120 — Polling, Progress, and Pitfalls: An Insights Journey with Angus Reid

Lenny: 00:00:00

Hello, everybody. It’s Lenny Murphy with another edition of the Greenbook Podcast. Thank you so much. Take time out of your busy day to spend it with myself and my guest and kind of continuing on with an informal theme here lately of market research legends. And today we’re going to go a little north of the US border, and I have the pleasure and privilege of talking to Angus Reid. Angus, welcome.

Angus: 00:00:36

Good morning, Lenny. How are you?

Lenny: 00:00:38

I’m doing all right, and it’s great to chat. Now so, I introduce you as a legend. I’ll set context for our listeners. If you have worked in the Canadian research industry, at some point you have probably worked for Angus or for one of his companies. I think it’s safe to say that your influence across the entire Canadian market just cannot be understated. Now, you tell me where I’m right or wrong in that conversation.

Angus: 00:01:04

Well, you know, we—I’ve had sort of three chapters in my career. I’m 76 years old, so, you know, I did my first survey over 50 years ago, actually 55 years ago. So I’m a crusty old guy in this business. But no, we’ve had sort of three goes at it. I used to be a university professor. I’ve got a PhD in sociology and tried that for a number of years, was a tenured professor at one of the Canadian universities. And it’s a little too slow for me. So I decided, in 1979, that I would start up what became Angus Reid Group number one, which we sold Ipsos in 2000 for a record $100 million. So that was a very good deal. And we built that company over 20 years. And we had a fairly significant US operation at the time as well. I hired Eileen Campbell, ex of Millward Brown fame, and she and I have had a variety of associations since then, but we were largely Canadian, and that was sort of number one. We were about a $50 million company. And as I say, really, really did get a very good price at the top of the market for Ipsos. I then got involved with my son Andrew with Vision Critical. Vision Critical, I had a non-compete because of the Ipsos deal. So by 2006, I became CEO of Vision Critical. And we took that from about a $5 million base in ‘06 to about $90 million in ‘13 when I left. So that was a very big run up. And part of the story of Vision Criticals is we had at the time a technology company, but we also had a sister research company. We felt that we were building these things called insight panels, and a lot of clients needed pilots to run them. If we were in the airline business, we were Boeing—oh, maybe not Boeing, maybe Airbus these days—but we were building really good technology. But a lot of the large players don’t want to do-it-yourself. So we had this combo play, and for a while we actually called the research arm Angus Reid Strategies. We decided in about 2010 we would call it Vision Critical everywhere. That association ended for me, at least in about 2014, ‘15. We had a big battle with some early shareholders, some private equity guys who wanted to go one way, I wanted to go another way. They gave me more money than I could really refuse to take. So I said, thank you very much, and moved on. And then, quite to my surprise, in 2019, we got going on three fronts as the Reid family. I said Andrew, my sister Jennifer, started up Rival Technologies, and I started up Angus Reid Group again, only because I have a bunch of colleagues who came to me and said, “Hey… let’s get the band back together one more time.” And we also have a very big research operation. Well, big—growing research operation based in Chicago called Reach3, so we’re not just Canadian. But that Reid family enterprise in five years is doing around $50 million. So it’s been a very good startup, you know, organic all the way. And, you know, I’m having lots of fun at this age. So, yes, I’ve had a lot of involvement in the Canadian market, but also have found some very good colleagues to work with in the US market and indeed internationally.

Lenny: 00:04:24

Sure. And I’ve—for the audience and you know this—but you know, I’ve had the pleasure of being a customer of Vision Critical, early-stage customer in 2005, and then also working with you guys in all the various iterations, a few little consulting gigs here and there. You know, I talk to Andrew and Jen regularly, the Rival Tech stuff. Saw Matt Kleinschmit just a few weeks ago at P&G, had a good chat. So our paths always cross.

Angus: 00:04:51

It’s a small world.

Lenny: 00:04:52

It is a small world.

Angus: 00:04:53

Very small world.

Lenny: 00:04:53

But you have a big footprint [laugh].

