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Insights, Marketing & Data: Secrets of Success from Industry Leaders
Insights, Marketing & Data: Secrets of Success from Industry Leaders
J.D Deitch (Part 2): Market Research’s Quality Crisis....and what the industry can do to solve it.
Ever wonder why your “representative” online sample may feel brittle, noisy, or oddly familiar? Well, there's no one better than J.D. Deitch to provide a highly knowledgeable - and objective - perspective on why this may be.
Alongside other issues we get into:
- How the programmatic sample market rewards speed and completions, not care and candour.
- We map the real supply chain behind panels today, from proprietary communities to rewards sites and intermediaries that resell traffic through APIs.
-. We explain how to spot when you need real people and where synthetic respondents fall short on detecting change or answering outside the model’s scope.
- How to use AI as a force multiplier in creative testing and workflow.
- We also pull back the investor lens: why legacy cost structures struggle, where private equity is placing bets, and how AI can improve both revenue velocity and margins for leaner operators.
If you buy sample, lead insights, or build research tech, this is a candid (albeit selective) tour of what’s broken, what’s working, and what to do next.
All episodes available at https://www.insightplatforms.com/podcasts/
Suggestions, thoughts etc to futureviewpod@gmail.com
My view is that there's a structural problem in the industry these days, and it is one that's led to essentially a failure of the market in economic speak, where this market is not intrinsically producing great respondents. And part of it is because there's this disconnect between buyers and sellers. I don't think buyers really understand what the modern sample ecosystem looks like. The sellers certainly have way more information on their own sort of costs and quality profiles than the buyers will ever have. There's not a great deal of transparency around that. But I also think, and this may be an unpopular opinion, but I also think that buyers are also not necessarily sending signals that they want great quality supply either.
SPEAKER_01:Now, I won't reintroduce JD, but as mentioned in the intro to part one, we've now moved on from important stuff like cheese and Man United to some elements that may be more controversial within the research sector. So amongst other subjects, we get into things like the challenges of buying sample by panels. In fact, is there such a thing as different panels? We question whether researchers place too much focused on ideas like statistical validity, even whether the research sector really has the appetite and the will to embrace AI, that and much, much more. So let's get into it. And so on that question of sampling and data, do you mind if we touch on panels for a second? I don't know. You've you've produced quite a lot of content examining the panel world. And obviously it's an era where you have some expertise in, I mentioned in terms of so on and so on. And so without getting too into the weeds on this, what are some of the key issues that buy as a panel sample should be aware of?
SPEAKER_00:I mean, look, I always I always talk about there essentially being sort of two challenges to to buying sample. One of them is is dealing with what is pretty rampant fraud in the industry. And the other one is, and I I I think it's the bigger problem, is the attention that people pay, getting people to really sort of be engaged when you're trying to ask them questions. It's a challenge that is not uh facilitated by the way that the industry executes these days. I mean, the the programmatic execution, meaning the the buying and selling of sample through an electronic ecosystem through APIs and things like that, while it's very good from an efficiency point of view, has created a market for panel respondents that is is basically crowding out decent people and allowing fraudulent people to kind of fill their places.
SPEAKER_01:When you say fraudulent people, sorry to butt in, JD, but when you say fraudulent people, do you mean as are they really people or are they bots or do you mean it's a combination of both?
SPEAKER_00:There's two kinds of fraud, right? And and you need both to make it work. So you have it you people must register in order to receive the monetary rewards, right? So at some point in time, a human has intervened to join a panel company or to join some sort of rewards community because that's the only way that they can capture the money from that. Now, how then they choose to defraud a sample buyer could be very sophisticated, right? I mean, we're certainly seeing that now where people are trying to point AIs at surveys, which will allow them to answer open-ended questions, do all the things that they need to do, or they can just do it in the old-fashioned way, which is just hammer their way through surveys and try to qualify and and just lie about what they do, right? And there's a huge variety of of people and who who you know kind of come in, there's this range of of people on an engagement scale. There's all sorts of different ways that people try to defraud the industry. You know, it's one of the things the industry has spent a lot of time trying to figure out as well. I mean, look, my my view on it, and it's not one that's kind of easily described, but my view is that there's a structural problem in the industry these days, and it is one that's led to essentially a failure of the market in economic speak, where this market is not intrinsically producing great respondents. And part of it is because there's this disconnect between buyers and sellers. I don't think buyers really understand what the modern sample ecosystem looks like. The sellers certainly have way more information on their own sort of costs and quality profiles than the buyers will ever have. There's not a great deal of transparency around that. But I also think, and this may be an unpopular opinion, but I also think that buyers are also not necessarily sending signals that they want great quality supply either.
