At a high-level, an agent touch is an operation performed by the agent on a ticket. For example, it could mean that the agent:
- Added a public or private comment to the ticket
- Changed a ticket field, for example the ticket group
- Changed the status of the ticket, for example from Open to Solved
The method you'll use to determine agent touches will depend on your business needs. In this article, you'll learn about how you can use Explore to analyze agent touches in a few different ways. The examples assume you have some familiarity with creating Explore queries. If you need some help, see Creating queries.
This article contains the following sections:
Analyzing ticket comments
If you want to measure agent touches by the number of comments your agents make on tickets, then Explore has you covered. The ticket updates dataset contains a built-in metric that measures this when you add it to a query. You can add attributes to slice this number however you want, for example by ticket ID and subject.
Example
This simple Explore report displays a table showing the your tickets and how many agent comments they received.
To create a report to analyze ticket comments
- Create a new query using the Support: Ticket updates dataset.
- In the Metrics panel of the query, add the Comments > Agent comments metric. Explore displays the total number of agent comments received for all of your tickets.
Tip: The Explore ticket updates dataset might contain a lot of data causing your queries to take a long time to return results. Consider adding a filter like Time - Ticket update > Update - Date to reduce and focus the results returned by the query. For more information, see Working with query filters.
- To break down the number of comments by ticket, add the attributes Ticket ID and Ticket subject to the Rows panel of the query.
Explore displays a table showing all of your tickets broken down by the number of agent comments (each comment counts as one agent touch).
Analyzing ticket updates
Sometimes, you might want to report all updates made to your tickets, not just comments. For example, other updates might include changes to ticket status, priority, assigning the ticket to someone else, and more. Again, the ticket updates dataset contains a built-in metric that measures this when you add it to a query. You can add attributes to slice this number however you want, for example by ticket ID and subject.
Example
In this example, you'll create a query that shows all updates to all of your tickets. You'll then add attributes to slice this number by the date of the update, the ticket ID, and the person who made the update.
- Create a new query using the Support: Ticket updates dataset.
- In the Metrics panel of the query, add the Updates > Updates metric. Explore displays the total number of updates made for all of your tickets.
Tip: The Explore ticket updates dataset might contain a lot of data causing your queries to take a long time to return results. Consider adding a filter like Time - Ticket update > Update - Date to reduce and focus the results returned by the query. For more information, see Working with query filters.
- To break down the number of updates, add the attributes Update - Date, Ticket ID, and Updater name to the Rows panel of the query.
Explore displays a table showing all of events where at least one ticket update was made, broken down by date, ticket ID, and the name of the person who made the update.
Analyzing tickets with low agent touches
Explore records the number of agent replies it took to solve a ticket into the following brackets:
- One-touch tickets: Tickets that were solved with only one agent reply.
- Two-touch tickets: Tickets that were solved with two agent replies.
- Multi-touch tickets: Tickets that were solved with more than two agent replies.
Example
In this example, you'll create a query that shows the number of one-touch tickets created each year by your agents.
- Create a new query using the Support: Tickets dataset.
- In the Metrics panel of the query, add the Agent replies distribution > One-touch tickets metric. Explore displays the total number of one-touch tickets in your account.
- To break down the number of one-touch tickets by year, add the attribute Ticket solved - Year to the Rows panel of the query.
Explore displays a table showing the number of one-touch tickets in your account each year.
6 Comments
Can you please define what is counted as a "Touch" in the following metrics? I have reviewed our metrics and based on the initial percentages, it appears this only counts public agent replies.
Hi Chanteena Murphy! Taking a look at the formula used for the Agent replies distribution > One-touch tickets, Two-touch and Multi-touch metrics, I can confirm that these metrics are based on Zendesk's Agent Replies metric.
The Agent Replies metric will only include the number of public replies added to a ticket by an agent. This help article is a really a helpful resource for identifying what each metric means in Explore.
Hi! Is there a way to understand ticket touches for tickets submitted by an end user, not just those created by agents? I'd like to understand the number of tickets submitted to our team and the breakdown of touches between the ticket's submission and it being submitted as closed.
Hi David Reed! These queries should return results for both tickets that were created by the end-user as well as the agent.
However, if you're ultimately looking to report on the number of touches per ticket for both the end-user and the agent, there are a few other comment-specific metrics that you could look at.
You'll find these metrics under the Comments section in Metrics.
Hi team - I'm just looking into tickets that may have multiple ticket touches, do you have any "How To" documentation on how to create a trigger for tickets with 4+ ticket touches, so I can create a view with all those tickets?
Hi Matt - If you'd like to create a View based on multiple touch tickets, the best way to accomplish this would be to first create a trigger that adds a tag based on the number of Agent Replies.
The Trigger itself would look something like this:
From there, you could then build a View that looks for tickets with the specific tag you're adding in that trigger and any other criteria you'd like to build into this view (i.e. ticket status).
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