The AI Takeover, Gen Z's Impact, and the Evolution of Research

Check out the full episode below! Enjoy the Exchange? Don't forget to tune in live Friday at 12 pm EST on the Greenbook LinkedIn and Youtube Channel!

In this episode, Karen Lynch and Lenny Murphy dive into the latest market research trends, starting with insights from the Grit Forum, where fostering audience engagement and sparking critical thinking took center stage. They explore the game-changing acquisition of Hazy by SAS, which promises to revolutionize AI and synthetic data use. From the bold cultural impact of Gen Z to new challengers like Perplexity shaking up Google’s search dominance, the conversation is packed with fresh perspectives.

Plus, they tackle Spotify’s AI DJ, flawed polling methods, and why critical thinking is the secret sauce for staying ahead in the fast-evolving insights world.

Many thanks to our producer, Karley Dartouzos.  

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Transcript 

Karen Lynch: We're already oh no now we are There we are. It's so funny because when I did a um, I did that webinar this week I still had the or or the grit forum and I was still like wait Are we live like I still had that same feeling because apparently that's become a habit now to say wait are we live?

Lenny Murphy: Which by the way and I will say this publicly for those who don't know I was supposed to do the grit forum and I couldn't because my neuro crap flared up Karen jumped into the gap And I've heard nothing but wonderful things was on a call with Laura from Recollective, just so complimentary. And so you rock and everybody knows it and they see it. Oh, thank you.

Karen Lynch: I will never turn down a compliment. I will always say, thank you, graciously accept. But the reality is, is, you know, I enjoy, I enjoy the interviewing, the commentaries, they were great. I loved every minute of those conversations because I, you know, at my core, I love having conversations with people. So that is- No you don't.

Lenny Murphy: What are you talking about?

Karen Lynch: What? Well, shall we say I love having some conversations with people.

Lenny Murphy: I know exactly what you mean.

Karen Lynch: Anyway, my point is, Nelson also really did a great job presenting the data that he lives and breathes. He did. And so I think it was a great opportunity for him to speak. And also, what I really appreciated about that was, you know, and he had shared that he was going to say that in advance, and I said, I think it's great. But the idea that like, look, we put out these hypotheses, we really encourage people to do their own critical thinking and kind of wrangling of this data. And he enjoys and shares like this, let's discuss the findings, let's discuss what we're learning, go ahead and, and contradict us. And I don't know, just make it like a living, breathing report.

Lenny Murphy: So I really liked that point of view that he brought to that conversation so and for our audience so Karley probably don't have this but I'm going to copy a link and I'm going to send it Karley in our exchange so people can still register by our standard register to to watch this was our grit forum going through all the results really great way to kind of condense and synthesize all of that and Karley here I'll pop it

Karen Lynch: Into our, yeah, because I did have somebody else say that they, or two other people actually, uh, you know, somewhere on LinkedIn, somewhere on LinkedIn and say, wait, I missed it. And I'm like, oh, you can still watch it. So yeah, you can watch it on demand, get caught up. Um, uh, you know, a bunch of, uh, a bunch of really cool trends in there and things that we're tracking.

Lenny Murphy: So anyway, great stuff. All right. And we're in our two week cadence now. And we had got, we were just talking for you guys to get on here. Uh, here's the trade-off we're learning is the news doesn't stop. There's a ton of stuff, but we don't have time to go through two weeks worth of links. So we're still trying to work this out, everybody, and the right way to do this, to have a condensed version of a curated discussion. But just tell you, there's a lot left on the cutting room floor. Yeah, and I really would.

Karen Lynch: I think this is a great time for us to say, please give us feedback. Please email Lenny and I at the exchange at greenbook.org and say, every other week is fine. To, you know, like we can handle it, or we really like this every week. Like, I think we might need some consumer or customer input, audience input before we make this decision, because there's pros and cons to a different cadence that we're dealing with. We will not be here next Friday because we will be with our respective families, you know, feeling all the gratitude that we have for their existence.

Lenny Murphy: Or shopping.

Karen Lynch: You know what? Black Friday. I know you'll be talking about Black Friday right now. We didn't even get to that in Black Friday, Trent. I have a daughter who really likes to get out there. And I have had years when I have indulged her once she became old enough to be like, OK, fine, we'll go out at midnight. And those were some of the most tiring of my life.

Lenny Murphy: I like clicking the button.

