A resource for customer experience (CX) and experience management (XM) professionals.
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It’s Moving Really Fast

Release Date: June 4, 2024 • Episode #319

If you go back in time 10 or 15 years you’ll find it was common for a market research function within a company to send out a single survey each year to all customers asking about their satisfaction with the products and services they interacted with. The field has since greatly evolved as what we now call customer experience regularly receives customer feedback from multiple surveys and unstructured data, and we get that data from across multiple channels. But we still have a lot of evolution left if we want to keep up with the changes our companies are dealing with. Host Troy Powell welcome Isabelle Zdatny from the Qualtrics XM Institute to discuss the evolution of customer experience and experience management.

Isabelle Zdatny

Isabelle Zdatny
Qualtrics XM Institute
Connect with Isabelle

In this episode:

  • Chapter 1: Introduction to Modern Experience Management (00:01 – 00:54)
  • Chapter 2: The Evolution of Customer Experience (CX) Management (00:54 – 08:02)
  • Chapter 3: The Limitations of Periodic Feedback (08:02 – 14:18)
  • Chapter 4: Shifting from Data Gathering to Insight Propagation (14:18 – 17:48)
  • Chapter 5: Enhancing Listening Mechanisms (17:48 – 19:59)
  • Chapter 6: Leveraging Unstructured Data and AI (19:59 – 26:39)
  • Chapter 7: AI’s Impact on CX and Organizational Adaptability (26:39 – 31:06)
  • Chapter 8: Looking Ahead and Take-Home Value (31:06 – 33:11)

Highlights

Looking Ahead

“…if we look ahead, what we expect is that a CX program is able to provide their organization with this ongoing flow of human-centric insights, customer-centric insights, even, again, employee-centric insights, and these insights are embedded into every single decision-making and operating process across the organization.”

Count on more unstructured data

“…one of the benefits of AI tools is that they’re going to help you process massive data sets, including unstructured data sets at speed and scale. And so that type of unstructured data is going to be coming in at a much faster rate into your organization. And again, CX tends to own a lot of those channels that it will be coming in, whether that’s through contact center conversations or social media channels or online reviews. So I think we can expect more unstructured, unsolicited data as AI permeates our CX efforts a little more.”

