Insights in the Cloud: Microsoft’s Barry Jennings on B2B Research and the Power of AI

In this episode, Karen Lynch sits down with Barry Jennings, Director of Cloud and Commercial Business Planning Insights at Microsoft, to explore the fascinating world of B2B research and its intersection with cutting-edge AI technologies. Barry shares insights from his extensive experience at Microsoft, Dell, and BlackBerry, providing a behind-the-scenes look at how research drives innovation in the cloud and AI sectors.

From tackling sample quality issues to leveraging AI for faster and smarter decision-making, this conversation is packed with actionable insights for researchers and marketers alike. Whether you're curious about the evolving role of insights professionals or looking for strategies to thrive in the age of AI, this episode delivers thought-provoking ideas and practical advice.

In this episode, we’ll explore:

• B2B Research Dynamics: How Barry’s team at Microsoft supports the commercial business, including cloud and AI solutions like Azure, GitHub, and Fabric.
• Insights Professional’s Journey: Barry’s career path from fieldwork to leading insights teams at major tech companies like Dell and BlackBerry.
• Leveraging AI in Research: How large language models and AI tools are transforming research workflows, increasing efficiency, and enhancing storytelling.
• Challenges in B2B Insights: The unique hurdles of engaging technical audiences, tackling sample fraud, and monetizing innovative cloud-based products.
• Future Outlook: Barry’s advice on adapting to AI advancements and becoming a smarter storyteller to make a bigger impact.

Resources/Links:

• Barry Jennings on LinkedIn
• Microsoft Azure

Many thanks to Barry Jennings for joining the show. Thanks also to our production team and our editor at Big Bad Audio.

Transcript

Karen: Hello everybody. Welcome to another episode of the Greenbook Podcast. It’s Karen Lynch, and I’m so happy to be hosting today. Good to be with all of you again, and it’s really good to see today’s guest again. I am excited, and I have the pleasure of talking to Barry Jennings. Barry Jennings is with Microsoft. He’s the Director of Cloud and Commercial Business Planning Insights, and he was just one of our headliners this past fall at our IIEX AI event. He’s an amazing speaker, a dynamic professional who’s going to bring a lot of insights to us about the type of work that he does in this highly technical B2B space. Barry, welcome to the Greenbook Podcast.

 Barry: Thank you very much, and thanks for having me.

Karen: My pleasure. My pleasure. So, why don’t you tell everybody a bit more about your role? I don’t want to get too deep into it, and I find that bios come best from the person themselves. So, tell us a little bit about your role and what you’re currently doing at Microsoft.

Barry: Sure. And yeah, all the words on the bio definitely need interpretation [laugh]. So yeah, I work in the Research and Insights Group at Microsoft. It’s within Microsoft’s marketing organization, and I run a team that supports three areas that are focused in the commercial area. So, my work is all B2B, not consumer, but all B2B. And so, one portion of my business supports our cloud business called Azure, and inside of that are things like infrastructure—which makes things like ChatGPT work—development tools, there’s something called GitHub that just about every developer on the planet uses, and we have other developer tools. And ultimately, we want people to use developer tools to build things on our cloud, but you can build them any way. I also am responsible for data and AI. AI, really popular right now, believe it or not. But also lots of work done in databases, everything from SQL to a product that we have called Fabric. That is the cloud portion of my work. Another portion of my work supports something called, what we call our Global Demand Center, and that’s essentially database marketing. And so, we do a lot of digital marketing in the commercial space. It’s a pretty big, massive effort. If you’re a really big, huge customer, like say, oh, I don’t know, Coca-Cola, you probably have a person who takes care of you. If you’re a little bit smaller, there’s probably some team that helps you, maybe via telephone. If you’re everybody else, it’s mainly digital. And we do work around customer journeys, messaging, lots of other things to get people to download a white paper, to open an email, all those things that get people, ultimately, to get into our marketing funnel. And then the last thing I do is we support a group called business planning, and that is how we come up with how we monetize our products and services, and so it’s a lot of pricing work, [unintelligible 00:03:06] analysis, discrete choice, work like that. The interesting thing is, a lot of the products we do are new, and because they’re new, it’s really challenging to price them. Because, you know, long, long ago, we used to be a software company. We made some software. We said it was final, then we burned it to a DVD, for those over there who remember that, or we made it something that you can download, but it was done. And it was a low cost to make that business work, right? It was very low, low OpEx. Today in the cloud, we have this thing called COGS. We have to think about the cost of goods sold because it consumes energy, and all this other stuff. And so, something like our AI product Copilot, it consumes a fair amount of energy. It’s fairly expensive, and we have to think about charging for that very differently than, I don’t know, somebody in a small business who just wants Excel. And so, we do a lot of pricing, packaging type work to really figure out how to do that. And a lot of times it’s ultimately, how do we build a brand new business model to support how that business will operate?

