The CX Leader Podcast: "The Story of Customers and Employees": Audio automatically transcribed by Sonix

The CX Leader Podcast: "The Story of Customers and Employees": this wav audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.

Pat:
There's always a story waiting to be discovered between your customers and your employees. But how do you piece together that narrative?

Kevin:
A lot of times the EX folks and the CX folks will create Journey Maps, which is great, but you want to make sure that you're not only creating those independent journey maps, but think about those shared moments that matter. And where are those intersections where your personas on the customer and employee side are going to connect? And what do you really want to measure at that moment?

Pat:
Connecting your customer experience and employee experience on this episode of The CX Leader Podcast.

Announcer:
The CX Leader Podcast with Steve Walker is produced by Walker, an experience management firm that helps our clients accelerate their success. You can find out more at walkerinfo.com.

Pat:
Hello, everyone. I'm Pat Gibbons, guest host of The CX Leader Podcast and thank you for listening. As we like to say around here, it's never been a better time to be a CX leader and this podcast explores topics and themes to help leaders like you leverage all the benefits of delivering amazing customer experiences. As more companies realize the potential of a customer centric culture, discussions have focused more and more on how experiences of your employees affect your customers. Employee experience, or EX, has often been siloed in human resources. And in fact, we've covered that in several episodes that you can find on cxleaderpodcast.com. But what about the connection between customer and employee experiences? How does that change our approach? What data do we collect and how do we activate a CX plus EX culture to make the best use of what we discover? Well, my guest today has literally made a living out of answering these questions. Kevin Campbell is an employee experience scientist at Qualtrics. Kevin, thanks for being on the CX Leader podcast.

Kevin:
Thanks for having me.

Pat:
Yeah, it's great to have you. And full disclosure, I think a lot of people know this, but Walker and Qualtrics are partners. We do a lot of work together on EX and CX and everything. So this is always kind of a timely topic, you know, and I kind of like to put out some table stake, you know, here. I think most of our listeners by now probably know that happy employees make for happy customers. We're going to go a little deeper than that, right, Kevin?

Kevin:
I think we're going to scratch way below that surface.

Pat:
All right.

Kevin:
Everybody knows that to some degree, but there's the. So what related to that? The now what and the how. Yeah. And really digging into what parts of those connections are going to yield you the most return on action for both of those statements.

Pat:
Perfect. Yes. Sounds like a good plan. So to give it a little context, let's let people know a little bit about you and your background. Tell us about yourself, Kevin.

Kevin:
So I'm an organizational psychologist by training at the master's level. Prior to going into this field of people and EX scientists, I was actually a headhunter, was recruiting semiconductor engineers for companies like Samsung and Intel. And eventually I landed at Google as an internal recruiter, recruiting software engineers from around the world to their campus in Mountain View. And despite working at the best place to work, according to all the workplace lists at the time, I still saw a high degree of variance in terms of how engaged people were in their role, and I wanted to figure out what it was that actually makes people happy and the business outcomes associated with that. And that's why I went back to graduate school and worked as a consultant with Gallup, Deloitte. I've done my own thing for a while and now I am working with Qualtrics as an employee experience scientist, helping organizations identify and close gaps in the employee experience and increasingly identify the ways that that employee experience connects back to important business and customer outcomes.

Pat:
Yeah, now great background. And you know, it really, I think really it has evolved. You know, I think a lot of people, even in the CX role, have just kind of said, well, EX, you know, the measurement of that that's over in HR or they're working on that. And it's a little different when you're just trying to gather feedback from employees to understand how they feel, how loyal they are and everything. It's a little different when you're trying to say, what's the effect on customers? How have you started to kind of put together those two things?

Kevin:
Well, I think the first thing is to is in many ways it mirrors the experience with measuring employee experience in that there are outcomes and there are drivers. So what's the ultimate outcome that you want to achieve over and above the operational data? How do you want people to feel as a result of that experience? And then on the employee side, what are the actual actionable driver related things that you can have an impact on? So if you want more customer loyalty, if you want customer likelihood to return or satisfaction, rather than just measuring the outcomes on the EX side and trying to link those, go back to what's the ultimate behavioral measure you can have so you can operationalize that for front line leaders and employees to say, What can we actually do to help reach this outcome rather than measuring things like and these are great questions. I'm a I'm a psychologist, right? So I love questions like I feel energized work or I want to give extra discretionary effort, but you can't walk up to your employee and go feel more energized at work, feel more proud to work for this company.

Pat:
Right.

Kevin:
Right. And you do a better job of recognition. You can do a better job of setting expectations. You can give them the materials and equipment that they need. Right. So how do you break that down to the actionable pieces and build that into your measurement so that you're building in the actionable things from the very beginning of how you set out to to approach your listening strategy and your action strategy so that when you find that connection, you know what to do with it, right?