Transcript

Troy:00:00:01
With modern technology like AI, we’ve come a long way from just asking people to fill out a survey.
Isabelle:00:00:07
If we look at kind of the business environment that our organizations have to operate in today, it’s moving really fast. And so the ability of an organization to be able to listen and respond to its environment quickly and at scale is becoming increasingly essential to business success.
Troy:00:00:26
Let’s take a look at the evolution of experience management and why it’s important to CX professionals on this episode of The CX Leader Podcast.
Announcer:00:00:42
The CX Leader Podcast is produced by Walker, an experience management firm that helps our clients accelerate their XM success. You can find out more at walkerinfo.com.
Troy:00:00:54
Hello everyone. I’m Troy Powell, host of this episode of The CX Leader Podcast and thank you for listening. It’s a great time to be a CX leader, and we explore topics and themes to help leaders like you develop great programs and deliver amazing experiences for your customers. If we go back in time 10 or 15 years ago, it was common for a market research function within a company to send out a single survey each year to all customers asking about their satisfaction with the products and services they interacted with. The field has evolved a lot since those days, as what we now call customer experience regularly get customer feedback from multiple surveys and unstructured data, and we get it across multiple channels. But we still have a lot of evolution left if we want to keep up with the current and future changes our companies are dealing with. Well, I’m happy to welcome someone to the show that will explore these questions with me. Isabellele Zdatny is the head of thought leadership for the Qualtrics XM Institute and is no stranger to the podcast. Isabelle, welcome to The CX Leader Podcast.
Isabelle:00:02:04
Hi, Troy, thank you so much for having me. Excited to be here.
Troy:00:02:08
So, Isabelle, as we think about this topic, really of the evolution of CX or XM, however you want to talk about it, which, you know, I do like the idea of experience management as kind of this overarching realm, but we know customer experience is, you know, obviously a core to that. But as we think about that evolution, you know, and you’ve written some great done some great work on this, written a great blog post, spoken about it, all sorts of places. What is kind of your thought on the evolution of the field? Both. You know, where it’s been, where it currently is. But then obviously, you know, where do we think it’s going? Where does it really need to go, is the question.
Isabelle:00:02:53
Yeah, absolutely. So I would say if we look back, as you said, you know, five, ten years ago, um, most organizations had little to no understanding of how their customers were thinking and feeling at any given time. Right. And if they did want to develop that understanding, they would deploy, you know, a generic survey, um, a generic kind of research project. Maybe that’s an annual NPS study if we’re branding it out to all of experience management, which includes employee experience management, that might include an annual employee engagement study. Um, so we do these kind of once in a while, periodic ad hoc research projects that would take months to design and field and analyze, and then the results would get shared out with just a handful of stakeholders across the organization, often in the form of static spreadsheets or reports. Um, and those stakeholders would look at their results, maybe use them to make a few decisions, and then they would just set those insights aside, right, never to be looked at again. Um, and so that’s where a lot of CX programs started. Many of them have begun to move past that point, um, but are not yet, uh, at the place where we call embedded human empathy, which we see as really the end goal of an experience management program. So if we look ahead, what we expect is that a CX program is able to provide their organization with this ongoing flow of human centric insights, customer centric insights, even, again, employee centric insights, um, and these insights are embedded into every single, uh, decision making and operating process across the organization. So customer experience management really becomes this like underlying infrastructure for the company that helps them to ingest a continuous stream of signals about the world around them. Uh, translate those data and signals into actionable intelligence and then embed that actual intelligence into the day to day operations of the business.
Troy:00:05:04
Yeah. So, you know, I love the point of kind of this movement from periodic to more ongoing or integrated.
Isabelle:00:05:14
Yeah.
Troy:00:05:14
I mean, I love the word embedded. I probably use it too much, you know, but
Isabelle:00:05:18
Yeah.
Troy:00:05:18