Karen Lynch: Yeah, I like clicking the button. Exactly. So we will talk to you after the fact, maybe we'll find out how this, how this day, um, you know, compared to years past is, you know, what's, what's the shopping trends as we kick into the holiday season, when we get back.

Lenny Murphy: So anyway, but in advance, happy Thanksgiving, y'all. Happy Thanksgiving, everybody. Yes. And we will not be, not be here, but let's dive into the, the, the squished, the squished down version of, uh, version.

Karen Lynch: Yeah. So, you know, know, some of these are in no particular order here. But I don't even know, SAS acquired a synthetic data specialist hazy. So we're going to start with that one. Because synthetic data, I don't know how you know, when I kept looking at this, I was like, we really have to talk about this. Because, you know, again, back to back to our horse. We're at the synthetic, like we're already here, you know, we might have been talking about it. Is it a good thing? Is it a bad thing? Here we are, right? Like, it's a thing. So SAS acquired synthetic data specialist hazy to bolster its AI applications and enhance synthetic data capabilities. So big providers are making a move in that space. Yeah.

Lenny Murphy: I mean, remember the hypothesis when SES bought Qualtrics was to connect all of their kind of enterprise level data, customer data to the CX data of Qualtrics and AI didn't exist then. It probably would have that a hell of a lot easier if it happened then. But this kind of AI, right? This kind of AI. Right. This type of AI, yes. So, but that, yes, they sit on a lot of data, not necessarily the type of data that we think about within the research space. But lots of data flows. And yes, building, building synthetic data profiles off of buyers for instance, that's powered by SAS? Yes, absolutely. Why wouldn't they be doing that?

Karen Lynch: It's going to enable better, better, better modeling, right? So better modeling of the synthetic people profiles, you know, whatever they are. But if the modeling gets better than that, that methodology becomes stronger and more credible. And, you know, less, less kind of compromise of integrity, which is really, you know, if we, if we get to data integrity, like, this is going to be a very interesting space to watch.

Lenny Murphy: So, yep. Yep. I did not beat that horse too much, but it was just an interesting point in a conversation earlier this week, um, where somebody, uh, somebody said, we need a better term, the synthetic sample, because that idea is that it's not necessarily based. Their perception was a synthetic sample meaning it's not based on real individualized consumer data. Um, I, I personally don't, didn't see it that way, but it was, uh, it was a good thing to, to recognize. I would say that this is an example, you know, of, uh, what is doing is off of real data. So if we're calling a synthetic sample, fine, maybe we just need different shit, the differentiate, uh, between synthetic sample that's based on, uh, just amassing general data, like through, you know, through chat, UBT, versus purpose built off of real, real data, individual level data records.

Karen Lynch: Yeah, because there's something about the the word, the word lover in me is like, rolling around the semantics right now, there's something about synthetic that if we think about, like, oh, well, there's, you know, there's synthetic materials, which are fake and manufactured to act like, so I understand connection and the use case, but also there is something else that we might need that makes it a little less fake and more based on a true story.

Lenny Murphy: Yes. So, um, yeah, our friends at Brock's have been calling that shadow sample. Um, you know, cool term, not sure that I particularly, yeah.

Karen Lynch: Which means brings you to darkness and is it right?

Lenny Murphy: Right.

Karen Lynch: It's like, Oh, my shadow self, you know, to tell y'all, but, um, Yeah, let's find the right word. So again, talk amongst yourselves, talk amongst yourselves, find the right word, send it to Lenny and I, say, this is the word, let's change the word.

Lenny Murphy: So anyway, but cool stuff. Yeah, absolutely.

Karen Lynch: I just think we should talk about the Kantar Media, you know, that was actually both, I think we have one from either MRWeb that we're sharing the link of, but it was also on, you know, Research Live and, you know, making its, making its way across the industry also. And I feel like this, this potential sale, right? And I think there's private equity, you know, if you read that, read the, click on the link, private equity firms are showing interest in a billion dollar deal here. You know, I think it, it, it points to things that we also would be paying attention to, right? Yes.

