"What are the best metrics for my customer service team?"

It's a question I'm frequently asked. In some environments, like contact centers, leaders have access to so much data it can be overwhelming. In other situations, customer service leaders don't feel they have enough data.

So let's settle one question right here: there's no single metric that's best for every situation.

The trick is to figure out which metrics will be most useful for you, your team, and your business. It's like being a detective who is looking for clues to solve a mystery. The clues themselves only make sense when they help you crack the case. (Now is a good time to think about exactly what case you're trying to solve!)

Here's a guide to help you pick the right metrics along with a few caveats.

Ask Questions, Then Find Data

The biggest mistake customer service managers make when selecting metrics is they think about metrics first without considering what problem they're trying to solve.

You'll be much better off by asking a few questions and then finding metrics that provide an answer. Here are three questions that can help:

1. What does your boss care about? By boss, I really mean the executive that the customer service function reports to. Executives usually have a hot button issue that they're very concerned about. For example, I recently had the metrics conversation with a customer service leader when he showed me an email from his company's president discussing a customer retention problem.

I advised this leader to look for metrics that were directly connected to retention. Were customers more likely to defect if they experienced a particular issue, contacted the company a certain number of times, or had to wait a certain period of time for service? It will take some digging to find the answer, but when he does, this leader will be able to help solve a problem his company's president cares about.

Find a business issue your boss really cares about and then find a metric that describes how your team can help. 

2. What is your customer service vision? Elite customer service teams have a shared definition of outstanding service called a customer service vision. (If you don't have one yet, create one with this handy guide.) 

It's helpful to have a metric that tells you how well your service is meeting your vision. This is often a customer service survey (here's a guide for that), but it doesn't have to be. A wholesaler client of mine uses order accuracy as a key metric because of the headaches that inaccurate orders cause its retail customers. Mistakes on orders also cost the company money to fix, so there's a direct financial incentive to improve as well.

3. How do you evaluate individual contribution? At some point, you'll need to decide how you'll evaluate individual performance. The counterintuitive trend is to find metrics that evaluate behaviors rather than outcomes.

Why?

Let's say you want to evaluate employees by their average customer service survey score, which is an outcome of a service interaction. The challenge is you may find employees doing things you don't want them to do to make their metrics look good. One of the worst behaviors is survey begging, where an employee pleads with a customer to give a good survey score.

A better approach is to focus on the behaviors that drive good survey scores. For example, perhaps you notice an employee doesn't offer a warm greeting 37 percent of the time. You know first impressions are key to customer satisfaction, so you have a coaching discussion about greeting customers the right way. Help the employee improve their performance and you'll see survey scores go up.

A Few Caveats

Here are a few lessons about goal-setting that I've learned the hard way.

1. Fewer is better. The more metrics you track, the harder it is to focus on any one thing. Here's a short video that demonstrates how difficult it is to focus on multiple items.

2. Existing data is better than new data. It generally takes a lot of effort to collect new data to feed your metrics, so you can be more efficient if you first try to use the data you already have.

3. Set good goals, not bad ones. We often set goals around key metrics. That's OK, but make sure your goals fit the good goal criteria if you want to drive the right behaviors.