Angus: 00:04:58

Exactly. Yeah. No, no, it’s been that—you know, the industry’s changed so much. I mean, the very first survey I did in 1969 as a guy doing my master’s degree, was an in-home, face-to-face survey, where I was the team coordinator up in an unknown place called Churchill, Manitoba, which is up on Hudson’s Bay. And that was my first taste of survey research a la in-home, face-to-face. And we did a lot of that in the early ‘70s, even after I founded my company, because in Canada, long distance telephone rates until sort of the late ‘70s were prohibitive. You could pay—you know, spend a dollar a minute making a call so I had a lot of experience with that. And then we did the transition to telephone, like everyone else, and that was a great play in the ‘80s, early ‘90s, CATI, et cetera. That technology kind of fizzled out, in part because—I remember being on radio shows in the, you know, late, late ‘80s, people would call and say, how come no one ever calls me? And by the late ‘90s, it would be, please stop calling me. I don’t want to talk to you.

Lenny: 00:06:03

[laugh].

Angus: 00:06:03

So we had these massive refusal rates that shot up right across North America, indeed, in most parts of the world. So then we had entered the Internet. So it’s been an interesting time for me to look at how our industry has changed over 50 years of new technology and new challenges.

Lenny: 00:06:22

Yeah. Well, and it seems like, though, my take is that your first love is polling still. Is that true?

Angus: 00:06:33

Well, listen, there is no question that I have personally a desire to get involved in studies that are probing the social, economic, political underbelly of North American society, not just polling in the—I mean, the problem is a lot of people think of polling. They think of horse race polling; what’s happening in the election. You know, that field is so crowded, so full of players, so full of a mixture of very legitimate companies, and then a lot of misfits, and people just want to get their name in the paper. So, you know, that part actually has less interest for me than work on trying to really understand what’s happening in society. We have, you know, across most of the western world, major culture wars underway. The culture war file is an amazing one. And we—as for me, as a sociologist, I find it one of the areas where we can use the tools that we have in front of us to really try to probe deeply and understand what’s happening there. And, you know, hat and other issues—today, we have a massive underclass in, again, across North America that’s having trouble buying a house. That has very different prospects as they look into the future compared to younger people who were around in the ‘60s and ‘70s, where all of those obstacles just didn’t exist. So, yeah. Yes, I have an interest in—I’m a sociologist by training. I have an interest in understanding society. The polling industry as such—is sometimes viewed as the barometer of accuracy. But that’s increasingly difficult because there’s so many players in it, so many aggregators. A lot of the aggregators take every piece of crap and say, “Okay, well, I guess we’ll just add all that together.” And I think that’s really unfortunate because—you know, particularly the online world, you know, anyone can be up and running and saying, they’re running a polling company for the cost of a website on GoDaddy. I mean, it’s pathetic.

Lenny: 00:08:33

Let’s dig into this more since it is an area that you’re passionate about, and I’m a political junkie. I don’t know if you ever knew this. My second job in research—my first job in research was run in a phone room doing customer SAT surveys. My second job in research was with the polling company, with actually Scott Rasmussen was our biggest customer, so Rasmussen Reports. Anyway, so I have the same interest, if not the same background [laugh] as you in understanding—well, too, methodologically, the changes were where we are today. It is harder to get anything close to a random sample, from my perspective. I think it’s really challenging.

Angus: 00:09:14

Exactly. Yeah, I think that’s right.

Lenny: 00:09:16

Secondly, of course, as a business owner, a father, a husband, you know, what the hell is going on in the world, where is it going to go? Because it is rapidly changing. And without any judgment on any of those components—so, listeners, we’re not going to get into a political conversation from that standpoint, but more so the value of the methodology to understand and try to predict where things are going to go. So with all that said, just kind of disclaimer, tell me about how you’re trying to first deal with the methodological issues today to get good samples, et cetera, et cetera. And then we can maybe go into some of the areas that you’re focusing on to try and understand and get a sense of prediction from there. So let’s get into the research geek stuff first. [laugh] So…