Lenny Murphy: And I, I mean, we, this is, this was kind of positioned in the article as like a new thing for sale again. No, they've been for sale. Um, the, uh, what's more interesting to me is one private equity, uh, is flowing private equity money is flowing. Uh, they are showing a lot of interest in the space and large assets like our media, um, is specifically large data assets like Cantor media. Uh, so that's the, that's where I kind of clued in, uh, is that there's, you know, uh, if you own a data asset, and that data asset can drive more value and be monetized in new ways, private equity money is looking at how to build new solutions off of that. So I think it's just indicative of the trends overall in the industry. We just see it at the big guys first, because, you know, you guys don't know this, like that, you're trying to get money, it's easier to get a billion dollars than to get a million dollars. Literally. Your lips to God's ears.

Karen Lynch: I know. Boy, I wish I could experience that.

Lenny Murphy: Right, exactly.

Karen Lynch: Yeah, they're just looking at large enterprises.

Lenny Murphy: We'll see more of that as we head into, there may be a couple of deals squeaked through before the end of the year. More likely we'll see a lot of activity like this in Q1.

Karen Lynch: Yeah, pretty cool. All right. Speaking of things like this, the changes which have to do with, you know, sales and acquisitions and all the other stuff, you know, QuestionPro, a valued partner, of course, just partnered with Thematic to offer their, like, customer feedback analytics platform with QuestionPro's survey platform, right? So we've got, we've now got that same sort of thing that you and I were talking about for weeks now, which is, you know, a melding of the skill sets to be able to be more comprehensive. So, hats off for that partnership. Question problem thematic, you know?

Lenny Murphy: Absolutely. And shout out to Vivek and his team. I mean, they've been doing this, building out this enterprise grade platform that does so many things for years. Quant, Qual, and all these different capabilities. So it's pretty cool to see, to see that happening where they want to be the hub.

Karen Lynch: Yeah. Yeah. So, yeah. Specifically when it comes to customer feedback, which, you know, segue, segue, segue into more customers, you know, customer feedback, customer experience. You know, we, you know, kind of one of the articles that came up in the last two weeks was about in-moment launching the CX industry's first AI powered journey insights tool. So, you know, whether it's first, but what there's, you know, we don't know, but what they're talking about is what I found interesting, Lenny, is this integrated experience experience improvement or XI solution. So now we have another X acronym in the mix. Hold on, XI, I haven't heard of that yet. You know, and maybe that's just them differentiating themselves about, you know, what, what do we call experience management and what does Qualtrics own and blah, blah, all that stuff. But what was cool is their, their, their approach is journey specific, not pill, not a pillar division, not channel, whatever you call that. It's not like customer service has this and your marketing has this and blah, blah, blah. You know, it's, it's based on the journey and where they are, where the customer actually is. So it actually makes some logical sense. It's about their journey, not our division of pillars across our industry. So anyway, I just thought that was kind of cool and a new way of looking at it.

Lenny Murphy: So kudos to that launch. Yeah. Yeah. I love that. Taking the holistic view. Um, that's fantastic.

Karen Lynch: So, uh, yeah, go, go, go ahead.

Lenny Murphy: Yeah, so our friends at Material, Material Spotlight, Agile Insights product. What's interesting is Material has always firmly been on the strategy consultancy side of things. So this makes me think of back when McKinsey launched McKinsey Periscope many years ago. We have these companies that take on larger, more strategic positioning and projects and now, you know, continuing the trend of how different projects can become more efficient, because of technology, they don't want to lose that revenue. So they're kind of shifting their business to be able to capture a larger share of potentially larger share wallets. Even though it's a smaller revenue type of projects, by leveraging their tech, it is very, very smart to do that. I think Ipsos has done it, you know, I mean, all of these companies continue to kind of find a balance between full service strategy consulting and automation of kind of just lower, just easier things that lend themselves towards automation. So, yeah.

Karen Lynch: One of the things I liked in this is that if you click on the, again, I'm pointing over to my other screen, where I have stuff. But like, if you click on the, if you click on the article over there, you know, or on your own browser, and you look at it, one of the things they talk about is recommending first reporting, that meets real time sensitive business needs. And I really, I love it when a phrase hits me, as we've discussed earlier today, but recommend first reporting. I imagine that a lot of people have done things like that, like, you know, you speak to you speak to the objectives, or you meet the business questions first. But I really like this, I don't know, I just liked that language of recommendation first reporting, because boy, does that just hone in on a different way of looking at a strategic report for a research initiative. Anyway, hats off to them. You may not be the only ones to say it, but you were the first ones to say it in that way, that it landed with me in this way, and I think that's kind of cool, and I would look into it for that specifically. Like, all right, you're giving me that consultant information first. Like, hey, yeah, we'll tell you what we did, but first we're going to tell you what to do, which I thought was pretty cool.