But that, you know, evolution and, you know, I think of the, the periodic nature and we still see that a decent amount where it is. Okay. We’ve, you know, we went out and we listened. Let’s go do a report. And even though we may have a dashboard that can change, that’s dynamic. You know, we’re not maybe feeding new data into that. And so it’s here’s the report right now go and work on some stuff and then we’ll do this. You know, we’ll do this again in six months, three months a year, you know, whatever it might be. So talk a little bit about you know, why that can really fail an organization in the modern world.
Isabelle:00:06:03
Yeah, that’s such a good question. Right? If we look at kind of the business environment that our organizations have to operate in today, um, it’s moving really fast. There’s lots of disruptive things happening all the time. Right. Putting aside the pandemic, we have things like geopolitical conflicts and workplace transformation. And probably most importantly for us, right, this looming AI revolution, we’re not sure where that’s going to land. Um, and so the ability of an organization to be able to, uh, listen and respond to its environment quickly and at scale is becoming increasingly essential to business success, the ability to kind of sense and absorb all the changes that are happening in the world around you is increasingly important for organizations to do in order to compete. And, uh, that’s kind of the heart of what customer experience can provide to an organization.
Troy:00:07:02
Yeah, I love using that word. You know, the sense I, while back, could produce some stuff on this idea of like, sense and sees as being the core of really every business intelligence function, but is ultimately that, you know, that it’s it’s the idea of you need to be able to sense and not just every so often, you know, that’s…
Isabelle:00:07:25
Yes.
Troy:00:07:25
…not going to work. You need to do that. But but then not only bringing that information inside in, but also this idea of making use of it. Right. So seizing upon the…
Isabelle:00:07:38
Yes.
Troy:00:07:38
…insights to actually, you know, make the change, capture the day, whatever you want to do of seizing that to make the change. So so talk a little bit about that because that’s um, you know, we think the listening part has gotten a lot better with see, we still have…
Isabelle:00:07:54
Yeah.
Troy:00:07:54
…a long way to go, but the seizing, like the acting and embedding part is still such a struggle. So.
Isabelle:00:08:02
Yeah, I will say I like, uh, sense and see. It sounds like a modern Jane Austen novel, so I like that. Um, so. Yeah, I mean, if we think, like, stepping back out of what a program is able fundamentally to offer an organization, right, it enables three critical capabilities the ability to continuously learn what the people around it are thinking and feeling. Right at the heart of any strong CX program is going to be that ability to listen, to capture data and feedback about how people view your organization. Again, sense and respond to what’s happening in the environment around you. But then exactly to your point, you’re not just kind of passively monitoring what’s happening, it allows the organization to then do what we call propagate insights, right? Get those insights out across the organization to the people who are best equipped to take action on them and get that intelligence out, not just to the right people, but also in the right form and at the right time within the systems and the applications that people are already using. So it doesn’t become a separate activity. They don’t have to go to different dashboards, right? It’s embedded into their normal, uh, day to day workflow. And then third, it helps them what we call, um, rapidly adapt to that increasing volume of actionable intelligence. Um, it helps like quicken organizational metabolism, uh, and empowers everyone across the organization with the ability to take, you know, timely and meaningful action on those insights coming in. So that’s where you start getting into change management, even things like automated workflows, right? We’re empowering every person to deliver those, like contextually optimized experiences within the course of their everyday role. And when that flywheel gets up and going continuously learn, propagate insights rapidly adapt. Um, that’s where we’re going to be able to start driving our organization towards embedded human empathy.
Troy:00:10:01
You know, I love that the, the flywheel sort of, you know, concept too, because it is like it takes effort to get that moving, you know, and I think that’s where a lot of us are at in this is okay, we maybe have it moving a little bit, but you know, it’s not to the point where it’s kind of easy or easier…
Isabelle:00:10:23
Yeah.
Troy:00:10:23
…to keep moving. So, you know, so what are some of those tips of, you know, from where we’re at currently to this view of, you know, the modern XM of the kind of embedded human empathy, like what are some of the things that we can start doing and acting on now to help get that flywheel moving?
Isabelle:00:10:47