Angus: 00:10:07

Well, yeah, I mean, I think that—look, we are pretty much committed to online research. I have a tremendous amount of respect for the folks at YouGov. And indeed, when I got involved with Vision Critical, I popped over to Britain on several occasions. Indeed, I think I’m the guy who introduced Nadine to Doug Rivers and those people who came together back in the early aughts. But I thought that YouGov really was onto something and felt that this is a model that we should be using in Canada, in the US, and elsewhere. So I have a deep commitment to online polling. You know, the challenge is to build a large enough and diverse enough panel that you can extract from that good samples. You know, there’s an old saying in stats that burrs of a feather fly together. And so you need to have, first of all, very geographically diverse samples. I mean, the problem with in-home, face-to-face interviewing is that, you know, for a country like Canada, there may only be 150 sample points for, let’s say, a 1500 survey just because of the cost of sending people out to do a random walk and collect data. And unless you were, you know, a government agency that could spend millions on a single survey, that was what you were faced with. You know, telephone was great because telephone really allowed for a massive level of pixelization of samples. You could have literally 1500 sample points if you wanted if you had the right base of phone numbers. As we move into online, I think that you really have to begin with very good geographically dispersed panels. We have a couple of things that we think are very important. Number one, we never put our panels—we have a panel in US, about 100,000 Americans, and that’s growing by about 20,000 a month. And we have a panel about the same size in Canada. We never put our panels on any routers as a matter of policy. Ever. Ever. Zero. There are some panels. You can join a panel, and you’re getting four surveys a day. We think this is a respondent killer. The biggest single issue today in market research and polling is respondent engagement. And you’re not going to get a respondents to engage and join a panel if you’re going to—unless you’ve got, you know, people in Vietnam doing seven surveys every hour in order to pick up whatever, you know, loose change they can pick up, you have this massive problem. So keeping out of the routers and keeping sort of our panels hermetically sealed as much as possible—and I don’t mean to say that in kind of way that disparages the rest of the industry, but I just know there’s some guys who—and women who easily fall prey to the easy money from taking their empty airline seats and saying, “Well, you know, we’ll put them out to some discount guy.” Well, unfortunately, that’s a killer when it comes to really good, serious panels. Secondly, we really like to pepper about 20 percent of our engagements with our panelists, with social, economic and political stuff. Not so much political stuff, not the Trump versus Biden stuff necessarily, but, you know, some of the issues I just raised before: how they’re feeling about aspects of the culture, how they’re feeling about Israel versus Gaza, how they’re feeling about various countries around the world, how they’re feeling about their own lives. Those are all engaging questions. And I’ve been at this long enough to know that a lot of respondents enjoy getting that kind of service. It’s great to do work for Procter & Gamble on soap, but after a while, if that’s all you’re getting, it can sometimes feel a little boring, and you get a lot of churn. The third thing though that is really important is fraud detection. Fraud is a massive problem in market panels today. We recently spent a lot of money buying sample from a bunch of different suppliers in both Canada and the US and put it through a new product we’ve developed. And this is not advertising the product, but it’s called Survey Sentinel. And basically the problem is this: they used to be able to spot fraud through, you know, response set bias. People just answer everything yes. Or you detect fraud by open ends. Well, a lot of people have sorted their way around that now. So again, if you’ve got, you know, the shop in Vietnam doing these things, they can very quickly add a bunch of BS. AI is a huge problem there. AI can just sort of populate stuff. So you need to have a multilayered defense on fraud. We’ve detected—again not naming any names, but we have done some work in the US recently looking at and buying sample and putting it through Survey Sentinel and finding that about 20 percent of the sample is indeed fraud. And one of the ways you detect fraud—you know, the multilayers I won’t go into huge depth with here—but you need to look for internal inconsistency. You need to look at actual logic breaches. A person who says in one question that they really care deeply about the environment and later on a question that if you really care deeply about the environment, you’d have some different views on, let’s say, the sale of coal to China. Well, if there’s a massive inconsistency there, then obviously there’s something wrong with that respondent. So Survey Sentinel has been a very big feature in terms of trying to prevent this. But—so respondent engagement and honesty are two of the biggest issues that we have to deal with, and they’re not going to go away. AI, yes, AI helps in terms of analyzing open ends. My son and daughter at Rival—I’m actually a big shareholder there as well. AI is a huge productivity booster. There is no question about it. And if you’re doing chat based surveys, it can make them much more realistic. Fabulous. But AI is also a huge threat because of both synthetic surveys and survey fraud.

