1 00:00:11,200 --> 00:00:15,080 Speaker 1: Hello, and welcome to another episode of the Odd Lots podcast. 2 00:00:15,160 --> 00:00:19,520 Speaker 1: I'm Joe Wasn't All, and I'm Tracy Alloway. Tracy, remember 3 00:00:19,600 --> 00:00:23,600 Speaker 1: how you claimed on a recent episode of the podcast 4 00:00:23,680 --> 00:00:26,759 Speaker 1: that you're a millennial. I knew you were going to 5 00:00:26,880 --> 00:00:31,000 Speaker 1: start with this again. Uh, yeah, I did claim. I 6 00:00:31,120 --> 00:00:34,279 Speaker 1: backed it up to even by your own definition of 7 00:00:34,360 --> 00:00:37,200 Speaker 1: being a millennial, which is someone that had Facebook while 8 00:00:37,240 --> 00:00:40,160 Speaker 1: they were in college, I am, in fact a millennial, 9 00:00:40,240 --> 00:00:43,680 Speaker 1: although I am an older one. I admit, Okay, did 10 00:00:43,720 --> 00:00:46,559 Speaker 1: you ever? But here's the thing. Did you ever do 11 00:00:47,640 --> 00:00:52,520 Speaker 1: online dating? No? Is this another is this a new 12 00:00:52,600 --> 00:00:56,240 Speaker 1: definition of millennials that you're going to start using? Kind of? 13 00:00:56,640 --> 00:00:59,920 Speaker 1: I mean, don't necessarily, but I do think that's pretty important. 14 00:01:00,080 --> 00:01:02,920 Speaker 1: And the fact that you never did online dating and 15 00:01:03,000 --> 00:01:05,160 Speaker 1: neither did I it kind of makes us both not 16 00:01:05,280 --> 00:01:08,360 Speaker 1: really millennials. Yeah, I think. I mean, I'm definitely not one, 17 00:01:08,480 --> 00:01:10,600 Speaker 1: But I also kind of think maybe that's another thing 18 00:01:10,640 --> 00:01:13,880 Speaker 1: where I'm like, that is a pretty big thing in 19 00:01:13,920 --> 00:01:17,080 Speaker 1: the world that really divides people by a few years, 20 00:01:17,120 --> 00:01:20,399 Speaker 1: wouldn't you say? Yeah? I think so, And I have 21 00:01:20,480 --> 00:01:25,160 Speaker 1: to admit I have absolutely zero personal experience with online dating, 22 00:01:25,240 --> 00:01:28,240 Speaker 1: although I don't know about you, but I've always been 23 00:01:28,440 --> 00:01:31,880 Speaker 1: sort of curious about it, and whenever I meet up 24 00:01:31,920 --> 00:01:34,800 Speaker 1: with my single friends, like I would sometimes borrow their 25 00:01:34,840 --> 00:01:38,679 Speaker 1: phones and look through their Tinder profiles and the Tinder 26 00:01:38,720 --> 00:01:41,080 Speaker 1: app and just sort of play around with it, which 27 00:01:41,120 --> 00:01:44,080 Speaker 1: was kind of interesting to see how it works. Do 28 00:01:44,120 --> 00:01:48,240 Speaker 1: you swipe for them? I do? I do? I swipe 29 00:01:48,240 --> 00:01:51,040 Speaker 1: on everyone and then just see what happens. Yeah, I've 30 00:01:51,040 --> 00:01:53,440 Speaker 1: heard that's like a thing like people who never did 31 00:01:53,480 --> 00:01:57,760 Speaker 1: online dating vicariously swipe it on behalf of their friends. 32 00:01:58,000 --> 00:02:00,360 Speaker 1: I think that's like a phenomenon. Anyway, I do really 33 00:02:00,440 --> 00:02:03,080 Speaker 1: think this is a pretty big bright line dividing one 34 00:02:03,160 --> 00:02:06,520 Speaker 1: generation from the next, and especially because there will never 35 00:02:06,640 --> 00:02:11,880 Speaker 1: probably be another generation in history that didn't have online dating. 