Karen: Thank you so much for sharing all that. It’s fascinating, from my standpoint, to kind of think about the same methodologies that I might have seen in other instances, being applied in your work. But I want to talk a little bit about your background and some of the steps that led you to this place where you’re handling this sort of high technology B2B insights, you know, data, analytics, all of this space. Because, I mean, you were, you were at Dell for a significant amount of time, you were at Blackberry—speaking of throwbacks [laugh] you know—and so just talk a little bit about how you kind of carved out this niche for yourself. Did you know you wanted to go into this type of work?

Barry: It’s kind of, like, being in research in general. It’s sort of like the mafia. You somehow find your way in it. We can just never get out. Yeah, you know, it’s interesting, I was talking to some interns at the University of Wisconsin about my background, and I kind of tell the story the same way because I think it’s, you know, perspective, and it also makes me feel very old. But if I go way, way, way back, back in the day, you know, I was in college, my parents said, “Hey, we can’t pay for college as much as we thought we could. You’re going to have to get a job.” And so, I got three, and one of my jobs was as a telephone interviewer at a market research agency. I like to talk, believe it or not, and the cool thing about the job is my shift was like 5:30 to 9:30, perfect for a student. I’d walk from home from the University of Texas, go get on and do my shift, then catch another bus home. And we did everything from consumer packaged goods, newspapers, when they were actually made out of paper and delivered to every door. We also did social… I don’t want to call it social justice. It was more like social issues work. So, we did a project called the California AIDS Study. I did in-person, interviews in prisons and on the streets, asking people about their sexual behavior practices. It was pretty humbling. Learned a ton. Learned how to talk fast, [laugh]—

Karen: [laugh]. With all the subtext around that [laugh].

Barry: Absolutely. Absolutely. But it was a really interesting experience. But at that job, I talked on the phone for a while. I did pretty good at it, and what happens when you do pretty good? They promote you and make you the supervisor. So, I was a supervisor. And I did that. I managed the field house for a while, and that was kind of cool. Got a couple extra bucks. That was necessary, and let me quit one of the other jobs. Then I got promoted again, and I was a field director. I was running the whole field place, shifts, and all that other stuff. I got to interact with some of our customers a little bit, and that was kind of interesting. And then I finished school, and then I went over to the research side, and I became a research manager, learned questionnaire design, learned—back then—how to program for [Caddy 00:07:03] because that was a new thing. And again, a wide variety of work, hair products, food, beverages. I did a project where I got to place bottles of products like Zema but dry, and I would go to frat houses on the University of Texas campus and say, “Here’s a box of 165s and a box of 223s. I’ll be back next week to see how you guys liked it.” Made me real—

Karen: That’s awesome.

Barry: I got invited to a lot of parties.

Karen: I just have to stop you for a second, then we’ll continue, but one of my first gigs—and I have a background in qualitative—and one of my very first interviewing gigs was I was doing in-store intercepts—I feel like I’ve talked about this before—in-store intercepts in liquor stores for the Elvira Campaign—

Barry: Nice. 

Karen: —Mistress of the Night—

Barry: Oh, yeah.

Karen: So, [laugh] I just want to share that because I’m like, oh, you’re speaking my language right now because we were at the same—apparently, at the same time, doing the same kind of weird, weird stuff [laugh].

