In this recipe, you'll learn how to create a report to show the number of comments your agents have made on tickets each day.
What you'll need
Skill level: Easy
Time Required: 10 minutes
- Zendesk Explore Professional or Enterprise
- Editor or Admin permissions (see Adding users to Explore)
- Ticket data in Zendesk Support
How to create the report in Explore
Use the following steps to create this report in Explore.
- In Zendesk Explore, click the reports ( ) icon.
- In the Reports library, click New report.
- On the Select a dataset page, click Support > Support - Updates history, then click Start report.
- In the Metrics panel, click Add.
- From the list of metrics, choose Comments > Agent comments, then click Apply.
- In the Columns panel, click Add.
- From the list of attributes, choose Time - Ticket update > Update - Date.
- In the Rows panel, click Add.
- From the list of attributes, choose Updater > Updater name, then click Apply.
- Click the Update - Date attribute from the columns to filter it to your preferred dates.
- By default, Explore chooses a column chart to best display the data. To change this, click the Visualization type () icon and choose Table.
- You'll see something resembling the following table:
- By default, Explore lists all users in your account. Now, you'll add a filter to show only the names of agents. In the Filters section, click Add.
- From the list of attributes, choose Updater > Updater role, then click Apply.
- Click the Updater role filter, select Admin and Agent from the list, then click Apply.
- The report was, by default named New report. Click the New report text and replace it with a title of your own.
- Finally, click Save.
Hi Mark, is there a difference between using the "Obsolete - Updater Name" and "Updater Name" attributes for a query like this?
How are side conversations via Slack counted? Are they counted as an agent comment? What about replies to the Slack thread? How are those counted? Or are side conversations not counted towards an agent comment? Are they counted as an internal comment?
Are comments in Messaging tickets counted for this report?
I have a report that uses the COUNT(Agent comments) property alongside the D_COUNT(Tickets updated w/comment) property to count the number of messages an agent sends and the number of tickets they update by sending a message or making an internal comment.
However, one agent yesterday had the value of "3" for both metrics. This doesn't seem possible if Messaging ticket comments are included, since he made 3 comments in just one Messaging conversation.
I think it is best if I see the report you currently have where you added these two metrics so I can better understand the issue that you seem to be having from your end. I will create a ticket on your behalf. Kindly wait for an email notification regarding this ticket. Stay safe! :)
Hi can you help me w/ this one. I wanted to count the solved tickets in real time view and count the other agents internal comment w/ the same ticket.
The closest to a real time report on solved tickets is the widget in the Live dashboard in Enterprise Explore plans (the Solved tickets widget displays tickets that were solved out every 30 minutes). To report on agent internal comments, you will need to create a separate report under Updates history dataset, similar to the recipe discussed above. You can slice the metric Internal comments by Ticket ID and Updater name to see the names of all the agents that added an internal note to each ticket; then filter the report by ticket status to only displayed those that are in solved status. Note though that Explore datasets are updated every hour (sometimes, up to 2), so the data displayed in your Updates history reports aren't in real time.
I hope you can help, please. We have many different teams working on tickets which are being re-assigned from 1 team to another. To measure my team's productivity accurately, I want to set up a report on their "touches" on the ticket. So for example:
Anna/Ben = Support
Victor = Retentions
1. Anna picked up a ticket in the Support queue and sent few replies to the customer, made calls or left internal notes
2. She then passed the ticket to Victor in the Retentions queue; Victor worked on the ticket and before he solved it in his queue, there were few internal re-assignments back to Support team
3. Ben who is also in Anna's team worked on the ticket
4. Ben then passed it back to Victor who solved the ticket in his queue
How do I calculate this ticket as Support = 1?
I got to the point where I can d_count agent's updates on the ticket to show me 1 even if they made quite a few updates within that ticket, but I can't figure out how to calculate Anna and Ben's updates as 1 = Support.
Could you please help?
I am running into an issue within Explore. I am trying to determine how many comments a specific agent makes within a given week. I have an agent who did not work or comment on anything for a particular week but the metrics are showing 207 comments made by them for that week.
I have a similar question to Marta Lagut - would love to know the best practise for reporting on that kind of data.
Same here. It's been very hard for us to measure agent touches with the different channels, side conversations, etc. I would also love a recipe similar to what Marta Lagut suggested so we can accurately measure agents' contributions on any given day.
I'm afraid I can't see from the list of metrics; 'choose Comments > Agent comments, then click Apply'. Comments or Agent Comments don't appear in the search bar or from the list of options in 'Metrics'. Please explain how I can get to them.
The same goes for 'Updater name', I can only find 'Assignee name'. Is this the same thing?
Hi Tom Castle, it's possible that you're in the wrong dataset. When you start creating your report, make sure to choose the Support - Updates History dataset. The metric and attributes from the recipe should then be available.
We attempted to run this report however our Jira integration is added to the count of public replies, and we use a webhook to auto send those replies, is there a way to discount those replies so we get a true understanding of agent productivity.
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