Redefining Market Research with AI for Tech Companies

Priscilla McKinney: Jay Shutter is the CEO of Illuminos and he has spent the last three decades doing research all over the world with technology companies and more. I love talking with him about where we’ve traveled and we do share book recommendations and also just interesting cultural and anthropological little ditties. So that’s super fun. You’re going to hear in our conversations that we know each other well. And that’s really the goal of this podcast is to bring senior leaders on who really have expertise to share but are absolutely willing to leave behind their egos and have these great conversations with me. But he has spent so many years interviewing CIOs, senior IT leaders about their organization’s technology investments across all kinds of transitions. I mean, he’s seen PCs, client servers, internet, data centers, all kinds of conversations.

This might be the place where I mentioned to Jay that I once owned a beeper. So there’s that. But of course, now he talks to people a lot about virtualization, about the cloud, and of course, digital transformation. And la, la, la, we’re going to drop it right in the very beginning, AI. So Jay, welcome to the show.

Jay Shutter: Hi Priscilla, thank you very much. I had that tool belt as well. I had the beeper, I had the pager, two-way pager, and I had my phone. So they used to make a lot of fun of me, but that’s what we used to do, right?

Priscilla McKinney: You are one of the best kinds of nerds that I like, take that as the best compliment.

Jay Shutter: Ha ha ha! And happy to be it.

Priscilla McKinney: Okay, well let’s talk about that evolution. Let’s start there. I think that’s really grounding because you’ve witnessed almost every major technology transition over the past three decades. And I’d like to hear from you how you perceive those fundamental shifts. How have technology buyers specifically changed the way they make decisions with this evolution? And then kind of second part, I’d love to know that thought because what I’m getting at is then what inspired you to really launch Radius Tech. So that it’s charter, but I think it really is first the context and your perspective and then into what’s going on today.

Jay Shutter: Yeah, that’s a long journey and it’s a great journey. So I’ll do my best to compartmentalize as much as I can. Look, I was fortunate. I stumbled into this from an MBA program at University of Texas. And it was early in the technology industry growth. It was just after, not too long after, IBM launched the PC with the AT and XT, different PCs. And it was an exciting time to be watching the Macintosh launch and involved in those early days.

And then the internet came around, right? And I was already working at one of the first high-tech market research firms in Austin, Texas, a company called IntelliQuest. They were really one of the first ones that were dedicated to high-tech market research. And we watched all of this go on and watched how valuable research was because these early technology companies, and we’re not talking about little companies, we’re talking about IBM, we’re talking about HP, we’re talking about Apple to a large extent, we did a lot of work for them, trying to figure out how to penetrate the market and get more companies to adopt technology to run their businesses.

And then you go from the advent of the internet, which obviously changed everything, to the fact that suddenly e-commerce came online. I remember shopping on Amazon when they first came out. It was amazing to buy books. That’s what you could buy on Amazon.

Priscilla McKinney: Okay. I’m gonna confess here, the first year that that was possible, I remember doing that on dial-up and I went stupidly, because we don’t know enough about tech at the beginning, and did my entire family shopping. And of course, it’s like the line-by-line page loading, only to get to the very last one, or second to last one, and everything completely failed. So I remember those early days of how hard it was to shop online, but gosh darn it. We tried, Jay.

Jay Shutter: Well, and a lot of that is what goes into the research that we do is understanding the challenges that consumers and businesses face when dealing with this technology. But it’s been an amazing journey, right? And we started Momentum Research Group inside of a premier high-tech PR firm in 1998. We were calling it Momentum Research Group at the time. We eventually became Illuminus as, of course, we were involved in lots of different mergers and acquisitions. But it was still great because we were focused and dedicated to doing tech research.

So while all these market transitions, these incredible inflection points in technology were happening, we were right there doing the research. So whether it was the internet coming online or measuring the internet economy for the first time in 1999, which is what we did for Cisco, or looking at the consolidation and virtualization of data centers, which brought on cloud that enabled all these things, it was just incredible to watch those changes not only impact businesses, but society as a whole. So Momentum Research Group and then Illuminus was there throughout all of that.