Lenny Murphy: Good call out. Good call out. Yep. Very cool. Yeah. Talking about morning consult. It's almost no offense. These next couple of ones kind of like, yeah, they're out on AI.

Karen Lynch: Yeah, yeah. I know. I know. I mean, no offense, guys. But it's true.

Lenny Murphy: It's true, right? Yeah. I mean, it's that you're waiting to see these companies like doing this morning Morning Consult, the Morning Consult AI, help users unlock smarter, faster insights from their proprietary data. Morning Consult sits on a butt ton of data. They do lots of brand tracking. They do political polling. They do lots of stuff. And yeah, unlocking more value creation out of that. So I think more companies are doing those types of things because it just makes sense.

Karen Lynch: Yeah, and this one also goes back to, I think they say specifically, decision but it's the idea that this is all of this work is AI is great, but it has to help us make more informed decisions at a high level in the organization. So that's what we need to be using it for. So like, where have we migrated with the use cases? It's like, okay, let's make some better decisions as a result of it. Like we're using this as the tool to this AI programs and platforms and features to get to better, stronger, faster decision maker making. Which I think is key. So decision intelligence, good stuff.

Lenny Murphy: Yeah, but you found this.

Karen Lynch: Yeah, Revolt. So, you know, we've had, you know, we've had, you know, speakers from Revolt. If you don't know Revolt, you know, they're a black owned kind of multimedia company. And they've unveiled something that they've called Blackshift, which is an AI powered research initiative. And so it can give you, you know, with its agency, the agency, what's it called? The agency, six zeros, six zeros. So six zeros is, you know, helped them put forth this information about Gen Z's values, aspirations, behaviors. And it's all within this context of how Gen Z generationally is really making an impact on culture, right? And I think that is so interesting because we know that we people of one generation will own our Generation X label at this moment. It is a different culture. We had our own subculture at that age. So the concept that there's a subculture, a different culture at that age is not new. We had our own subculture, right? We can talk about that time. Oh, yes, we drove a lot of kind of influential cultural shifts, but that's what's happening with Gen Z So this is a great place to go to tap into that generation and find out what's going on with that lens So I'm really excited about that for them and you know hats off to their agency for helping with that creative work.

Lenny Murphy: Yep, absolutely the Yep It just occurred to me. Do we call ourselves the MTV generation or what? You know, I mean just the 80s kids we 80s kids It's coming of age in the 80s, Annie.

Karen Lynch: I know. I know. And we can wax nostalgic for back in the day. And I'm sure, again, it seems so old. It seems so old. But you think about the generation before us who had those thoughts about us also. Yes. Anyway, we thought everything was so cool. And that's what they think now. Everything is so cool. And they're not wrong. Absolutely appreciate it.

Lenny Murphy: Oh, let me be clear. I still think that everything that we did was cool. Let me be clear about that. The peak of coolness was in the 80s. I just, you know, sorry.

Karen Lynch: I really don't know about that. Sometimes. Anyway, sidebar. Sometimes I just like these things that I am shown the, you know, by, you know, by the generation that's, you know, that's peaking at the moment right now, I'm like, it's just cool. There's just cool stuff. It's cool that I don't know, it's just cool. So it was inspired by us. It was okay. I know you'd like some of that credit. Creative, I think that the you know, social media shorts and, and the kind of trends that go viral that just feels really creative that speaks to my soul, right? The means speak to my soul. You know, I, Karley, you know, shout out to Callie, I had seen somebody else use a meme that Karley had shared last year about something that was going on internally, and I just saw somebody else republish it, and I was like, oh, that's our girl Karley, who found that meme first, or at least shared that meme first with us. I just love creativity, and I love that there's a whole world of let's create something to get this message across, or let's create something that can then go viral. I don't know, it's a creative generation, You know, it is. It's very cool.

Lenny Murphy: Yeah, it's cool.