Yeah, that’s the trick, right? Um, so we think of a framework that we call modern experience management, modern XM. Um, in this framework is really a modernization of those three elements I just talked about. Again, continuously learn, propagate insights rapidly adapt. And so if we break those down one by one, right. So taking that first one, how do our efforts need to evolve across continuously learn. How do we need to get better at listening. And to do that we need to move from static surveying, right? That like once in a while we are asking people a standard generic set of questions that are triggered at predetermined points along the journey. Um, most of our kind of listening efforts are structured and survey based, maybe with a little bit of operational data coming in, and we need to move away from that type of static surveying and towards what we call dynamic instrumentation, which is where an organization is able to, um, dynamically adjust both its structured and unstructured listening posts and its sampling strategy. Um, in order to satisfy this changing set of not only customer needs or employee needs, but also business needs. So depending on what business outcomes you are trying to drive at a given time, you can spin up or spin down, um, different listening mechanisms, uh, to provide you with the insights that you need to fuel your most important decisions and actions.
Isabelle:00:12:22
So that would be the first shift. Um, and here we’re thinking about things, right? Like how are we expanding our existing listening portfolios again, capturing that more unstructured, unsolicited data, which are going to be much more emotion rich and flexible. Right. Those data sets are, um, much better at explaining complex relationships. We need to get better at how we’re targeting survey feedback requests. So we’re not just asking every person the exact same question. Uh, we’re able to deploy very specific questions, um, and feedback requests based on things like where people are at in their journey, what segment are they part of, what are their personal communication preferences? What are some real time behaviors like rage clicking? Um, so move from kind of more generic targeting to more adaptive, uh, and individualized targeting. And then we also need to shift from being interaction focused, um, and collecting feedback and listening at an interaction level to looking across a customer’s entire end to end journey and really using that, um, end to end journey lens as the blueprint for deciding what data we’re bringing in when. So that was a lot. And that was just the first shift.
Troy:00:13:40
Yeah. No. Well and it’s a uh, you know, and I think it is again it’s a core function of, and, and…
Isabelle:00:13:48
Yes.
Troy:00:13:48
…we need to continue to think of ourselves well beyond just the listening component. And you and I have…
Isabelle:00:13:56
Absolutely.
Troy:00:13:56
…talked about that. And you know, it’s something that I firmly believe, but yet we still have to recognize that that kind of voice of the customer perspective, sentiment of the customer is a key piece of information that we’re often charged with bringing in to the org. So it is critical and can’t…
Isabelle:00:14:17
Yeah.
Troy:00:14:18
…stay there.
Isabelle:00:14:19
I would say it’s the foundation, right, that everything else is going to stem from. Um, it’s also often what the organization expects us to be doing with CX professionals. Um, and so if you come in and the organizational conception of CX is that you will be listening to customers bringing that voice of the customer perspective in and you’re like, no, no, no, I actually want to do all these other things over there. You’re probably going to run into some frustrations and disconnect. So.
Troy:00:14:51
Yeah. Well and, you know, and I think there’s, you know, this piece of that core functionality and what it’s look like in the past that I think is important but difficult to break from, which I would say is maybe twofold. Um, and your input there, you know, one being, we think that if the data, the customer data that’s going to be used and their voice kind of has to come through our channels and our methods, and then two, that there has to be some kind of like consistency of trending. Right. Like, hey, that, and I know in a lot of times like trend is God. It’d be like, hey, we hate this survey and we hate this question, but we’ve asked it for ten years, so we can’t…
Isabelle:00:15:39
Yeah.
Troy:00:15:39
…change it, you know? And so those two…
Isabelle:00:15:41
Yes.
Troy:00:15:41
…pieces that you do have some importance that we sometimes need to break with. So talk a little bit maybe about your thoughts there of how we break some of those habits.
Isabelle:00:15:53
