The adoption of AI into customer experiences, and marketing efforts is happening—rapidly. But it’s not enough to just slap AI onto an existing interaction. Success lies in how humans plus AI work together to create what my guest today calls boundless experiences.
Today, from the Forrester CX Summit North America, we are thrilled to have JP Gownder, Vice President and Principal Analyst at Forrester Research, with us to discuss the crucial alignment of customer experience, digital experience, and marketing.
J. P. Gownder is a vice president and principal analyst on Forrester’s Future of Work team. He covers the impacts that technology and human factors jointly have on the future of work. He helps clients design strategies that drive productivity, collaboration, and effective hybrid work. His research also covers how technologies like devices, collaboration software, extended reality and the metaverse, and artificial intelligence and automation reshape the future of how and where we work, what our jobs look like, and how we can drive productivity, collaboration, and the employee experience.
Previous Work Experience
A prolific writer and speaker, J. P. has written articles for publications such as Mashable, Information Week, ComputerWorld, Forbes, The Los Angeles Times, and The Washington Post. He has also been quoted in The Financial Times, The Wall Street Journal, The New York Times, USA Today, Wired, and many other publications, and he has appeared on NBC television, Bloomberg television, Voice of America, National Public Radio, and other media outlets.
Education
J. P. graduated from Harvard University with a BA (magna cum laude) and an MA in political science. He also conducted research at the Harvard Business School.
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Transcript
Greg Kihlstrom:
The adoption of AI into customer experiences and marketing efforts is happening rapidly. But it’s not enough to just slap AI onto an existing interaction. Success lies in how humans plus AI work together to create what my guest today calls boundless experiences. This is certainly something we heard about a lot at the recent Forrester CX Summit North America in Nashville. Today, I’d like to welcome J.P. Gounder, Vice President and Principal Analyst at Forrester Research, to join us today to talk about the crucial alignment of customer experience, digital experience, and marketing. J.P., welcome to the show. Thank you for having me. Yeah, looking forward to talking about this with you. Why don’t we get started, though, with you giving a little background on yourself and your role at Forrester?
J.P. Gownder: Sure. I’ve been at Forrester for 19 and a half years, so quite a long time. And as you can imagine, across that period of time, I’ve done lots of things. I primarily work on the employee side of the world, of late, employee experience, the future of work. I do a lot of generative AI, as you might imagine. But of course, for this event, I went full in on customer experience, marketing, and digital business with my keynote.
Greg Kihlstrom: Great, great. Well, yeah, so let’s dive in here. We’re going to talk about this concept of boundless experiences and how this is replacing traditional customer life cycles. So let’s start with that definition. How does a boundless experience differ from what many marketers and CX professionals think of as maybe something like omni-channel CX?
J.P. Gownder: Yeah, I think that boundless experiences go even further than omnichannel in terms of the expectations that customers have. So traditionally, as you referenced in your question, we had customer lifecycle stages where someone discovers a potential purchase and then they engage with it, they evaluate it, maybe they purchase it, they’re going to have an experience with the product, some kind of support, and hopefully loyalty at the end of that. But we tended to look at that as kind of a linear, or even if it’s a circle, it was a step-by-step process where you had to go from one step to the next. And what is happening is that that’s kind of collapsing. There’s a lot more opportunity for things that involve experience to happen earlier, or marketing to happen later, or being able to be digital across the entirety of that relationship you’re building with a customer. So as a result, we need something new to talk about this. Omni-channel is a prerequisite, it means you’re going to get that consistency across channels, but it means that we’re going to be zigzagging and we’re going to be involved in all these different stages, and some of those stages may simply just go away altogether.
Greg Kihlstrom: Yeah. So there has been a lot of focus on at least the Omni-channel, component of this, certainly based on some initial successes, but how do we know that this is what customers want?
