12 Help Desk Metrics For Finding The Best Help Desk Software

How can you determine if your business’s help desk is meeting end-users technical needs? Help desk-specific measurements or key performance indicators (KPIs) can achieve this. Let desk metrics help you monitor, maintain, and improve service. Help desk managers have lots of performance data, but some measures are more significant. Your help desk software KPIs may rely on your aims and the type of consumer you serve. To ensure your help desk is working effectively and can be enhanced, watch these metrics/KPIs. The first few measures measure ticket/call volume and identify potential causes.

Organizations always want the best help desk ticketing software. We have discussed many different ways to find the best helpdesk system in our previous articles. But we never discussed how organizations could test the performance of their enterprise help desk software so that they could know if their help desk software is the best or not. So, in this article, we have discussed 12 help desk metrics for finding the best help desk software. We hope it will be really helpful for you. So, let’s start with our main topic.

12 Common Help Desk Metrics

The following set of KPIs addresses personnel quality and service availability, followed by end-user satisfaction, the ultimate goal of any support/service department. Some of these help desk metrics are industry standard, and some are commonly used metrics. So, the following are these help desk metrics for finding the best help desk software.

1. Ticket Volume

Ticket volume is the number of tickets produced over time. Overall ticket volume, ticket volume by support channel like email, phone, text, or social, and ticket volume per help desk technician are some of the most fundamental metrics to monitor. Ticket volume measures help desk inquiries by day, week, month, quarter, or year. Monitoring this data periodically may reveal seasonal or other volume trends. This data and other corporate data like network maintenance schedules, software rollout dates, new recruit start dates, and others can help you predict and prepare for ticket volume increases. Call volume always rises following a holiday weekend. Users forget passwords, connectivity troubles, PCs not restarting correctly after sleep, etc.

It would be worth investigating to see if password reminders or more help desk workers could alleviate these concerns. Ticket volume by support channel can also provide insights. Your users may not know about or feel comfortable using your help site or email address if you get more phone calls. Employees may struggle with the support portal. These may improve. As you shall see in the next metric, ticket/call traffic increase is not necessarily bad, depending on whether you are servicing internal users or external customers.

2. Contacts per Customer

Simply divide the number of calls, contacts, or tickets generated in a given time period by the number of customers or users. I created this metric while administering Track-It! Technical support. As a fast-growing firm, we struggled to scale our support personnel to accommodate rising call demand. Upper management worried that product issues could be causing the increased call volume, so we should fix them instead of hiring more support employees that we could have to lay off later.

That made it crucial to determine if the call traffic increases were reasonable and expected owing to increasing customer counts or caused by product difficulties. The contacts per customer metric helped us determine if we needed to address product or service delivery issues or simply expand call center workers to accommodate our growing client base. We calculated this number daily or weekly because we were developing so fast that the customer count may climb significantly in a week or month. I think daily is the best approach to measure this metric because you can easily use the number of contacts and customers from a day. Use average customers to measure this metric weekly or monthly.

We noticed that our contacts per customer remained consistent even as our call volume and customer count increased. The contacts per customer were the same when we added customers quickly and increased call volume. Only product, service delivery, or industry issues increased contacts per customer. It showed that new customers, not Windows upgrades or product faults, increased our call volume. When this metric started to rise, we needed to figure out what was causing the call volume increase and fix it.

3. Customers who Contact Support

The percentage of your client base that uses your support services at any given time. Another statistic we devised to learn if we had the product, service delivery, or normal support issues was the percentage of consumers contacting us for help. To get this KPI, we divide the total number of customers by the number of customers who contacted support during the specified time frame. It is another number that I used to figure out daily, though a weekly average customer count will do in a pinch. How I came to that conclusion:

• Fifty clients contacted assistance today
• Customers served today: 500 50/500 =.01 or 10%

The percentage obtained in this case is 10%. This parameter is easy to track and can be measured on a daily basis. This statistic is recommended to be monitored to detect any significant shifts. The number of consumers needing assistance should remain stable if product quality is maintained constantly. There may be some ups and downs, but generally speaking, it should be stable.

4. Agent Utilization

Technician or agent utilization is the number of tickets one technician handles in a certain time frame. Increased help desk staff should reduce agent usage and first response time. Agent usage estimates how much time help desk employees spend on requests and tickets. Help desks utilize agent utilization to make staffing decisions because labor is such a high cost; this statistic helps managers identify failing agents and evaluate group performance to optimize personnel. High average agent utilization may indicate a need for more staff, whereas low average utilization may signal some layoffs.