SPEAKER_01:Yeah. Well, because they're constantly pushing on price, is that?
SPEAKER_00:Yeah. I mean, and and again, I think you have to contextualize this because what is the level of certainty that a buyer is looking for, right? What is the buyer trying to get? I mean, when we have conversations about 95% confidence intervals, I can assure you that unless you're making like, you know, multi-million dollar pound decisions, that your level of precision is not anywhere near your desire for that level of precision is not anywhere near what insights people think it should be. I mean, you know, for the most part, it's just like, should I turn left or should I turn right here? And when you're doing that, particularly in an environment where the clients are under as much budget pressure as the the research agencies are, then you make choices, right? And and so, you know, look, I'm just gonna take a quick dip because I just want a little bit of information to kind of de-risk me. Yeah. Right. And and I I think our our industry actually deludes itself in some ways by by you know talking in very lofty terms about insight and expertise and all the rest of that. And I'm not suggesting that we we don't produce genuinely insightful moments, but I don't think that's what clients are buying for the most part.
SPEAKER_01:Well, yeah, I'd I'd half agree. I'd say in that going back to the conversation we were having earlier, that I think in some cases they are, but from the more consultancy-driven specialist agencies. But then you have this weird you know, dichotomy whereby they're not able to charge as management consultants. So I think that there are some there are some.
SPEAKER_00:Yeah, no, look, I'd completely I completely agree with that. Yeah, sure.
SPEAKER_01:Whereas, yeah, it is a good point. I mean, some of the AI models I've been involved with, some of the businesses I'm involved with, you can sit and they're going like, you know, okay, fine. You run your creative through the system, and as you train the model, it gets better and better. And 60, 70% of the time, whatever like the AI is right, basically. It gives you a good prediction depending on the KPI you're trying to do.
SPEAKER_00:You have the ability, you have the ability to iterate really quickly, too. I mean, one of the one of the businesses I was advising this past year does exactly that and works with companies to do really, really fast early stage creative evaluations. It's amazing, right? I mean, the the extent to which you can create, deploy, test, iterate, improve on creative is unlike anything that we've ever seen. And yet, you know, if if this company is successful over time, what will make them successful is the fact that they can fit seamlessly into the execution of their client and and work the way the client wants to work so that they become part of the client's production process. How many insights companies actually can say that they do that? And it's you know, it's obviously it's not strategic in the sense here, it's way more tactical. But once you get into the production motion of a client, then gosh, that's a fairly significant mode, right? I mean, this is where else do we see that in in the industry? And the only other place you really might see that in the industry is if you are producing norms for a company, right? Like tracking businesses, a great example of this because the switching costs for tracking are very high, right? And and so, you know, that that's one example where you know these companies are using technology, using brain power, right? I mean, because it's not just the research either, but you know, they they they have people who understand the creative process and can speak that language to the creative team that allows them to elevate out of the insights function. Yeah, they sort of need to kind of tick that box. But, you know, that that's that's a it's a you know, they're they're a good example of of how really being close to a client's execution it really matters for the success of the business, right? You know, there may be other companies who are able to explain sort of why creative, you know, why what makes something more effective from a creative point of view or not. But if you're not helping the client then actually iterate and make better decisions over time, then you know, then it's it's sort of like a it's it's just a PowerPoint tech, right?