It’s so funny. I know you didn’t set me up for this, but that does actually bring us pretty perfectly into the next shift, um, that we recommend making. Which again, is that like propagating insights. So moving from repetitive reporting, where again, we’re just like periodically sharing out these static kind of documents, maybe spreadsheets, decks and into this, um, actual intelligence. Right. This highly tailored insights that are delivered through various different reporting mechanisms. Um, and the reason that you set me up so well for this is the first shift that we recommend under here is moving away from just obsessively tracking metrics, right. Those top line metrics can give you some useful snapshot of where your program is, how it’s trending. Um, it can help you compare against broader benchmarks. However, if we think that we’re living in this incredibly disruptive world, then historical trending suddenly becomes much less important than it has historically. Because the world this year is different from the world last year. Um, so I don’t think that, you know, top line metrics like NPS or customer satisfaction or anything are going away. But I think as XM professionals, as CX professionals, we need to get better at focusing on like, what are those key drivers that are affecting those metrics that we’re pulling in? You know, CSAT scores, effort scores, whatever it is, what is driving those scores? And then how are we, um, you know, prioritizing initiatives that are going to help move those, the needle on that. So, um, I do think as we move forward, we need to be conscious that we are responsible for understanding what is driving those top line metrics, even if they’re coming in from other departments.
Troy:00:17:48
No, that’s very good.
Troy:00:17:59
Well, you mentioned it a couple times, the use of unstructured data in that because that, you…
Isabelle:00:18:05
Yeah.
Troy:00:18:05
…know, again, I’ve been talking about that for a long time and CX and how to make use of it. And that is a common source that, you know, comes in from a lot of places outside of, you know, what CX produces.
Isabelle:00:18:19
Totally. And I think every organization is going to be different, right? Like, you know, the value of vendors, like for instance, Qualtrics is that it provides you with an enterprise application for hosting all of your experience data that you can pull in from different systems. Um, and then send back out to your other operational data systems like CRM, HCM, ERP and everything. So I think you know this your experience data like as a team, you are not going to be responsible for every single piece of data coming in. But you need to understand how the experience data that you own is playing within that broader tech stack. And as you say, unstructured data is going to be absolutely essential for that. Um, right now, unstructured data does a lot of work. It’s really hard.
Troy:00:19:12
Yes.
Isabelle:00:19:13
Um, but if we look ahead, you know, even a few years and I’m sure we’ll get to AI is kind of the unspoken, you know, underlying theme probably running through this conversation. Um, one of the benefits of AI tools is that they’re going to help you process massive data sets, including unstructured data sets, um, at speed and scale. And so that type of unstructured data is going to be coming in at a much faster rate into your organization. Um, and again, CX tends to own a lot of those channels that it will be coming in, whether that’s through contact center conversations or social media channels or online reviews. So I think we can expect more unstructured, unsolicited data as, uh, AI permeates our CX efforts a little more.
Troy:00:20:09
Yeah, well, and that is a perfect I had held off on bringing AI into the conversation
Isabelle:00:20:15
We did so well…
Troy:00:20:16
That’s been mentioned.
Isabelle:00:20:16
…for so long.
Troy:00:20:16
Yeah, because, you know, there are other things other than AI, but there is this, you know, and specter is not the right word. That kind of is a negative. There’s this, you know, bright shiny cloud of of AI…
Isabelle:00:20:33
Yeah.
Troy:00:20:34
…that’s, you know, definitely here and on the horizon. So, you know, as we think about this, you know, kind of near term evolution that in some ways we’re going to be forced to deal with if we don’t actively, you know, jump…
Isabelle:00:20:51
Yeah.
Troy:00:20:51
…on board. Anyway, um, talk a little about how AI will kind of one change the dynamics, but two potentially help us if we can grab a hold of it in the right way. Help us move forward in this evolution.
Isabelle:00:21:05
Yeah, I think at its core. Right. Ai is going to help us do a lot. Not all, but a lot of our existing CX activities. Um, much more quickly and economically. I think it’s also going to help us kind of uncover new ways of understanding and serving our customers. Um, right. But as we look across, again, this modern XM framework, think about how it helps us continuously learn. Right? Listen to people better. As I just said, it’s going to help us ingest and process much more information at speed and scale. Thinking about propagating insights or getting those out across the organization. AI is going to help us, um, transform that raw data we’re pulling in into actionable intelligence much more quickly. Right? We have a not just set of statistical analytics tools, but now AI powered analytics tools like predictive modeling and journey analytics and generative AI that are going to help us kind of, um, get more meaningful hidden insights, find those patterns in these large data sets. It’s also going to help us democratize those insights across our organization. Right. Like generative AI allows everyone to explore and query data using natural language prompts or will, which is going to help everyone kind of uncover actionable, prescriptive insights that they can use in the course of their everyday role.
