Performance metrics

Performance and productivity metrics tell you how quick and efficient your agents are with respect to solving customer problems. Quantitative metrics like these help you draw important insights to improve agent and team accountability, implement new support tools and processes, and even predict future workforce requirements. We've divided the metrics in this guide into basic, intermediate and advanced based on the complexity required in tracking them.

Basic metrics

Monthly ticket volume

It refers to the total number of support tickets received by your company each month. If there is an increase in the number of times customers contact support, it indicates that you need to drill down deeper to find out why this is happening. You should analyze if there are any problems with your product or service, if the quality of your customer service is up to the mark, and if your existing resources have been of help to customers.

Average first response time

This metric tells you how long it takes for your agents to send the first reply to customers. It gives you an idea of how quick your agents are in responding to customer complaints. It is recommended to also analyze individual tickets that had a high first response time, and identify where the lapses lie.

Average response time

Knowing the average time your agents take to respond to a customer's message gives you a good estimate of how quickly your agents are able to prioritize and respond to customer issues. By comparing the average response time over a few weeks or months, you can identify new problems in your support process, and work on improving them.

Number of resolved tickets

This refers to the number of resolved tickets in your helpdesk over a specified time period. By comparing the percentage increase or decrease over previous weeks/months/quarters, you can draw data-driven inferences on your support team’s performance and their ability to resolve customer problems quickly.

Number of unresolved tickets

This tells you how many tickets in your helpdesk went unresolved over a specified time frame. By analyzing specific tickets and the agent replies to them, you can narrow down on the reasons why they didn’t get resolved. Based on this, you can make changes to improve the quality of your agent responses.

Average resolution time

This is the average time taken by your support agents to resolve a ticket. The average resolution time tells you how strong your team’s product knowledge is, helps you gauge how well-staffed you are, and whether you are providing your team the right tools to help them resolve tickets faster.

Number of support tickets by type

In order to understand what kind of issues are reported the most, you should also analyze the breakup of support tickets based on the type of issue. For example, a software company can have categories like bug reports, feature requests, refund issues, and more. By seeing the exact split between multiple categories of problems, managers will be able to find out what kind of issues are the most prevalent.

Channel attribution 

You can use the channel-wise split of all incoming support queries to identify the channel that is most preferred by your customers. Strategic decisions can then be taken to improve response times on that channel. For example, if a majority of your customers reach out on social media, you can hire skilled agents to exclusively handle social channels like Facebook and Twitter.

Top support agents leaderboard

A leaderboard with all your agents ranked on the basis of performance metrics such as individual response times, resolution times, FCR and CSAT  helps maintain agent accountability and motivates them to do well and stay on top of the charts. 


Intermediate metrics

First assign time

It refers to the average time taken for incoming tickets to be assigned to a support agent. This metric gives a good idea about the efficiency of the workflows you’ve set up in your helpdesk. You can then make use of workflow automations to set up better ticket assignment rules and reduce the first assign time.

First contact resolution percentage

It gives the percentage of tickets that were resolved within the first agent response. With this metric, you can also measure how efficient your customer service is, how well trained your agents are and how well they use their existing knowledge and resources to offer the most relevant solutions to customers. 

First response SLA percentage

Service level agreements (SLAs) are the mutually agreed upon time limits within which a support ticket has to be responded to and resolved. The first response SLA percentage gives you the percentage of tickets where the first response from an agent was sent within the SLA limit. It is an extremely important statistic as it tells you how well your team is adhering to the SLA policies. If your team is consistently seeing a low first response SLA%, you need to either work on improving individual agent productivity or tweak the current SLA policies so you don’t overpromise and underdeliver. 

Resolution SLA percentage

This metric gives you the percentage of tickets that were resolved within the resolution SLA limit. It tells you how well your agents are equipped to handle different kinds of customer problems and see them through to quick resolution. A lower resolution SLA percentage indicates that you need to improve your agents’ product knowledge and their time management skills. It could also mean you need to invest in newer and better tools to improve productivity.

Number of agent responses per ticket

The total number of agent replies needed before a ticket is resolved. If a customer conversation has too much back and forth, it does not reflect very well on the agent who was handling the ticket. Using this metric, you can work on improving individual agents’ performance and help them resolve tickets in a more optimal manner.