You know, your question about how has that buying journey changed? There are a lot of things that have stayed pretty static through that, is to a certain price level, right? VPs and below can just make those decisions. They can buy technology. But above a certain threshold, of course, you have to bring in a committee, CFO, CEO, board, even at some times gets involved in those decisions. That kind of thing has not changed. Of course, you have to have control over what expenditures are.

What has changed a lot through all of this is the fact that technology buyers today can’t just think about what they’re buying for today. They can’t say, well, we need to refresh our servers, and that’s all I care about. Because technology changes so fast that you as a buyer, you have to think about today and the future. You have to think three to five years out because ultimately a lot of the brands that we do work with, they’re out there messaging in the market saying, work with us because we prevent vendor lock-in. We make it easier for you to seamlessly change and do all these things.

Well, that’s never really the experience from every CIO or VP of IT that I’ve ever talked to. Right. It is always a challenge to do those things. And so most companies do not want to do that. So when they look at a major investment now, they especially have to think about the fact that I need to be with a partner, vendor partner that I trust and will be with in three to five years because I can’t afford to make another change, right? So I think that’s as technology has evolved, become more complex, been more integrated into our businesses and the fact that we’re seeing this such rapid evolution of technology, those decisions are a lot harder to make and you need to have better understanding of what that CIO, that CSO is worried about security. Has to think about in terms of who they decide to partner with, what technology they make that final investment in. It’s a big change. It’s not like they didn’t think about it before, but it was a lot different, right? Because technology wasn’t moving that quickly. It’s moving, as we see with AI, faster than we could ever imagine.

Priscilla McKinney: You know, we did have this real explosion moment of these kind of simple, not apps, but they were all the SaaS companies. Everybody was kind of allowed to buy this and buy this and buy that. And I agree with you is that we have this change. People in these pretty high roles were given the agency to buy what they wanted. But I have seen the buyer groups getting larger. Right? In the B2B world. But I want to underscore the important thing I think I heard you say, which is that this is a complicated purchase because of two main things. Technology itself is complicated, but technology stacks.

And so what you’re buying at one point really starts putting you down a path as to your point, as much as they tell you it doesn’t, it does. And so these ramifications, even from when someone in an IT role departs from a company, they’ve left behind a legacy of kind of a direction that companies have to go to in IT. Companies have wisen up to this and so have figured out that they really need to think this out. And so to that point, where you’re talking about that challenge, people who are selling this technology need to be able to figure out what is going on in those minds. You know, are they looking for just that short term or are they really being mindful and thinking about that long term growth? But tell me a little bit, that last piece I wanted to hear is from that perspective, all those experiences you had, then why Radius Tech? Because this is something new and this is what I wanted to talk with you about because I think you do have a unique perspective on why this needs to stay focused on technology.

Jay Shutter: You know, as a small research firm, you’re always trying to figure out what your advantage is and how you can create opportunity. And throughout the time period from when we started this little group inside of Cunningham to when we bought it back in 2016 and operated on our own for about six years, you know, we kept looking at the market and saying, boy, we should diversify. We need to be in more than technology. But it was hard because technology was still just growing so fast. We had to turn away opportunities to do work because we knew the segment. We understood technology. We understood the importance of categories.

Tech buying is about categories. Yes, at some point, if your brand becomes strongly associated with a category, you don’t have to think about category. You just think about brand. So networking equals Cisco way back when. And you could just say, we need to buy Cisco. But that’s not the way every category starts. It starts with, I need to have a tool that does load balancing for all my workloads across my different clusters of servers that are all my applications, right? So, well, that’s the category. And then I start looking and saying, who does this well? Well, there’s five brands here. I look through all that.