Because the help desk is paying fewer people to do more work, high agent utilization lowers contact costs. Remember that high utilization, while lowering labor expenses, increases staff churn. Agents with utilization rates over 70% may quit due to burnout. Increasing agent usage is a balancing effort between competing interests. This measure is harder to manage and compute; however, dividing the time spent processing tickets by the total time worked gives a straightforward calculation.

5. Tickets Open vs. Tickets Closed

The ratio of open tickets to closed tickets for a given time period is a simple metric known as “Tickets Open vs. Closed.” You may use this measure to keep an eye out for trends that could lead to a significant backlog by comparing the number of tickets to the number of tickets your team can manage. There may be issues with your ticket traffic projections, the availability of user or customer training resources, the size of your help desk personnel, or the expertise of your help desk staff if more tickets are opened than resolved each day. This statistic may also serve as an early warning sign of an upcoming backlog and consequent drop in service quality. If this is an ongoing problem, you should examine other help desk metrics to learn more about the root causes and potential fixes.

6. Contact Resolution Rate

One key indicator of customer satisfaction is the proportion of calls that are resolved on the first try. Customers are generally more content when the FCC rate is high, so that is something to keep an eye on. Support teams should exercise prudence and not let this statistic become their sole focus to the detriment of other KPIs. Suppose help desk technicians are only held accountable for their Initial Call Close rate. In that case, they may become too concerned with resolving the issue as soon as possible during the first contact, regardless of whether or not the issue has been handled. It would help them achieve their First Call Close rate objective, but at the expense of increased ticket traffic (because customers will need to call back) and customer satisfaction (since the problem will not have been handled entirely on the first call).

A high First Call Close Rate at the help desk usually correlates with a high-end User Satisfaction Rate, provided that all other metrics are monitored and handled effectively. Callbacks and further escalations are avoided when the first agent and end-user contacts are able to provide a satisfactory resolution to their issue. Ticket escalation can be costly for help desks and frustrating for end-users, but if necessary, following some ticket escalation best practices can enhance the experience.

7. First Response Time KPI

One primary indicator for gauging the effectiveness of a help desk is the time it takes to reply to an end user’s first email or voicemail. Typically, three elements determine this:

• Ticket volume
• The number of help desk technicians available
• Resolution Time

Besides software and tools, the aforementioned items are generally good metrics to monitor as drivers of response time. Other factors, such as inefficiencies in the system used to record tickets, the lack of a ticketing system, or the process by which calls/requests come into the help desk, may also contribute to response delays. The initiation of a reaction can be affected by fluctuations in these additional parameters. The following is an illustration:

• The typical ticket load will overwhelm a help desk that is understaffed, extending response and resolution times.
• Any time there is an unexpected spike in tickets because of an outage or other major problem, even a team that is properly staffed will take longer to resolve the issue.
• A large help desk staff that is poorly prepared or under-trained may take too long to resolve tickets, even at a regular ticket volume.

A slow help desk may struggle to satisfy users. In today’s connected world, individuals demand fast responses practically instantly, and the help desk must manage those expectations. The longer an end-user waits, the more likely they will dislike the engagement. Thus, a poor first response time can doom a help desk right away. This measure must be monitored to maintain a suitable level.

8. Resolution Time

Between ticket opening and resolution is ticket resolution time. This measure may indicate the difficulty of help desk issues, your help desk staff’s ability, or your end users’ technical ability. Monitoring response times by technician, ticket type, or requestor might expose difficulties, staff performance, system improvements, and training needs. Long resolution times can be good. Your help desk may take time to resolve difficult situations. Like many help desk measures, focusing entirely on Resolution Time could lead technicians to quickly close cases that may not be solved.

These data should be monitored alongside help desk measures, including response time, tickets per technician, and end-user satisfaction. Your help desk’s ideal resolution time depends on the assistance type, users, and systems. It would be best if you chose the finest option. In most cases, the best method is to monitor the average ticket resolution time and check for trends or significant changes that could affect performance.

