The Role of AI in Market Research with David Boyle at Audience Strategies

126 David Boyle

[00:00:00] MRII Announcer: Welcome to MRII’s Insights and Innovators podcast, where we talk to top market research professionals to get their inside stories about innovative and enduring best practices. Today’s episode is sponsored by Full Circle, named the panel company of the year. Full Circle is a leading provider of high quality online insight, leveraging survey experience, advanced tech, flexible community strategies, and unparalleled quality controls.

[00:00:27] MRII Announcer: We give you immediate access to proven data for better insights. Now, here’s your host. For

[00:00:34] Jon Land: years, there’s been an outcry that market research needs to be more perceptive and more consultative to truly add value. With a pragmatic emphasis on segmentation and the use of technology, David Boyle’s firm, Audience Strategies, takes an enlightened view towards turning insights into action.

[00:00:52] Jon Land: I’m John Less, president of Sports Leisure Research MRII. In this episode, we’re going to dive deeply into meaningful [00:01:00] trends redefining the insights profession. From the vantage point of audience strategies, David Boyle, who has as much to say about the confluence of insight strategy and AI driven innovation in providing direction to leading brands.

[00:01:12] Jon Land: David, it’s great to have you on Insights and Innovators.

[00:01:15] David Boyle: Thank you so much. It’s a pleasure to be here.

[00:01:17] Jon Land: So I want to get started right away with, with a real brief overview of your own personal career journey. Um, your career has spanned consulting, politics, retail, entertainment, And now AI Driven Insights, and I’m curious, as a fellow journeyman who’s been all over the place, how has your diverse background influenced your perspective on innovation and marketing research?

[00:01:41] David Boyle: How to answer that in a quick response is the challenge. Um, okay, I started consulting, making strategy decisions, and we didn’t use much market research. I felt that was wrong, I felt it was siloed, I felt it was gatekeeped, and I felt like that was the problem. And I carried that problem [00:02:00] with me into, uh, running research teams many years later.

[00:02:03] David Boyle: Um, my goal was to make research available and useful, uh, to strategic teams making strategic decisions, not just tactical decisions. So I re engineered research teams, um, to, to try to be more strategic. And I realized that you could, you could point research at business strategy and it could move the needle on really, really big decisions.

[00:02:23] David Boyle: So I’d say I spent my second career doing exactly that. Um, and then AI came along, uh, and knocked my socks off, uh, late November 2022, two and a little bit years ago, and stopped me in my tracks because suddenly that could do a lot of things. That I thought were really special, and you had to be a very, very skilled researcher to be able to do.

[00:02:44] David Boyle: So I guess that’s the start of my third career at that stage, then.

[00:02:48] Jon Land: Nice. Always great to see, you know, that evolution and kind of thinking about how today’s leaders kind of got to where they were. You know, you talk about AI, and there’s a popular quip that I’ve been known to [00:03:00] share with colleagues across the industry, and that’s if we had 10, 000 for every time someone in today’s marketing environment used the letters AI, we could probably all retire.

[00:03:09] Jon Land: Um, So what fundamental shifts have you seen in how organizations connect with their audience? And what role is a I playing today on into the future? Help us kind of separate the hype from the substance.

[00:03:24] David Boyle: Yeah, and I was I’ve got to say I was a slightly Embarrassed to say I worked in market research for a little while.

[00:03:30] David Boyle: I used to say I work in research, but I’m not a researcher because, because research often didn’t, didn’t deliver. And now I’m slightly embarrassed to say I work in AI because there’s so much hype. And so maybe I’m drawn to careers where I try to do things a bit differently. But okay, there is so much hype in AI.

[00:03:47] David Boyle: I try not to use the phrase AI. I try to use the phrase language models because that’s the thing that’s making the big difference. Let’s be specific. These are machines that let you put some words in and get some [00:04:00] more words back out again as a result, not numbers, we’ll do that separately. Um, but the simple fact is if you put the right words into these things, you can use them for all sorts of different things that we do all day, every day.

[00:04:12] David Boyle: There are four things I think they’re very, very good at synthesizing information. We have a lot of that in the research world, particularly words, particularly QUAL. We can synthesize it like never before, all that QUAL that went untouched, untapped, or unanalyzed. And there’s a lot of that in organizations, if we’re honest, can now get processed in a more effective and more efficient way.