SPEAKER_01:Yeah, and and I think you know, I'd been involved with a lot of businesses around that sector, just using creative as an example and going back to some of the themes we talked about earlier. I think one of the challenges is that the there is uh a lot of knowledge, some of those businesses maybe quite embedded in the client's processes, but the knowledge is difficult to scale. It's held in a few people's heads, and it's almost it's quite anecdotal, that knowledge, rather than actually being genuinely institutionalized from a technological perspective where you can scale it and you'll just constantly be able to feed it in. And if I look at it from a more positive perspective, I think there are opportunities to do that now. But then you also have some of the challenges you've touched on are the business models of the agencies such that they can actually afford the investment who institutionalize that knowledge and make it kind of more scalable. I think I think a lot very understandably struggle to break away from their existing models.
SPEAKER_00:Yeah, I mean, again, I I think that is going to be, and it's hard to know how quickly that might happen. But I think that's gonna be the main factor that sort of helps us understand whether these businesses are gonna be able to find their way through this transformation. Because it's unlike anything that we've seen, right? In the same way, probably 15 years ago, when we started to see real adoption of mobile technology and how that changed so much of the go-to-market for for the clients in our industry. I mean, AI really has the potential to change both the revenue side of the business and the cost side of the business, but it is the i it is something where in order to capitalize on it, there's a a huge transformation that the business needs to make. And and you know, that is is something, you know, it's this the question of where does that funding come from? Where does the appetite come from, particularly for publicly held companies, right? I mean, you know, there's and we see a couple of them right now trying to go through that, right? You know, maybe some of them will survive just by virtue of their size, right? There are still businesses that that that thrive because they're just very big in their household names, right? Yeah. But I think there's a there's way more of them that are that are gonna struggle with this. And and you know, I think that's one of the really interesting things when you sort of look at where investors are are kind of digging into businesses right now in our industry. You know, there was a huge glut of PE and VC funding was probably tennis-ish years ago, and it probably corresponds with uh the way that the size of the industry changed when SMR started counting other parts of the the world of the sort of data ecosystem.
SPEAKER_01:Data ecosystem, right?
SPEAKER_00:Yeah, and and so it it I think it was a good thing at the time. It attracted a lot of of funding. But I also think that there's a reality to that, which is what SMR calls a cohesive industry is not at all a cohesive industry. There are two parts of that industry, and I can guarantee you now that the biggest part of that, so that the these data companies do not see themselves as insights. They would not define themselves as insights companies at all. Right. And you still have sort of traditional MRA and sample companies and even DIY companies that are now the the minority of the it's the you know the less than 50% of the the total market. These are very different companies. These are this is a very different value proposition. And I think, you know, I went to this Restec or Capital Markets Day earlier this year that Patrick Homer from SINT and Sima Vasa from Infinity Squared put on. And you know, they're obviously two very well-known voices in the industry. And you see PE companies kind of looking around a lot of these businesses right now. The ones that they're investing in are the ones that don't have this legacy cost structure behind them, right? Who and and they're they're way more reticent, I think, these days to kind of believe in the the this idea that DIY is going to save everything. But certainly AI is going to help keep the business on a path of or at least should help keep the business on a path towards profitability and and and scale. And you know, that I think these the traditional MRAs that we see right now, that's the big challenge for them is getting is getting through this. And I it it's just not going to be easy.
SPEAKER_01:Yeah, so JD, I I would agree. I think again, opportunities and challenges. Before we wrap up, I did just want to kind of go back to this question around panel management. What would you recommend if you're if you're on the buying side? What what's best practice? What should sample, the purchasers of sample, be aware of? Key considerations.