Barry: Absolutely. But there’s something about, you know, handwritten questionnaires, quality control, editing work, looking at the data, making sure it feels right, and I think I got some pretty valuable skills, and that was great. I finished with school, got married not too long after that, started having kids, then you really need more money. And so, there was a company called IntelliQuest at the time, and they were doing this thing called technology brand tracking, which I had no idea what that meant, but I thought it sounded cool. And the company now was bought by Millward Brown, and is now a part of Kantar. And I started doing this international brand tracking, so I, one, learned international research. There were these modules, and I ran the Japanese module—I don’t speak Japanese—I ran the European module, and a couple of others. And we were tracking all sorts of technology brands, back when there were like 15 different brands of printers with, you know, names like Olivetti, who I don’t know exists anymore, and when Lexmark was just being born. And I learned that it was also the word ‘tech’ was kind of getting pretty big. And so, there were a lot of brand new companies, well before social media even was a thing. I did that for about three years, and then the last three years I was there, I did work on pricing. And so, I worked with Bryan Orme, who is the CEO of Sawtooth Software right now. He was my officemate at the time [laugh] for quite a while. And so, we worked on, again, pricing research for a lot of different technology companies, and I really cut my teeth on that field for quite a while. And it was my real foray, I was very much more—I skewed more B2B than B2C. We did kind of both, way back then because computers were relatively new. But again, it skewed a little bit more on the commercial side. And it was great. I stayed there for a while. Really enjoyed it, and I just didn’t know what happened next. I did the research, I knew everything that happened in data collection, data processing, blah, blah, blah design. Here’s a report. I wasn’t the guy who presented the report. We had a really cool, interesting gentleman named Michael Gale, who’s out and about, too, in the world of research right now as well. But I didn’t know what happened with that research. One of my customers was Dell at the time. They were a Tracker client. They had an opening, and I jumped to Dell and then I was on the brand side. And being able to match the research with how the business works was new, and interesting, and compelling, seeing how what we did turned into something that helped the product become a product, helped a marketing campaign actually have the right words, or at least, we believe had the right words. It really opened my eyes, and it was really, really cool. And I worked on just about every product type at Dell from consumer laptops, and everything in the enterprise space. And so, back then, I worked on, first, our desktop lines for commercial desktops, when desktops were really big thing. I worked on some of our first laptop computers back when they were like three inches thick, and when they got to be really that big.

Karen: It’s good to—are you even a professional if you didn’t have one of them? Because it feels like we all did.

Barry: Yeah, absolutely, absolutely. And then I worked on our first workstation, which was kind of neat. And then I got into the server, storage, and networking portions of the business, which were hard, technical, weird, and I spent a lot of time talking to IT pros. And it’s a very different—you’re right—very niche skill set because they’re an interesting bunch of folks, but they buy a whole lot of technologies, and you have to be—you have to fake being at least as smart as they were. And I stayed at Dell for 18 years. And again, I continued to learn across almost all of that 18 years. Towards the end, they had a really good [laugh] voluntary separation package. I was ready for something new, and then I wound up at Blackberry. Didn’t stay there very long, but it was really interesting. I had been in the client-server, and the edge-of-the-cloud, type of work, hardware. Then I got into mobile, and I learned a ton. I got to build a team from scratch. I got to help the company do a hard pivot away from the consumer world and into the B2B world because that’s where sort of the better chances were for the company. I learned really important lessons, like, no amount of great research and strategy can undo really… bad decision-making. I was going to curse. I didn’t ask if we could curse here, but I’m—

Karen: [laugh].

Barry: Really crappy decision-making.

Karen: Yeah [laugh]. 

Barry: We’ll leave it at that. And by then, my wife was working for Microsoft. We had relocated to the Seattle area. I had reached out to Reed Cundiff, who previously, when I was at Dell, I somehow got him to be a keynote speaker at the first CRC. And I was like, “Hey, if you ever have a thing,” he’s like, “Hey, guess what? I have something on my server and cloud team.” And so, that’s what got me to Microsoft. And I again, it’s been nine years and eleven months, and a wild adventure.

Karen: Yeah. I have so many questions about that, but I also just want to stop and point out—and thank you for that journey—there’s a couple things that stand out to me that I think I just want to anchor for our audience. One, there’s lots of people out there, probably, who are like, you know, in their minds, thinking, hey, how do I get that great, like, end client job, you know? How do I leave the supplier side and get there? And I’d love that you shared kind of, you know, about how, like, look, you were working with Dell, you were doing a good job for Dell, and then the opportunity presented itself, and you took it. Like, I think being a good researcher is probably the most important thing for making that—being a good researcher on the vendor-partner side probably is the most important thing for then getting an opportunity, when one arises, at the end client. Would you agree?