Lenny: 00:15:52

I couldn’t agree with you more. If our audience could see me, I think I threw my neck out nodding through all of that. But it does bring up an interesting point. I’m a pragmatist at heart, right, and I look at the emergence of these new technologies and think, “okay, this is going to happen. So we’re not going to stop the AI train. So we better figure out where we can use it and what’s fit for purpose.” And obviously, yes, all the productivity enhancement stuff, that’s easy. But we have experienced firsthand, even in the GRIT Report, where somebody trained an AI agent to answer the survey as a research—as a market researcher, and the only way that we detected it was that the open ends were too good. So…

Angus: 00:16:33

Yeah. Yeah, well there—yeah, again, I should—Andrew Grenville, who’s our chief research officer, who I’ve worked with for many decades, has developed Survey Sentinel, and they have some ways of sorting that out, but it’s a much more complex, multiple layered exercise than it used to be—a I said, just, you know, looking at some inconsistencies. But you worry about, you know, clients getting sucked into AI. You know, AI, we’re going to have an interviewer that’s going to sound like a real interviewer that is going to be, in fact, not a real person, but it’s just going to be an AI bot or an AI robot or whatever. So there are a lot of those issues that I think confront us, and, you know, you can have AI talking to AI, for all I know, down the road. So, I mean, I’m not quite sure where it is all going. I do know that there will always be a place for real, live, sentient human beings who are going to talk about their experiences and their preferences. Now, there’s some areas where, whether it’s AI or whether it’s online or telephone or whatever, that are just really difficult. You talk about the forthcoming US presidential election. If you’re in one of the eight to ten swing states, the amount of survey research, the amount of polling being conducted there is so overwhelming. That’s going to be difficult for anyone to be accurate because, you know, the odds of—and I’m not sure if Kentucky is one of those. I suspect not. But you may have to go a little north from there, Lenny. But, you know, the odds of getting a poll in any given week is probably greater than one. That’s a lot of weeks that all add up. So there’s some volume problems when you have so much money in certain areas thrown at polling that makes it very, very difficult for anyone, under any circumstance, to really get it right.

Lenny: 00:18:31

So we could go on and on about the AI stuff, but we’ll leave that for the moment. I actually want to dig in on that. So in 2016, Greenbook and ARF teamed up to do basically a post mortem on the election. And we had several pollsters—and they are traditional pollsters, Ipsos and, you know, all those guys from the news agencies, but we also brought in some folks that use non-traditional methods, social media analytics, for instance, to try and evaluate as—for all the reasons you just said, right, fatigue and bad experience and just lack of engagement overall—mean, like, can’t reach some of the population, they just won’t engage. What would be the alternatives to be able to actually predict outcomes? And I think that the consensus of that conversation, it was like, you know, a half-day panel, was that it was just going to keep on getting more difficult. My belief is that it is far more difficult now than it was in 2016 or in 2020 because of all the things we said, we mentioned, but also just fragmentation of audience, fragmentation, the ability to engage people across the board. I think AI is already—especially search is not reliable because everybody’s moving towards just giving the answers that are needed, and we’re not seeing, you know, patterns of search to try and get an indicator of topics of interest or support. It just seems like it’s really, really hard, right, to have a good read on where the public lies in thinking or feeling about something, by any metric. And I’ll give you actually one more example I saw last week. I don’t know if you saw this, that, that Elon Musk made likes anonymous now on X, and he shared within just 24 hours or so. During that, the number of likes skyrocketed. And my read on that was, well, sure, there’s the—you know, people didn’t want to comment or like things out of—afraid of being judged for whatever reason. So all of these various models or approaches that we have tried to approximate understanding seem very, very hard right now. What is your take? You’re in the trenches. So…