SPEAKER_00:Wow, we might need to do a whole other podcast for this. I mean, look, let's let's try to kind of keep it really simple and and straightforward. I I think it sort of starts with an understanding of what the supply ecosystem actually looks like. I think a lot of buyers still kind of remember these days where we had online research panels, right? And yes, there are still companies that have online research panels, but there is a ton of people that come through other different channels that have nothing to do with research and are, you know, sort of largely, you know, sites where they go to try to get paid to do something, right? Um, that doesn't, it's not intrinsically bad in that case, but really understanding kind of where people come from. And then the roots that their suppliers have to market. You know, there are research companies that have their own panels. There are panel companies, there are rewards communities, there are companies that buy and sell respondents, even though they have no asset of their own, just by virtue of the fact that they can hook into the ecosystem through an API someplace. And the companies, the suppliers' route to market has quite often a very significant impact on the quality of the people that they put through, right? And whether they're real or fraudulent, whether they're attentive or not. So kind of that understanding and knowing where your suppliers fit in that landscape is important already. I think the second thing is knowing what KPIs to monitor and then actually monitoring them. And the industry has not always been transparent. You know, I think it's easier in a programmatic environment to be transparent because you just have data and you have an inherently there's a data collection mechanism behind it. So it's as long as your supplier is being open with you about that, then you can see that. But you know, there's still a ton of researchers in our space who you know kind of think about the world in terms of incidence rates when conversion rate is way more important. And what do you mean by that? Incidence rate is a is a sampling principle, right? Like if I need to go find people who diabetic, right? Then you know I can look at national statistics and I can estimate that X percent of a population is diabetic. And so that's my incidence rate, right? Except that from the moment a person starts a survey to the moment that they potentially end it, a bunch of other different things could happen, right? Maybe they were over quota on that person and they shouldn't be there. Or maybe they do qualify, but the survey is so punishing that they drop out, right? And because what for the supplier's point of view, the supplier cares about incidence rate in the sense that, yeah, I want to know whether it's a difficult or hard group of people to attract. Can I target for this, all the rest of that? But at the end of the day, they get paid based on whether somebody has completed the survey. And so there's a bunch of other things that can happen. And that's how suppliers make decisions, right? They make decisions based on their earnings per entry into a survey platform, and sometimes even earnings per entry per minute. And so understanding that decision making and what it means for the supply that they get is also really important. And then, you know, and then it's it's it's monitoring those KPIs, understanding who are my better suppliers, who are not, where do I see fraud, where do I not? There are certain types of studies, maybe why I want to use this type of supplier versus some other type of supplier. And really being able to make informed decisions by that, right? I think one of the interesting things that we will see is a consequence of the AI revolution. I think it is a revolution, is that the I think people sort of gravitated to larger suppliers and in marketplaces and things like that because it was easier to get uh quantity, right? Easier to work with more people, particularly for small suppliers, small panels, their route to market, they never had the developers who could go integrate against multiple different APIs. So they would integrate against a large marketplace that they had the most exposure, the most demand. I mean, I built an API in 15 minutes yesterday, right? Using AI. I think it will become easier for people to connect directly with panels. And I think panel companies will be happy to do that because they're not paying a middleman. There's no margin on top of that. So I I think buyers need to be really careful with their choices and then be really attentive to the data, to what the data are telling them by virtue of the fact that you know they most of what they need to see is is there, right?
SPEAKER_01:Yeah, there's this whole sort of murky world behind it. I mean, picking up on one of the points you made, JD, around I guess, crossover between different panel sources, and you know, that you have that a lot of it's not exclusive.