Karen Lynch: All right, well, let's talk about another thing. Look, I think this is cool. Did you experiment with this at all? So we're talking about perplexity, introducing a shopper feature so you can go into perplexity. You can do it without being a pro user, but pro users have kind of an unlimited ability to do this, where you can research and purchase a product right from the platform. And you're going to in the future, if you read this article, going to be able to take a picture of something, where can I get this, put it in perplexity. So it's Google search-ish, but it has this agent acting as, oh, I'm also going to connect you. I'm going to take what you're searching for or what you're interested in. I'm going to jump you a couple of steps ahead and you can click to buy. So it's integrated the whole path to purchase in a way that I think is really cool. So my experimentation was, you know, gifts for something like gifts, gifts for, um, a picky 20 year old female or something. And then it's like, I'm like, Oh, okay. You know, and it wasn't just an article that listed 10 gifts to buy for your picky 20 year old daughter. You know, it wasn't that it was, here's some cool products for you. So just, it streamlines that whole shopping process. Anyway, and apparently they're going to bring out a new merchant program as well. So you know, pay attention to that, because then those, those, those retailers are going to have access to that search trends, shopper trends.

Lenny Murphy: Yeah, that path to purchase. And point out, even though we don't have the link in it, right, the, I mean, this new the week, the efforts to break up Google, the assumption that Google will always be the default search engine, not necessarily, right? Yeah, there are credible competitors, emerging perplexity is certainly at the top of that list. And they keep doing stuff like this that goes through that revolutionizes that process. As researchers, we need to understand those things because they have an impact. I'm going to cough.

Karen Lynch: I'm sorry, Karen, talk about the next two weeks. You're good. You're good. Everybody wait. So you're allowed to cough. You don't have to say I'm sorry. The thing about this to Google point is, you know, I think everybody really, we had this idea like Google's this monopoly, and this was all brought about because does Google have a, you know, is Google a monopoly kind of thing? So that's why I think that ended up in that space of even being investigated. But the reality is, is the natural progression of the capabilities in today's world, it's almost like it's going to solve itself, because I bet this is the first time Google is like, wait, what? I have threats. I mean, I think it's interesting. The parallel of those two things I think is very interesting because they haven't had anybody coming at them. It's not even been close. And now all of a sudden, it's game changing for them. Such an interesting time to work at Google.

Lenny Murphy: I think we have some friends there, but it's an interesting time. Absolutely. So the cool stuff. All right. Spotify's AI DJ. Um, I thought, why don't you talk about this? Cause I thought this was just right in your wheelhouse in my wheelhouse.

Karen Lynch: So, yeah. So, and maybe you've played with it, uh, you know, and I feel like we've talked about it before, but this AI DJ, my husband actually just recently was like, I love my AI DJ at Spotify. But in the article, it talks about this guy saying like, I don't like it because. He's like, I'm a writer. I think it's the verb, right? So the verge and he's like, you know, I'm a writer. I can't really have lyrics. So, the AI doesn't really know the content. Of my listening, because during my workday, which might be the majority of my listening, he has to have a certain, you know, ambient noise or, you know, types of non-vocal music playing, but he certainly wants to jam out over the rest of the weekend, right? Not in so many words. So what I think is interesting is it talks about, from a qualitative research standpoint, the value that a human being would bring to the understanding of somebody's music listening is what comes to mind. If the AI asked him before just saying, hey, I'm your cool DJ and I'm gonna pick music, maybe the questions are, if there was qualitative research or even just a chat not asking, do I have it right? Is this what you want today? Do you need a different kind of vibe today? Why is it that you listen to this music? My playlist is so ridiculous because my kids hijack my playlist all the time and play what they want. So it does not know me. No matter how I slice it, it doesn't know who I am because my listening is largely other people telling me what to play. So anyway, shouldn't it have a qualitative component to it, Spotify? That's the request.

Lenny Murphy: Yep. Agreed. Well, it is interesting to think about that as we progress through this, the level of nuance. Synthetic data that, you know, individualized, you know, we, we're not far away from having our own synthetic persona agents that hopefully will have that type of nuance and can be more predictive in those types of things. Oh no, you know, Lenny likes, you know, singer songwriters, but you know, blah, blah, right. Whatever that context can be. So it'll get better, but it's not perfect yet.

Karen Lynch: Karen likes singer songwriters. Writers, but her kids are with her much of the time when she's having leisure time and can't listen to what she wants to listen to, you know, so.