Barry: I do. I do. And I think, you know, I have an employee who was having an issue with one of her stakeholders, and because my—she was asking a lot of questions. I said, “Look, your job, literally, you get paid to ask questions.” And because that comes with what we do, I think that transition was really cool because I had a zillion questions. Like, “Wha?” And you learn important things. Like, there are reasons why research tells you the right answer for the customer, potentially. But you have a finance department that has to—that’s meaningful, and you may do the right thing for the company—or the person, but it’s the wrong thing for the company, and that’s not sustainable. And really understanding how the research makes the business work, that was huge, and I don’t think I could have gotten that if I hadn’t known how to ask questions.

Karen: Yeah, cool. I also just want to say one other thing because, you know, a lot of people talk about brand tracking, right? And a lot of people say, like, there’s a there are plenty of people that think that’s just kind of like the grunt work, you have to do it, it’s not very glamorous, is just, you know, and I love that you started with some of the work that you did, and it’s sort of, there’s something poignant to me in that you just kind of learned very early in your career the importance of, kind of having the pulse of the customers, and how they perceive your brand. And I’m wondering if that learning that you took into account then about brand tracking, even though it’s not what you’re doing necessarily right now, if it informed your work today?

Barry: Well, I still have a [better 00:15:13] tracker [laugh] so yes.

Karen: [laugh].

Barry:  You know, at the end of the day, customers interact with products and services via brand, and so, yeah, we have a brand tracker that probably, like many, does more than it should [laugh], but it is a great learning instrument. It’s great to get the pulse of the customer, how they react to you and the competition. And I will say, we were able to bind that with newer techniques like our social intelligence program. It is faster, it is instant, it has a way, way different scaling, and it’s really good for certain things, and getting you certain brand insights. It’s best for really weird audiences, or things that are super new. But that brand tracker, it’s kind of like, it’s kind of like the cruise ship, right? Everybody likes to get in, there’s something for everybody, and it just works. It does its job pretty well. It’s definitely always useful, and it’s always a big part of the toolkit.

Karen: Yeah. I love that. Thank you. Let me just ask you another kind of clarifying question, too, because the obvious B2B nature of your work—and you were saying how, like, you kind of were drawn to it; you liked it, you enjoyed it—how would you clarify for people who don’t do as much B2B, right, or maybe they are shifting, where they’re maybe being offered B2B work, but they’re just not sure. You know, how would you differentiate it from what you know about consumer insights from the early days, too? Like, what makes it tick, what makes it unique, what makes it special?

Barry: I’ll start with something that’s a bit more important than that, if it’s okay. At the end of the day, we talk with people, consumers or not. If you think about it, everybody who’s a buyer oftentimes is a consumer as well. I promise you, a developer uses a whole lot of Xbox as well as Visual Studio and GitHub, which are some, you know, more geeked out developer products, and never forgetting that they’re people, that’s the continual connection. What’s different? I don’t know if you have an IT person who you interact with, but they have a very different job than you do, and they have to protect the company in ways that you don’t. They have to think about the greater good, and so they are a decision maker that has to think about the entire company, not whether more people like Macs versus PCs, not—right because that is sometimes a thing, and I’m not judging either way—but they have to think about what they have, their environment, the budget, security, and all sorts of things. And so, unlike—and I hope this doesn’t come across horribly; I walk the line here—but it’s kind of like being the mom. It’s great to buy the Cheetos, but you got to put some apples in there because they’re good for the kid, and maybe some milk. And if you only bought what people want, that’s not good. If you blow your budget, that’s also not good. If you buy things that nobody’s going to eat, you’ve wasted money, and that’s not good, right? And so, being able to think about them from that perspective, they have a little bit of outsized power in that. Now, the other thing that’s interesting in our world is, we work with kind of decision-making units, the IT person, even the CIO, well, they’re only part of the equation. Oftentimes, the CIO may not even have the biggest technology budget. Many times it’s the CMO because they have database analytics, and the way advertising works this way, and they buy subscriptions to the, a lot of times, Salesforce and whatnot. And so, the things that are different, it’s just more like how they purchase. They often are purchasers that they may not be using users of themselves. I also talk to developers. They typically are our most user-based set of folks that we deal with. And they’re very special. They’re kind of like interviewing doctors. They’re very expensive to reach, they’re very technical, they’re very specific, they’re very… you have to treat them differently than we do our typical consumer, or our typical IT person. And then kind of another area that’s the big three are, we talked to business decision-makers, and so the CEO, the CFO, the VP of Sales, the Head of HR, folks like that, they influenced technology purchases because their employees use those things. They need them to accomplish certain things. If the technology isn’t fast enough for the trading floor at an investment company, sure, you think it’s just computers, but the CEO of that company is like, “That cost me $800 billion because we were too late in buying that NVIDIA stock.” Right? And so, that technology becomes a really big business asset. And so, their lens is very different. And so, the one of the more different things—and I guess this happens in a family as well—but the stakeholders are fairly broad for technology. The distribution of budget is different, the distribution of power is different, and it creates really interesting dynamics.

