In this episode of the Greenbook Podcast, host Lenny Murphy is joined by Seth Minsk, principal of Finish Line Insights, for a deep dive into the evolving role of insights professionals in the age of AI. Seth shares his unique journey from his early days in research to leading global insights for brands like Allegra and Advil at Sanofi, and now helping businesses navigate transformation. The conversation focuses on how AI is shifting insights from traditional research methods to more strategic, business-impacting roles. Seth discusses the growing relevance of AI in automating processes, unlocking faster decision-making, and transforming insights teams into true business partners—illustrating how insights can go beyond answering questions to actually shaping the questions that businesses should be asking.

You can reach out to Seth on LinkedIn.

Many thanks to Seth for being our guest. Thanks also to our producer, Natalie Pusch; and our editor, Big Bad Audio.

Hello, everybody. It’s Lenny Murphy with another edition of the Greenbook Podcast. Thank you for taking time out of your busy day to spend it with myself and my guest. And today I am joined by Seth Minsk, principal of Finish Line Insights. Seth, welcome.

Thanks, Lenny. How are you doing today?

Doing all right. Doing all right. It’s good to have you. And I’m still—our audience doesn’t always see the video, but I’m still just loving the wood paneling. It just brings back such nostalgia. I wish I could convince my wife to let me put it up in my office.

Trying to keep things retro.

You know, it’s—we need those touchstones, right, to our youth. Anyway, so [laugh]…

[laugh].

Seth, so you’re currently with Finish Line Insights, but you actually have been around the industry for a very long time. And for those who don’t know you, why don’t you talk a little bit about your bio and background for the audience?

Yeah. So, you know, first I just want to say that I’ve been using Greenbook ever since it was a literal green book. And so just really happy to be here on the podcast talking to you. You guys just have so much great content, which I really lean on to keep up to date in the industry, discover new things. So I am really glad to be here. I am currently leading a consulting practice called Finish Line Insights. And what I do is I help companies with things like insight, strategy, transformation, and capabilities. How do we, from a strategic perspective, navigate, you know, the really rapidly changing environment for insights that we all live in? I help companies with strategic projects—basically any kind of insight support where a company needs someone who’s been doing this for a really long time. Before that, in my last role, I was leading global consumer insights at Sanofi Consumer Healthcare, which is the number three, number four, OTC consumer healthcare manufacturer in the world depending on which version of the rankings you look at—brands that in the US we would know, such as Allegra and Dulcolax, a lot of brands outside the US that are leaders in their categories. My team was responsible for insights for all of the global brands, as well as for building insights capabilities for the local market teams as well.

What about before Sanofi?

Yeah. So I’ll talk about my journey in insights for a minute or two. For me, it all started in a dorm room at New York University as an undergraduate where I was taking my marketing major. I was taking my market research class, you know, had all my crosstabs, printouts on the floor of my dorm room, and really just fell in love with this discipline, which is a combination of, you know, marketing, psychology, economics, problem solving, journalism, storytelling, just all these things kind of combined into this one field where you can make a tangible impact on a business. That’s a phrase you’ll hear me use a lot over the next half hour. And so from there, I started my career at IRI, now Circana—terrific place to start a career on the supplier side. I moved into some dot com startups just in time for the crash of the dot com bubble. Got laid off twice in five months and moved from there to the pharma world, the consumer healthcare world at Whitehall-Robins Consumer Healthcare, which became Wyeth, which got bought by Pfizer, which merged with GSK. So 18 years sort of went by in the blink of an eye. Worked in business intelligence, analytics, brand, and then, you know, a number of years in dedicated consumer insights role. Terrific good fortune to work on a ton of great brands: Advil, Thermacare, Centrum, Chapstick, you know, with great people doing great things. But, you know, as far as my journey in insights, I’ll say that my career really reached an inflection point about ten years ago where I was supporting innovation teams, and I was doing a lot of qual/quant basis, qual/quant basis over and over again, and really kind of started thinking like, is this all there is? And how do we really kind of get deeper than that? And also thinking really heretical thoughts like, do I really even believe in a top two box purchase interest anymore?

[laugh].