9. Cost Per Contact KPI

Cost per contact estimates the overall cost of each support desk engagement. The call cost usually includes the agent’s pay, a tiny percentage of the help desk technician’s system cost, and the call’s duration. Cost per contact, like other firm costs, should be kept low. It is another metric that should be studied in conjunction with others. (See a pattern?) As the cost per interaction decreases, it may disguise additional difficulties. A low cost per call does not guarantee the help desk’s success and end-user satisfaction. If help desk staff rushes contacts to cut costs could mean the opposite.

The total cost of resolving the ticket is the sum of all contact expenses. Service standards and cost per contact do not guarantee low ticket resolution costs. Help desk agents may hurry through calls, escalate users to higher support levels, or take numerous brief contacts to resolve the issue to lower their cost per contact. In some circumstances, ticket resolution may cost more than planned. The support desk must find a balance to keep prices low and service high. If customers are unhappy and their issues aren’t fixed, it doesn’t matter how low your prices are.

10. Lost Service Hours KPI

Lost service hours are hours when the help desk was planned to aid end-users but wasn’t. To accommodate the projected load, your help desk staff needs five technicians to work 40 hours each week, or 200 total hours. If your team was online 150 hours that week, you might have lost 50 hours of service availability. This value should be 0, but that’s unrealistic. Still, minimizing missed service hours is crucial. Sickness, accidents, vacations, attrition, and other circumstances may affect weekly personnel availability. Therefore, you may wish to have someone on call or arrange a particular amount of loss each week.

Some favor this indicator above service availability, which can be misleading. A 99% service availability rating seems fantastic but considers a 24/7 mission-critical support desk. This firm has 8,760 hours of service availability each year; thus, a 99% success rate looks fantastic, but it means service was unavailable for 87.6 hours! Longer hold times and response periods can frustrate customers and cost the firm. Helpdesks must minimize lost service hours.

11. Agent Satisfaction KPI

Not only customer and end-user happiness matters. Agent satisfaction affects help desk performance too. Training, compensation, career advancement, mentoring, and work environment should be measured twice a year for this statistic. A help desk with high agent satisfaction has happy, respected personnel who work hard to serve customers and users.

The team and company benefit. Employee turnover, first-contact resolution, end-user, and customer happiness, and absence rates will certainly decrease. Retaining employees is cheaper than hiring and training new ones. Retaining customers costs less than getting new ones. Investing in well-trained help desk personnel will keep them happy and your customers happy.

12. End-User Satisfaction

The best help desk software aims to satisfy customers and end-users, and Help desks aim to solve end-user issues. Post-ticket survey emails measure this parameter. Some organizations randomly call or email end users and survey them in person, but in my experience, an automated system where each user is presented with the same questions the same way without any outside intervention is the best way to get honest feedback and record results in a reportable and actionable way.

Unsurprisingly, several of this list’s KPIs affect this indicator. Slow first response, resolution or lost service hours might affect end-user satisfaction. This metric is unique in that a help desk may focus on it alone and improve its service. Track end-user satisfaction if your team has limited time and resources for measurement and reporting. Satisfied users may not respond or give positive survey responses. Unsatisfied users will nearly always give negative survey responses. Best practices:

• Don’t drag it out. The public dreads long questionnaires. No more than five questions, please.

i. Incorporate scale-based queries into your survey.

ii. Please rate our service on a scale from 1 (very poor) to 5 (excellent).

• Do not forget to ask the industry standard, “would you recommend us to others based on your experience?” for your net promoter score.
• Create a text box for people to add their own remarks regarding their experience. It is a treasure trove of ideas on how to serve better customers and comments on which employees should be commended.
• Don’t forget to update your team on the progress made. Help desk workers can better empathize with customers when they read their actual responses.

Conclusion

As a help desk manager, focusing too much on one statistic without considering others might hurt your enterprise help desk software and generate more service difficulties and poorer satisfaction. For instance, professionals may focus too heavily on First Contact Close, regardless of whether the issue is handled, which might affect end customer satisfaction. Tracking your help desk’s KPIs can improve results dramatically. You may think tracking all these things is a lot of work and that you won’t have the resources or knowledge to fix the issues once they’re found. Don’t fret. Start measuring.

Go with your top 1–2 metrics. Stop measuring data that doesn’t matter to your firm. You may require more or other measurements. Organizations vary. Daily learning and improvement are the only ways to improve your business. Don’t worry about measuring everything we’ve discussed from day one and making beautiful reports and slide presentations. Measure your top 1–2 priorities. If you don’t start, you’ll never get there.

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