Pat:
So to get the outcome you want, it works all the way back to what data you're collecting. Is that is that a good way to think about it?

Kevin:
The great way to think about it.

Pat:
Yeah. So when you're looking at all that, are there certain types of data that are most common that you find put that kind of link together that results in action?

Kevin:
Yeah. So it's, it's oftentimes there'll be a relational survey on the customer side and what we would call or consider a relational survey on the employee side. So like an engagement survey or a pulse survey. And then oftentimes we actually find an even stronger relationship. When you're thinking about the relational survey on the EX side, like an employee engagement or a pulse survey, and then connecting that back to specific customer transactional surveys. Right? Because the the mindset of the employee at the time of that transaction is what's going to inform the satisfaction with that transaction, the amount of effort that that the customer had to put in, and the degree to which they were able to successfully accomplish what they set out to do, because a more engaged employee is likely to go above and beyond in those instances and really create those above baseline experiences for the customer.

Pat:
Yeah. So let me ask you this. I think we can learn a lot from the ways we do things. Maybe not so much the right way or, you know, what can we learn from mistakes that you've seen when people look at how they collect data from employees and customers?

Kevin:
Well, I like to think about it in terms of what's the way that organizations normally approach this and what are some of the knock on effects that we see around the way that organizations normally approach this and how we see people that are really getting this right do it.

Pat:
Okay.

Kevin:
So a couple of common themes that we see is just mining the data for any kind of statistical finding. A lot of times the EX folks and the CX folks will create journey maps and develop personas for their customers and employees, which is great. They will focus on the direct connection between employee experiences and how that impacts customer outcomes. And a lot of times what's underpinning the motivation for all of this is using advanced analytics to uncover insights that you might not normally see. And all of those things on the surface are amazing. However, there are some results associated with that that you'll see from a lot of other firms that might not work with someone like Walker or Qualtrics. Is that mining for those those insights and testing every connection is great. But sometimes when you test all possible variables, it can lead to some really questionable or un actionable findings. Right? Like okay example of that from stats is ice cream sales go up when sunscreen sales go up, but we know that one's not driving the other. So it could leave you scratching your head right. And creating journey maps is is great. I do a lot of that work we do a lot of that work with customers.

Kevin:
But you want to make sure that you're not only creating those independent journey maps, but think about those shared moments that matter and where those intersections where your personas on the customer and employee side are going to connect. And what do you really want to measure at that moment? And while it's important to look at how employee experiences directly impact customer experience, oftentimes there's operational data like employee retention. That's often the missing link. We had talked before we started recording a finding that you had, and I said, you know, maybe there's there's an operational piece that's relevant there. Right? And so so sometimes that direct connection is important, but what are those indirect loops and moderators and mediators that can really amplify things? And then last but not least is I'm a I have some statistical training. I'm an organizational psychologist. I love advanced analytics and fancy dashboards and charts, and I can create those for days. But you have to always think about how do you want to translate that into practical actions for employees and frontline leaders so that they know what to do with this information and they can make it move forward?

Pat:
Yeah, you know, that's kind of where I was going to go next. Do we make this too hard sometimes?

Kevin:
Absolutely. So, you know, and I can I can tell you a story for days around that. Right. Like I was working with a large hospitality company that doesn't own any hotels and they had a full people analytics team. And these folks were econometricians. So they they had statistical chops that a lot of data scientists don't even have. And I was working with their organizational development manager as well, who is really great at just working with people and driving action and doing training. And they had done an analysis where they looked at what were the drivers of employee engagement over the last five years. So they did some time series data, they factored in bunch of demographic variables, ran a multiple regression that controlled for things like tenure and gender and a lot of really interesting things to make sure that they were getting a real accurate understanding of based upon all the data they had over the last five years, what were the top five drivers of engagement? My analysis that I had off of the platform that I was working with just did a bivariate correlation of like when X goes up, does A go up? When Y goes up, does A go up when Z goes up, does C go up? And guess what? Four out of the five drivers in both of the analyzes were exactly the same. Now their analysis was way more accurate and way more insightful.

Pat:
Right.

Kevin:
But try and explain that to an organizational development manager.

Pat:
Right.

Kevin:
Right. Like I could explain in a few seconds what my finding was. And more importantly, what do you want to go do with it? And there's I don't know if we ever really got to the bottom of of what that meant for her. So so sometimes less is more and sometimes you it's okay to have a directional point of view rather than an absolute understanding if the action that you're going to take is a low risk, high reward action.