You know, certainly, right, 90 percent of things that are basis tests fail. So, you know, do I even believe some of those metrics and, you know, working in some very emotional health conditions, where we are interviewing people about their motivations and about why they act the way that they do—you know, I was working for many years on the Rx to OTC switch initiatives around Viagra and Cialis. So, you know, not only super emotional conditions, but men—asking them to be articulate about their feelings? And do I even believe the feedback that I’m getting from that research, where we tend to ask direct questions? So those kinds of thoughts led me down a dark path to things like behavioral science, you know, which led into agile and DIY, you know, which has led into AI, but really developing this outlook towards the industry of we do so many things because that’s how it’s always been done, and are we doing things in the best possible way to get the outcome that we want? Is there a reason why we’re sticking with the traditional, and how do we incorporate these new things? So for me, it also led to thinking about innovation and insights, not from a standpoint of, you know, this is the shiny new toy, right? And that’s the danger when we—you know, and I think that that happened after a while. You know, there’s a backlash to each of these new things, behavioral science and agile and whatnot. So not thinking about things in terms of the shiny new toy that we’re going to adopt because, you know, it’s sexy. But how do we build this into a totality of a view that we can take into the business, you know, to make a tangible impact on the business. There, that’s the second time I’ve said that five minutes, which I think has really informed my leadership perspective on insights and how we build teams and how we build capabilities.

That’s fantastic. And if you’re a heretic, then I’m a blasphemer. So we’re [laugh]—

[laugh].

—in good company. And similar, even though my experience all on the supplier side and then this weird consulting role, but kind of backing into what’s—there is no orthodoxy here. What is the best solution to get to the business answer in the best possible way? And, you know, ‘best’ can—it shifts the definition of what that is. Sometimes it is price. Sometimes it is speed. Always quality is just table stakes. And as all these tools have come on—we’ve both been around the industry about the same amount of time. Right? We’ve seen lots of bright, shiny things, some that I still think are really interesting, and they’re never—they will never reach scale. You know [laugh]? They—I just don’t see a path where that will ever happen. But they’re kind of cool. Other things that we, we have certainly seen, like behavioral science, right, that the technology has allowed them to reach scalability. Therefore, we get cost and speed efficiencies, and we see the impact over and over again. So I share that perspective. And then along comes AI. Right? [laugh] So what an interesting time to launch a consultancy focused on kind of helping insights organizations, you know, transform and innovate and think through because I think we’re at that other—another inflection point where it’s not just the bright, shiny thing. It is a—it’s a fundamental process change that unlocks lots of other interesting capabilities going forward that can deliver more impact. And we have to rethink some of our assumptions on what that looks like. Where’s your head at? Right? So you’re launching this consultancy in this interesting time. There is a lot of change. It’s happening faster, I think, than any of us anticipated or had experienced in the past. What’s your take now?