Isabelle:00:22:40
So I think it’s going to fundamentally transform any number of our activities. And even moving into the last one right under rapidly adapt where we’re going from these type of periodic improvements that you and I were talking about, to just embedding these insights into the continuous flow of day to day business operations, um, AI is going to help trigger automated workflows off the back of, uh, data elements and analytics coming in. So. For example, if a customer leaves a comment on your website through passive feedback using a word like bug or issue that can just automatically create a ticket in JIRA for your web engineering team to address in its next sprint. Or you know, the contact center agents empathy scores are trending down. It could automatically set up a one on one meeting with the manager to, um, to work on that and pull relevant data snippets from their conversation. So I think across kind of this listen, understand, act, it’s accelerating every element across there. Sorry. That was a very long answer.
Troy:00:23:49
Yeah. Well, no, it’s a very…
Isabelle:00:23:50
Yeah.
Troy:00:23:50
…big topic.
Isabelle:00:23:51
Complex.
Troy:00:23:51
Right? So yeah, I wanted to be careful how we brought it out because it could, you know, obviously there can be lots of episodes solely on AI.
Isabelle:00:24:00
Totally. Yes.
Troy:00:24:00
So I think what I’ve liked about your approach and how you guys talked about it is this piece of, okay, there’s a ton, you know, and in CX, we’re kind of at this like intersection of two forces, which is one, you know, how AI can kind of change the way we do our jobs and change the what our functions really are, but then it’s also changing the way all of our companies are interacting with and delivering experiences to customers. And we have to stay abreast of that. And that’s that adaptability you talk about becomes even more critical now because things are changing. And so if we’re surveying in a certain way about certain things like that, we’ve always done like it’s going to be irrelevant. And you know, that…
Isabelle:00:24:50
Totally.
Troy:00:24:50
…listening post completely no longer matters in a few months, perhaps. So, you know, we’ve got to adapt to our businesses plus adapt our functions. And and that’s, you know, a lot.
Isabelle:00:25:02
I love that point because like as I’m thinking about it, right, like AI is going to accelerate CX but CX can also accelerate your organization’s adoption of AI, right? Because again, we have this continuously learn, propagate insights rapidly adopt. We have those, um, human centered design practices to help understand how our customers are receiving AI. Do they want to be talking…
Troy:00:25:31
They are.
Isabelle:00:25:31
…to a chat bot? Um, roll it out, make sure it’s working as expected, and make sure that we’re designing AI driven interactions that are resonating with our customers and employees. So I think there’s a very symbiotic relationship happening here. Um, and there’s a big role, you know, we’ve talked about before, I think one of the struggles as a CX professional looking at AI is that at the end of the day, good AI models require lots of clean data, right? Compounds that…
Troy:00:26:02
Right.
Isabelle:00:26:02
…garbage in, garbage out issue. And a lot of that is outside the control of a single CX team. You probably don’t have the necessary skill set on your team to build these advanced AI models. And so I think we all can kind of see how CX and AI are related. Um, but we’re also a little bit outside of it, and a lot of elements are outside of our control. So I think we can help kind of shape up the use cases, um, help make sure that we’re providing strong experience data to feed those models. But it’s going to take some figuring out for us as a profession.
Troy:00:26:39
Yeah, well, we’ll definitely keep talking about it for sure, I think.
Isabelle:00:26:42
Yeah. I don’t think AI is about to go away.
Troy:00:26:46
No, doesn’t
Isabelle:00:26:46
Probably…
Troy:00:26:46
Seem like it.
Isabelle:00:26:47
…if I had to guess.
Troy:00:26:49
So, you know, there’s a lot we’ve talked about of things to change, adapt, start doing, pushing forward on. And you know it can seem both daunting and sometimes like, okay, are we prepared for this. Is this something we can even do? So talk to me a little bit about why you’re kind of optimistic or hopeful that now is the time for CX to be able to make some of these changes.
Isabelle:00:27:17
Yeah, that’s such a good question. I think as we think of ourselves as a profession, again, historically, I think we’ve seen ourselves as kind of gatherers and shares of data. And as we get better and better at right, like listening, understanding and acting on this continuous flow of insights, we’re evolving as a profession beyond that, we are now able to provide our organizations with like a operating model for successful business transformation, which again, given things like the disruptive environment, the rise of AI, the maturing CX skills and capabilities, it’s still a pretty young profession. CXPA was founded in 2011, right. Um, given the advancing CX platform capabilities, I think these are all accelerating our work, helping us kind of embed our insights and practices across the organization, um, at a faster rate and is a perfect time for us to step up and say, hey, we’re able to provide the company with value beyond just like a once in a while survey.