All the work that we did over the years in understanding these technology transitions and understanding how buying decisions are being made and how brands can differentiate and communicate their value proposition is something that we just kept looking at saying, look, we’re really good at this. We understand this better than just about any other insights firm out there. And we’re just going to stay focused on that. And we continued through 2024 on our own and decided it was time to become part of a bigger engine. We wanted to be able to do more and offer more to our clients and seek other opportunities. And the easiest way to do that is to build that operations engine either yourself or through merger and acquisition. That’s what we did.

Radius is an amazing global insights company. Some of the smartest and coolest people that I’ve ever worked with, known them for a long time. It’s a small industry, if you will. We kind of all know each other. And so it was a great opportunity for us. We were very excited about it when we joined them last year. When we looked at what we were as Illuminus and said, you’ve done this work. You’ve done this. Is it a house of brands or a branded house? I’m a big believer in a branded house.

House of brands is hard to maintain. It’s done with a lot of big companies that are great at doing that. But I think in general, it’s a smarter value proposition to say we are one brand, we’re one radius. And so we knew Illuminus at some point was going as a brand for us was going to be Sunlight. Of course, we had a sister company in the UK. They still operate as Illuminus. They will continue to operate as Illuminus. But we are going to become Radius.

And as we looked at the opportunity, we recognized that, wait, tech is that advantage that Radius can bring to the marketplace. And Radius already had some sub-brand practice groups, Radius Financial and Radius Auto, and it made total sense to put together Radius Tech, which brings together Illuminus, the really incredible tech experts at Radius, and another group that was acquired right around a year before us, Strive, in the UK. We brought the best in thinking, the thought leaders in technology together to create Radius Tech, and we’re super excited about the fact that I think we are no one has what we have to bring to the table. And so we like to call it unrivaled expertise in the technology industry.

And I think that’s super important, right? Because you can start working with us and you don’t have to get us up to speed. We understand your category. What we want to understand is your business problem and apply our expertise and designing and delivering insights to help you solve those challenges. And so that’s why Radius Tech just made so much sense to us to do.

Priscilla McKinney: I understand what you mean by that time when you bring a vendor on and then you have to bring them up to speed with your industry. It’s like what a waste. You know I don’t want to sit and explain to someone what we do. I want to have them start addressing my problems right from the beginning. So I think that makes so much sense. But this is maybe that moment in the podcast where I break that fourth wall and say, dear listener, dear watcher, is this the time when we actually drop the phrase AI? Because I know a lot of people kind of have a deep side. We’re going to go into this topic because it has transformed what you do. For you with a tech view, it has even more deeply transformed what you do because it is not only changing how you work, but it is a part of some of the major challenges that your clients are coming to you with. And so you’re getting it from all different directions.

And so I want to ask specifically first about AI’s impact on the research methodology you use with RadiusTech. So specifically, how is AI transforming really the depth and the quality of insights that you can extract from your market research projects. And particularly when it comes to understanding emotional and social drivers that are behind the B2B tech purchases, I think that’s an area where a lot of people are missing the point. They’re looking at data. They’re looking at, you know, quote unquote, the facts. But the facts are that there are a lot of emotional and social drivers. So can you help me blend that use of AI, which is this, you know, absolute accelerant to the fire with still being true to but what these buyers are still human just because they’re buying majorly large pieces of technology. They’re still doing that from an emotional and from a social place.

Jay Shutter: I’m going to answer your question by bringing some thoughts up on your last comment about that human emotional part of it, which is it’s always going to be a human emotional part for a buyer making a decision on a technology that’s using AI. And we’ve been very fortunate over the years to be early on testing. At the time, we didn’t necessarily call it AI. It was the slash AI. It was machine learning, right? And machine learning was amazing, right? It could do incredible things, very algorithmic, could truly look at you. Digest a lot of data, come up with some conclusions, some insights, et cetera. But it’s not like the AI that we know today. But we still always call it ML slash AI, right?

