Simplicity in contact center analytics

Data isn’t just for dashboards and boardrooms. From the contact center to the sidewalk, the trout stream to the team meeting—we’re analyzing constantly.

In this short explainer, we explore the idea behind Analytics Outside—a Zenylitics video series that reveals how real insights happen anywhere. It’s about making sense of information, whether you’re coaching an agent, choosing a fly for the water, or just taking your dog for a walk.

At Zenylitics, we believe data should work for people—not the other way around. This series reflects how we live, work, and think: flexibly, curiously, and always searching for better insights.

Join the conversation:

How do you use data in your everyday life? Drop a comment and let us know.

Transcript

We recently had some healthy friction with a new customer. They’re a sales organization with a really straightforward use case. The problem that we ran into was they’re trying to measure every behavior under the sun and it was really slowing their progress. This got me thinking about why simplicity is one of Zen’s guiding principles. I’m going to relate this to something that’s going on in in my life right now.

And to do that, I’m going to introduce you to Earl. Proper name, James Earl Bones. We rescued Earl a few weeks after I founded Zen back in 2017. He’s been with me since the very beginning. We work from home, so we spend a ton of time together.

It’s been great. He’s an awesome dog. He went to the vet recently, and he was told that he’s gotten a bit husky. Dog pun is fully, fully intended there. He’s not alone.

Full disclosure, I’m right there too. We work from home. We have a lot of awesome snacks around the house. We don’t nearly get enough exercise, you know, a few of the pitfalls of working from home. So we started looking into diet plans.

So what do you think? Paleo? Keto? How about walkies? Okay.

Walkies. We were absolutely inundated with advice. Intermittent fasting, keto, carb cycling, paleo. It was too much. Then I remembered, Earl is a dog.

Let’s just keep it simple. Reduce our caloric intake, and make sure we get our steps in. So “hot Earl walks” were born. A little bit of background. I learned about these things called ”hot girl walks” from one of my neighbors.

I guess they hit on TikTok a few years ago. They’re these walks for health and mindfulness. I had to coop that term. So you’re likely asking, what the hell does this have to do with conversation intelligence and analytics? Every day at Zen, we talk to contact center leaders who are trying to boil the ocean.

It’s an easy trap to fall into. Too many of us really want to focus on this massive suite of metrics like AHT, wrap time, utilization, hold time, schedule adherence, service levels, complaint volumes, customer sentiment, a myriad of QA scores covering every behavior you could possibly imagine. It’s just too much. More than likely, you have one or two key metrics that will determine the success or failure of your conversation intelligence program. These are what we would call your primary KPIs.

You know what these are. These are metrics that essentially tell you what happened. So for a sales use case, that’s something like a close rate or a conversion rate. In a customer experience use case, think customer sentiment, NPS, CSAT, etcetera. Then you’ve got your secondary metrics or your leading indicators.

These are the metrics that should influence those primaries. These are the levers you can pull. So when we develop these secondary metrics as analytics, we ask ourselves this simple question. What can I do to improve insert primary metric here? And then we form a hypothesis, how we’re going to do that.

Now back to our real world example. This customer’s primary success metric is conversion rate. Really straightforward. Book more deals, revenue goes up. It’s pretty simple.

As I said before, they wanted to measure everything. Pull every lever, turn every dial. Sales call flow, customer profiling, sentiment, objection, rebuttals, every sales behavior was just too much. So what we did was we analyzed their interactions. We distilled it down to a few behaviors that had strong correlations to those positive outcomes.

What did we find? We found that agent usage of discovery language and mentions of product benefits had a high correlation to success and were being underutilized by their teams. That’s it. Our hypothesis was that if we get better at these things, we should see an increase in conversions. Straightforward.

The team trained and encouraged their staff to focus on these behaviors, and we measured and read out on the results so we could monitor their progress. And it worked. Conversion rate went up and revenue followed. Now, just because we’re talking about keeping it simple doesn’t mean that it’s easy. So here are a few recommendations, three recommendations to help you keep it simple.

First and foremost, start small. Pick one primary metric and no more than two or three secondary metrics that support your hypothesis. Number two, commit to action. Those secondary metrics. Choose the secondary metrics that you can actually impact, and you have to take the steps to actually move the needle there.

It might be training. It might be ongoing support for your teams. Whatever it is, you have to take action. Last, inspect what you expect. Monitor, monitor, monitor.

Keep testing to ensure that the results are what you expect. If it isn’t, revise your plan. Adjust. So Earl and I decided that to lose weight, our primary metric, we’re going to focus on getting our steps in with hot girl – “hot Earl walks” — and reducing our caloric intake. Those are our secondary metrics.

So what’s your “hot Earl walks” in conversation intelligence or contact center analytics? Is there some business problem that you struggle with simplifying? Drop a comment. Let’s chat. I love these conversations.

I’ll check back in a few months to let you know how Earl and I are doing on our progress. Thanks a lot.

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