sometimes jarring) difference in numbers and how I should be comparing tickets created and solved?
@... While I'm not sure of the exact reason you're seeing different Created and Solved Ticket numbers in the Tickets dataset versus the Ticket Updates dataset, I do know that there are slight differences in terms of what each dataset is able to report on that could be causing this.
For instance, the Ticket Updates dataset allows you to report on tickets that have a status of deleted whereas the deleted status is not available in the Tickets dataset. Zendesk's Support team might have a bit more insight for you here.
Since it sounds like you're looking to analyze the current state of past tickets, I'd recommend using the Tickets dataset. I typically only use the Ticket Updates dataset when I want to report on actual update events (such as number of comments, group reassignments, update handle time, etc).
Based on your post, it sounds like your primary use case for using the Ticket Updates dataset was so that you can report on these two metrics within the same chart. You should be able to achieve this using a Date Range Calculated Metric. This is helpful when you want to restrict metrics by a different time attribute within the same query.
Here's an example below which shows a new Created Tickets metric that is based on the Tickets metric and Defined On the Ticket Created attribute (Past Year).
You could then build a similar metric that is based on Solved Tickets and Defined on Tickets Solved (Past Year). Do you think this helps you get the numbers you were looking for?
Thanks for taking a stab at this, @...!
I appreciate your suggestion to use a custom metric. Unfortunately, the queries we created need to have their data manipulated in the dashboards they're put in. So while this is great for the one-off yearly review I'm working on, I would still have to question the numbers I'm looking at in our day-to-day dashboards. (Probably should have mentioned we also look at created versus solved in other places.)
Like you recommended, I'll reach out to Zendesk Support to see if they can provide some clarity. If they are able to shine a spotlight on what's going on (that's not specific to my account), I'll add it to this thread in case it could be helpful for anyone else.
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