And when we were talking about that, for example, with networking decision makers and saying, hey, this company has this solution. And they ingest so much networking data and telemetry that can help configure networks for you. And it can give you all this information. And what would you imagine that could do for you? And they would say, that’s wonderful. Come up with all that data, make some recommendations. I’d love to take a look at it and make those decisions. And then you, of course, do the next step, which is to say, well, what if it made the decision for you and configured the networks automatically? And that’s where the human piece stopped and said, yeah, no, nobody makes any changes to my network without me looking at it and approving it and having one of my lieutenants look at it and approve it, right?

And that’s because it doesn’t matter whether it’s AI or whether it’s a human delivering something. You’re always going to look at it and say, that’s interesting. What do you think of this? And they’re going to go to the person they trust the most to do that second evaluation. So I think human is always part of the equation. Pulling this back around to what we’re doing at Radius is that one of the big reasons we joined Radius, of course, as well, was the fact that we were already doing AI, using AI to automate the coding of open-ended questions and verbatims, to do analysis on open.

Because text analysis has been around for a very long time now, as we all know. Hasn’t been great, but it’s obviously infinitely better because of the AI element. And so as a small business, it’s hard to take care of clients and do development at the same time. So becoming part of Radius gave us access to all the great things that they were already doing from an AI development perspective. The one that we’re the most excited about is what we call Radius IQ, and that is the assisted open end.

And the idea is that as a respondent enters a verbatim response to that open-end question, whether it’s a other specifier or actual open-end, we have the AI assistant there who can look at that response and then probe. And we’ve been doing that forever in the tech, in the research industry. We had live people intercepting on a survey saying, hey, I saw what you answered. You, right? But you can’t do that with 1,000 respondents. With AI, you can.

So it became so much more manageable. And the beauty of that AI assisted open end, that little qualitative element, is the fact that you can put a boundary around the AI. You can already pre-code it with prompts to keep it within the frame of things that you’re looking for responses to. So it’s not a free form. AI can ask any the follow-up questions that it wants. It follows what a really experienced moderator would do in that kind of situation. So that’s an example of the things that we’re bringing to every one of our quantitative studies to allow for that incredible marriage of good quant and deep qualitative in a time frame and a price point that we never used to be able to do before. I think that’s pretty incredible, right?

We also have, of course, fully automated AI-driven qualitative interviews. If the client wants to do that, I think we’re talking about a generation today that’s perfectly comfortable talking to AI agents. And even though maybe you and I might not want to because that’s not our generational thing, I think it is different. We have to accept the fact that there are people that are happy to just go through that process. And so that’s another area that we bring to the table.

And then, of course, we’re doing a lot in terms of what we call netnography, going out and actually using data that we find on the internet and communities, on websites, combined with other data that we have and reports to put together an AI-driven solution that gives us a whole analysis of the key themes that we’re seeing and data points that we should be aware of and tracking and paying attention to in terms of decisions that we’re making. So the netnography is this incredible tool. And then, of course, we’re all doing the data lakes where we’re building and putting together these big repositories of data that we’re letting AI go through and find and search and come up with responses to the questions that we’re asking. It’s opening up incredible amounts of data to us, data that’s just been sitting there unused. Now coming together with fresh data to give us new perspectives and insights into what our customers are doing.

Priscilla McKinney: Okay. Well, in the world of digital transformation and specifically to this podcast, digital transformation success, not just doing it, but being successful at it and coming at this from a tech perspective, truly, I see what you’re doing is redefining how market research is applied for tech companies. And one thing I was really interested in is in one feature that you all have been pioneering and that is something called Radius IQ. Can you give us a little bit of a background there and what it is you see is going to happen with that in the future.

Jay Shutter: Yeah, I mean, Radius IQ was what I was alluding to before. And that is the ability for us to bring in an AI component to a qualitative survey. I’m sorry, quantitative survey. So imagine you’re doing a brand tracking study, right? And questions are just traditional closed-end questions. Rate these brands. How do they compare, et cetera, et cetera, right? Well, one of the things that we always want to do as a researcher is get to the why. And too often, we look at quantitative data and we’re like, why are they saying this? Why is it trending this way?

