66 — The Tapestry of Insights: Embracing Generative AI for the Next Era of Market Research with Larry Friedman

Lenny: 00:00:10

Hello, everybody. Welcome to another edition of the GreenBook Podcast. Thank you for taking time out of your busy day to spend it with us. And, eh, I’m a broken record. I always say the same thing but by us, it means that I do have a guest.

Larry: 00:00:55

Actually, I was thinking I’d like it if my wife could have been listening [crosstalk 00:00:57]—

Lenny: 00:00:59

[laugh]. I know exactly what mean Larry [laugh]. So, Larry Friedman. Larry, welcome to the Greenbook Podcast.

Larry: 00:01:07

Pleasure to be here and talking to you, Lenny. It always has been, always will be. And I very appreciate the things you’ve said.

Lenny: 00:01:13

Well, thank you, sir. You are a gentleman. Now, for those who don’t know you the way that I know you, why don’t you tell the audience a little bit about yourself and your background so they understand why I’m offering such effusive praise overall.

Larry: 00:01:25

Okay. Well, I mean, it’s now nearly—actually, you can say it’s about 50 years since I’ve been a researcher. I got a PhD in Social Psychology from Columbia University in the ’70s, and then, I did a lot of work in pharmaceutical research. Basic research, Psychiatric Research. And then I decided that I needed to go make a living, so I wound up in market research because I thought it was similar to what I was doing, and would provide a living for me.

d to have you on as a guest:: 00:05:21

so we could kind of have that perspective. And you also—and let’s give the shout-out that for quite some time, or at least a, what, a year or two? Something like that—

Larry: 00:05:45

Yeah, it was a couple of years. I forgot to mention that.

Lenny: 00:05:49

Yeah. You are the editor of Greenbook Blog, so you assumed that role when I got pulled in other directions. And we worked really closely together in that. You participated in GRIT, other studies that we’ve done. So, for our audience, I mean, Larry and I have worked together closely within GreenBook, while also having, you know, certainly knowing him from afar through his role as Chief Research Officer at TNS and industry influencer.

Larry: 00:06:13

And I’m still on the GreenBook board, so Lenny has to be nice to me.

Lenny: 00:06:18

[laugh]. Yes, although I would do that anyway. So—

Larry: 00:06:42

Well, you know, see, the thing is—and, you know, I’ve been thinking about this lately and participating in our conversation today—I do—I mean, this was a way obviously, for me to make a living. I mean, let’s be honest about that. But I’ve always been interested in why people do the things they do. That’s why I got a graduate degree in psychology and I got my PhD. So, this is just a continuation of a lifelong passion for me.

Lenny: 00:07:39

I love that, and that’s a great segue, right? So, you and I chatted about this, and let me frame it for the audience kind of my thinking, and then you react to it. You know, the trendline for years has been that technology impacts the who, what, when, where, and how of data, right, that informs the research process. Throughout the years, we had to do more active things to acquire that information, and as technology has progressed, that’s become easier and easier, to the point where often the skills to know how to acquire that information accurately is now to a great extent, supplanted by technology that can do that for us across a variety of data sources.

Larry: 00:09:19

Well, see, I would actually take it, you know, a step further. But before you step further, I think you need to step back a second. I think it’s very natural for us to sort of, you know, do a lot of navel-gazing. You know, we’re looking at our small corner of the business world, and you know, we focus in on that. But what the industry has been dealing with is just one part of the larger digital transformation of business.

Lenny: 00:14:06

Yep, agreed. [I want to say 00:14:07], it’s an eloquent way to put that trend together. And now, I think—see if you agree with this—I think if we look at the chart of history, the trend line of history and the research, you know, there’s been specific points where we saw massive transformation—generally technologically-driven—you know, from face-to-face, door-door to telephone, telephone to web.

Larry: 00:14:32

And I saw all that, and you know, and I saw all the arguments that took place. And when I started in market research, we would still do door-to-door for certain kinds of big important studies.

Lenny: 00:14:44

Which is still done in other countries as well, so let’s acknowledge, we’re not talking about archaic things. There is—all of these tools still exists and are still absolutely in use. It’s they’re just more specialized based on the business issue, which is what it should always—that should always be the—in my mind—the deciding factor. Fit for purpose, right?