J.P. Gownder: Yeah, I think we find some examples of this in their existing behavior and in their pain points, right? So take an example, I won’t use any specific names here, but I think we’ve all experienced an instance where the marketing that we’ve experienced about something that we purchase doesn’t at all seem to be reflected in the experience we get after we buy it. And that kind of misalignment is not useful to organizations that are trying to serve customers, but it also, you know, it’s tremendously frustrating. It may undo our loyalty to that entity for the future. It’s quite possible as well that new technologies, when you use them the right way, can actually point people in the right direction. Generative AI, for example, can be used to create a lot of personalization. that takes into account what you’ve been told before who you are what your expectations look like what your behavior look like we’re not completely there yet but we’re building toward a world in which we simply understand each individual customer better and we can deliver a better promise to them as a result.
Greg Kihlstrom: Yeah. Yeah. And I think, you know, certainly the, the research bears this out and Forrester has, has plenty of supporting points for customers wanting things like you mentioned, like personalization and really just consistency across channels. You mentioned you work a lot on the employee side of things in the future of work side of things. You know, I’m wondering, Most people, most leaders probably know this, that this is valuable and know that there’s potential here. But what’s getting in the way of brands actually delivering on this concept of boundless experiences?
J.P. Gownder: It could vary quite a bit depending on what kind of an employee we’re talking about and what kind of environment in which they work. I’ve done some recent research into the frontline, for example, which is often really interesting to CX people because these are employees who are working directly with the customer. And there are a whole host of problems of misalignment that employees have. To take a simple example, let’s say we’re talking about retail. Somebody who works in that space may be juggling multiple jobs. And so if they have poor shift scheduling software, or maybe not even software at all, maybe they’re using, you know, a list on a board, which still happens in far too many places, it makes it hard for them to balance out their life because they have multiple jobs, they don’t have access to trading off their shifts. Something as simple as that can lead to you not having coverage for your retail outlet at a time when there’s lots of customers coming in. On the white-collar or corporate side, a lot of things can happen poorly there as well. Maybe there’s poor collaboration between these different functions. The people who design the customer experience aren’t collaborating effectively with the digital team or the marketing team. And so we need to make sure that all of these things come together not just technologically, but culturally to build great collaboration. Without that, you’re not going to be able to build these experiences.
Greg Kihlstrom: Yeah, yeah. And so you mentioned AI a couple of times already, and I wanted to talk about that a little bit more. One of the themes of the Forrester CX conference this year was humans plus AI. And to me, that speaks to something certainly that is top of mind of how do we augment humans work with AI rather than kind of just slapping AI onto a situation? Because I feel like that’s what a lot of companies trying to jump on bandwagons are trying to do, whether they might be trying to justify it with strategy, but it’s still kind of slapping a band-aid on a situation. So can you talk a little bit about, you know, what is humans plus AI mean when done well? And, you know, how does that compare to maybe doing it the wrong way?
J.P. Gownder: Yeah, it’s a crucial question. Here we’re saying humans plus AI, not AI plus humans or AI running around doing things on its own. That there is, at this stage in the market, it’s tempting to fly too high, too fast, to try to embrace AI as a cure-all or a panacea. And oftentimes what happens is that you’re not going to get very good results. And that’s not even necessarily the fault of the technology, but the expectations that you’ve placed upon it. So human plus AI means that human wisdom, intentionality, oversight, and sort of guardianship exists in all of these situations. Now, let’s take an example where AI plays a strong role. That would be something like contact centers, where maybe with today’s AI, you can do tier one support using AI. That’s still going to be governed by a lot of human governance and sort of judgment and strategy of how it gets used. What are the moments where we escalate to tier two? And so getting that balance right, even in a highly automated AI environment, is really important. Ultimately, what we want to make people think about is go into any particular problem you’re trying to solve, think of it as primarily a business problem that has certain outcomes you’re going for, and bring to bear the skills that you have available to you, whether they’re human or AI, but always keep humans involved, humans in the loop as you deploy it.