Angus: 00:20:50

Well, you know, I think that, first of all, you’ve got to—I think there is a certain amount of American exceptionalism right now in terms of just the volume of polling. I mean, the more polling that is done in a particular state, you know, Georgia or whatever—and my problem of just the amount of money. Citizens United opened up a massive amount of money, which is unique in the US. And I’m not here to adjudicate one way or the other whether that was good or bad. But the billions that are now spent in election polling in the US, coupled with the very divisive—we polled in 2016 like everyone else. We had Hillary ahead by two points. Okay. Nationally, actually. Who cares about national polling in the US? They’re largely irrelevant. So I think that it’s possible to look at some of this stuff through only an American eye and say, well, you know, we have these problems. I think some of the problems are related to what I referred to earlier. I also think that there’s a media expectation of precision that frankly doesn’t exist. When you talk to 2,000 people, and I’m trying to extrapolate to 400 million or 300 million, I mean, there are known errors associated with this. All this closest to the PID stuff is a bunch of, in my view, bullshit. I mean, for most polling that’s done worldwide, we do a pretty good job as an industry, notwithstanding the fact there’s some fraud and there’s some characters that are of dubious background who have come into the industry. Broadly speaking, we do well. There’s an election taking place in a week or so, a week and a half, in France, and it’s a really big election because we have the extreme right, you know, looking like it is ascendant, and then we have the left on the other side of that. Well, the amount of polling in France on that will be minuscule compared to the amount of polling in Michigan. I mean, so there really is—so expectations are really over the top. And people get burned for, “oh, well, you missed that by three points.” I mean, the media no longer spends much money on polling because the media is largely broke. We have party pollsters spending, you know, literally millions. So I think the expectations plus volume in certain jurisdictions can really cause a problem. Now, I think that when you were—I mean, for a lot of the issues that we look at, again, outside of the specific question of who you’re going to vote for, there is a lot of good intelligence that comes out of that. I mean, the, you know, where Gen Z and millennials are at with respect to their own personal finances, there’s a tremendous amount of material in that, that I think whether it’s—whether it’s 42 or 46 percent who are really hurting, the story is there’s a lot of people who are really hurting. So I think there’s a lot of runway for people in the polling industry and in market research generally, but particularly for those in the polling industry, to, I think, inform American society and in the sense of global society on what’s going on. When we get into this very unique situation of a super-divided America and a lot of emotion, a lot of money, I think it makes everyone’s trouble trying to predict things a lot more difficult.

Lenny: 00:23:59

Yeah, well, and the line between politics and public policy is, at least here in the US, is nonexistent now. As you said, it’s all culture war. So the shades of gray in that people—that doesn’t sell from a media standpoint, right? So…

Angus: 00:24:15

Well, yeah, no, it is. But although those shades of gray are interesting only because you know, the electoral system, maybe in California, where I spend my winters. I mean, you have a state the size of Canada that one [laugh] percentage point allows someone to take the entire electoral college vote. I mean, this is a, this is a very, very different situation. So, but I think that, you know, I worry that the American media—which is, by the way, you know, is the world’s leading media. I suppose there’s also some good stories out of Britain. But that the disparagement of the polling industry, I think, fails to recognize the very unique situation that we’re in today, which I don’t think is going to continue forever. I think that the kind of divisions—hopefully, the kinds of deep divisions that we see now are, you know, going to be viewed at some point as a bit of a historical blip, but we’ll see.

Lenny: 00:25:07

So do you ever—I’m sure you’ve thought about this or experienced it yourself, of the concern of the lack of trust or disparagement around polling, having a blowback effect around commercial research as well. Is that something you’re currently concerned about, or do you think we’ve dealt with it for 50 years; it’ll be okay?

Angus: 00:25:28

Well, you know, I think the blowback is everywhere. There was a very good piece in The Economist recently, which looked at established government polling on things ranging from the consumer price index to other areas where governments survey people. And even there, there is a crisis. So, yes, in what we’re seeing in polling exists everywhere, and that is, how do you engage with a proper audience? I mean, in market research, in commercial research, there is a bit of a crisis going on in tracking. Because people are looking at tracking data and they’re not quite sure. “Well, is this really—you know, is this 10 percent increase or drop, is this really because my advertising worked or didn’t work? Or is it because someone changed suppliers out of their grand constellation of how we pull things together? “ Because so many firms now aren’t building their own panels. They’re simply using aggregators or in some cases even using the river. And so I think that these issues exist everywhere. I think that the smart research buyers are doing one of two things. They’re going increasingly to qualitative, where they know for sure they’re looking at real, live people. You can do online qualitative. And sorry, AI is not quite good enough yet to put Lenny Murphy’s face as a person around the virtual table commenting on things. Maybe in 20 years, Lenny, but we’ll worry about that then. So I think there’s that. And then I think the other side of it—and this sounds like I’m pressing the insight community side, but, you know, we’ve gone through, I think, a bit of a change in insight communities. We got in that business. We formed that business at Vision Critical in the early aughts. I think that there’s a lot of competition that’s come in now. I think that there’s customers and companies that are saying, “hey… I can be sure. If I’m using my customer list and if I’m using some of the known sources of respondents, where I can really dig deep, I’m going to have people take a picture of the QR code in a package that was sent to them. And then I’m going to panel them up so I can ask future questions.” There, I’m dealing with a known, true group of people who I can engage with. So I think that the crisis, if there is one, or the problems, exist more at the market panel level and the broad market level, where I think it’s very frustrating to be a customer of polling or a customer of market research to say, okay, am I getting good data?