Larry: 00:16:31

Well, it’s hard to say right now. I mean, certainly, I mean, there is a huge amount of experimentation going on. And I think that’s great. I mean, we should be experimenting with these kinds of technologies. And I’ve seen how they can be enormously helpful. In one of the companies that I consult for, as you know, is [Converzion 00:16:53], which does, you know, analytics on social media data, and through the use of AI can do some really powerful analytics that were difficult to do before AI—let’s call it—and can be used as predictive models. So, I’ve seen the power of what you can do with AI.

Lenny: 00:19:39

I agree with you one hundred percent. And let me give you an anecdote that was last week. A colleague who’s been exploring these solutions—and I won’t name names, but they’ll know who they are when they’re listening—they had done a large segmentation study in a previous life, right, for a client, and they thought, “What if I could duplicate that only using prompts in ChatGPT?” And long story short, they did. So, this was a half-million dollar, six-month, you know, major strategic project that they got to the same outcome, which was effectively, you know, segmentation of this population, solely using prompts in a series of prompts and discussion with the open version, right, of ChatGPT.

Larry: 00:22:09

This is something that’s been talked about for 10, 12 years or so, with the desire to do something like this.

Lenny: 00:24:28

I share that. This is where we get into the economic components of the industry, right? I mean, the scale-the large companies are effectively production houses, right? And certainly, they are now where the technology companies dominate, if not revenue, certainly valuation, right, and where the money flows for additional investment. Those are process-oriented—these technology companies, they are inherently about production. That is the goal.

Larry: 00:25:50

It has always been that way. In terms of what that means, though, for the future, I see two things or two possibilities. One is that added value becomes part of what the people inside corporations—you know, the teams working on those business issues are the ones who then do that.

Lenny: 00:26:12

Which would not be good news for the supplier community.

Larry: 00:26:15

No, it’s not. And the other one would be even worse. The question I’ve asked myself and I ask other people lately, so why does it now have to be researchers who do this? This is the job for the consultants who can charge a lot of money. That added value point, you’ve got the technology-driven companies—the search companies, let’s call it—who are there whether they are [unintelligible 00:26:40] user, you have these AI systems to help clients extract all these different kinds of information, and analyze and do what your friend or colleague did there. Maybe it’s now the consultants who have the real skill set to take that one step further. Because it’s never been a [strain 00:27:02] for the research companies.

Lenny: 00:27:04

So, you and I collaborated quite a bit in defining the GreenBook’s own proprietary market segmentation model and how we incorporated that into GRIT—and particularly on the idea of strategic consultancies—and remember when we first started asking questions in the way to differentiate between market research companies and strategic consultancies, and how often we saw the engagement levels with those companies, you know, the [McKinseys 00:27:27] and Baines and those guys of the world [laugh] we didn’t hear the full-service companies being mentioned in the same breath very often, right?

Larry: 00:28:47

And I think you’re going to see that accelerate. I think that that’s the one thing that I see happening. So… it’s hard to see where the research—you know, the large research companies, where they go at this point unless they’ve got some real added value that they could bring to the table, which could be knowledge of some specific sectors, there could be, you know, certain kinds of research, technically, are beyond, you know, the consultancies. So, unless they’ve got something that they can uniquely bring to the table, this sort of regular analysis that was the bread and butter for full-service market research companies, I think a lot of that has the potential to go away. And fairly rapidly, depending upon how well some of these things with AI actually prove out.

Lenny: 00:29:44

The other component I would add to that as that—you know, would be, you know, specialization, niche business issue, or sector specialization, or what I call data currency. MillerBrown, Nielsen, IRI, right? I mean, these you know, these standards, these normative databases that are highly—that within organizations, really function as currency. “What’s our Nielsen rating?” Right? It’s kind of the typical example.

Larry: 00:30:06

Well, all that is changing rapidly, so—

Lenny: 00:30:10

Yes, it is. Because people don’t want to be held captive and they’re looking at different solutions now. So, do you envision—just hypothetically, right, just throwing out names—do you think we’ll see… you know, McKinsey by Ipsos? That type of mashup?