J.P. Gownder: Yeah, there’s a few different problems that come up. Some of these are going to be solvable technology problems, trying to figure out how to make adding generative AI to your tech stack work effectively, securely, choosing the right technology that’s going to perform in your scenario. But that’s a very solvable problem. I mean, it requires some engineering work, some work with your IT colleagues, but it is a fixable problem. The second is going to be the temptation that some leaders have to over-automate too quickly in the face of promises and hype, rather than taking a methodical approach that tests out what makes sense. And again, our thesis would be that we’re not at a stage where there’s a lot of replacement that can go on of human labor, which I think is a good thing, right? We actually value the people that we employ. And thirdly, though, Most organizations are on the cusp of underinvesting in upskilling and training their employees on how to use AI and generative AI appropriately by an order of magnitude. I have a framework I call AIQ. It’s Forrester’s way of looking at this. AIQ are the set of understanding and skills and ethical awareness, things that you need to know to be able to use these technologies wisely. So something like I have prompt engineering capability, which is actually pretty important right now, or I know when to question the outputs of AI, which is super important in a world of generative AI hallucination. So when you cover all of these, you know, different bases, you’re going to be in a much better place to deploy these things. But don’t overshoot into the world of AI everything.
Greg Kihlstrom: Yeah, yeah. And, you know, the next thing I was going to ask you was about, you know, how do we measure progress towards this goal? You know, you mentioned AIQ. Is that one way of doing this? Are there other things to keep in mind as far as measuring progress?
J.P. Gownder: Well, yeah, I think that certainly our framework isn’t the only one in the world that exists. I’m sure there are other ways of doing it. But what you need to understand about the measurement is that it is not something that is super simple where you can just sit people down in a classroom for an hour and bang out all the points that you need to know. Something like I know when to question the output of AI is a very subtle skill, and it’s not something that’s easily taught in an hour. Now, in an hour, you could teach somebody some heuristics and capabilities, but it’s a potentially long-term kind of training thing. There are other areas that are even harder in AIQ to teach, things like confidence. Do you feel confident about your ability to adapt to a world where AI is playing a role, or do you feel motivated to learn how to use these technologies? So, it is a mix of hard and soft skills, of understanding, of awareness, of motivation, and you may be using a variety of different measurements for each of those things. One that we like is aside from AIQ, is employee experience. So you’re probably surveying your employees about a variety of different issues, including questions and focus groups and surveys about how they are interacting with new deployments of technology can be really helpful as you try to fine-tune how you use those tools as well. But again, generative AI is kind of a new ball game. There’s some new things that happen where it can make stuff up, for example, that is just new to the scene for your employees.
Greg Kihlstrom: Yeah. Well, yeah. And so along those lines, you mentioned several really valuable things that employees 10 years ago probably had no idea they would ever need to learn. But being able to trust results in AI and being able to determine all of those things, it’s like, these are new things. And some may be adopting it more quickly than others. What should companies be doing to get their human team members ready for this human plus AI future?
J.P. Gownder: Yeah. Well, look, the first thing to note is that change requires a change strategy and that when you have a change strategy in place, it requires patience, it requires investment, it requires iteration, and it requires listening. So you want to actually be getting a lot of feedback from your employees along this journey as to what is working, what is not working, maybe co-create some of this for them. I’ll give another example that, again, I think is very pertinent to CX marketers and digital business, which is when you are looking at somebody in Home Depot, a retail associate. They have a lot of technology in the form of their smartphone and the applications that they’re given. And that really directly impacts the customer experience, how well that all works together. Over time, you’re going to find that more and more generative AI comes to the front line. which means that the frontline workers who didn’t know that they had to learn this brand new kind of technology and tool, who may not be well prepared for it, you need to rethink the investments in the level and types of training that you give them. You’re also going to want to prepare aside from skilling and training, you’re going to want to make sure you have some good governance structures in place for how things get used, how you vet through solutions, how you manage data. The more you want to get personalized with your customers, that’s great, but that also then has implications for how you govern the privacy of the data that they have and are you convincing them that you’re treating their data with respect and security and privacy. So the to-do list is actually reasonably long, but it is achievable stuff. It just means try to take a really holistic approach that involves what your customers want to need, what your employees want to need, what the technology is capable of doing, and broader governance guidelines and best practices that you can bring to bear. Yeah, yeah.