Lenny: 00:27:57

Well, the most recent GRIT data agrees with you, 100 percent. Right? We asked that question in the report we just released a couple of weeks ago.

Angus: 00:28:05

Sample, sample source is right at the top the last time I looked at the GRIT Report.

Lenny: 00:28:08

Yeah, yeah. And folks are—so what are we asking? What are you doing about it is the follow-up question and the exploring alternative sources, building own panels/communities. Absolutely. And I do think that the—your point on qual is interesting as well. Because that is one of the benefits of AI is this ability simply to ingest and analyze information more effectively. So how we think about qual as a group? Well, there’s really nothing preventing us from having a qualitative interview with 1,000 people. That can be done, and is being done.

Angus: 00:28:41

And at Rival, we’ve developed some tools which allow you to take open ends and use AI to dig deeper in the open ends. So, you know, did the package arrive? And it’s not that hard to set it up so that then the person says, “No, it was damaged.” And then, you know, the AI response, “I’m really sorry to hear that. How was it damaged?” I mean, so in other words, I think that’s the positive side of AI. The efficiency, the ability to go, you know, to really go deeper is wonderful. But yeah—there’s like everything else, there’s kind of a yang and a yang to this.

Lenny: 00:29:14

Well, and I think the brands are also recognizing—and they’ve always known it. But I think now the advent of AI has brought that sharply into focus for them, that data is an asset, and it is an asset that does give them competitive advantage, and they’re investing appropriately. I mean, we see stories coming out now weekly of the major investments by, you know, P&G and Coke and Unilever and, you know, all of those folks on developing their own LLMs, not relying upon what’s out there. And leveraging one of the training sets is research data. And I think that we get to the point—I want to circle back around because you mentioned this earlier—that I’ve been using the term last-mile data a lot for this concept of. Sure, is there—you’re P&G. You’re sitting on a ton of information. Right? And as you go through this, can you ask fewer questions on pretty basic things around, you know, brand perception, whatever the case may be? You’ve been running this ad campaign for two years. You know, do you really need to ask this? No, you’ve got a good density of information about it, fine, in that synthetic sample from that standpoint, internally. Okay, but now you want to do something new. We want to change something. Well, we need to ask more questions. We need to ask what we don’t know about. And that will always be the driver of insights, as you said. Right? The need to be able to connect people to other people that want to get their information. And we do that as efficiently as we can, and the quality will just become more and more important overall. And I think that’s a good thing. I think we hit the bottom of cheap and fast sample. I think we’re coming out of that now, that there’s a recognition that maybe our cost savings need to come through process on the back end, not through by giving people, you know, a quarter for 20 minutes of their time. [laugh] So…

