July 30, 2021

The Importance of Segmenting Customer Service Metrics by Channel and Ticket Type

Gauging the health of your customer service operations is tough, especially as you add more channels. When you start with just email, it's a bit easier.

By
Jon Tucker
CEO HelpFlow
The Importance of Segmenting Customer Service Metrics by Channel and Ticket Type

Gauging the health of your customer service operations is tough, especially as you add more channels. When you start with just email, it's a bit easier. But as email volume skills up and you add chat, phone, social media, and other channels, it can be challenging to know if your team is doing an excellent job of keeping customers happy.

It's possible to measure the health of the CS operation and the happiness of customers easily if you use a few simple metrics and then segment which channels and types of tickets you measure during your analysis.

At HelpFlow, we run 24/7 live chat in customer service teams for over 100 stores that have built a robust process for managing customer service operations over the past six years. In this post, I'll break down how we measure and make decisions in a customer service operation with multiple channels and a wide range of tickets.

 #1 Measure the Right Metrics

You can measure a ton of different things in customer service, but there's only a few that matter to gauge the health of the customer service operation and the happiness of your customers. We went deep into this in another post, but here are the basics.

Measure the Experience of Customers

  • First response time - how quickly do your agents respond after the customer submits a question on the channel.
  • Resolution time - how long does it take your agents to resolve customers' issues, even if it takes multiple tickets.
  • Customer satisfaction - at the business or channel level, how does the customer rate their satisfaction when the ticket is resolved.

Measure the Effectiveness of Agents

  • Agent capacity - how many tickets are your agents handling compared to the benchmark for how many tickets a single agent can handle per hour.
  • Handle time - how much time does it take for your agents to work on the ticket and get it resolved.
  • Customer satisfaction - at the agent level, how does the customer rate the satisfaction on the ticket once it's resolved.

By measuring the six metrics, you can get a good understanding of how happy customers are and how effective the CS operation is.

Tracking the metrics is relatively easy, but the insights you get will be confusing and somewhat useless if you simply measure the entire customer service operation as a whole. Instead, it's important to segment your measurements by channel at a minimum (i.e., email metrics, chat metrics, phone metrics, etc.).

The metric you track can typically be the same between channels or slightly repurpose for the specific channel you are measuring, but the general intent of the metric will remain the same. For example, in chat and email, you might use first response time. For phone, you would use answered time. It measures part of the customer's experience.

As part of segmenting the channels, it's important to have different standards of success depending on the channel. For example, in live chat, it's incredibly important for first response time to be <10 seconds. But with emails, that number can be more like 1-2 hours and still wow customers.

Measuring these metrics and segmenting by channel will enable you to optimize the operation of the channel level. But there's one more layer to consider here...

#2 - Segment Measurements by Channel

Tracking the metrics is relatively easy, but the insights you get will be confusing and somewhat useless if you simply measure the entire customer service operation as a whole. Instead, it's important to segment your measurements by channel at a minimum (i.e., email metrics, chat metrics, phone metrics, etc.).

The metric you track can typically be the same between channels or slightly repurpose for the specific channel you are measuring, but the general intent of the metric will remain the same. For example, in chat and email, you might use first response time. For phone, you would use answered time. It measures part of the customer's experience.

As part of segmenting the channels, it's important to have different standards of success depending on the channel. For example, in live chat, it's incredibly important for first response time to be <10 seconds. But with emails, that number can be more like 1-2 hours and still wow customers.

Measuring these metrics and segmenting by channel will enable you to optimize the operation of the channel level. But there's one more layer to consider here... 

#3 - Sell with the Customer's Language 

Even within one channel, such as email, certain types of tickets will cloud your data and insights if you don't segment them out.

  • For example, your helpdesk likely gets a lot of automated messages that you don't reply to at all, and mark resolved to clear them out. They should be segmented out of all of your metrics.
  • But even legitimate tickets like "where is my order" questions should be evaluated separately from tickets that can't easily be standardized.
  • You might even consider segmenting your measurements by pre-sale versus post-sale questions. 

In segmenting down to the ticket type level, you were able to deeply optimize customer experience in the effectiveness of your agents at each channel level. By using a proper tagging process or categorization process in your helpdesk, this metrics tracking process is relatively simple to use once it's set up.

What's Next?

All customer experiences are not equal across channels or even within the same channel for different ticket types. If you're not tracking the metrics above at all, and obviously start with that. Even if you already have a robust metrics tracking process, start segmenting by channel and take a step to see the deeper insights you get.

If you want to see more examples of how to optimize your customer service process, check out these other posts we done the past.

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