Karen: And and as you’re talking, I can’t help but think about [laugh] research, research budgets. And as you’re talking, I’m thinking—again, qualitative researcher background—I’m like, oh, those are some expensive people to talk to. But, you know, I mean, that was—and so even that puts it sort of in a different category in my mind. Your—

Barry: Well, it does. I mean, the company has blessed our team with being able to shepherd significant amounts of investment.

Karen: Yeah. It’s an investment, for real. Yeah.

Barry: And again, we’re a fairly large company, and we do pretty well, but in order to build a data center, for example, they cost billions of dollars, and so your company has to grow, and the company has to be profitable. And so, understanding how to create the right value equation becomes that much more important because it’s both a quarter-to-quarter thing, but it’s also a decade-to-decade thing. Microsoft is going to celebrate its 50th anniversary next year. Wa—and—

Karen: Oh, wow. I’m sure we’ll be seeing about that, I’m sure. That [crosstalk 00:21:32] going to be talking about that [laugh].

Barry: Right, right. And all of that has been kind of a fairly successful one, and strong, and takes a different type of vision. And so, that framework kind of really governs how we do a whole lot of things.

Karen: Yeah, cool. So, you know, I want to talk a little bit about some of the expertise from the AI event that we had, and from your background, also because I think that your talk, particularly at AI, was leveraging the law of large language. And I just want to kind of just extract some of that intel from you because this has been a part of your work also. And so, many people are tuned into AI right now, for all the obvious reasons, right? Tell us a little bit about the value of that in the work of an insights professional, in your opinion.

Barry: And of AI in general?

Karen: Uh, yes, and all of this access that we have from the help of these large language models, and, you know, how these technologies are advancing teams. Because you are, as a company, ahead of the curve because your company is in this business. So, you’re not only a user of it, but also it’s your company’s—where you live, right? So, just talk to me a little bit big-picture for you about all of this for the insights professional.

Barry: Yeah, for us again, we there’s this concept of, well, you have to eat your dog food. That’s what we do. If we make it, we got to eat it. We got to try it out. And so, at scale, we have to learn, how do we transform how we do work, leveraging AI? And it started out by just experimenting everywhere and trying to do things that we’ve done one way, trying to do it in another way. And I think from a researcher’s perspective, the gains in things like productivity are pretty stark. You know, going through, how do we create an RFP, send out that proposals, and then start comparing those proposals. You can do that way easier and faster with an LLM. All of the tasks that we do as researchers, looking at open-ends, you can look at thousands of open-ends in milliseconds versus a human reading those, and it’s really, really, really good at that. And so, we think about, how does this make a researcher more efficient? And if a questionnaire gets draft of a questionnaire gets made in, like, eight minutes and it’s 80% good, you’re spending far less time getting to that 80% good the first time, and that saves you days, right? And again, I think researchers have forever heard, “Research is great, but it’s a lot of times too slow.” This is a way of getting back that time. And the efficiency is one thing, being able to re-leverage all the work that you’ve always done, we have a tool called Hub, that’s where we dump all of our research, and so being able to leverage all of that all at once and extract research value out of work that we’ve already done. It’s done things like answered questions in the room. I think that’s the big dream of every researcher. If I’m in the room with an executive and I can say, “Oh, I can tell you right now, we did this project a year-and-a-half ago, 86% of the people want us to do X.” “Oh, yeah. That’s a great idea, see?” And it could shift that com—that in the moment. We’ve all been in those research presentations where we say, “Hey, that’s great idea. I think we’ve done research in the past. We’ll get back to you.” By then, it’s a little too late. We always do it, but it’s three days later, more often than not. And so, being more effective in the room is another great benefit. Being able to not do things because you already have an answer. I think sometimes, again, I’m very guilty of making those questionnaires a little bit fatter than I need to be, and then you use the six things that you need, and you never go back to it. Now, we’re almost always going back to it. It’s a greater place to start. It’s helping us not do research, or, better yet, it’s helping us do the research that actually matters more. Because if I can give you a you know, again, 75% of the answer with something that we did four months ago, let’s use that $50,000 project to do more than what we had originally planned to. Let’s get that new information. And again, over time, we’ll have agents that will have a lot of personas built in, and they can answer a certain class of questions that’s meaningful. I tell people all the time, senior executives, they make decisions. That’s what they get paid to do. They’ll make it with great information, they’ll make it with very little information. Hell, they’ll make it with no information. They’ll say, “Oh, my gut tells me this is the right way.” I think we have a new opportunity. I always think that research informs the gut of executives. We’re, like, the microbiome [laugh] of executives sometimes because they’ve heard these things. We’ve planted lots of learnings in them. AI makes that just a little bit more available to everybody, and I think that just lifts the starting place.