So, you know, there’s always the impulse whenever a transformational technology comes along to say that the past is the past, and we’re moving forward now into a completely new world. What was, you know, no longer is. And, you know, now it’s all AI. It’s all something else. AI is a tool just like every other tool that we have in our toolkit. It’s a transformational tool. It’s a tool that is going to have far reaching ramifications, not just on the insights industry, but on our marketing partners, on our companies, on the entire, you know, economy. So insights is not the only discipline that is grappling with what do we do with AI. It’s a set of enablers that I think really unlock the potential of the insights function in ways that we haven’t been able to before. So when you think about insights, insights is, you know, sometimes thought of as being slow. You know, you got to go out and field research. It takes a while. We have all this past research. How do we dig through that? So AI really—and I’m going to talk on the client side now. You know, certainly on the supplier side, AI is massive key to efficiency, to reduce time and cost and workflows and things like that. On the client side, AI is really the key for us to change the way that we spend—the balance of the way that we spend our time in ways that will be massively beneficial to the business. So let’s take just, like, a step back a couple years and think about DIY. Right? I think DIY is a terrific set of tools when you can implement them. What a lot of client side companies have found is that they’re not structured or staffed to really do DIY in-house in a very impactful way because, you know, you’ll have a band of director level people who, you know, will be dedicated to business lines, and you need them to spend their time with the business. You need them to bring the consumer, to bring the empathy for the consumer into the business. You can’t also expect them to go off and be programming Qualtrics surveys on their own in their free time, and then analyzing all that and then bringing that in and presenting it to the president of the division with strong, solid recommendations. So, you know, that technology, I would say, didn’t really fully realize its potential on the client side because of how we tend to be structured and staffed. AI, fast forward now, has the promise of cutting out a lot of those steps that it takes. So you’re shortcutting a lot of that work that nobody really had time to do anyway: getting to answers faster, really mining what we already know in a very fast, impactful way. You’re cutting out two—instead of getting a question and saying, well, I got to get back to you in two weeks. I got to go do this meta analysis, and I got to find all this stuff. And, you know, it might be in four different SharePoint drives. It’s going to make it so much easier within an hour for us to have answers and then really shift the balance of our time to thinking about what’s the solution. What is it that we’re telling the business to do based on what it is that we’ve learned. And really rapidly getting to a sense of this is what we know and this is what we don’t know, and so we can structure the right very limited scope research to as quickly and efficiently go out and get the answers that we don’t know. And maybe that answer comes from synthetic respondents, and so it’s almost instantaneous, or maybe, you know, we have a basis to have the AI write 75 percent of a survey for us. So it’s really going to make us much more impactful and let us spend more time solving the business’s problems, which is, I think, something that we’ve perhaps gotten away from a little bit in the insights functions, as we’ve just kind of been immersed in so many different things that lead us to be more research managers than, you know, business strategists. So to me, AI, the promise of it is make that shift, you know, finally from primary focus on being research managers to being business strategists, provocateurs, and really not just answering questions for the business, but telling the business what questions they should be asking.

Could not agree with you more. Although, I do have a slight concern, and I think I know why I shouldn’t be concerned. But here’s the concern. The DIY, I totally get it. Automation, a little bit different, right, in terms of the client side option, in terms of all you have to do is push the button type of thing. And for years on GRIT, we were tracking a day in the life, right, and that’s what we were looking for. We were looking for that shift in how people were spending their day. And all through the last—let’s call it last five, six years, right, the automation bloom in the industry, we never saw it. We just saw people doing more of the same thing. So we saw a bandwidth increase of doing more projects but not changing—fundamentally changing how they were spending their day. Now that said—I think that it didn’t occur to me until right now as you were talking. I think the limiting factor there was that so much of automation was around fairly tactical issues to begin with, so they were more throughput oriented. Right? We can’t do twice as many of these things because they’re tactical, and we didn’t see a real shift in the strategic aspect. I do think that is what AI unlocks now is a lot more flexibility in terms of the workflow and inefficiencies on workflow and potentially unlocking new ways to approach strategic issues with other types of datasets. So we’ll be tracking that going forward in GRIT as well. I suspect you are right. We’re going to now be able to measure that shift, but we hadn’t seen it yet. DIY and automation did not get us there. So we’ll see if this is the great unlock for people to be more focused on the business rather than being in the business.

Yeah, and, you know, I think it’s hard to talk about DIY and agile separate from AI. Like, they’re just so interwoven with each other as enablers. And I think that when you talk about DIY, like phase one DIY, like entry layer is faster, cheaper, and do more stuff. And so it definitely, if you do it in that way, it lends itself to just continuing that role that some insights teams have around just churning projects, like you said. Level two, right, on DIY is really building in the automation and the templating and the standardization. This is how I think about insights. Number one is you need a good knowledge management system. You use the AI tools to do the automatic summaries, to search across all your stuff to tell you, here’s the key themes, and you’re right away in minutes informing your hypotheses, that used to take you two, three weeks; and tells you what you know, what you don’t know, and it helps guide you to where you need to go. Number two then is you need to template and standardize and automate all of your common use cases, even to a point where, you know, the insights teams are building it out with, you know, limited abilities for customization so that the marketers can go and just basically say it’s this category. You know, these are the attributes that I want included. Upload the stimulus, go. It goes into your data set. And then, you know, the insights teams are really focusing on doing analysis across studies, building up the value, again with the AI tools, of that body of knowledge rather than just managing individual tactical projects. Third level, then beyond that, once you have that, is that when you do need to go out and design research—I have sort of like six points, six on my checklist. And not everything is going to be all these, but it’s got to be at least a couple. Then it’s got to be agile. It’s got to be behaviorally based, either behavioral science or capturing an actual behavior. It’s got to be digital, you know, utilizing digital data. Can I get it from social, from e-com data, things that exist already? It’s got to be empathetic. It’s got to be forward looking, not backwards looking. And it’s got to be tech enabled. So that’s then the checklist for when you do need to go out and do custom research beyond the things that you have templated, beyond the things that you know that you can already get using your AI tools and your knowledge management system, then how you go out and think about research on a forward basis.