Greg Kihlstrom: And so looking at it that way, it’s, you know, just talked about what team members may need to learn and what leaders need to help need to do to train their employees. What do organizations maybe need to unlearn or just maybe either throw out or think very differently to take advantage of some of the biggest opportunities here?
J.P. Gownder: Yeah, I think some of it comes down to the linear command and control deployments that people are accustomed to. Like, here’s the new tool. Here’s how you’re going to use the new tool. Now, that doesn’t mean that there aren’t standards or that there aren’t guidelines or that there aren’t, you know, areas that need to be in compliance. But it does mean that you’re going to be doing a lot more iterative rollout. You’re going to be doing it in concert with a lot more training, again, more listening. listen to what’s coming up along this journey. I think you’ll find that generative AI tools can be incredibly powerful. They can create magic, but they can also create mayhem. Employees may be the ones who are on the front line and able to really identify those moments of mayhem so that you can deactivate them if necessary or remediate them over time. Finally, the way that people will want to use these tools will continue to evolve as well as they become more comfortable with them. They’re not there today.
Greg Kihlstrom: Yeah. Those that are out there maybe looking to change careers or aspiring leaders out there, what should they be doing to prepare for their next role if they want to be part of this human plus AI future?
J.P. Gownder: Yeah, I think that a combination of learning and experience, finding ways to get experienced, integrating this technology into the work that you do, there’s going to be a stage here where it’s going to be a lot of hype and check the box. We were joking on my team recently that there are instances where you’ll find a job description that requires five years of experience in generative AI, and generative AI hasn’t really been around for five years, right? Some of the traditional ways of looking at this are less important than genuinely being engaged in the space, trying some things out, learning where you can, maybe get some certifications if you can along the way. and be willing to just invent new stuff in concert with those who are maybe more technical experts or ethical experts or data experts. There’s just so much that can be done here, but it does require a lot of open-mindedness and experimentation.
Greg Kihlstrom: It also sounds like perhaps collaboration with teams either in different ways than done previously or maybe new collaborations between you know, between team members, would you say that’s true?
J.P. Gownder: I think so. I mean, you know, again, I mentioned the alignment that’s necessary between marketers and customer experience pros and the digital team, and they need to be going in the same direction. But in order to do that, there’s often going to be solving some more fundamental problems that sit underneath if they’ve been siloed in the past, if they’ve been disaligned, Well, that means it’s not even just a technology challenge. It means that there’s some fundamental decisions and conversations that need to be had and that need to be adjudicated in one direction or another. Before you can row the boat in the same direction, you need to figure out what direction that’s going to be. So a lot of this comes down not to just technology on its own. That’s always a fixable problem. But what is the level of alignment and communication, collaboration and unanimity of you know, convincing everybody to get on the same ship.
Greg Kihlstrom: Yeah, yeah, absolutely. Well, JP, thanks so much for joining today. One last question before we wrap up here. Just got back from Forrester CX Summit North America. What was the highlight for you?
J.P. Gownder: Well, you know, I think it was telling this story about humans plus AI because right now I think most of our clients who I work with all the time, they’re very much in the weeds of what should we be doing with generative AI? How can it help us? What are the dangers? But a lot of them are overlooking some of the human dimensions of it. And anytime I get the chance to highlight that humans come first, human judgment is most important, human governance, human guardrails, and the skills that humans themselves have are crucial to the future and success of AI or generative AI. For me, that’s a good day because it’s so easy to lose track of that as you’re trying to nail down some kind of deployment.