Pat:
Yeah, I think, you know, one of the the traps we all fall into when we have an appreciation for statistics and analytics and so forth, is we want to tell everybody everything about it. And I think one of the things you're saying is, you know, keep it simple, get the point across about the actions that can be taken and, you know, really give easy to follow direction. Maybe you've got an example or you can comment on that as well.

Kevin:
Oh, yeah. I mean, I love to use that, that acting on feedback is as easy as ABC. One, two, three. So A is is action oriented. The point of looking at this information is to focus in on something and do something with it. B is business relevant. So sometimes I'll encourage people to have a conversation around business goals before you do any kind of action planning, before you look at any dashboards or reports. Take a step back and say, What are our objectives and key results for the quarter and what do we want to get done? And then once you have that clearly in mind, look at your results and and see how that informs how you might act on that. And then the C is conversation based. So, so keep it conversational. And a lot of times leaders will go into a corner and look at all the information that's at their disposal and come back to employees with an action plan that they've hatched in a silo. But the way that's going to get you more buy in from people and have a higher likelihood of follow through is to have a conversation around that and a co-creation with your employees.

Kevin:
And then when it comes to communicating what you've done, keep it as simple as one, two, three. Take one area of focus. Do two things about it and communicate it three times through three different channels, because oftentimes it's not whether or not the action happens, it's whether or not the action is salient to the people that the action is being acted upon. Right. So we did X because we heard Y from you. A lot of times they'll see you doing Y or they'll see you doing X, but they won't connect that back to Oh, that was part of that conversation that we had last month, that conversation that we had last week. This was part of something that I came up with as an idea, and now I'm seeing it actually being put into action. Wow. How engaging is that? So yeah, keep it. Keeping it simple. Having a simple framework and focusing on on moving the needle with the data is probably the most important piece.

Pat:
Yeah, that's a great framework. I love it.

Today we're talking to Kevin Campbell. He's an employee experience scientist at Qualtrics, sharing some really interesting insights on combining employee experience and customer experience. Let me mention a few of what I see as kind of obstacles to combining CX and EX. And the first one I'd mention is the silos. I think there's just kind of a general understanding or a general practice that CX is run by a CX team or a marketing team or something on that side of the business, and EX is run by H.R. And in many cases they don't interact or share the information at all. What do you recommend as far as trying to put that together?

Kevin:
I recommend start with the people that are your people that are cut from the same cloth. And I think there are two personas that I see in both the EX and the CX side. It's business minded HR professionals and culture minded business professionals. So whichever of those two personas you identify with. Find your kindred spirit on the other side. And I think Bruce Temkin, the XM Institute, he's he's been a guest on this podcast about sometimes there's an overemphasis on organizational alignment. And that's not to say that we don't want to build governance, that we don't want to create those structures to break down those silos ultimately. But the way to get there isn't always from the top down. Sometimes it's from the bottom up or from the side to side. So find people in the other pillar of your organization who want to collaborate. Do great work for them, make them successful, and then start a revolution from the bottom up. It'll catch like wildfire when people start to see their success and they're going to start to want it. So I think start small, find your kindred spirits and do really, really great, impactful work for them. And then you'll see results happen over time.

Pat:
Yeah. Now that's great. Another potential obstacle is, you know, the technology or the things that facilitate gathering the feedback. In many cases they were probably purchased separately. They might be using different platforms. I know that that's kind of an area that Qualtrics is focused on. Any anything you can tell us at a high level about how you combine the information?

Kevin:
Great question. And I want to caveat my response by saying that I am on this podcast is Kevin Campbell. I do work for Qualtrics, but I'm not acting as a representative of Qualtrics. So anything that I say related to platforms or related to anything that we've covered is just based upon my personal experience and not any part of any kind of official statement from from Qualtrics proper. With that being said, there are a lot of exciting things that you can do with the right technology in the right platform, such as having it all in one place makes makes that analysis and creating those data joins and building those data models so much easier. And it's it's it's not just about because I've seen some systems out there that say they bring these things together. And what they really just mean is that they'll put the reporting side by side on a dashboard, which isn't a bad thing. But the thing that is actually useful is to say, what's the connecting point between those two? How do you bring those together in a seamless way that doesn't require a lot of manual processes? And how do you create a shared unit of analysis quickly and easily so that you can run your analysis in a way that is really as easy as a click of a button? Right.

Kevin:
So if you look at you have thousands and thousands of records oftentimes on the customer side, and you have hundreds of thousands, hundreds or thousands on the employee side. But analyzing that data at that level isn't always useful. What's what's more useful is when you can aggregate it at that shared moment that matters or that shared unit of analysis. So maybe it's a location based business or it's bank branches, it's restaurants in a call center. It might be different customer service teams, might be technician teams, but aggregating at that shared unit of analysis so that every data point is the average of your employee responses for a time period and the average of your customer responses for a time period. So now you're breaking it down into maybe a few hundred locations or a few hundred teams, and you can put that on a two by two and see that clean relationship between customer experience and employee experience. And you can break down the specific behaviors. And when it's when it's when you when the data is all in one place and you can combine that right away, you can you can hit your your button, run all of the bivariate analyzes and be able to see within seconds what's going to what's giving you the biggest bang for your buck.