Karen: Yeah, and I love that you brought that up about, you know, about the gut because one of the things that I always talk to people, especially people on the brand side, is, you know, how do you balance when either you’re making decisions or whether you’re informing other decision-makers? You know, the data-driven information, with the intuition, and you know, your intuition, which comes from you know, either just, you know, that gut feel, or it comes from years of experience, too. Like, how do you balance that in the B2B space, you know, which is a little bit different from—you know, I had this conversation with somebody at PepsiCo not that long ago, or somebody at Mondelēz not that long ago, where they’re talking about it, but they’re talking about it about, like, kind of, you know, daily consumption of just, you know, men and women. Is it a challenge, or is it an easy balance for you? Talk to me a little bit about that. 

Barry: Always a challenge. I mean, things change all the time. That is hard and interesting. We’ve missed whole areas like social media, for example because it was just too late. And so, speed matters, complexity matters, human beings matter. For example, when we think about AI, we’ve been tracking work really early, and some of the work that we’ve done, we’ve been doing a tracker on AI, and we got a lot of consumers. So, our first tracker said, “AI means aliens from space. Aliens from space.” That’s not what we had expected, right? And then in the B2B world, that’s not what they say. They know exactly what it is. They’ve been using machine learning for over a decade. But we have to push both of those groups forward. I’m probably not answering your question very well, but it’s, we have complexity, change, and a great need to also maintain what we’re already doing, all at once, and it’s sort of a tricky balance on any given day.

Karen: Yeah. Yeah, I think that’s really the bottom line, and that’s why I would ask that question, is because it is a balance, and it is tricky, and nobody has this the secret sauce for how to [laugh] how to—nobody—you know, everyone’s like, we’re all just doing the best we can here, trying to, you know, make data-informed decisions and intuition-based decisions, and at the end of the day, we’re hoping that, you know, we all get it right in these organizations. So, you know, I do want to be mindful of our time here, so I’m kind of watching our clock, but you know, another question I would have for you, really, is, are there other challenges that come with this B2B space where you’re working? Anything else that, like, you think is kind of a universal challenge that maybe we should just kind of put out there, and maybe you have some nuggets of information for people, or inspiration for people.

Barry: Wow. Like I said, it’s real similar to what everybody does. Some special things, like sample quality is a huge deal for certain populations, and so we spend a whole lot of money on trying to improve sample quality. We use a lot of premium sample because we have to talk to the right person. And a lot of our technical audiences are highly, highly at risk for fraud, so we throw away a ton of interviews due to fraud. You know, it’s interesting. I love the change in innovation, and usually the people who make it, they love it, and they see where it’s going to go. Getting the people who actually need it [laugh] to be on the same page, that is a challenge. And how you do research with that is also a challenge. How do you get people—you know, if I were to tell you four years ago, you know, you’ll be able to type a thing into your computer and it will totally redo your questionnaire, and it will make it so much better. It’s going to take, like, five seconds, and you can do 27 questionnaires in one day, whereas usually you might have been able to do four questionnaires in a day, if you’re really great. If I’d have told you that four years ago, you’d have [crosstalk 00:30:28]—

Karen: No, no. I wouldn’t have believed it even two years ago, when I thought it was a possibility, for some of the conversations that, you know, I might have with the language model. Like, I wouldn’t have believed it. So, the way it’s made its way into my work life is shocking. So.

