Response Accuracy


This chart lets you track the overall performance of your support team, based on how quickly agents resolve tickets everyday. It can be used to identify how easily and quickly your agents resolve tickets on a day to day basis. Ideally, you want your resolved tickets to be high and go along with first contact resolutions and SLA compliant tickets.


Raising red flags:

FCR ↑ Reopens ↑


Try incentivizing with more points for first call resolutions over quick responses.


Create an escalation policy Escalate tickets when customer interactions go up.


Incentivize agents for accurate responses and First Call Resolutions.

SLA low, Resolved low


A dip in resolved tickets could mean that one of your agents may not be available to work. This is probably because you don’t have enough agents taking tickets everyday.

Incentivize agents to respond fast as well as resolve more tickets in your helpdesk.
Reevaluate your SLA policies if current rules are impractical.

SLA low, Resolved high


When the number of tickets is high, but you are way out of your SLA limits, it could mean that your agents are too slow to follow up with customers even if they eventually close down tickets.

Make sure you have your business hours set up properly so timers aren’t ticking during your off-hours.


Try negotiating and setting up a different SLA policy for more serious issues.

SLA high, Resolved low

You might need to reevaluate your SLA policies and make them more stringent.




Response Time


This chart shows you how quickly responses are sent to tickets across your helpdesk. It can be used to compare overall support performance directly between two points in time and also take note of dips. Ideally, you would want first response time to be low, and the red lines relatively closer to them, indicating that there are more first contact resolutions.


Raising red flags:

Average First Response Time (bad)

Average Response Time (good)


When your agents are generally fast, but take a little longer for their reply, it could be because the tickets aren’t getting assigned to them quickly enough

Assign tickets automatically so agents don’t spend too much time picking up tickets.


Incentivize fast responses and first call resolutions.


Average First Response Time (good)

Average Response Time (bad)


When your agents rush and make their first replies, their average responses could get slower when they forget to follow up with existing tickets


Try adding canned responses and solutions to help agents send the right response in the first attempt.


Incentivize First Call Resolutions.


Average First Response Time (bad)

Average Response Time (bad)


When all your response times are taking a toll, it could be because your team isn’t large enough to handle incoming tickets and you might have a scaling problem in hand.

Add occasional agents to your service desk to handle momentary surges in ticket volume.



Average Customer Interactions vs Average Agent Interactions


This chart shows the number of customer responses against number of agent responses. It can be used to find out if your agents are being proactive with their support. Ideally, you want to have fewer agent and customer interactions on each ticket.


Raising red flags:

Average Customer Interactions ↑

Setup a escalation rules number of customer interactions go up on a ticket.


Incentivize first call resolutions using the Freshservice Arcade.

Average Customer Interactions > Average Agent Interactions

Create rules to remind agents about follow ups and reopens that have not been responded to.




Ticket Assignment


This report lets you measure performance in the service desk based on the number of reassigns before tickets get resolved. It also lets you know whether tickets get escalated to a different team member before getting closed. You want this to be low so that tickets gets resolved quickly on average.


Raising red flags:

Number of Reassigns ↑


Tickets get reassigned frequently, when you aren’t categorizing or assigning your incoming tickets properly

Categorize tickets properly and assign them to solution experts.


Create support groups based on expertise with a topic and filter out tickets to each one as and when they come in.


Improve agent knowledge with shared canned responses, and solutions in your knowledge base.