Pat:
Mm hmm. That's great.

Kevin:
Download and recode and combine and… ahh!

Pat:
So if somebody's listening to this and they're like, yeah, you know, this makes sense, I've got to get started somewhere. Where do they get started?

Kevin:
It's interesting because in the ideal world, they would get started with creating those combined journey maps, thinking about what are the outcomes they want to build, and being very intentional about thinking about what hypotheses they want to test. But we don't live in the ideal world, we live in the real world. So oftentimes this continuous improvement is a cycle and you can enter that cycle at any point, right? So you can start with what I call visioning, which is sort of that that top down testing of hypotheses based upon your theory of what's happening in the organization, which is my preferred approach as a scientist, and I think most consultants would probably prefer that. But you're really only going to be able to do that if you have people playing nice together, you're you're already kind of a little bit more mature. You're bringing these programs together or maybe you're the owner of both programs, or maybe you want to start bridging that conversation. So that's one place to start. Or you can start on the other end of the spectrum, which is more bottom up generation of theory based upon observable data. That's a little bit more exploratory. So maybe you've had some existing programs and they they weren't designed with that joint analysis in mind. But you can do some data spelunking, right? And you can go in there and you can say, okay, well, well, what are the connections between these things? And once you have that, you can start to build more a priori hypotheses and do some more top down visioning. Or if you start with a top down visioning, you'll test your theories, you'll get some data, you'll run the linkages, and then you'll, you'll say, Oh, wait, this works, this doesn't work. And then you'll start that cycle over again. So there's a quick answer is there's one right place to start, but there's a right way to do each of those. And there's cautions and risks with each that you want to take take into account.

Pat:
Mm hmm. You know, I think it's good advice because I think sometimes we're under the impression of, well, I have to figure out the starting point, and it's all linear. I start here and this is the path. And I think what you're saying is it really depends. And you can enter that cycle at any different stage and none of it is necessarily wrong. Better to get started than to try to spin your wheels, trying to figure out where to start it, right?

Kevin:
Yeah, absolutely.

Pat:
Well, we've come to that point that we ask you for the take home value. It's kind of our staple of the show. We ask every guest for one tip that companies can put to use right away. So what is your take home value, Kevin?

Kevin:
It's a little bit different than what we've been talking about, but since we're talking about experience management. I think it's helpful to unpack this idea. And I think the the main person who articulated this best is Daniel Kahneman. He's a just a hero of mine. He won the Nobel Prize in economics despite not being an economist. He's a psychologist. That doesn't happen. But if you're to oversimplify his the main thrust of his findings, it's that a small percentage of human decisions are based on rational, deliberate thinking and decision making. The vast majority of human decisions and the way that we experience reality is through emotions and biases and heuristics. And my main takeaway is that to be a true XM leader, it's to see that feature of human beings not as a bug, but as a feature. That irrationality, that emotionality is what we need in today's economy, especially because if you can't compete on price for your customers and you can't compete on wages for your employees, the only place where you can compete is on experiences and irrational behaviors that connect back to people's emotions and their psychological connection with you and your brand and your workplace and your people.

Pat:
Excellent insights. Kevin Campbell is an employee experience scientist at Qualtrics. Kevin, thanks for being on The CX Leader Podcast.

Kevin:
My pleasure.

Pat:
Can people reach you or are you available on LinkedIn for additional conversation?

Kevin:
I am a LinkedIn open networker, so please find me on LinkedIn. I'm Kevin Campbell. I have a string of letters after my last name, XMP, ACC, MA. I don't have a PhD, but I figure if I get enough other credentials eventually it'll lead up to one. But it's an easy way to find me. Kevin Campbell, the one with all the letters. Send me an invite. Let's connect. I'm very generous with my time and open to talking to pretty much anyone that that wants to geek out on this stuff along with me.

Pat:
All right. I love it. I love it. And if you want to talk about anything you've heard on this podcast or how Walker can help you with your business customer experience programs, feel free to email us at podcast@walkerinfo.com. Be sure to check out our website cxleaderpodcast.com to subscribe to the show and find all our previous episodes, our podcast series, our contact information so you can let us know how we're doing. The CX Leader Podcast is a production of Walker. We're an experienced management firm that helps companies accelerate their XM success. And you can read more about us at walkerinfo.com. Thank you for listening. And remember, it's a great time to be a leader. We'll see you next time.

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