156: Year in Review: Metrics

Charlotte Ward: 0:12

Hello and welcome to episode 156 of the Customer Support Leaders Podcast. I'm Charlotte Ward. This week I continue to look back at 2020. Metrics. Something of a dirty word if you're an individual contributor, frontline agent, that technical support engineer. They're a time sump if you're a team lead or a first line manager. A necessary tool for understanding an informing strategy if you're a department lead or an exec. In customer support there's something of an obsession at all levels. But I think most organizations fail to put them to good use. Metrics are most often used to measure the effectiveness of your staff. Are your agents responding fast enough? Are they closing out cases quickly enough? Did they close out enough cases last month? Is their CSAT score above an acceptable minimum? And if the answer to any of these is no, then how can you improve that agent's performance? That is precisely where this process, this ethos breaks down. If you'll indulge me in a little twentieth century history, you might or might not be familiar with the name of Charles Goodhardt. He's a British economist, an alumna of both Harvard and Trinity College, Cambridge, and at time of recording in his eighties, who authored an article in 1975 criticising monetary policies of the time. In that article he said any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes. Insightful as that was, it's a little bit obscure too. It was more clearly phrased by Marilyn Strathurn some twenty-two years later. She said this when a measure becomes a target, it ceases to be a good measure. Whatever measures and metrics you place on a system or an organization or an individual, they're open to being gamed by the participants. If people believe their performance review or any other assessment of success is based solely on the outcome of a metric or two, they will adjust their behaviour to succeed only by those measures. In the world of customer support, this means that teams will respond in ways to ensure their own success, not the success of their customers. Tickets get cherry-picked for the easy ones, ripe for picking and closing quickly. To hit the relevant metric, which is now a target, and to get a plus point on their upcoming reviews. It doesn't end there. So many metrics, so little thought as to what you're trying to measure. I once came across a post in a forum which I'll quote for you now. Here is a list of the 26 metrics we want to track at the company level. Customer acquisition cost, customer retention cost, churn rate, retention rate, monthly recurring revenue, average revenue per account, MRR churn, MRR growth rate, time to value, average days to onboard. Most common issue. Active user change weekly, monthly active users, active user change monthly, disengaged users, disengaged users change. Mean timed disengagement. Support tickets submitted, feedback tickets submitted, support channel breakdown, first contact resolution, average response time. Take a moment to gulp if you need to. As isolated entities, each of these metrics is a concrete measure of something. The question that springs to mind reading that list is what judgments of customer or service or product success can you draw from such an extensive compilation? How do you even begin to tie this together? How do you weigh and assign values to each? What customer stories can you actually tell? What is the cohesive why that pulls this list together? This is what is often missing in the design and planning of a metric system in customer support. The why. And as I so often say, the why of your system should be based on the value your customers find in your service, not the value you define for them. Design systems to support your customers' needs and then only measure what enables their success in that system. Use metrics to gather data on the success your customers find in your service, to be able to tell the stories of customer experience and adjust your service delivery to better enable their success. Use metrics to gather data that supports the stories of your customer success. Don't use metrics just to measure staff. It never works. Let's hear some other leaders talk about metrics.

Craig Stoss: 5:46

I was presenting some metrics on response times to my peers, and the average response time was quite high. And I said, this looks really bad if you kind of just judge it based on that number. But when I looked into it, you know, it was something like 65% of the response times were less than one hour, which is which was much better than our SLA was in this particular instance. And I said, And if you look at the 35% that didn't meet that, there actually is a clear trend on why we didn't. And I went into it and explained that trend. And it was incredibly well received because it basically showed that even though that number was skewed quite high by that 35%, we're really of the 65% case and the case that we know we can achieve, you know, we're still meeting all of our SLAs, and we can now uh start to even improve more and more.

Vanessa Subramaniam: 6:35

My approach to support is um data-informed, customer-centric all the time. And when you're looking at the customer experience as a whole, these data points that you're coming up with for your metrics are so important to understanding how well you're doing for the customer. Um and right now I manage the customer support and sales team. So it's kind of an interesting space because it's B2C and we have a revenue target, but we also have an NPS target. And that all falls under my umbrella. Um, when I look at individual agent metrics, I am looking at kind of the traditional stuff, call time, how many tasks are you completing, what's your um one contact resolution rate? Um, but I'm also looking at your sales targets and how well are you doing along those lines. Um I think a lot of the metrics are kind of um dependent on each other. So when you're seeing someone sell a lot, they might have a longer call time. And a lot of it as a manager is me assessing is this okay? Is it okay for the call time to be seven minutes for someone who is not selling a lot? Is it okay for the call time to be 20 minutes for someone who is selling a lot? And for complaints, is it okay for the number of touch points to be five if you take a whole day to do this? Or is it okay for the number of touch points to be one if you solve it in one go? So it's a lot of if-then kind of propositions, but the main thing is that you're measuring it and you can look at it and you can slice and dice your data because there will there will be trends that you didn't forecast would matter. And if you're collecting the data at least, and you know, in an ideal world, you have an incredible business intelligence team who tells you, hey, this is something that's spiking.

Charlotte Ward: 8:32

Or a huge spreadsheet, right?

Vanessa Subramaniam: 8:34

Whatever you whatever it is that you need, you work with what you've got.

Meredith Molloy: 8:38

Ooh, my favorite metric. I always want and strive to measure and show a balanced measurement between, you know, the the nitty-gritty, like tactical, the the service levels, the average time to first responses, and the volume goals and the contact to order ratios. But I have to say I have a real sweet spot, and it's the experience part of me that's a little cushier. That, you know, I have a real sweet spot for the quality metrics, um, and the whole and looking at them as a full picture of the not just support, but the you know, holistic customer experience um story that's being told at an organization. And so seeing how CSAT and MPS and customer effort all sort of intertwine. And if they're telling the same story together, if there is an outlier, um, I really love looking at those altogether.

Chris Taylor: 9:42

I am a sucker for metrics. I love reporting, I love data. Bring into light new metrics that have never been seen before. There are so many out there you can easily start drowning in them. I worked in an operation once where we had 15 different metrics that we were tracking on a weekly, daily basis. And because they had become such a crutch, like you need to hit this metric consistently to achieve this goal, it just completely crippled the team, and it meant that you had no flexibility and you started treating your staff like we're in the army running drills. Know what you want to show. Uh know your goals and how your metrics relate to them, and don't muddy the water with random metrics.

Simone Secci: 10:24

You see somebody uh performing particularly well in terms of like CSA, and and then maybe you can couple that with the type of issues they're working on, and that tells you like was it okay, they're working on a lot of bugs and they're making a lot of people happy. And if they were in in in a in an escalated support position, maybe they should or people that are particularly skilled at writing, like you you can't there's a lot that you can learn that maybe you you you know you haven't learned um by just reading tickets that they that they work on in that sense and and also yeah, analyzing um I do a lot of like issue analysis of trends over time with specific uh issues or specific targets or or or tracking outages, for example. The other side, the external side, is presenting a story to people that are outside support presenting the core the the right story and and within the terms that the UDM appropriate because you get one chance to uh you know to advocate for yourself in terms of uh accomplishments and challenges that you're facing.

Charlotte Ward: 11:45

That's it for today. Go to customer supportleaders.com forward slash one five six for the show notes, and I'll see you next time.