SPEAKER_00:We all fish from the same we all fish from the same waters, right? The economists call it the tragedy of the commons, right? And when we all fish from the same waters, no Really has an interest to keep the water clean, right? Not certainly not for anybody else's panel, right? I'm I want to keep my water clean, right? But I'm not so worried about uh what happens to anybody else. And it just creates a sort of perverse set of incentives. I mean, you know, I when I worked at NPD, my boss, Steve Coffey, who's been in the industry for years and is, you know, is one of the absolute gurus on this, he once made this sort of offhanded comment to me. He said to me, It's, you know, it's all just one big panel anyway. And, you know, this is uh it's probably 15, probably maybe 20 years ago now. And I probably dismissed it out of hand because I'm like, no, no, no, everybody has their own panel. No, it's all one big panel. And when you work with sort of large marketplaces, exchanges, the you will you will see that and you will see it very clearly. And even when you don't, right, the networked nature of the ecosystem is such that you will see the same people coming in from multiple suppliers, and you have to be on top of it, right? Because duplication is is another problem that we face. And issue is not fraud, right? Because these people, you know, maybe they're they'll come and be like, oh, I've seen this. Have I seen this survey before? Maybe I've seen that survey before. Um, it's not the same thing as fraud, but it's it's it's still a problem. And you know, I I think we're starting to see a lot of people trying to tackle this, this issue of duplication, the issue of fraud. I mean, there's you know, there's all sorts of initiatives, or private companies at least, that are trying to tackle the issue of quality in the industry. I don't think our we're never gonna find sort of a collective solution on this. I just don't believe that there's no interest economically for people to sort of come together and magically collaborate. I also don't think the associations are gonna save us. I don't think they have the resource. And I think more broadly, the the work that we do does not lead itself or lend itself to really clear definitions of what fraud is and what engagement is, right? So it really is a caveat empty world, right? Let the buyer beware.
SPEAKER_01:And what's the solution? What do you think the solution to this is then, JD? I mean, do you we talk about smaller, highly commissioned proprietary panels? I don't know what's the answer.
SPEAKER_00:I mean, some of it depends on what you're trying to build as a business as well, right? You know, if you're in a business that's built on growth and you're trying to grow and you're trying to be big, uh, you will run into this problem because in the industry that's the the this is the way that the market is set up. And for you to grow as a panel company, you more often than not, people you know just simply go where the clients are and try to chase the revenue. And in doing so, you know, kind of put themselves in positions where they opted to compromise a fair bit, right? Because they they panelists do not grow on trees. It is very easy to have a retention problem with the panel, right? Very easy. And again, you know, as we kind of mentioned earlier, we don't really see clients saying, oh, you know what, I'm going to spend more to have high quality panels, assuming that that is even possible to do, right? Like, is it like wine? Can you spend more and have a better, a better quality of panelists? And I don't think we see those signals in the business. I think what people will do is, you know, to the extent that they have these types of communities, I think you have to be really careful about where you search for demand for your supply. I don't know that I have a ton of answers around that either, right? I think what we are I think what we will see, because the, you know, the synthetic panelists problem, the the thing that we see about synthetic panelists right now is a direct response to how bad the situation is with real people, right? But synthetic panels, as far as anybody can tell, are not going to allow you to answer questions that are outside the scope of which the their models were based, right? They're not going to help you really detect change. And so I think, you know, if I'm a panel company, I'm going to be looking for people who still really need real people. I'm going to try to create direct relationships with them because I think it's it's technologically possible. But it's it's I I you know it's I I don't know that I have the answer. I think if I if I did, I I would probably be working in a panel company right now. I think it's a I think it's possible to build a panel business that can be profitable and effective and you know produce money for you as a business, if you're gonna try to chase the growth that most people try to chase, then I I you're gonna run into a problem. Unless you say there are only there are only so many fish in that in that sea.
SPEAKER_01:It's exactly right.
SPEAKER_00:I think I think the other thing too, I think we need to realize this, and it's is like if you look at the revenue trends in a lot of the MRAs right now, this is not an industry that's growing very significant numbers, right? When you see people in the space who are growing significantly, they are either finding other budgets or they're taking share from existing agencies. So I I think that is equally a challenge, too, right? You know, we as an industry, particularly an industry that is based on cost plus pricing, we have you know the research agencies have lost the ability to sort of control their own financial destiny. They are far more at the sort of the the whims of the of the economic winds and what's happening with clients. And you know, that it as if they needed more problems, right? I mean, you know, that's that is that's a really, really, really significant challenge, right?
