When it comes to optimizing your help desk performance, there’s an overwhelming amount of data you might choose to track.
From how many tickets your team can process at a given time to how often your customers call in about a recurring issue, there are a ton of potential metrics for you to measure and monitor.
So, where should you focus your energy and resources? How do you decide which metrics are most valuable?
Let’s take a look at 15 of the most useful help desk metrics you can track and what they can reveal about your customer support strategy.
Also referred to as total tickets and total conversations, this metric is simply the volume of incoming support tickets for a given timeframe. It shows you how many tickets your team is receiving and, therefore, how quickly they must work to keep up.
Whether it’s based on the day, week, month, or quarter, a simple monthly ticket inflow report provides valuable data for any company. You can use this information to break down how many tickets your team is receiving per support agent, which can help with future scheduling and hiring decisions.
Once you know how many tickets you’re receiving, it only makes sense to track what percentage are successfully resolved. This metric reveals whether your support team is meeting the current demand or is drowning in more tickets than they’re able to resolve.
Comparing the number of new tickets against the number of tickets resolved gives you an understanding of how well your team is performing week over week.
If you’re consistently receiving more tickets than you’re solving, it’s an indication that your team is understaffed or needs further training to help them address customer issues more efficiently.
When your customers have a question or problem, are they more likely to pick up the phone, send an email, use live chat, or send a message via text or social media?
Tracking ticket volume by channel allows you to determine which channels your customers prefer as well as which channels are the most popular at specific times, so you can allocate company resources effectively.
For instance, if you find that a certain channel is underserviced or understaffed, you can assign more agents to monitor those types of tickets to optimize help desk efficiency.
If you use an omnichannel help desk, this should be easy to put data from all channels into a single view for easy oversight.
This is a measure of how long it takes, on average, for a customer to receive an initial reply from a support agent.
The longer your average response time, the more likely customers will have a negative first impression of your support team. However, if you’re able to shorten the wait period between when a request is submitted and when an agent acknowledges it, you can demonstrate that you value your customer’s time and consider their needs a priority.
Even if you can’t offer a solution right away, your customers want confirmation that someone is aware of and looking into their issue. Simply acknowledging a support ticket shows the customer that their concerns have been heard and a solution is in the works.
Unlike time to first response, your average customer wait time measures the entire customer experience from ticket creation to resolution. This includes time spent talking to your help desk as well as time spent waiting to hear back with a solution.
So, if a customer calls in and explains their issue to an agent on a Monday, but it takes until the same time on Tuesday for the problem to get fixed, then their wait time would be around 24 hours.
Although average customer wait time isn’t the most precise way to measure help desk effectiveness (as it only takes a few outliers to throw the average out of whack), it does provide a simple benchmark to use as a starting point.
There are two help desk metrics related to resolution times that you should track:
Since some support issues stem from underlying problems and can occur more than once, you should track both of these metrics to capture the whole picture.
If you find there’s a consistently large discrepancy between first and full resolution times, you may need to investigate further. It could be that the issue isn’t being diagnosed correctly during the first customer interaction.
Response time bands show you the percentage of support requests that receive responses within various timeframes. For example, you might find that 20% of all customers receive a reply within 1 hour of contacting support, 50% receive replies within 2 hours, and 95% receive a reply within 24 hours.
Unlike time to first response, average wait time, and resolution time, response time bands are not based on an average of customer experiences. Rather, they break down different customer experiences into easily comparable brackets. Since response time bands are not skewed by outliers, they can provide a realistic understanding of how long your customers must wait for solutions.
This valuable metric compares the number of tickets solved during the first customer-agent interaction to the number of tickets that require multiple touchpoints.
In other words, ticket transfer analysis looks at what percentage of tickets are transferred between different agents or groups. Tracking this metric makes it easier to spot complicated issues that eat away at your resources and, hopefully, allow you to find more effective solutions.
If your support team isn’t resolving tickets as quickly as they come in, you’ll end up with a growing backlog of tickets in your support queue. Tracking your current backlog gives you an idea of how effectively your team is handling incoming support requests. Whether your backlog is growing or shrinking can indicate whether you need to increase your help desk staffing or create more comprehensive knowledge resources for your customers to find answers themselves.
Once you’ve started tracking your backlog on a regular basis, you’ll have a history of data points to reflect on – which can then be used to predict future backlog for upcoming time periods.
For example, you might notice that certain teams or individual agents accumulate more of a backlog than others. Or you might find that certain days are quieter and can be used to catch up on the predicted backlog for the week.Your predicted backlog can also be used to inform upcoming hiring, staffing, and scheduling decisions.
Regardless of how well your team is performing based on internal metrics, you also need to look at things from your customers’ perspective.
You can collect customer feedback by including a simple form on your website or in a follow-up email to customers who recently called in for support.
Whether you ask for a rating out of five stars, ask for open-ended comments, or ask how likely they are to recommend you to a friend, gathering data on customer satisfaction ratings can help you optimize your help desk and alert you to any major flaws in your current support strategy.
If certain support agents are performing better than others, it’s important for management to know who’s excelling and who needs further training.
Identifying successful support agents not only gives you the chance to commend and possibly reward top performers, but it also creates an opportunity to learn from them.
For example, if you can find out what motivates successful agents, what training or background they have, and what tactics they use to resolve customer issues quickly, you can then use that data to improve agent performance across the board.
Your support team’s job satisfaction is closely linked to agent performance and customer satisfaction. Having team members who feel unfulfilled or underappreciated can lead to higher turnover rates and absenteeism, along with lower employee morale. Not to mention the quality of service provided is likely to suffer.
The better you understand what makes your agents tick, the better you can inspire and motivate them to deliver extraordinary customer support. Of course, it doesn’t hurt that higher support agent satisfaction also reduces turnover and reduces hiring costs in the long run.
Monitoring where your web traffic comes from, which page of your site most visitors land on, and how long they spend on each page can tell you a lot about the effectiveness of your blog, resource pages, and FAQ section.
For instance, monitoring bounce rate can tell you whether or not customers are finding the information they’re looking for when they visit your resource pages. A customer who spends time reading your FAQ and then leaves without messaging your agents on live chat has presumably found their answer.
On the other hand, if customers spend a bit too much time reading a piece of technical documentation, it’s likely that they’re having a hard time understanding it.
Adding tags to your tickets can provide you with plenty of actionable data. That’s because support request trends reveal what your tickets are about – and, therefore, which features or products you should work on improving next.
For example, if a percentage of incoming tickets relate to questions about product costs, that could mean you need to clarify your pricing structure.
Although you don’t have to track every single metric we’ve discussed, it’s worth the effort to start monitoring the metrics that seem most relevant to your customer service strategy. After all, the more data you can gather about your help desk performance, the better prepared you’ll be to deliver high-quality customer experiences.
At Boomtown, we take our data and analytics seriously. We believe that better customer, team and operational insights can lead to superior customer experiences. See if our reporting and analytics can help improve your help desk services.
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