Lenny Murphy: Right, right. So, yeah, I thought it was really interesting that Y Combinator, its requests for startups. It's the ideas and categories they want to see people to go after. So take a look at it. What occurred to me was, well, one, if you're an entrepreneur, and you have a bright idea to do this, Y Combinator wants to give you money. Um, so there's that, but even more of, you know, these guys are pretty darn good at predicting, uh, future trends from an enterprise standpoint, that that is their job. Their job is to identify companies that are going to tap into markets and make a buttload of money. Yeah. So, uh, when you look at this thing, okay, well, these are the types of markets, uh, and products and solutions that, uh, there is a need for, they will be emerging. They think this is going to be, you know, uh, worthy. Investments, therefore, they will be things that impact our world. So it's a kind of an early indicator. Yeah. Well, I love the ones on there that I think are the first one's on robotics.

Karen Lynch: And you and I've talked about that before. And I think you just talked about it recently on a webinar with somebody also. But one of them says using machine learning to simulate the physical world. And I thought, well, that is from an insights, you know, market research industry point of view. I know that some of the companies, for example, have these kind of real world simulation research things like, can you use, can you use a virtual product assessment tool, for example, where you're not actually applying the makeup, but you're using an augmented reality, like all of that technology, I started to think like, oh, we're, we want to simulate the physical world from a research standpoint, that could be interesting. If you are in that space developing that, there could be some cool opportunities. So that was one that jumped out at me. And of course I want to cure cancer. Like, yeah, please, like, they're not in our audience. I don't think, I don't think those data scientists are in our audience. Maybe they are.

Lenny Murphy: No. Well, and there was another one that was kind of a catch all, I think it was like, uh, you know, automation of back, back end business processes. Yeah. We're, we're living through that now. Right. We talk about this every session, you know, with the application of AI, but not just so, uh, which tells me we're not, we're still at the beginning of that curve, right? These guys still see investment opportunities to make big businesses that are doing those types of things. So yeah, check it out. It's interesting. They don't always publish this. They are this year. And pretty compelling stuff. All right, I know we're near the top of our hour, but we wanted to, we made a promise that we would at least offer a perspective two weeks ago. Do you want to?

Karen Lynch: Yeah, and I like this one. Out of all of the articles, ladies and gentlemen, we're talking about polling. Notice it's at the end. We don't have a lot of time. We're not going too far into it, right? But in this article, Mary Meehan, who is the author of this Forbes article that she published, talks about this a lot. If you go to her LinkedIn, you can kind of see some of the things about polling that she has published. And this article kind of discusses, and I invite everybody to use critical thinking about this, the need for changes in election research methodologies. So without getting into the politics, Lenny, there's been a lot of conversations. But the question really is, and I think she poses it, can we finally say that polls are flawed and rethink how we seek to understand the voting public? And I'm like, I think we're there. I think most people are there. 100%. I think it's a really important piece for everybody in the insights industry to ponder, right? Because, and I know that you're anxious to chime in too, so I don't mean to keep talking, but I think that the hesitation that I had a conversation with somebody else about is if we look under the hood at the polling methodologies, are we going to find flaws across all of insights? And we're afraid to have that conversation. Afraid to say, year after year after year, they get it wrong, but our research is credible. So we don't want to talk about this. We don't want to do that. And yet, I think the points that Mary goes on to make, which I'll stop talking for a few minutes, but then come back to, I think they're spot on that the polling is not holistic enough to really understand. And maybe that's what we've discovered. Anyway, your two cents.

Lenny Murphy: No, so I did a podcast interview yesterday with JD Deitch, which will be released soon. And I think it's a real banger for an interview. And we touched on this from the sample. That's what I've been zeroing in on, is that when we have these public examples of a miss, it's not about whether it's 2%, 3%. That's not the case, right? The issue is, it is very apparent that we are not engaged with chunks of the population. And the example I always say is P&G doesn't care who you voted for, but they do care if you're going to buy their toilet paper. And if these are examples, if they show that there is a problem with our ability to reach and engage specific populations, it doesn't matter why. Well, it does matter because we need to fix it. That's a problem. Because if we can't get to them for polling, we're not getting to them for commercial research. Guarantee you. And they can't understand what's driving their decision-making from a commercial standpoint. So it's, it's, you know, that that's the lens and Mary points that out as well. This is, there is something flawed with our ability to engage the population effectively so we can talk to them and understand them regardless of the business use case. It doesn't matter where it's about their, you know, their, their voting habits or their buying habits. I know. Start getting to them.