SPEAKER_01:Yeah. I mean, I have to say, and I people would probably hate me for saying she said it may not be a popular viewpoint, but if I was in a client's shoes, I would be tempted, and I could see this happening quite quickly, where they know how much sample costs. They can go, okay, fine, I'll I'll source my own sample and let's assume I'm going to try to control it well. And now let's break down your costs in a transparent manner, which sometimes happens, but not that often. Because, okay, hang on, you you're charging me how much for programming, how much for project management, how much for analysis. And I think that when clients see the amount that's going to your point, JD, into project management, that that would be problematic given that you know, if everybody, you know, you and I are experimenting with all sorts of AI enhanced systems, and we're finding it way, way easier to do things than we did in the past. And clients are doing the same thing as well. You know, they're so I I can see it being problematic.
SPEAKER_00:Yeah, I I mean clients as a matter of principle, clients don't mind when they're paying for real value. But why am I paying you so much to manually run my projects, right? I yeah. Look, I agree. I I I agree.
SPEAKER_01:You know, chat to you all day, but we should probably start to wrap up as well. And so I might just jump on to just a couple of questions in a sort of semi-quick far round. Sure. Let's do it. If you would have dinner with a couple of people outside your partner, whoever they may be, I don't know if you have a partner, but if you do, who who who would they be and why?
SPEAKER_00:Oh, this is one of those like which famous pre person would you like to have a meal with, or something like that. I I don't know. I I don't I don't tend to think of it that way. I mean, if and and maybe this is because some of my best eating experiences have come over the past 15 years, just being with friends in in France. I mean, I I would just sit down with a a group of people whose company I enjoy who who like good food and let's just have a nice meal together.
SPEAKER_01:And just see how see where it goes from there.
SPEAKER_00:Yeah, yeah. I mean, I've I've you know, interestingly enough, with all the Man United stuff, I mean, I've I've been able to, you know, sort of meet you meet some of your heroes, right? I mean, and and that's you know, it's all well and good. It's you know, it's it's fun and enjoyable and stuff like that. But for me, I mean, the best part of a meal is that moment where you know you sort of have that first bite and it's like, God, this is fantastic, and a little sip of wine afterwards, god, this is fantastic. And that's it for me, right? I mean, like, I don't I don't necessarily need a famous person next to me to make it better.
SPEAKER_01:But now I but now I have to ask, and you don't have to name any names, but the old thing, like you shouldn't meet your heroes.
SPEAKER_00:True or not true? Gosh, you know, it's it it depends on the on the people, and it depends on the you know, the sort of the way that you deal with them as well, right? You know, I I I think it we have a in in our world today there are people who get sort of starstruck around celebrities and start filming them and and start acting in ways that are sort of terribly uncivilized, right? Terribly just disrespectful in many ways. And I mean, I I I've never had sort of a a bad run-in with anyone before. You know, and I've I've met tons of I've met interesting people in my life, right? And I just I don't know, I think if you treat people decently, then they they sort of trigger you back, right? Yeah, that's what I'm always talking about, kids. I hope it's I hope it's true, and I hope it's sinking. It's it's worked for me so far, right?
SPEAKER_01:It's worked for me. So um and then do you have any you called out a couple of people earlier, but do you have any kind of like mentors within the sector or kind of people you'd really look up to that you might call out?
SPEAKER_00:Yeah, I mean, look, I've I've worked with some really great people in my life, and it's yeah, let's I mean, like, look, let's go through it. I mean, my the first sort of executive leader that I worked with, sort of VP of marketing, helped me really understand how to navigate politics in an organization. Steve Coffey at NPD, I mean, I wouldn't be in France if it weren't for him. I mean, taught me so many things about the industry, about how it works, about what I need to do to be successful as a researcher, as an operator. Going through. Let's think here. Oh gosh, when I was at P2 Samples, it was the company that, the programmatic sample company that uh that got bought by Synt, and that's how I got to Synth. Matthias, who is the the founder of that company, being able to work with somebody who is direct and open and ego-free completely changed my perspective on leadership. Some some folks at Synt, you know, I think you know Richard Thornton, Jake Wolf, Tom Bjulman, our old CEO, and just fantastic executives who who I always tried to do right by, and they always did right by me as well. I mean, you know, there's there's there's a really small sort of handful of people you can sort of look at and and be like, yeah, those those guys, you know, they were really they were they were really great. There's an another you know, there's an another list of as well of kind of peers and peers and and and even employees too, where you like, you know, you just you you know you're around great people. And and it's it's what makes it's one of the things I think I like about the industry as well, is that it's small enough, interestingly, where you can get to know a lot of people. And it's a lot of really good people in the industry, and you know, sort of one of those things too, where like you have to be really careful to make sure you're nice to those people because you will see them again, right? I used to joke that I used to joke when I first got to NPD that I was the only person in the organization who did not have a past in some other market research organization, right? I can't make that joke anymore. I've or for MPD, Ipso, Synt, consulted with a a number of businesses as well. And you know, it's it's it's it's a great, it's it's a great little industry.