Barry: Right. And in order to do that, and like, some of our problems, especially, like, on a monetization side, we have to explain things that are kind of straight out of the lab, or may still be in the lab. And so again, four years ago, how would I have described to Karen that we work with a company and they have this thing called the large language model, and it will generate answers from all this data, all the data in the world, in seconds. And you’d be like, “Yeah, right. You mean like my web browser?” No, it’s not like your web browser. And so, a lot of—you know, one of the things that is not surprising to people, when I say it, the amount of qualitative that we do is truly astounding. And sometimes ten IDIs with the right people at the right moment, are way more powerful than the, you know, 750 sample-sized study that I’ve done in two countries.

Karen: That’s cool. Well, again, the qualitative researcher in me loves that because I’m like, “Yes.” [laugh]. It’s great. Yeah.

Barry: And then we’re complimented with all the other stuff that we have. You know, we have a strong data and analytics team, so we look at our customer data. We look at qualitative, quantitative, social, causal inference modeling, you name it, and the people on my team, their job is to be really good questioners. Be really, really good in [unintelligible 00:32:19] analysts, and probably most importantly, really good storytellers. And those things, I think, we’ve been talking about data and storytelling for decades now, and they don’t get old. It’s just the storytelling part gets to be more important because you have a little bit more time to deal with it. And that’s how you make a difference in the room. And I think that’s how we really create better impact.

Karen: Yeah. Well, and that’s been a theme through this whole conversation, is making a difference in that room, and how we can do it, so I love that. Last question for you, and then I again, I want to let you off to be mindful of your time that we have together, too, but what’s ahead for an insights professional? Like you’re just saying, like, you’re just saying, like, four years ago, we couldn’t have predicted where we are now. What does an insights professional today maybe need to have their eye open for four years from now?

Barry: Yeah. I am absolutely positively not afraid of AI taking anybody’s job. I will say those who leverage AI with their job to make them better, those are the people you should probably be scared of. And so, again, arm yourself with the new tools. Use them, figure out how they work. I think that’s going to be key. And I think that also means a good analyst, again, they know how to analyze things, whether it is a quantitative survey from a brand tracker, a couple of IDIs, some analytics from your customer data warehouse that has four or five data elements that are germane to the question that you trying to ask, and some social intelligence data that somebody scraped off, you know, social media with your key audience. How you weave that together and tell a story gives you something better to bring to the picture. We’ll be able to do that faster. We’ll be able to do that across more topics, I think, because hopefully, we will be doing far less busy work. That time that we researchers always crave to say, “If only I had enough time to kind of sit back, look at the data, play with my slides, make that story really great, and then reflect,” that time gets created to connect the dots, as opposed to we said we’re going to get it to the 15th, get it to him on the 15th. That’s the day after tomorrow, and we’re going to be here all night, getting the slides together and spitting out a deck, when you—right—you get all of that stuff ten times faster. How do you use that time to make it all better?

Karen: Yeah. And become a smarter—be or present yourself as a smarter storyteller who could see the threads and connect those dots to tell the story, to inform those decisions.

Barry: Because that’s the value that Microsoft expects from the research team. They don’t expect us to do 750 different surveys, 1200 qualitative projects, 16 data—right? They don’t—that’s not what the thing is. They want the insight that can help create impact. And that’s the hard part, and it takes all those things to get there. 

Karen: So cool, Barry. Thank you so much for this conversation. I have enjoyed talking to you, and I feel like we could probably talk for two hours [laugh].

Barry: [laugh]. I’m a bit wordy, so probably could.

Karen: Yeah, yeah. Well, it’s just such a pleasure, and I appreciate you bringing your kind of B2B background and your experience at Microsoft to everybody in the Greenbook audience. Thank you so much.

Barry: It was my pleasure. Thank you so much. Great chatting with you, Karen.

Karen: You’re very welcome. And listeners, thank you for joining us. It’s wonderful to be able to bring you these interviews, you know, week after week, and we can only do it because you are out there listening to us, so thank you so much for being here. Thank you to our editor, audio editor, Big Bad Audio. Thank you for all that you do. And Barry, once again, thank you to you. It was a real pleasure. Until next time, everybody, bye-bye.