And now, and you can still have the open-ended question to ask that, like, why did you say that? But it always invariably leads to the next question. Okay, well, I see why you said that, but then what’s driving that? What emotions are you feeling as a result of that? So, radius IQ gives us the ability to not only push a little bit on the question that was answered and the open text that we have, but to ladder, for example. Why did you say that? How did you feel knowing that you made that decision? What did that get you to do? So we can go the full laddering technique all the way through the action that we want the respond. Did you actually go buy something? You go to the website and look this up? Like what action?

And it’s all done by an AI agent. Is extremely professional. The experiences that we’ve seen and heard feedback from respondents on it is that it was an amazing. It was very natural and the quality of the response as well was very, very good. So it really opens the doors to get those insights that are really hard to get when you have to do, hey, we’re going to do a quant study and then we’re going to follow up with a qualitative study. No, we can actually put a lot of that together now and get much deeper and richer insights using those AI agents to probe and push those open-ended responses.

Priscilla McKinney: Well, that richer insights that you’re talking about happens when the respondent is having a good experience. And for me, regardless of my generation, I want to interact with something that is efficient. And if it can ask me the right questions and if it’s making sense in the order of operations, I’m going to give it the time of day 100 % because I’m a CEO and I’m about efficiency. And I think, you know, from your deep tech experience, it’s hard to get these CIOs and CTOs and everybody on the line or get them to respond or get them to be involved in research sometimes because they are a need. And their valuable perception of their time is different than say an 18 year old male who wants to answer a survey, you know, that from generic to a very specific respondent.

I want to underscore what you’re saying is you’re getting this really high quality response, but I think that’s because you’re still being able to create a high quality experience for the respondent even though this respondent is a very high level professional.

Jay Shutter: Yeah, I mean, certainly the feedback from those more senior levels has been very positive, right? They certainly see the value of it. Of course, every time they take a survey, they’re like, wow, we could be doing something like this for our customers, right? And then they quickly go to their insights team and say, are we doing this? And so clearly, as a CEO, you’re going to see value in this type of experience. Now, I wish they would take my surveys all the time, right? But we’re all so busy, we don’t always have time to do that. But when we do engage with them, we want them to be good surveys, short and sweet, efficient, as you suggest, and a great experience overall. And I think that is what’s sitting in front of us.

I think in the context of the consumer audiences that we survey, it is absolutely a wonderful vehicle for getting richer and richer insights, and in a more efficient way, and across the entire sample frame that you’re after, whether it’s 200 interviews or a thousand interviews or more for that matter. It’s incredible what AI allows us to do there. But we’ll talk AI and I will extol all the incredible things it brings to you, but I will never step away from the fact that that human element is still critical in all that, right? Because it’s the human element that’s teaching that AI agent to be able to probe efficiently as a moderator would, right? And so there’s always going to be this mix of and as we say, H.I., human intelligence, right, as part of this equation.

And it’s still early days, believe it or not, if we can say that, when you consider how fast it’s evolved in just two years, right? And we do this survey every year. It’s called the National Technology Readiness Survey. We’ve been doing it since 1999, about 25 years worth of data. And we started tracking perceptions and perspectives around AI among consumers and business people as well. And what we find is there is still there’s a camp that absolutely is hopeful about AI, and there’s been a pretty steady and slightly increasing camp around maybe a little bit fearful of AI for all the reasons that we could expect, right? Things that it could potentially do wrong, the fact that it could take our jobs, all those different kinds of things.

But those people who understand technology better, and again, we have a little segmentation we can do inside of that NTRS survey. And it scores people by their willingness to adopt technology. Those that are more likely to adopt technology look at AI in a much different way than those who are still a little bit skeptical. And then they have right to be skeptical because technology just has its, as we started the interview about, has its ability to show up and have problems when you don’t want it to.