Number of reassigned tickets

This gives you the total number of tickets that were reassigned after being initially assigned to an agent. It helps you understand the kind of problems that agents run into before they have to reassign the ticket. Using these insights, you will get a better idea of the skill level of each agent and the type of issues they feel comfortable handling. This will, in turn, allow you to implement features like skill-based ticket assignment.

Total time spent on ticket

It refers to the total time spent on every ticket from the time it was created to the time it was resolved. It paints an accurate picture of the skill level of your support agents, their ability to pacify angry customers quickly, and the effectiveness of your existing support processes and tools. This metric will also nudge you to take decisions on staffing, hiring more experienced agents and trying new methodologies to improve support efficiency.

Advanced metrics

Number of reopened tickets

It gives you the count of the tickets that were reopened after they were marked as resolved in a specified time period. By looking at these tickets, you can examine the agent and customer interactions and find out what went wrong. If you notice a pattern in the identified problems, you can tweak the process of training your agents to help them resolve customer tickets optimally.

Percentage of escalations

This will give you the percentage of tickets that were escalated to managers because of SLA violations. You can use this metric to hold agents more accountable and ensure they quickly follow-up with senior management if a particular problem is out of their capacity.

Ticket load analysis

This refers to ticket volume reports that tell you what time of the day/week/month/year sees the maximum ticket load. This will help you plan better workflows and rotate your employee shifts optimally. It will also help you ensure that your team is working at full productivity during peak time periods.

Monthly ticket volume by region

This gives the geographic split up of all the customer tickets that come into your helpdesk. It helps you drill down on the countries where a majority of your customers are facing problems. You can take strategic decisions on staffing and rotating employee shifts based on this metric.



Customer satisfaction metrics

These metrics tell you how happy your customers are with the quality of service that is provided to them. You can use this data to spot dissatisfied customers, obtain their feedback, and make critical changes to your existing support workflows. Unhappy customers can thus be converted into loyal advocates of your brand.


Basic metrics

Customer satisfaction score

At the end of every support interaction, customers are sent a satisfaction survey where they give feedback on the quality of service provided. The customer satisfaction score refers to the percentage of customers who picked a positive response to the survey questions. If the satisfaction score is low for your company as a whole or for specific agents, you can take steps to deliver a better support experience. This can include hiring more experienced agents, investing in a full-fledged helpdesk solution, or offering goodies/discount coupons to customers who’ve had an unsatisfactory experience.

Net promoter score (NPS)

The NPS is a 10-point scale that measures a customer’s willingness to recommend a company’s product or service to others. It is a good indicator of how loyal your customer base is and whether they are satisfied with the product/support experience they have been receiving thus far. A low NPS rating is a cause for concern and an indicator that your brand needs to invest more money and effort in improving the quality of service.



Intermediate metrics

Number of customer replies on each ticket

This refers to the number of replies sent by customers on a ticket thread before the issue is completely resolved. It gives you a good idea of how relevant the offered solutions are, and if your customers can easily understand the solutions given by the support agents. Typically, a lower average number of customer replies indicates customer happiness without any miscommunication or excessive back and forth.

Rating response rate

This gives the percentage of customers who have responded (either positively or negatively) to your satisfaction survey. A high percentage here indicates an engaged customer base, that your customers genuinely understand the value of good service, and expect the best from your brand. You can use these responses to receive further feedback from customers on improving support processes.

Churn analysis

Customer churn rate is calculated as the percentage of customers your company has lost over a given time frame. Although this is not a metric that is a direct reflection of your customer service, you can use it to identify reasons why customers are churning and implement support strategies that can bring this number down. For example, providing 24x7 customer support is a strategy that can reduce churn and help build customer loyalty. Similarly, by looking at the customer retention rate (percentage of customers your company has retained over a given time period), you will know what aspect of your business has been well-received by customers. You can then use this knowledge for future improvements.


Advanced metrics

Customer effort score (CES)

The CES is a metric that measures user experience with a particular product/service. Customers are typically asked to rank the ease of using and navigating a product on a scale ranging from ‘very easy’ to ‘very difficult’. If a high percentage of your customer base ranks your product as difficult to use, you can work on improving the overall experience and make it more accessible. This in turn, will reduce the number of support queries your agents have to deal with on a daily basis.

Customer analysis by segment

This report splits your entire customer base into various segments to dive deep into common behavior patterns. For instance, analyzing your list of NPS promoters against a list of NPS detractors can help you understand what is working, and what isn't.  You can also track high-value clients separately, analyze the different verticals/industries and geographical regions your customers belong to, and create personalized experiences for each.