[00:04:35] David Boyle: Uh, writing, we can be more compelling in our, in our, uh, reports, uh, in our, in our explanations, uh, in our pitches, and, uh, we’re often not great at that, researchers as well. Uh, thinking, we’re pretty good at thinking about audiences, and we can do it more, more often, and, uh, more deeply than we used to. But also we often fail to think through the implications of our work, [00:05:00] hence the challenge integrating insight into strategy, whereas now we can do much more thinking about the so what’s of different audience insights, different opportunities and different challenges.

[00:05:11] David Boyle: Um, and so, yeah, there’s a bunch of different things these things are very, very, very, very good at. And, um, for me, it’s about helping with lots of little tasks all day, every day, rather than one single breakthrough at any one point in the journey.

[00:05:26] Jon Land: Yeah, I guess another input, if you will. I mean, it’s funny because I think one of the traits that we both share, and I’ve talked about it on the podcast in previous episodes.

[00:05:35] Jon Land: Is, is just, it always amazed me, and still to some degree does, that there are not enough researchers that think like strategists, that think like consultants. The line that I’ve used, and people are probably tired of hearing me say this on this podcast, was I always used to pick on McKinsey, only because I almost worked there, and that was the difference between what we do and McKinsey is only about a million dollars in engagement, and now technology, I think, helps us even be sharper in, in that regard.

[00:05:59] Jon Land: [00:06:00] And, and, and kind of drafting off that a bit, you, you’ve emphasized. In your firm, developing strategies based on audience needs. I’ve also been a big fan of talking about understanding audiences, about understanding the value of audiences, particularly in the media space where, where I came from before having my own firm.

[00:06:18] Jon Land: How has AI changed your approach to understanding audiences in particular in the means of segmentation, which is also something that has a personal affinity on my as well.

[00:06:29] David Boyle: Yeah, I mean, just on that broader topic for a second, coming from a background in first strategy consulting, helping a broad range of industries, and then doing strategy work in media and entertainment industries, luxury goods, you know, strategy comes from lots of different directions.

[00:06:45] David Boyle: It can come from financial strategy or business strategy or all sorts of other strategies. It is not at all obvious to the strategy field that audiences should be at the heart of it. I think I’ve always seen and shown that. Uh, it’s not [00:07:00] only a perfectly valid place to start your strategy, but actually I think it’s the most logical place to start your strategy.

[00:07:06] David Boyle: So I firmly believe that strategy should be absolutely rooted in, it should start from, uh, what audiences need, category related needs, audience needs. And so that’s a philosophy which is absolutely not shared by the wider strategy industry, but it is. That’s something that’s incredibly powerful. So I think there’s a lot to that, and I’m glad we share that enthusiasm.

[00:07:29] David Boyle: Um, yeah, and I think quite, I mean, quite simply to use your McKinsey example, um, I think that they, to crudely categorize the sector, they’re pretty good at the strategy, and they’re weak on the research, on the insight, on the evidence base is often, particularly audience insight, pretty good on market insight, market strategy, uh, Uh at numbers and that kind of stuff but audience you scratch the surface of market research from big consultancies often a little bit lacking and Market researchers are often the [00:08:00] flip though Yeah, very very very robust on the research kind of lacking on the strategy There’s so lots the implications that are going to resonate with those kind of colder harder more strategic People so I one of the big benefits is this helps us bridge the gap It helps us do the kind of strategic thinking that we’re not Researches are often not trained to do.

[00:08:21] David Boyle: It helps you extend your range beyond being a deep expert in audiences, which we must maintain as our core and reach out into those business conclusions, reach out to help us better understand stakeholders and better communicate with them and better think through the implications for each of those stakeholders.

[00:08:39] David Boyle: Um, and then never mind on the research, the segmentation side, you know, the process for us has been completely upended, uh, by, uh, AI. I was doing one this morning for a client with a couple of colleagues, actually. So, uh, brainstorming audience, uh, brainstorming, uh, category related needs is one of the first things we do.

[00:08:57] David Boyle: That used to take us a week or two, [00:09:00] and sometimes took qual before we could really understand it for a new, uh, new category we’re working in. Uh, that can be done inside of an hour, bringing vast data sets to bear and coming up with, uh, category related needs hypothesis, uh, that are much better than the ones we used to.