Karen Lynch: It's like the say-do gap, which we talk about all the time. And why do we think that that doesn't apply in other situations? Because the reality is, people are complex and their decision-making is complex and their behaviors are complex. And she goes on to make a case for understanding why voters feel the way they do. Then it's like, right, because we're not having quality qualitative conversations with them. We might have a very biased, you know, kind of televised focus group, which is not a focus group, right? We may have a conversation that's like, oh, we brought these 10 people in.

Lenny Murphy: Oh, please. Like, it's just, it's for television.

Karen Lynch: But the reality is, if we're not talking to people and understanding, you know, I think qualitative research being brought into some of that, some of the polling data that we have would probably help bring things to light in a much more holistic way. And I feel shame on the pollsters for keeping it with that singular focus like that, because it does not help. It does not help anybody.

Lenny Murphy: Well, it's the same problem that happened with the sample, right? I mean, the pollsters, you know, I'm old enough and worked in this that, you know, we used to do Katie. Right? Telephone, RDD, random digit dialing, right? And those, and that's still called the gold standard, because it's really expensive, right? Back then, there's no other choice. So we have these economic concerns that have pushed the, it's been price compression, and the sacrifice has been quality. And not just quality because of fraud, etc, etc, quality, because the systems we have put in place to be able to engage your people goes to the easiest to engage.

Karen Lynch: Yeah. Yeah.

Lenny Murphy: And then we rely on, you know, waiting or whatever to try and get to an answer. But our weights can't even be right when we don't understand the drivers of change in specific populations. We can't just look at demographics. Right. There's other stuff. So this is a bit I think it's a wonderful opportunity for the industry to do. Assess and realize, yeah, you know, maybe the emperor still has some close, but you know, I never see some stuff we don't want to see. We just need to deal with that. It's not, it's not a, not a value judgment. Nobody did this on purpose. You know, it's just, it's an issue. We need to fix it so we can deliver value. And I appreciate you bringing it up. Yeah, yeah, no, I knew there'd be a time when I could talk about it.

Karen Lynch: And this article, like I said, I like a good, an article that is, um, that encourages, just going full circle to what we said in the beginning with Nelson's disclosure before the grit forum is encouraging critical thinking, encouraging people to use their brains to mull over something, right? Like take the information that's here and say, okay, what does this mean for me personally as an insights professional? Like, do I agree with this statement? Does this statement, you know, put me off? Do I agree with the premise that it's flawed or, you know, know, do I want to defend it and say, No, no, no, it's not flawed. Like, okay. Like, I think that's what really we have to turn over in our own brains as insights professionals. So where do we stand on this? And, and final shout out to Yeah, sorry. Sorry. Go ahead. No, no, no. I was just gonna say until the next time. Do your thinking. Yes. And I just want to give a shout out to Miriam Meehan, Metametrix. She's been, she's a wonderful person, been part of our, the the Green Book family events, etc., etc., because she's just so, she's such a great thinker. I really appreciate you bringing this example of this. Here's just another example. Check her out, if you haven't. Deep, a deep thinker in ways that we, we need more folks trying to help solve these problems. So. And writing about it and putting it out there. So, you know, making, making their opinions in this context, you know, move the industry forward, which is what we're here to do. So. All right, are we done? I think we have to be. It's 36 minutes in and we went over. We did two weeks. We did a good job. We're still trying to work this out, as we said in the beginning. And it'll be two weeks again, as we said. So we'll see you in December. I know. Can you believe that? Not just December, like well into December. I know, well into December. And then we'll have that, then we'll have I think another one, and then it's... Then we're done. 25 before you know it. So. It already feels that way. All right. Take care, everybody. Thank you. Thank you. Have a good one.

Links from the episode:

2024 GRIT Forum 

SAS Buys London's Hazy to Boost Synthetic Data Offer 

Kantar Media Back on the Block? 

Thematic and QuestionPro Partner to Offer Best-in-Breed CX and Market Research Tech 

InMoment Harnesses NLP and LLMs to Launch the CX Industry’s First AI-Powered Journey Insights Tool 

Material Launches Agile Insights Product, Material Spotlight, Offering Fast, Powerful Decision Guidance 

Launch of Morning Consult AI  

REVOLT Launches Black Shift 

Perplexity’s AI search engine can now buy products for you 

Spotify’s AI is no match for a real DJ 

Y Combinator releases its latest “Requests for Startups" 

Election Research Needs To Change