Number of discounts and offers applied

It refers to the total number of discounts, offers, freebies and goodies given to customers over a specific time period. Although it is good to reward loyal users, doing this excessively to pacify angry customers is not recommended in the long run. Rather than trying to win frustrated customers over by offering discounts, your support agents should be able to handle the situation and explain the nuances of the problem better.


Self-service metrics

These statistics tell you how well your self-service resources are being used by customers. If your self-service content is working well, you will see a significant decrease in the number of support tickets your company receives over a particular time frame.


Basic metrics

Number of page views on knowledge base articles

It refers to the number of unique page visits your knowledge base content receives month-on-month. A higher number indicates that more customers are actively using your self-service resources to troubleshoot their problems. You can also check if an increase in the knowledge base views has contributed to a significant decrease in support tickets.

Number of chatbot conversations

Most businesses today use chatbots to give faster answers to basic customer questions. This metric gives you the total number of conversations your bot has had with customers. It’ll give you an idea about the type of queries users ask the bot, so that you can program it to give better and more accurate answers.

Number of new forum posts

Community forums are a successful tool for customers to interact with each other and resolve problems among themselves. The number of new forum posts tells you how actively your customers are relying on the forums to find answers to their questions.

Intermediate metrics

Article bounce rate and time spent on page

The article bounce rate refers to the percentage of sessions where there was no interaction with the page. A high bounce rate means that users did not find your content particularly useful in solving their problem or if they are unable to grasp the instructions. You can also look at the average time spent on the page to draw inferences on how users interacted or scrolled through the page.

Number of upvotes and downvotes

It refers to the number of likes and dislikes your help content has received from customers. More upvotes means the content is being received positively and a similar style can be used to create more resources. More downvotes means that something different needs to be adopted in future self-service resources. It could be something simple like changing the writing style and making it more conversational, or even trying something new like creating quick video tutorials to explain different product features.

Knowledge base success rate

This metric gives you the ratio of the knowledge base views to the submitted support tickets. You can use it to analyze how successful your knowledge base content has been in deflecting potential support questions. If you see this ratio increasing over a particular time period, it means your self-service resources are doing their job and customers are increasingly preferring to find answers on their own over contacting support for every minor concern.

Bot success rate

This metric tells you how successful your bot strategy has been. Ideally, your bot should be able to handle most customer questions, and deflect potential support tickets. However, if you notice a significant number of bot conversations that were converted into tickets, it means that you should train your bot to handle more complex questions and situations in the future.

Forum success rate

This metric tells you how many customer issues were resolved within discussions on the community forums. If this number is showing a significant improvement over time, you will know that a large proportion of your customer base is reliant on the forums. You can thus increase engagement, and use the feedback obtained on the forums to work on new features and product improvements.

Social media metrics

As social media is increasingly becoming popular for customer service complaints, it’s important for your company to prioritize this medium and look at how the quality of service can be improved. If you're hiring a dedicated social support team, you should be looking to track the following metrics.


Basic metrics

Source wise split of issues - Twitter, Facebook and more

This metric will give you the split up of all the social channels you’re receiving customer issues from. You can then focus your resources on the channel that gets the most traction. For example, if most of your customers prefer reaching out on Twitter, you can increase the number of agents handling Twitter requests, make use of Twitter’s dedicated support features, and more.

Response time for social tickets

This gives you a measure of the time taken to respond to tickets raised on social media sites such as Twitter and Facebook. When customers reach out on social media, they expect quick responses and fast resolution. Therefore, it is important for you to maintain quick response times on social media to ensure satisfied customers.

Engagement - Number of likes, retweets or positive replies/mentions

The number of positive replies/retweets/comments on social channels is a good sign of how helpful your social support team is. Since social responses are mostly public, more prospective users will see the good work put in by your brand. This will help improve customer loyalty.

Advanced metrics

Resolution SLA% for social tickets

This tells you the percentage of social tickets that were resolved within the SLA. It is extremely important to keep this number high as slow responses on social media don’t go down well with customers. This can further lead to negative word-of-mouth for your company which might sway buying decisions of future prospects.

Issues resolved using Twitter/Facebook bots

Twitter and Facebook have their own bots/mechanisms to handle certain simple customer questions. You can adopt these features and keep track of how many customer questions they are able to tackle without human intervention. The higher the number, the more you can trust these bots in the long run.

Learn more about customer service metrics