That’s a great checklist. So we should publish that. You know, “Seth’s six rules for effective research.” So we were chatting before the show on the kind of pace of change, and here’s my take, and tell me your take. Last year it was, whoa, what is this? What is this brave new world we find ourselves in? What is this thing called AI? What? What? This year already shifted into—well, end of last year to this year was, okay, we got it. Now, what does it do for me? Right? What is the business impact? What is the value proposition here? We took the low hanging fruit. You know, the easy thing, synthesizing information, summarization, all of that good stuff, and then quickly started moving into workflow automation. And three months ago, my sense was that there was still—we hadn’t crossed the chasm of adoption. There was still an awful lot of, well, I’m not too sure. And already, literally in the last three months, perhaps even in the last month, a tangible change that we are picking up, which is, okay, we got it. We’re all in. It’s time to really focus on implementation and on early stage. And even a sense, on the supplier side, saying you have AI anymore is like saying you have a steering wheel in your car. Right? I mean, it is now table stakes. There is no differentiation about it. It’s, yeah… and? [laugh] You know, of course you do. What—how is this better to answer my business question, right? That is the focus. So I think there’s been a sea change that has happened literally very quickly in the last few weeks. And my proof points on that—you have some perspective from being at a IIEX North America is why we’re recording this. This is the week of IIEX EU, which is a much more skeptical audience traditionally. Right? So our European event has always been the, I don’t know about you Americans and all your tech. Right? So let’s [laugh]… That was not the case. So massive client side engagement, lots of interest, lots of focus on, you know, show me how this is better and an openness to that across the board, which I don’t think was there just a few months ago. So that’s my very long window way of saying my sense is the pace of change is far faster than anything we had ever experienced. And the inertia that the industry has maybe experienced in the past with kind of these sea change shifts, it may still be there, but like everything else, its condensed, and we really are rapidly moving into a whole new world. And my suspicion is that that is mostly because of the need for the insights organization to keep up with other users of research that are outside of the insights organization. And that’s what’s dragging this along. That’s my hypothesis. What do you think?

Yeah, yeah. I mean, not just other users of research, but all other teams internally. So the creative and media teams are using AI tools, for example, with creating all the hundreds and hundreds of pieces, you know, once you get the campaign, creating all the different versions of the marketing copy that go into different platforms and whatnot. And the supply chain and manufacturing teams are using AI to optimize what’s going on in the factories. So OpenAI launched ChatGPT, what, I think it was in October of 2022?

Yeah, late October, early November. Yeah.