Priscilla McKinney: But as a cultural anthropologist, I would like to just insert that the car was technology, the telegraph was technology. These things did take other people’s jobs, but we changed as a society as well, right? Let’s talk about a really specific thing that happens in the tech space where you are an expert. That’s channel research. Not a lot of people are experts in channel research. So tell me a little bit about how these modern marketing automation tools are reshaping the way tech are reshaping the way technology companies understand and engage with their partner ecosystems. This partner ecosystems and channel research is really important in the tech space. Tell us about that.

Jay Shutter: Yeah, I mean, when you look at most technology companies, and it’s especially in a B2B scenario, right? The vast majority of their revenue comes through their channel partners, the resellers, the systems integrators, whatever the partner role be, whether it’s developer, whatever it might be, right? There’s lots of different partner roles, but they bring a lot to your ecosystem as a company. So most technology companies have built a really big ecosystem around their products and services and software. And they are the ones that bring in a lot of the opportunities and lot of the revenue. But that’s a real challenging scenario, right? Especially today, because it has to be a win-win. So you as a brand have to win and my partner has to win for them to continue to want to be a partner and stay in my ecosystem and make all the investments that they have to make to know my brand, to know my products, to understand our selling process, go to market, et cetera.

And that’s gotten a little bit more complicated lately because of the introduction and use of these marketing platforms, right? And the fact that technology in general has shifted to be more software driven. So in the old days, if you wanted to update your network, had to buy a new router or switch. And that was what you did. And it came with new software, and you would do updates every once in a while. Well, we’ve moved to a world now where the box itself really is more of a white box. It’s not as differentiated. It still is. But it’s moved in that direction.

And now all of the services and capabilities and functionalities coming through software. You can unlock it if you pay for the subscription and you get the codes to unlock it. You get updates and all those different things. It’s very software driven now. And that creates the opportunity for some partners to be left out of the equation because as a vendor, for example, if I’m Cisco, I don’t have to include a partner because I can sell the software directly to my customer. Because that’s the way subscription works and that’s what they want is that annual recurring revenue.

So it’s a very complex model now and the marketing platforms themselves have done two things. One, they’ve created opportunity for the vendors themselves, the Cisco’s, the HP’s, the Microsoft’s of the world to create richer relationships with their partner ecosystem, right? To make sure everyone’s getting all the data and information on marketing, how to go to market, all the things that a good marketing organization does. And it’s creating opportunities for the partners to identify new customers to sell to because that’s that equation, right? Which is the customers are not looking to the partner necessarily. They’re looking to the vendor for a product or a service. Well, typically then you end up back at the partner to get that deal to happen, right?

And so that’s what the partners are hoping for is they want those vendors to help them create new sales opportunities. So once again, that marketing platform is key to identifying warm leads versus cold leads, and then understanding how to take that sales opportunity to the close, right, and getting that deal to be done. And so those platforms are changing everything, whether it’s a consumer buy or a B2B buy, those platforms are incredible. And as we all know, it’s all about account-based marketing these days. It’s about knowing who your account and your customer is, knowing what they need and how to sell to them and their preferences. That’s what these platforms bring to all of us is that, again, those insights, that data to make the right decisions on how we close the deal and make a win-win out of the whole arrangement.

Priscilla McKinney: Well, I do love a good win-win and you know, I love a win-win-win-win-win. I love to bring partners together. It is a really important ecosystem. I’m going to end the podcast more with some forward thinking. So I’m giving you a little prep time to think about like what’s coming for, you know, in the future. But before I ask that, I want to kind of get your opinion on kind of what’s happening right now. So you’ve helped a lot of major tech brands through pretty significant transformational shifts. What have you seen over and over are some of the biggest blind spots that companies have when they try and position new technologies like AI to these skeptical enterprise buyers?