Larry: 00:30:25

I don’t see why they would want to.

Lenny: 00:30:28

[laugh]. Oh… oh—

Larry: 00:30:35

No, no, no. You could have said the same thing about any company.

Lenny: 00:30:36

Right. Right.

Larry: 00:30:37

I mean, if anything, you know, maybe they would buy… I mean, Qualtrics is out there again, you know? Or [unintelligible 00:30:44] or somebody else, you know? I mean, if they had the technology platform to build on, that might be interesting for them. But maybe not, you know? I don’t see why they would want to buy, you know, a large, full-service market research company.

Lenny: 00:31:11

Right. Yeah, as an example. Well, and here’s another wrinkle we’ve talked about for years and thought we would see it happen, and now we are, which is a brand that we would think of who has a tremendous amount of data assets, they have a large audience, they have access to lots of information now launching direct bespoke research solutions. And acquiring. So, I mean, I am aware of companies sniffing around—you know, companies we think of as brands, sniffing around to acquire research technology companies—not service companies—but technology companies to incorporate into what is both an internal customer-focused solution as well as an external solution. We’ve seen hints of that over the years, but there are multiple, very large, large, large, especially retailers, that all seem to be moving in that direction, or sending pretty strong signals of doing that.

See, I think, [unintelligible: 00:32:40

integrate different kinds of information, focus on business issues. You could probably have a lot more impact there than you could on the supplier side.

Lenny: 00:33:12

So, as we think about examples of brands that have very—because this isn’t a new concept, right? That there are brands who have basically internal research operations within the organization. So, 3M comes to mind, Novartis, I mean, heck, even P&G.

at was part of the training:: 00:33:32

you worked for their internal supplier.

Lenny: 00:33:40

Yeah. I mean, all the signs are there during that as well. My only question then—and maybe this is the role of this strategy consultancies is when they want to get that strong second opinion, right, to make sure that they’re not drinking their own Kool-Aid, so to speak and introduce bias. You and I—and audience, Larry and I can go off for a long time talking about this stuff. We’ve had lengthy hours and hours long conversations; I want to be conscious of our time and what our listeners [laugh] can put up with—so we started out thinking about the industry shifting to answering the question, “Why?” and, “Now, what?” And we’ve kind of gone through all of the factors that kind of drive us there, including some of the potential downsides.

Larry: 00:35:00

Well, I think a lot of the limitations that I had to deal with early in my career were constraints, rather. And a lot of—all these things we’ve been talking about, take a lot of those constraints away, you know? It used to be that you couldn’t really use old data together with new data to address a problem. Because research companies made their money on collecting new data and doing stuff with it. You were discouraged from reanalyzing, even, you know, the new data on a survey that you just did, if you thought, “Gee, you know, maybe if I break the data this way instead of that other way, I could learn a lot more.”

Lenny: 00:37:52

That is a great point.

Larry: 00:37:55

So, there was a—God help us—a young Larry Friedman getting out of graduate school, could have a better career now than what I had. [unintelligible 00:38:03] I got—you know, I had a good career, but you could do even more now. But as you said, Lenny, you know, the structures are going to be different, what a research community is like, whether it’s within a large organization like a P&G or whatever, or in these things we used to think of as research suppliers and research companies, all that’s going to change for what it’s historically done. But there I—I think you could have a great career.

ly, what I [try to instill in: 00:38:42

learn the skills that you need to be able to make a positive impact in the world and, you know, we can ride the changes. So hopefully, that’ll play out.

Larry: 00:39:08

Yeah. Well, I think it’s more than just riding the changes. I think they could be exploited in a way that are good for people, you know, in whatever—however you want to call this industry, as well as certainly for the brands and companies that we do all this for.

Lenny: 00:39:25

Yeah. All right. Larry, it is always an honor and a privilege and a pleasure to talk to you.

Larry: 00:39:31

Well, thank you. It’s always fun. We’ll talk. And people listening, I look forward to speaking to people at IIEX. I’ll be there.