[00:09:16] David Boyle: Then coming up with audience segments off the back of them. Again, it used to be really hard mental work. We would do it, really hard mental work. We’d come up with a hypothesis before we wrote our survey. But now we can do that almost instantly as well and they’re better they challenge us We have great conversations right there in that first hour of shared work And so we can go into the pitch with a client with a hypothesis Of what the answer is Right there right there Which is 70 or 80 percent of what the answer will be when you pay us to do the research off the back of it.

[00:09:48] David Boyle: It’s like my old

[00:09:49] Jon Land: lamppost metaphor where, you know, you’re looking to, you know, for support as well as well as illumination at the same time. Yeah, it’s interesting because I’ve had a number of times and we [00:10:00] also go in and we say to our client, we want to understand. The utility of a project. What are you going to do with it?

[00:10:04] Jon Land: How are you going to apply it to something that moves your business forward? So it’s it’s kind of refreshing to hear you talk about that. And also with an orientation towards segmentation and audiences, because I think so. Oftentimes, that gets lumped or pushed to the side. Um, tell me a little bit about, you know, so, so this doesn’t sound like a radically different approach to me, but probably to a lot of other people that are listening to this.

[00:10:30] Jon Land: How do you, you know, if someone’s getting into the research business today and given the way that you’ve uniquely applied this technology driven framework, what are some of the skills that Insights professionals need to be developing to stay relevant and valuable, particularly as this only gets more pervasive over the next five to ten years.

[00:10:50] David Boyle: Yeah, that’s such a good question. And the answer is not obvious at all, I think. So, at once, all of the skills the research industry has are still [00:11:00] critical. Like, every single one of them is absolutely critical. Uh, AI doesn’t replace any of those skills. Uh, and asking AI for its ideas of what the answer might be doesn’t replace doing primary research in any way at all.

[00:11:16] David Boyle: But it does get you most of the way there pretty quickly and it can help you to do more of a wider range of tasks in your in your role than you otherwise would have done. So get ready to do more tasks than otherwise would have done. Get ready to have a broader repertoire of things that you do because AI will help you to do more.

[00:11:34] David Boyle: Get ready to work on more clients than you used to because each project’s quicker and mentally easier. as well. Um, get ready to be challenged more by an AI rather than by your manager, rather than by your peers, by your colleagues. Learn from the AI, use it to help you to learn and grow your career. So do all the things we used to do, but weave AI into every single one of them as a thought partner and as an accelerator and get ready to [00:12:00] work harder and faster, but also happier as well.

[00:12:02] Jon Land: So it’s additive rather than being a substitute.

[00:12:06] David Boyle: When used well, it’s absolutely additive. We use the analogy that it’s like an electric bike for the mind. You’re still in control, you’re still steering, you’re still navigating, you’re still pedaling actually, uh, but you know what? It’s an accelerant. And I think the danger is when people use it as an electric car for the mind, they zoom out as it zone out and watch YouTube instead of following, keeping their eyes on the road and keeping their hands on the wheel.

[00:12:32] David Boyle: That’s really dangerous. So, um, no, we don’t advocate for automation. We don’t advocate for replacing humans. You could make that case, but we’ve not seen it strongly. It’s an additive accelerant to human abilities. Absolutely.

[00:12:46] Jon Land: I love, I love the electric bike metaphor. I may have to steal that from you.

[00:12:50] Jon Land: That’s, that’s one of the better ones I’ve heard. That’s, that’s really cool actually. Talk about mnemonics and metaphors. You’ve written extensively about this four Ps framework for [00:13:00] effective language model use. Now, at the risk of showing my age, I mean, I still remember learning the four Ps, you know, the first day of business school.

[00:13:07] Jon Land: Talk about this framework and its application to, to language model usage. Okay.

[00:13:12] David Boyle: Yeah, we wrote this first for a big consumer goods client. We were redoing the product innovation cycle for them, uh, putting AI at the heart of it. And they kept coming to us and saying, hey, can you write me a prompt that will help us to do X, Y, or Z?

[00:13:24] David Boyle: And we said, no, there’s more to it than a prompt. And we came up with this idea that a prompt is only one of the four P’s that you need to use AI well. So prep is often overlooked. What is it you’re trying to achieve? What materials and context documents do I need to bring in order to put them into the AI, just to set the tone, to set the, um, the guardrails, to set the ambitions of the project properly.