Jay Shutter: I’ve spent 25 years of flying around the world testing messaging and testing ad copy and digging into value propositions and everything related to some of these companies. And the thing that stuck in my mind after reflecting on all this is the idea that I would put a message out there and sometimes my back is to the glass and the clients can see all the faces and depending upon what where I’m in the world, it might be the other way. Invariably still, when you put the messaging out there, somebody will look at me and do the eye roll like, geez, like I’ve heard this message before. And it’s not that they don’t value marketing because they all understand how important marketing is for their own companies. But the challenge is that how do you differentiate through messaging? And that’s the thing that I think that happens too often is we want to go out and put all these flowery words together and these incredible articulations of our value proposition and why we think you want to work with us and why we’re trustworthy and all these different things.

And in the end, the CIO is simply looking at saying, that’s great. I understand all that. But what does your product do? And they go immediately to, that’s fine. That’s great. Here’s some advice on how to fix it a little bit. Give me the specs. I want to see the specs. I want to understand why your product’s better than the competition. And so I think we sometimes miss the forest for the trees, right? We need to really focus on the tree and say, here’s what this tree is. Here’s why it’s different than that tree. Here’s why this tree is better for you. Here’s what more it gives to you.

And they really are just desperate for less obfuscation with these incredible marketing messages and more just direct, tell me how your product’s better and I will help you win. But if you can’t give me that information, I can’t make that decision. You’re no different. And I think that to me is that blind spot is that we can’t get caught up. You still have to message that high. I’m not saying you shouldn’t do that, but you’ve got to mirror it with that bottom up messaging to say the guys and women, the men and women who are really making those decisions, they care more about what your product, your service, your software does for me than the flowery message that you have.

Priscilla McKinney: Okay, horror of all horrors. Let’s say you can’t differentiate your product. Because this is happening. You mentioned that we are moving at a very breakneck speed and people are creating something. Even come to me and say, we’re the only ones doing this. I’m like, quick search. No, you’re not. So sometimes you can’t differentiate. What do you have to say when that’s the case about the product?

Jay Shutter: The importance of those messages and the differentiation is understandable, right? Because not everybody has a marketing budget like a Microsoft or an Intel, some of the big companies, right? And so the best you can do is make sure you have the right messages in the market at the time. So there’s absolutely everything right about doing that. But it’s just that advice to say, make sure you go up and down, right? Because you have to be clear. But I think if you peel that back and say, what should we be doing as a company? What we hear time and time again from everybody up that that IT chain, right, is look, I want to understand how you’re going to support me as a business. I’ll buy your product, but where are you going to support me and how are you going to support me?

Support is so incredible, right? It’s about that customer service and that customer service excellence makes a huge difference. It’s the reasons why I will pay more to buy your product than another product. The overall relationship, it can’t just be you show up when it’s time to renew. You show up when it’s time for you to sell me the newest thing, I’ll have that conversation as long as you’re taking care of all those other things. But if you’re not taking care of all those other things, I don’t want to talk about anything new until you fix the challenges that I have over here, right?

So I think that’s critical. If you don’t have that customer service focus, if you can’t deliver a quality product and make sure that it’s being taken care of and fixed if there are bugs or issues, and you’re not catering and taking care of that relationship, that relationship, it’s going to be harder for you to win. But you still can’t walk away from innovation. You still have to innovate. Even if it’s harder for you to get your innovation news out there, it happens a lot. Wow, yeah, they haven’t innovated in a while. What did you hear about X? No, I didn’t know they were doing that.

Well, guess what? IT people don’t have enough time to pay attention to all the innovations that are going out there. And you don’t have the budget to necessarily put it out there. It still means you have to continue to innovate. And you have to do everything you can to make sure your community, your ecosystem knows about the innovation and what you’re doing. That’s the thing I see that doesn’t happen enough is telling the story about higher innovating and what it means, why it’s relevant, and where it’s headed.