Angus: 00:31:10

Yeah. And even 20 minutes of your time is—I mean, one of the issues, the biggest issue that we have with clients—no, no naming of names—is that there’s a lot of clients that are still living in a wrong age. When I did in-home, face-to-face interviews, you know, which I did myself. Just as you had your background, I had mine in this industry. It was great because it—you know, you take three months to actually design a survey because you’re going to sit in someone’s home, and since you’re in there, you’re going to sit there for 45 minutes. But, you know, these long surveys are—the amount of repetition there’s—I don’t know it. Trying to get clients to understand that you can do things differently and that you’re going to lose engagement. I know that sounds like an old, hackneyed expression, but, you know, it remains relatively true. I think the problem that a lot of marketers have today is that the age of advertising has totally changed. I mean, Millward Brown, Eileen Campbell, my very good friend, used to run it there. Their specialty was doing advertising tracking over time. Guess what? Certainly outside of the G7, television advertising itself is largely dead. I mean, streaming services have taken over. So, yes, you’re into social media. You’re into events. My friends at Reach3 have developed a new product called BXP, which is an attempt to analyze events and say how—you know, a lot of the focus of advertising now is on events, in the moment research, and those become—so the whole reality of how end clients reach their customers has changed dramatically. The industry, to some extent, has not caught up with those changes. And I think there is—in terms of technology, everyone runs around with a hair on fire about AI. I think there’s more than AI in terms of doing the catch up. And that catch up is understanding where clients are at today, which is more in the moment, much more social media, you know, and this whole problem of trying to have verified clients or verified respondents.

Lenny: 00:33:14

Yeah, I think that the best summary is Marc Pritchard of P&G’s famous quote, right, their desire is to have a one-to-one relationship in real time with every person on the planet. Okay.

Angus: 00:33:26

[laugh].

Lenny: 00:33:26

I think that sums up the goal of every marketer in the world, right, within their organization. So now how do we do that? Right? What is the role that research plays and all the different dimensions of that? And we don’t play a role across the board, but we do play a fundamental role.

Angus: 00:33:43

You know, and I think that’s where that—in playing that role, it’s always been my philosophy that we have to bring to clients accommodation of audience, which is panel. We’ve got to bring them technology, which, you know, we’ve talked about has changed a lot. We’ve got to bring them expertise, really smart people who are able to look around corners and go toe to toe with clients on stupid things that clients want to do and innovate.

Lenny: 00:34:06

[laugh].

Angus: 00:34:06

But we also need to bring knowledge.

Lenny: 00:34:08

I couldn’t agree more with you, Angus, of course, on so many of these topics. And you and I could go on, on for a long time about this, and I hope that we get the chance to talk again soon. Let’s start moving towards being aware of your time as well as the audience. What are you looking forward to? What’s coming up as you think about the year ahead? What’s got you excited?

Angus: 00:34:27

Well, I think for us, we’ve been on a very good growth plane, as I say, five years going from zero to 50 million across the three companies has been exciting, somewhat unexpected, actually, but it really deals with those four pillars of panel technology, expertise and knowledge. So we want to continue with that mix. We think that that’s a very good cocktail, if you will, for an industry that’s looking for new ideas. So we want to continue to press that forward. We’re going to be launching a very aggressive program of what I would call sociological, economic, less political. Obviously, we’ll do some things on the political front, but we want to really start looking more in depth at American society. You know, one of my directors years ago was Dan Yankelovich. And Dan was, you know, such a bright, intuitive individual who really came from an era when the media and others used polling to understand what was happening in America. I mean, at the time that we had student riots, we had a whole ‘60s generation coming of age with different views and attitudes, et cetera. We have to figure out how to start moving back to that, to really, really understanding. That kind of turns my crank to the point that I started something called Angus Reid Institute, which is a not-for-profit Canadian foundation that does work across North America. I funded that with some of my own resources as my own sandbox. So I’m enjoying that at my age and stage the opportunity to say, look, I want to look at issue X, and we’ll just go out and do it. I mean, you know, we’ve just finished some work in both countries looking at student protests, and, you know, I’ve got data from the 1960s on student protests. Well, we got student protests now as well. There’s a lot of controversy around it. Let’s find out what people think. And you’re right, some of that maybe crosses over the political side of things, but some of it just deals in a sui generis kind of way with what is the role of student protests? Students have always protested. So that turns my crank. The growth of our businesses obviously— continues to be phenomenal. We want to take this up in the next three years to $100 million enterprise. And who knows? You know, I tend to sell companies rather than keep them [laugh].

Lenny: 00:36:45

[laugh].

