Every company is different. No approach to customer support metrics will fit every product or business model. Of course. Duh. But in some ways, support metrics – and good ways to start poking at them until you’ve refined an approach that fits you more exactly – can follow some general guidelines. This approach I’m about to lay out borrows heavily from Chief Customer Officer, a book I love and highly recommend.

When I talk to companies about customer support metrics, especially if they are setting up support as a new function, they tend to focus on ways to measure how quickly and efficiently the team is answering questions. Which is a great thing to think about, but is a very narrow slice of what a good support team should be focusing on. When you are thinking about what to measure and track, you should make sure you are looking at things under each of these three areas:

1. How many customers are we gaining and losing as a result of how we do things?

When I say “how we do things”, I’m not just talking about how support is handling stuff. How many people are you gaining, maintaining, and losing because of how the product works? Features you do or do not have? Your policies and request lead times? Pricing? Quality of support interactions? Other stuff? You will likely have to dig for some of this information. But it’s worth it.

Good things to start with:

  • New customers – volume and value
  • Lost customers – volume and value
  • Reasons why customers left (as specifically as humanly possible. DIG!!!)
  • Reasons why customers chose to renew (if you have a pricing model where this makes sense)

11. How good are we at helping customers who ask for help and rescuing customers who need to be rescued?

 This is where you get into the quick and efficient question answering metrics! More than just how many emails you are responding to and calls you are answering, there are several other things you want to know. What can you do to get better at what you are doing? Are you getting better over time? And are the interactions you’re having with customers good interactions?

Good things to start with:

    • Volume
      • What do we expect to be able to complete per agent per hour?
      • What do we actually complete per agent per hour?
      • What is the reason for the delta (if there is one)?
      • How are workflow/process/tooling changes increasing or decreasing what we are able to get done?
    • Efficiency
      • Median first response and full resolve times
      • If you have set goals or expectations for first response and full resolve times, what percentage of things are getting done within those timeframes?
      • What kinds of things take the longest to resolve? (Why?)
      • How many interactions does it generally take to fully resolve things?
      • What kinds of things take the most interactions to resolve? (Why?)
    • Quality
      • How do customers rate the quality of their support interaction? (CSAT surveys are a great way to start figuring this out)
      • How closely and consistently do the interactions we have with customers align with how we think they should be?

111. How well do we listen to customers and make things better?

All this digging and hard work and number stuff is great. But how are you doing at acting on all this information? Are the actions you’re taking making any difference at all? Has anything you’ve done made things easier for customers? How do you know?

Good things to start with:

  • ALL ABOUT ALL THOSE INTERACTIONS
    • Clear organization of all that awesome interaction information
    • Volume and trends
    • Close tracking of volume and trend changes in response to actions taken to (hopefully) resolve root issues
      • You’ve identified an issue with all this customer data and tried to fix something. Fixes can (and should) run the gamut of copy changes, FAQ improvements, new features, improved support messaging, etc… Make sure it was the right fix by checking to see that ticket volume related to the issue has dropped, or the CSAT surveys for tickets associated with that issue come back happier, or funnel conversion has become more efficient…
Beyond talking to customers and generating reports your company would also likely benefit from involving your customer support leader in the product planning process, if you don’t already. This will help your team intelligently plan for feature releases. In addition, support can give deep insight into what customers are actually asking and how what you are planning is likely to perform in the wild.

IMPORTANT NOTE: As you dive into tracking, don’t be sad that you don’t have all of this information right away. Setting up how you want to collect and report takes time. Collecting enough data for the numbers to actually mean something takes time. Resist the urge to use your first numbers as benchmarks and start drawing firm conclusions. Take your time in the beginning to just notice the numbers until they start manifesting trends.

To sum up, your customer support metrics should be about more than just response time. Develop a clear set of data that addresses more of the things your customer-driven company should be measuring: customer retention, support bandwidth and quality, and how successful you are at improving the overall customer experience.