you know, we’ve all seen the numbers on adoption of ChatGPT, right, relative to each different technology that had come out before that, and the fastest to 100 million to 500 million, whatever those crazy adoption numbers are. So we’re going through the same thing that everybody else is going through. Right? We’re not unique as a functional discipline. I’ll say that early 2023, when I was leading a client side insights team, I think there was a lot of questions around, what are you doing with AI? What are you doing with AI? And as a client side buyer a year and a half ago, I was very frustrated with what was available for me because nobody had developed the commercialize-able application yet, that—other than building something out custom, you know, if you’re, like, a huge, huge client with tons of data, with a supplier, there just wasn’t AI things that I could go out and even buy a year and a half ago, four or five, even six months after ChatGPT made such a big splash. I think the industry has done a terrific job of moving massively rapidly to build out all of these commercial applications for AI, you know, startups that didn’t exist two years ago. It’s just been a massive transformation of the supplier landscape. By the way, one of the things I looked at Greenbook to really help me navigate the resources that you guys have available—so you can double, double that endorsement check. And so, you know, now I think that there’s things that we can bring into the business in a very tangible way that exist, which just didn’t exist a year and a half ago when there were all these questions around what are you doing. What are you doing? What’s AI going to do? So I think, number one, the fact that it’s become much more concrete to the insight buyer community helps everyone come along that curve much faster because now there are things that people can look at and they can spend an hour with the vendor and say, okay, now I get it. I still got to get under the hood, but I understand, you know, why this is going to be an advantage for my business. I’ll say over the course of the past year, you know, I was at a competing insights conference about a year ago, where I think a lot of the discussion around AI was can we really trust it? What’s behind it? How do we know? This can’t be good. And that was just a year ago, not even maybe eleven and a half months ago. Fast forward to IIEX North America, which I was at in April, and I think it was very much a recognition among all attendees that this is here. This is here to stay. We have an exhibit hall where probably 60 percent of the vendors are, you know, doing things tangibly with AI that we couldn’t do a year ago. Many of the vendors who didn’t exist two years ago. I think that the—there was a noticeable shift in attitude to okay, this is here. It’s probably not going to take my job. And how do I leverage this to do my job in the way that I need to be doing it in 2024, in 2030? And how can we be thinking about what insights teams need to be doing to get themselves set up for that? You know, it’s not just future. The future is here now, the future ways of operating.

Now, we should probably point out too that the old William Gibson quote, “The future is already here. It’s not evenly distributed yet.” There are some brands that are slower to adopt not—and I don’t think it’s because of an unwillingness to. It’s just technical concerns, data privacy, data ownership, you know, those are engineering issues, which are being resolved as we go forward in many of the large brands of the world that have been vocal about we are not doing this yet because were building our own LLM, you know, behind our own walled garden. And as soon as that’s implemented, you know, here we go. The only limiting factors have been broader kind of existential questions, I think to an extent.

Yeah, and, you know, the industry will catch up. You know, the tech providers and the insight platform providers and suppliers will get the right privacy provisions in place, I think. I spent 22 years at consumer healthcare companies, part of larger pharma organizations, more conservative with adopting these kinds of things, more concerned with patient privacy and with things like that. But, you know, those businesses also recognize the value of AI, whether it’s for drug development, clinical trials, mining real world evidence, patient data, things like that. So, you know, everybody’s going to figure it out.

Yeah, absolutely. Absolutely. I think that the arguments for the skeptics are getting smaller and smaller, so there’s not much room there for them to go with that.

Yeah. And look, you know, I think we all need to be realistic. It’s a technology. Everything is a technology. And with every new technology, the questions are, what are we going to do with it? So, you know, nuclear technology is a technology. Are we going to use it to provide clean power? Are we going to use it to make, you know, weapons that can destroy the earth? Same thing with AI. It’s a technology. And the question is what are we going to do with it? How are we going to bring it into the business? And that’s up to us to build the right guardrails. I think we’re starting to learn about what some of the parameters and the things that we need to be concerned with are. And I think accuracy of the input data, to me, number one, far and away, the things around security and privacy. I don’t take it for granted, but I have confidence that the Microsofts and, you know, the tech suppliers of the world are going to put the right tools in place for people to tap into with their APIs and whatnot. So for me it’s really about the quality of the input data and how that affects the outputs and what I can do with it. That I think is the challenge for the insights industry is to make sure that, you know, we’re on top of that.

Agreed. Let’s go to another dimension of this then. So, yeah, tech, what can be automated is going to be automated, and that’s always going to be processes. And so much of the role of researchers has been process driven for a long time, the function. Where now we are looking at this point, kind of as we touched on earlier, that the process is not the driver of value for the role. In my mind, we are finally moving into the point where we can—it becomes really apparent that our job is to understand what questions need to be asked to address the business issue, making sense of those answers, regardless of method, to get to the information, and then the broader implications for the business that can drive more value. So kind of a high level. I think that’s just where we’re shifting into rapidly. Agree? Disagree? Coming from your client side experience, what do you think that the future role looks like for us?

So my philosophy has really shifted over the past, I would say, five years. All of the stuff around methodology and getting to the answers, that’s the inside baseball stuff, right? When you’re an insights team within an organization, your value, your utility, is not judged by how good of a job you do on that. You know, your CMO is not giving you extra points for an elegant research design.

