What Should Be in My Customer Support Reports
Reporting is a necessary and important part of any customer support managers job. Customer support is hectic and it’s easy to get trapped forever answering customer issues. It’s important to take a step back and access what’s happening, why customers are calling and how your team is performing. Not to mention your management team is probably eager to see your results. There are a number of reasons to report on your support data:
Keeping Tabs on Your Team
It’s important to monitor agent performance to make sure everyone is keeping up to standard. Agents on certain teams or on particular days may be getting inundated with tickets and there metrics like customer satisfaction or first response time may be slipping.
They may also be struggling in answering a specific customer issue, causing customers to become upset. When you are in the thick of it, this kind of stuff can be easily missed. When you report on your support however, these issues quickly become visible and can easily be fixed with changes in rostering or individualized training.
It is important to know how you and your team are currently performing. You need to know if it starts to slip and you can set targets to meet into the future. In order to have a basic understanding of your teams performance, and for pushing for even better customer experience, weekly reporting is a necessary part of your job. You should have benchmarks set for a number of key metrics so your team understands the minimum that is expected of them.
What You Should Do
Report on your customer support performance weekly to keep tabs on your key metrics.
Closely monitor areas where your team has been lagging or missing the set benchmarks.
Include your SLAs and how your team performed against them for the week, along with any comments or reasoning as to the weekly performance.
Show your quarterly targets and your progress and forecasted results towards these.
Finally, you need to include a section where you explain why your customers are calling in this week.
Why are Your Customers Calling
It’s all well and good to keep first response time and requester wait time below your set SLAs. But if you are ever really going to improve your support and your customer’s experience, you need to understand:
What your team or other departments can do to resolve recurring issues.
Today you can do this by reading through a portion of your tickets every week prior to building your report. This will give you a flavour of your top issues this week, but it’s really just that, a taste.
You won’t have any real facts or figures to show management or other teams. And without them it’s extremely hard to enact change in an organisation based on a hunch you may have.
How AI Can Help You To Read These Tickets
The other option then is to get an AI plugin for your Helpdesk. Artificial intelligence can now read unstructured text in the form of customer support tickets. And it understands the reason for a customer call.
Cx Moments analyses all of your support tickets and provides you with the results in an easy to use dashboard. It shows you your customer top reasons to contact your support along with how they have trended over time. This can all be exported to PowerPoint in one click. And it saves you 237 days a year reading support tickets to better understand your support.
What to Include in My Weekly Report
The metrics that matter to your support may differ wildly from company to company.
A rapidly growing B2B company that wants to scale its support might build an SLA based on ticket deflection ratio.
A retailer that knows it must provide quick support during the holiday season can create an SLA that focuses on a maximum first reply time for new tickets.
A company struggling to provide quality support must maintain a specific customer satisfaction rating.
Whatever you choose to be your specific goals, there are a number of basic metrics that should always be included in order to track your teams performance.
Your customer support report overview should be able to quickly show how your team is performing at answering your customer’s issues. Metrics to include in this section would be:
Created tickets: number of tickets created in the time period
Unsolved tickets: number of tickets in backlog, yet to be answered
Solved tickets: number of tickets solved in the time period
First-time reply: median time from ticket creation to first agent reply
Full resolution time: median time from ticket creation to full ticket resolution
It’s important to show this information on a graph so you can better see how these issues have trended throughout the week. It gives you an extra layer of information you don’t get with the stats above.
You may have a peak in unsolved tickets one week but with a graph, you can see that this peak in unsolved tickets actually only happened on Wednesday. The rest of the week is actually coming in below average. Real change can be made based on this insight like adding agents to the Wednesday group. Or taking a deeper dive into the tickets to see what may have caused this spike in unresolved customer issues.
Getting Extra Depth with AI
With an AI plugin, this information is automatically calculated and graphed for you to see. It gives you a further layer on top of what has been mentioned previously. You can now see these metrics related to specific customer issues. You can see what issues are taking up most of your agents time. And you can see what problems are trending up this week and may need further attention.
Efficiency helps you to monitor the energy effort of your team. It helps you do things well, successfully and without waste. The less touch points your customer has to deal with before their issue is solved, the better the customer experience and the cheaper your support. Metrics to include in this section would be:
One-touch tickets = % tickets solved by one public agent reply
Reopened tickets = % tickets that were reopened
Assignee stations AVG = average number of agents a ticket has been assigned to
Group stations AVG = average number of groups a ticket has been assigned to
Requester wait time MED = median time a ticket spent in new, open and on hold status
Here you want to include graphs that show your percentages this week. Compare them to previous weeks results and how it compares to your quarterly targets.
Finally, a useful section in any Support Managers’ report is an agent leaderboard. This shows you how each of your agents are performing against each other in a number of key metrics.
Monitoring agents against each other allow you to see what agents may be slipping, allowing you to try and mitigate this before it becomes a problem. Metrics like tickets solved, average first reply time, full resolution time and customer satisfaction for each agent should all be monitored. Each agent should be placed on the leaderboard based on their score.
High-Level Metrics can Hide issues Below the Surface
AI can again give you a deeper insight into agent performance. It allows you to see these metrics like customer satisfaction broken down based on customer issues. Vey often high-level metrics can hide issues under the surface. Agents which may have very good overall first reply time or satisfaction scores may be also struggling with specific customer issues like refund requests or delivery problems. With this insight, you can now tackle the issue head-on. Without AI this would slip through your fingers.
Customer Support Reporting is a hugely important part of any support managers work. It helps you to keep your team on track, spot issues before they become major problems and helps you to show off your results to your management team. AI can help to give you a further layer of visibility into your support data. Knowing why your customers are calling your support means you can start to make real changes to benefit the customer experience. You can spot customer issues that may be growing like problems with a specific shipping partner or easy fixes that have slipped through the cracks for months like password reset confusion.
The aim of reporting is to track your progress and set a course for better performance. Making this a part of your weekly schedule will help you to achieve this The best customer experiences are built on data and the information you gather on your team’s performance and the customer issues you receive should feed into every aspect of your company, helping you to build a customer-focused business.