Troy:00:28:43
Yep. Excellent. Well, now’s the time of the program that we ask everybody for this little piece of, uh, take home value, you know, in this context is a pretty loaded question. I know. Right. So but from the standpoint of a CX professional listening to this and saying, okay, like, you know, we’ve got a we’ve got a journey ahead of us, but what…
Isabelle:00:29:07
Yeah.
Troy:00:29:08
…are some ideas for a first step on that? So what are, uh, you know, an idea. There might be more than one in this case that but…
Isabelle:00:29:15
Yeah.
Troy:00:29:16
…that, uh, professional can take to get started on this journey.
Isabelle:00:29:21
Great news everyone! I have a silver bullet to solve all of our…
Troy:00:29:23
Oh, I love this.
Isabelle:00:29:24
…I’m just kidding.
Troy:00:29:25
Okay. Darn it!
Isabelle:00:29:26
Absolutely not. Um, I would say, right. As we’re looking ahead to all of these changes, a piece of advice I find myself giving clients fairly consistently is to work from right to left. Start with the outcomes that you are trying to achieve for your XM program, for your business strategy. Um, and use that to guide all of your downstream decisions and priorities. Right. Having that standard that people can look to and strive for is going to help, um, align efforts across the organization. If you know what you’re trying to achieve, it is going to help you make decisions like which AI use cases should we tackle first? What new types of listening mechanisms should we stand up? Right. There’s a lot of unstructured, unsolicited data out there. Um, Qualtrics has a statistic that like 90% of all data created going forward is going to be unstructured. That’s a lot of data. If you don’t have a plan in place and know what you’re trying to achieve, you’re going to get very overwhelmed very quickly. Um, if you don’t know which segments are most important to be collecting feedback from. So my advice is start from right to left, start with a vision, the outcome that you want, and then work backwards from there, because that is going to help you prioritize your tasks and activities and help you break them down into smaller, more, um, digestible chunks.
Troy:00:31:06
Yeah. Great advice. Well, Isabelle Zdatny is the head of thought leadership for the Qualtrics XM Institute. So, Isabelle, thank you so much for being a guest on The CX Leader Podcast again. And we really enjoyed the conversation and look forward to having you back.
Isabelle:00:31:23
I always love chatting with you too. I thank you for having me.
Troy:00:31:26
So what is the way if people want to continue this conversation, maybe have a deeper conversation, which I would recommend given the depth of your thinking on this topic, what’s a good way for them to reach you?
Isabelle:00:31:37
While the good thing about having a last name that is unpronounceable is it makes me very easy to find online. So always feel free to add me on LinkedIn. Send me messages. Um, Isabelle Zdatny. Z for zebra, D for dog, A, T, N, Y. Um. And I would also strongly recommend checking out our website, xminstitute.com. We have hundreds of free resources that are specifically designed to help, uh, customer experience professionals kind of grow their own personal maturity and the maturity of their, uh, customer experience programs. And all of that’s available for free, including a lot of the content I was talking about today. So, as you said, we just kind of brushed the surface. Uh, there’s a lot more depth and tactical advice on xminstitute.com, so check it out.
Troy:00:32:31
Excellent. Yes. And I’ll second that. And then, you know, I try and go out every week or two to the XM Institute website. And there’s always multiple new things to look at and, and get insight from. So and if you want to discuss this topic with one of our experts or have a great idea for a topic on a future episode, email us at podcast@walkerinfo.com. We’d love to hear from you! Be sure to rate The CX Leader Podcast through your podcast service and leave a review. Your feedback will help us improve the show and deliver the best possible value to you, our listener. Check out our website cxleaderpodcast.com. From there, you can follow the show and find all our previous episodes and a link to our blog, which we update regularly. The CX Leader Podcast is a production of Walker. We’re an experience management firm that helps companies accelerate their XM success. You can read more about us at walkerinfo.com. Thank you for listening and remember, it’s a great time to be a CX leader. We’ll see you next time.
* This transcript was created using an A.I. tool and may contain some mistakes. Email podcast@walkerinfo.com with any questions or corrections.

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