Right? You programmed a hell of a questionnaire, but yeah [laugh]…

Right. So, increasingly, as an insights leader, and I’m not going to downplay this, this is all super important. We got to be doing the right stuff in the right way with the right partners. Hugely important for us to be able to really fulfill our bigger mission, which is that, to me, the job really starts when the proverbial supplier—because there isn’t always a supplier involved—drops the proverbial hundred page PowerPoint deck off on the client’s desk. And then the question is, okay, how do we make sense of this? How do we integrate this with what we already know, with our framework for how we view the consumer? Is there anything in here that challenges, that makes us question our existing assumptions? And how do we turn this into something that the business can act on in a very impactful, meaningful way? So all of this technology stuff—and listen, I love getting under the hood of this stuff just as much as anyone. I still love being hands on, on these platforms when I have the opportunity to do it. But it’s all in service of what the mission of the function is, which is that, you know, the tools are the tools. And that’s great, but we have to move the business. We have to be the ones who illuminate the hidden things, the blind spots, see around corners, see over the horizon, whatever analogy you want to use, to bring the opportunities and challenges to the business and to start them off the path on what we do about that. That’s—at the end of the day, you know, that’s not a technology objective. But everything that we talk about with AI has to be in service of how do we, as insights people, become that, become those people for our organization?

I love that. I just thought of a new C-suite: chief illumination officer.

[laugh].

And, you know, when you said shedding light, that’s—we’re illumination engineers. That’s what we are [laugh]. Let’s see if that catches on.

I like it. I like that even better than prompt engineer [laugh].

Yes, absolutely. Because that’s the mechanistic part. So the illumination is what we bring, what we shed. So putting light in the darkness.

I think that as an insights function, we’ve kind of lost some opportunities that came our way during COVID. During COVID everybody was into insights. What’s going to happen? You know, how is behavior going to change? You know, what’s going to happen a year down the road? When is this going to settle down? What are things going to look like when this settles down? And I think we had the opportunity in that 2020 to ‘22 time frame to really demonstrate the value of an insights function, to say you need insights to show you the way and, know, kind of to be that partner who guides you to the decision. And I think that we didn’t necessarily capitalize on that, you know, sort of temporarily increased prominence in the organization as being really the go to’s. And I think that AI will let us get back to that and really let us build that role for an insights team on a sustainable basis into the future. But right now, I think that insights is really fighting against a relevance challenge, where I think some companies are saying, well, AI is going to just be the answer. You know, do we even need to do all this research? It’s so slow. It’s expensive. Not really sure what to do with the results when I get it back. I think we’re seeing analytics teams kind of on a long term trend basis over the past ten years expanding greatly and becoming very prominent, you know, sort of usually within an insights and analytics organization, but, you know, kind of siloed. So I think that insights teams, which I don’t have the data on it, you might have data—you know, are definitely shrinking over the past 10, 15 years with headcount increases on the analytic side. So there’s absolutely a relevance crisis right now for insights teams. There’s, I think, just that much added pressure on figuring out how we use AI to really actualize what we could be, what we should be, at this point in time.

We might have data on that. I don’t think we’ve looked at it from that perspective. I will talk to Nelson, my partner in crime and data guru, to see if we can actually look at that, because we might. We ask about organizational size. So we could probably get there. I just don’t think we ever thought to look at that. But that’s interesting. So Ray Poynter, for instance, famously, for years has said he envisions a future where the—there is no insight function because it is just spread out across the organization. There is a role, but there’s not a function. Far be for me to challenge Ray on that, although I’m not shy about challenging on other stuff, but I could definitely see it going that way. And maybe to your point that’s already happening. Is that the right read that the relevance of insights will not decrease, an organization will likely only increase, but the relevance of as a insight function will shift because it’s just going to be embedded across the organization?