SPEAKER_01:So yeah. Fantastic, JD. And final question. Any books you'd recommend? Like so long-term favorites or something you read recently that you'd you'd like to bring to people's attention?
SPEAKER_00:Any books. Oh boy. Trying to think. I think the best book that I read recently I came across Luke Burgess, who writes a lot about writes a lot about what we want as people. He wrote a book called Wanting, which talks about how our desires are formed. And it's you know based on a lot of work by a French philosopher called Renee Girard. But that book on wanting really sort of helped me contextualize a lot of things in life, in particular what I want from a professional experience as well. I would encourage people excuse me. Give me one second. I would I would encourage people to read this book, wanting. You know, that so much of our desires and the things that we see in life are shaped by social media, by the, you know, sort of things that we see happening and and and how we want our lives to be. And, you know, we we also operate in a world where we're sort of told that you know nothing is impossible and you know, you can you can do what you want. And and and one of the things this book did and Luke's writing in general speaks to me about is when you think about what you're doing on even on a daily basis, it's like, well, why am I doing this, right? Do I like to do this? Are these things that motivate me or not? Right. Like you see a lot of the whole hustle culture culture. If you read LinkedIn, you see founders who are like, yeah, I woke up at four o'clock and I ran a marathon by six, and then I was meditating for from seven to eight, took my kids to school, had a you know, a pumpkin spice latte, and then, you know, and I was done with work at 12, but then I went and go volunteered at all these other things. Like, wait, hang on a minute, right? Like, you know, let's kind of slow down and try to figure out what is it that actually motivates us as people? Are the are the dreams that I'm chasing my dreams? Are they things that I see out there? And I think that success is defined by being able to run a marathon or being able to have this designer clothing element or this piece of technology or something like that. And I find when you strip a lot of that stuff away, you're kind of left with what Luke calls the thick desires in life. Not the thin desires of sort of trivial things, but the thick desires, like the things that draw meaning, like your friends, the the things that the the things that sort of stimulate you intellectually, or that kind of give you this kind of profound sense of contentment. And they have unsurprisingly very little to do with technology and and and money and and things like that. So it's a it was a book that I read at the right time as well. It was right around the time where I was finishing up at Sint and sort of thinking about where I'm where am I gonna go from here and and how am I gonna do it. Anyway, so that's uh the book Wanting by Luke Burgess. I'd encourage you to read it and and sit with it for a little while just because it's I I think it can help people really try to understand what is at the root of their own version of kind of happiness and contentment, whatever that is.
SPEAKER_01:JD, thank you. It's a great recommendation. I really like that idea of thick desires and thin desires. I will add it to the list. I'll read it over the holiday period coming up. Thanks so much for your time. It's been a great interview and really fascinating.
SPEAKER_00:My pleasure, Henry. Thanks a lot for having me and letting me for go on and talk for so long, too. Not at all, not at all.
SPEAKER_01:Thanks so much to JD for the interview. It was really great to talk to him. Now, in our next interview, we're going to have Sam Clough, who runs Insights for Super Awesome. Super Awesome and one of the leading digital marketing agencies, indeed, exchanges, focused on responsible youth digital marketing. It's a really fascinating area. Highly recommend tuning in for that one. Thanks again to JD, Insights Platforms, and to you for listening. See you next time.
