I’ve noticed a pattern when talking to people who have worked in customer support at early-stage startups. As someone who runs customer support teams, I’m always interested in connecting with people who have this experience, regardless of how short their stint was.
The conversation will go something like this, starting with me asking:
Me: Oh, you handled support at Company X. Why did you leave X?
Them: I loved support. I was clearing the inbox every day, but I was getting burned out. When I talked to my boss about adding someone else to the team, the conversation didn’t go anywhere.
Me: So what’d you do? Them: I left for a position in a different role at Company Y.
Me: What happened to support at X when you left? Them: Oh, right. They ended up hiring 3 people to keep up with the inbox.
Maybe I’m missing something, but some back-of-the-napkin math says her manager could have added one person to the team like she recommended, given her a 50% raise, and still come out ahead. And the customers wouldn’t be left adrift while three new support hires learn the ropes.
So why didn’t that happen?
There’s this weird thing in customer support where we’re almost shy about rewarding—with higher salaries—queue-based performance. The doubts, which take about 30 seconds to conceive, sound something like this: “But support is much more than answering tickets,” or perhaps, “Throughput is nice, but what about quality responses?”
We’ll deal with the objections in a second. First, we have to recognize how we stand to benefit by properly valuing queue-based performance in customer support. Imagine a world where you’re able to attract and retain the very best people to support your customers and create a closed feedback loop for improving the product in response to what customers value. The result would be better products and happier customers.
Optimizing for queue-based performance will help you create that world.
Why you should optimize for queue-based performance
First, let’s narrow the scope of our discussion to speak specifically of customer support at growth-minded product companies where (1) customer experience is a differentiator and (2) support professionals are expected to help shape the product to serve evolving customer needs.
WHAT ARE SEGMENTS IN FULLSTORY?
In case you need a refresher, Segments are cohorts of user sessions in FullStory. Whenever you use OmniSearch in FullStory—for specific user behaviors, events, or whatever—you are segmenting your sessions. When you save those searches, you create Segments. With Segments, you can find the types of user sessions that matter most to you easily in FullStory without having to recreate a new search each time. For more about OmniSearch and Segments, read and bookmark this blog post.