You know, I think that the structural aspects of that are so particular to an individual organization and how they run the business and how the business is structured, that I think it’s hard to generalize. And you have to do what’s right, what ties to your mission and your organizational objectives. I think, you know, what’s happening in a lot of places now is that the insights teams are getting smaller, but there’s no—and the budgets are shrinking. But because, you know, costs have come down on a lot of the validation, routine type research, fewer people are just asked to do more projects, churn more things. So I’ll say that the org. structures, I think, definitely need to change. You know, first of all, I believe in tightly integrated insights and analytics teams because, you know, it’s almost like a hub and a spoke sort of setup, right? Because you need people who are dedicated to the business and who intimately know the business and the decisions that the business makes. But you also need all these people increasingly with these very specialized competencies now, you know, whether it’s taking in and cleaning data or statistics or programming or things like that. So I’ve seen other org. structures where you have roles that are like insights and strategy or insights and execution, where, you know, you have people who maybe are a little bit removed from the actual execution of the research, but who, you know, kind of can tap into a set of resources as needed for a business challenge, but really their focus is on, you know, being more generalist. And how do I synthesize an understanding of the answer of the consumer and bring that into the business to help them make a decision, you know, activate, push towards an outcome? So I think we’ll be seeing more of that. You know, and what that actually looks like is going to vary on an organization by organization basis.

I want to be conscientious of your time as well as our listeners. What would you wish that I had asked that I didn’t? Something you wanted to make sure we touched on.

Oh, boy. We could probably talk about a lot of things.

[laugh] Yeah.

So I would say some of the things that I’ve talked about. Like, I feel like I bring a very balanced view of the industry based on my perspective. Right? There’s threats. There’s challenges. There’s opportunities. That’s just, like, everything. I think what you didn’t ask me is about what excites me going on in the industry right now. And obviously, we’ve talked about AI probably for about half of our time. And clearly even the casual listener can probably hear that I am optimistic about what AI is going to do for us. You know, and granted, we have a lot to figure out, but, you know, there’s so much in this industry that I’m excited about. There’s so much innovation going on. There’s so many folks out there doing new, interesting things, whether it’s in neuro, whether it’s in behavioral science, whether it’s in, you know, platforms. And I think that right now people are a little bit more focused on AI, AI, AI, you know, kind of to your point that, you know, the steering wheel that you were talking about before. Now saying that you use AI is kind of like saying we use computers in our work.

[laugh] Right.

But the tools are there for insights teams to be able to become that thought provoking business strategist, business partner. And so I am actually more optimistic about the future of insights as a function now than I have ever been in—over the course of my career because the tools are there for us to use now. And things that we’ve always wished that we were able to do are doable now. And I think that it’s really going to take—it’s going to take leadership. It’s going to take discipline. It’s going to take willpower. It’s going to take allies in the CMO office to help us do that. But, you know, I think that if we do this right, then the industry is really, I think, on the verge of some really, really exciting things.

Well, I can’t think of a better place to end the conversation than on that uplifting note. And I agree with you. So I think we’re entering into the golden age of data impact, which means researchers have a strong role to play in shaping that future. So I’m right there with you. Seth, where can people find you?

You can find me at www.finishline-insights.com. There’s a contact form there. Or you can email me, seth@finishline-insights.com.

Okay. Really, really appreciate your time. I hope that we can have you back and talk more about this kind of the inside baseball stuff because it’s still—I still like doing that, and I think you do, too, while also taking the broader view of the league, I guess, to continue that analogy. But thank you so much for your time. I really appreciate it.

Thank you, Lenny. And I’ll just close just exactly on that point that the reason why my business is called Finish Line Insights is because, other than the fact that I’m a runner, big personal passion of mine, is that everything that we’re doing functionally as insights folks has to keep an eye on that finish line. The finish line is how do we become the business partners? How do we have a tangible impact on the business? And so we got to just make sure that we’re planning everything that we’re doing with that finish line in mind.

Oh, absolutely. Thank you. Good circling back around there, Seth. That was a good tie in. So [laugh]… All right, my friend. Thank you so much. I really appreciate it. I want to give a big shout-out to our producer, Natalie—she keeps all the balls in the air; our editor, Big Bad Audio, who makes everything sound better; to our sponsor; and most of all, to our listeners. So thank you for your continued support, for tuning in, and listening to us ramble about things that we think are interesting. And obviously, you do as well, so thanks for that. That’s it for this edition of the Greenberg Podcast. We’ll see you again at the next real soon. Bye-bye.