Priscilla McKinney: I am waiting for the day that AI is integrated into some of the tech products that I use so that when I log on it says, I can see you were doing this. This is something new. This will do it for you. So please, tech companies, can you get there? Not when I log on, ask me to take a survey. But when I log in or when I log in, say, here’s another product we want to sell to your point. It’s about really helping me, that overt helpfulness of a brand and to support their product. Product is so huge.

Okay, so I’m gonna hit you with the hard one here. Let’s talk about what Jay is doing looking forward. What does it look like? So you have a unique vantage point and with the interviewing of CIOs and IT leaders all around the world, you must be hearing about emerging technology adoption patterns. So what are you seeing and what do you think they should be preparing for?

Jay Shutter: Well, look, I mean, we can’t do any conversation today without talking about AI. And AI is absolutely going to change the way everything is done. I haven’t even had time to download and digest what ChatGPT 5 is bringing to us all, except I did see something about that. It really demonstrates how much closer we are to AGI than we thought we were. And so it’s just coming rapidly. I think this is where some of the best critique, if you will, about the current moment that we’re in is coming out, which is to say we have no problems teaching it and training how to get closer to that. We have yet to figure out how to control it.

And I think that goes without saying for how you use AI as a business. It’s going to be embedded into everything. But do we have the guardrails in place? Do we have the policies and procedures in place at our organizations? To make sure that it’s being used appropriately, that we’re using data appropriately with permission, because that’s the biggest piece is, have we gotten permission from all those people who provide all your customers who are providing all this data? So I think that it is going to be a game changer, but it’s going to have its challenges that we’ll probably start to see a lot more, which is access to data, controlling of that data, data privacy, the companies that do this the best that can demonstrate their policies and procedures are the ones that are going to have probably the easiest time of this, or at least to have the most early success.

The incredible thing about AI, though, is it’s just such a quick tool to level the playing field. It’s just a matter of, well, what are we doing wrong with our AI procedure? Feed it into the AI model, and it’ll come back and say, well, you didn’t do the following five things that these 20 other companies are doing. It’s going to be leveled very quickly. And I think that to me is incredible because what it does is pushes it back around to the human, which is if we’re all level from a technology playing field, what’s the differentiation? It’s back to us. How good are your people? How good is your relationship with your customer? How good are you at thinking through and addressing the needs of your customers until we know AI has some ability to emote?

Emotions do matter, right? Our ability to look across the table and see our customer space, fear, concern, worry, that’s not going to be picked up. Well, I probably could because with cameras and AI, they might be able to see. Again, it’s hard to do this sometimes. It’s not going, well, I guess it could do that, right? But I think that to me is managing those customer experiences is critical. And the only way to do that is with people. And that’s for our industry. Insights industry, think keeps coming back that we have. Yes, we’re going to use AI to automate things. We’re going to use AI to make things more efficient. We’re going to use AI to give you faster, quicker insights.

But you still need a Jay Shutter or Priscilla McKinney to go out and talk to a customer to really understand their motivations, their fears, what makes them happy and all those different things. And I really believe that that’s where this ends, is that we still need humans to talk to humans. Our insights profession will remain a vital part of this process. It’ll be changed, no question. It’ll be different. But I think you can’t get to where we need to go in the future no matter what without the human element.

Priscilla McKinney: Well, I would agree that while AI is changing really fast and it is getting better, it can read the emotions, can do sentiment evaluation, it can maybe even do micro expressions, a lot of things. Still, just remember as AI is changing and technology is adapting, so are humans and we have different reactions at different times and that is the viral, I hope. And so because of that, that’s why humans do need to be in the loop and I can completely see that value. Jay, you are the right person to talk to about how AI is being used in market research and specifically for tech companies. I know that was a huge value to my audience. Thank you so much for giving us your time and your expertise.

Jay Shutter: You’re very welcome. So I could talk about this all day long. So anytime you want to talk, I’m here for you.

Priscilla McKinney: I’ll just call you back later. We’ll chat.

Jay Shutter: Awesome. Good to see you. Thanks for selling. Bye bye.