[00:13:47] David Boyle: There’s a lot of work there, actually. Everyone skips it. Uh, prompting is next. There’s some skill to that, but it’s getting easier and easier as models evolve. There’s some skill to it though. There’s some tips and tricks there. That’s the second P. The third is [00:14:00] process. So how do you break a task like product innovation or audience segmentation?

[00:14:05] David Boyle: How do you break it into steps and solve each step one by one, inserting human expertise at the appropriate points, iterating and refining as you go? That’s a process challenge. It’s a segmentation process challenge first of all, then an AI process challenge on top. You’ve got to have a good process in both ways.

[00:14:21] David Boyle: And then the fourth P is Proficiency. That is using your expertise, your judgement. And we say that you have to CEO every AI output. That is to check it, that’s on you, not the AI. Edit it, because you’re going to want to take stuff out, add stuff in, refine it. And then ultimately, oh, own it. Ultimately it’s on you to say, I stand by this output, not chat GPT told me.

[00:14:43] David Boyle: So CEO it, that’s proficiency, that’s the fourth P. So yeah. I can give you a prompt, but it’s not going to help you having got the other three P’s, you got to do a bit of work,

[00:14:51] Jon Land: you know, it’s, it’s, it’s interesting, you know, there’s, there’s a lot of pragmatic advice there. And I think it behooves a [00:15:00] research professional, particularly as they move through their career to think in that way.

[00:15:04] Jon Land: I want to wrap up by eliciting some pragmatic advice for those who are looking to lead organizations. What are some things that you envision that today slash tomorrow’s leaders are going to need to be mindful of to not only harness technology, but to move the insights profession in a direction that not only assures its survival, but it’s to enable it to thrive in ways that, you know, I think, both of us have always felt were ways that it should have always thrived and maybe in our worlds it did, but, but not universally.

[00:15:39] Jon Land: What, what are your thoughts there?

[00:15:41] David Boyle: Well, I think the first point is that AI is, is an accelerant to almost everything that knowledge workers do almost every day. And It happens to be particularly well suited to what market researchers do so more than any other organization I would argue that’s [00:16:00] absolutely true in in market research firms So that’s an accelerant to everything we do all day every day.

[00:16:06] David Boyle: That’s organizational change that’s required there that’s training and support and guidance and mentoring and leadership and encouragement and incentivization that that is a complex organizational change process It’s worth it because you know what making everything your whole team does every day Better quicker and happier and reducing the mental overhead is an incredible boost and accelerant to the organization overall So you’ve got an organizational change problem there to uh to undergo not just the training not just the tool purchase challenge, uh lead from above why partly because It will change the way you run your firm.

[00:16:44] David Boyle: It will change the way you write and think And communicate with clients and learn Adapt and get up to speed. We’re showing that with senior leaders across so many organizations. You are not exempt It will help you as well. I promise Um, but recognize that it also helps the grassroots [00:17:00] Team assistants or interns are accelerated by this, sometimes more so than more senior people, because they’ve got more to learn.

[00:17:07] David Boyle: It’s easier for them to learn. This is a whole organization challenge. Recognize that some people are going to get it quickly and are going to be vastly more productive as a result. Support, enable them and manage their acceleration. Don’t hold them back. Don’t make them hide their work. Some people are going to be laggards because technology’s hard to learn and new ways of working are hard.

[00:17:30] David Boyle: So think about how you support those people. I would insist that they develop the new skills, but support them to develop the new skills. Give them the support they need as well. So again, I think it’s more of an organizational change problem. Uh than it is a technology problem or a systems problem And that’s a whole different way of thinking about it’s a whole different challenge.

[00:17:48] Jon Land: Yeah, it’s a cultural challenge. It’s it’s something that we often talk about You know, finding that happy space between high tech and high touch. I, I don’t know if that’s a good way to summarize it, but, uh, [00:18:00] this has been really, really have enjoyed, uh, this quick immersion into some of the ways that, that you’re thinking and the things that you’re doing, I wish we, we could spend more time, but, uh, that’s going to wrap up today’s episode of insights and innovators.

[00:18:13] Jon Land: Thanks for joining us, David. Thanks so much. Good luck, everyone.

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