Angus: 00:36:45

You know, I turn over my old pairs of jeans every ten years. But I’ve been really amazed at being able to work with some colleagues, in some cases, going back 35 years. We’ve got, you know, Gary Bennewies, who was the head of HR for Ipsos Worldwide, first worked with me when he was 27 years old. Well, he’s now in his ‘60s, and he’s a director over at Rival Group. So that, you know, being—having a chance to work with some of the people who have been around for a long time. Lenny, you’ve been around for a long time in this industry, and there’s a generation of us that over the next decade, hopefully longer, will have a chance to reflect and bring some wisdom to millennials, GenZs, and others who are coming into this industry that maybe need some context. So I find that interesting and frankly a lot of fun working with younger, university graduates who are very interested in market research but don’t have the kind of experience, just in terms of looking at how this industry has changed over time. So that’s frankly a lot of fun.

Lenny: 00:37:47

Yeah, that’s all great. Yes, I realize that I’ve now been in industry 24 years, and which obviously only half of your time, but think, yeah, I’d be considered an old timer now. You know [laugh]?

Angus: 00:38:03

[laugh] Well, you’re still pretty young there, Lenny.

Lenny: 00:38:05

Well, yeah, well, but, you know, duration wise, I mean…

Angus: 00:38:10

Yeah.

Lenny: 00:38:10

So it is interesting, and Angus, I wasn’t blown smoke in the beginning when I introduced you as a legend. I think that to your point, it is important that we recognize that we stand on the shoulders of giants, and as we go through this process of transformation, we’re obviously industry continue to evolve. It’s important to me that there’s a through line that folks understand that look, there are some things, all of these things may change, the how’s may change, even the whys may change, but there’s fundamentals that are important, and we need to make sure that that’s being communicated going forward so the profession, if not the industry of insights and analytics, as I call it, just to kind of encapsulate all these things, continues to deliver real value. So I really appreciate you taking the time to kind of share your experience.

Angus: 00:38:58

Listen, it’s great to do it. I would just say that, you know, over the years, the one thing I’ve observed is that, you know, every dictatorship in the world has two things they shut down. The first is journalism. The second is polling. We have a unique role to play in our little industry in terms of holding up a giant mirror in our societies to help people understand what’s happening. Otherwise we have demagogues on one side or the other who want to recreate the reality of American public opinion, whether it’s social, political or economic. And so the fact that we have this, this power to do it is something which is a real gift. And I think that people across our industry, you know, should recognize that and use it carefully.

Lenny: 00:39:42

Could not agree more. We’ll play off this for one more second. I had a conversation with John Kieran two years ago, a private conversation, but I don’t think you’ll object to me sharing this. And we were talking about the nudge units, the development of all the nudge units across governments and the discomfort with that and the recognition—you know, of course, John’s whole focus on, you know, non-conscious measurement and, you know, System One, System Two, and that, yeah, these are dangerous tools and that we do have a responsibility to, I think, to maintain an ethical view and to ensure that our powers are used for good. I’ve had my kids ask me during kind of the darkest periods of 2020, you know, to explain some things that they were seeing. And, like, you know, there’s some folks that may not be—maybe doing some of the things that daddy does for a living, not with the best of intent. And we need to recognize that and be able to help, you know, share that so that we can have a healthy body politic.

Angus: 00:40:48

Absolutely. If you look at Russia today, we have these polls suggesting massive support for Putin. I mean, do we really trust those? No. But I would say that—you know, so the industry does have probably bigger responsibilities. The stakes are bigger than they’ve ever been, and the challenge is also bigger than it’s ever been. And those two things make the future both scary and exciting.

Lenny: 00:41:12

Yeah. Well, on that note [laugh]….

Angus: 00:41:16

[laugh].

Lenny: 00:41:16

Angus, where can people find you?

Angus: 00:41:18

They can find me online, angus@angusreid.com. Len, this has really been a good session. You really are—you have played a really good role as cementing force in our very diverse industry. So it’s great to join you on your podcast here.

Lenny: 00:41:34

Thank you, Angus. I appreciate that. We do what we can do, right? So thank you for taking the time. I want to give a shout-out to our producer, Natalie; our editor, Big Bad Audio; to our sponsor, if we have one this week. I don’t know if we do, but if not, you should be a sponsor. Somebody should be a sponsor. [laugh] And to you, our listeners, we appreciate you taking time out of your day to spend it with us. That’s it for this edition of the Greenbook Podcast. Everybody take care.