36 00:02:11,960 --> 00:02:13,800 Speaker 1: It's kind of a big thing and kind of makes 37 00:02:13,800 --> 00:02:17,280 Speaker 1: me and you more similar to boomers and previous generations 38 00:02:17,320 --> 00:02:21,079 Speaker 1: too than millennials and so forth, so forth. But it 39 00:02:21,160 --> 00:02:25,160 Speaker 1: seems like the implications of the rise of online dating 40 00:02:25,200 --> 00:02:30,800 Speaker 1: are probably still at this point underappreciated and under explored. Yeah, 41 00:02:30,880 --> 00:02:34,000 Speaker 1: it kind of gets to a point that has been 42 00:02:34,000 --> 00:02:36,760 Speaker 1: brought up on previous Odd Lots episodes, which is this 43 00:02:36,840 --> 00:02:39,920 Speaker 1: notion that a lot of the economic models that we 44 00:02:40,000 --> 00:02:45,960 Speaker 1: still use today are sometimes based on really outdated notions 45 00:02:46,040 --> 00:02:48,720 Speaker 1: of society. So the idea that we're all going out 46 00:02:48,760 --> 00:02:52,000 Speaker 1: to say a bar or a restaurant and meeting our 47 00:02:52,120 --> 00:02:56,000 Speaker 1: future partners or spouses does seem pretty out of date 48 00:02:56,120 --> 00:02:59,560 Speaker 1: given the rise of online dating, and the same for 49 00:02:59,680 --> 00:03:03,840 Speaker 1: you know, meeting your future partner through friends, Like nowadays 50 00:03:03,880 --> 00:03:07,320 Speaker 1: you're just as likely to meet them through an online platform, 51 00:03:07,360 --> 00:03:11,560 Speaker 1: if not more so. So definitely something new that would 52 00:03:11,639 --> 00:03:14,800 Speaker 1: need to be sort of factored into a lot of 53 00:03:14,840 --> 00:03:18,320 Speaker 1: economic models, I think absolutely. You know, like an essence 54 00:03:18,960 --> 00:03:22,880 Speaker 1: of the economy is sort of predicated on people getting 55 00:03:22,880 --> 00:03:25,280 Speaker 1: married and having kids and buying a house and all 56 00:03:25,280 --> 00:03:27,960 Speaker 1: of that stuff, and if that process is going to 57 00:03:28,080 --> 00:03:30,440 Speaker 1: change in some way, then you would imagine there would 58 00:03:30,480 --> 00:03:34,680 Speaker 1: just be all kinds of ripple effects. So anyway, obviously 59 00:03:34,720 --> 00:03:38,680 Speaker 1: we're going to talk about online dating today, but specifically 60 00:03:38,760 --> 00:03:42,600 Speaker 1: we're going to be talking to a hedge fund manager 61 00:03:42,760 --> 00:03:45,760 Speaker 1: who I guess and his spare time or maybe as 62 00:03:45,880 --> 00:03:49,960 Speaker 1: part of investing Will find Out has done a lot 63 00:03:50,040 --> 00:03:53,440 Speaker 1: of research into the world of online dating and even 64 00:03:53,480 --> 00:03:57,600 Speaker 1: put out a very entertaining note on the subject. Examining 65 00:03:58,240 --> 00:04:01,600 Speaker 1: uh from a very from very US data points. So, 66 00:04:01,680 --> 00:04:07,160 Speaker 1: without further ado, let's bring in Dan McMurtry of Tyro Partners. Dan, 67 00:04:07,280 --> 00:04:09,840 Speaker 1: thank you for joining us. Hey, guys, thanks so much 68 00:04:09,880 --> 00:04:13,080 Speaker 1: for having me. So Dan, before we get started, or 69 00:04:13,120 --> 00:04:15,960 Speaker 1: I guess to get us started, why don't you tell 70 00:04:16,040 --> 00:04:18,760 Speaker 1: us a little bit about who you are, what you do, 71 00:04:19,040 --> 00:04:22,640 Speaker 1: and uh, why this was the subject that you thought 72 00:04:22,720 --> 00:04:26,039 Speaker 1: was worth spending your time on going through charge, collecting 73 00:04:26,120 --> 00:04:28,479 Speaker 1: data and even sort of writing up a note on 74 00:04:28,520 --> 00:04:32,240 Speaker 1: the subject. Sure. So I run a small long short 75 00:04:32,320 --> 00:04:35,479 Speaker 1: fund out of Manhattan, UM, and our approach is to 76 00:04:35,560 --> 00:04:39,000 Speaker 1: look for what we think are big thematic drivers that 77 00:04:39,040 --> 00:04:42,080 Speaker 1: are gonna play out over five or ten or twenty years. UM. 78 00:04:42,400 --> 00:04:45,400 Speaker 1: There's a million things you can research, and so when 79 00:04:45,400 --> 00:04:48,360 Speaker 1: we think about how to best allocator research time, UM, 80 00:04:48,480 --> 00:04:51,120 Speaker 1: we don't necessarily want to focus on you know, chief 81 00:04:51,160 --> 00:04:54,640 Speaker 1: socks or expensive stocks from amentum stocks. So much is 82 00:04:54,680 --> 00:04:58,400 Speaker 1: what we think are qualitative angles that are really um 83 00:04:58,480 --> 00:05:00,560 Speaker 1: starting to show up in data but I haven't really 84 00:05:00,560 --> 00:05:03,880 Speaker 1: been discussed. And we especially like things that are kind 85 00:05:03,880 --> 00:05:07,279 Speaker 1: of validated but are not appreciated for the magnitude of 86 00:05:07,320 --> 00:05:09,480 Speaker 1: the change. You know, I'm twenty eight, and so as 87 00:05:09,520 --> 00:05:13,159 Speaker 1: somebody in my age bracket, I've kind of observed this 88 00:05:13,279 --> 00:05:16,600 Speaker 1: shift where it's not just that online dating has become popular, 89 00:05:16,760 --> 00:05:19,920 Speaker 1: it's it's killed all other forms of how people meet. 90 00:05:20,440 --> 00:05:24,520 Speaker 1: And so it's now you know, sev of relationships depending 91 00:05:24,520 --> 00:05:27,520 Speaker 1: on where you live, UM and in some cities, I mean, 92 00:05:27,560 --> 00:05:31,400 Speaker 1: it's it's become completely dominant. And so this is interesting 93 00:05:31,400 --> 00:05:33,960 Speaker 1: and kind of in every part of my life became interesting. 94 00:05:34,040 --> 00:05:36,320 Speaker 1: One in terms of dating, it was the only option 95 00:05:36,400 --> 00:05:38,480 Speaker 1: and trying to figure out, you know, how the hell 96 00:05:38,480 --> 00:05:41,480 Speaker 1: does his work. And at the same time at work, 97 00:05:41,720 --> 00:05:44,040 Speaker 1: we were looking at, you know, how is that impacting 98 00:05:44,080 --> 00:05:47,160 Speaker 1: consumer spending, How is that impacting household formation, How is 99 00:05:47,160 --> 00:05:50,120 Speaker 1: it impacting you know, any number of other things. And 100 00:05:50,160 --> 00:05:52,440 Speaker 1: we've observed this shift, and so as we started to 101 00:05:52,480 --> 00:05:54,880 Speaker 1: dig into it and get some data, we realized, wow, 102 00:05:54,920 --> 00:05:57,240 Speaker 1: this is a much much bigger deal. So we've been 103 00:05:57,279 --> 00:05:59,479 Speaker 1: working on it for about three or four years UM. 104 00:05:59,520 --> 00:06:00,880 Speaker 1: And one of the as we do as we sort 105 00:06:00,880 --> 00:06:04,640 Speaker 1: of partner with people who are entrepreneurs or other things 106 00:06:04,680 --> 00:06:07,680 Speaker 1: like that and uh talk to you on kind of 107 00:06:07,720 --> 00:06:10,279 Speaker 1: the startup scene in private markets, and we were actually 108 00:06:10,320 --> 00:06:13,200 Speaker 1: looking at potentially starting a dating company several years ago. 109 00:06:13,240 --> 00:06:15,080 Speaker 1: So we did a lot of work and we spoke 110 00:06:15,120 --> 00:06:17,080 Speaker 1: to a lot of engineers. We were thinking about poaching 111 00:06:17,200 --> 00:06:20,120 Speaker 1: some for it for a little startup. We decided not 112 00:06:20,160 --> 00:06:22,280 Speaker 1: to do it because we saw it was a kind 113 00:06:22,279 --> 00:06:25,560 Speaker 1: of network effect business. But this day that's really kind 114 00:06:25,560 --> 00:06:28,040 Speaker 1: of came together. I spent some time in Asia and 115 00:06:28,040 --> 00:06:30,520 Speaker 1: in the Middle East this summer and kind of seeing 116 00:06:30,560 --> 00:06:34,599 Speaker 1: how these apps have affected culture globally really kind of 117 00:06:34,600 --> 00:06:36,680 Speaker 1: clicked into a place of view of what was going 118 00:06:36,720 --> 00:06:38,760 Speaker 1: on and how this was a much much bigger deal 119 00:06:39,600 --> 00:06:42,520 Speaker 1: than anyone really thought. Dan. First of all, let me 120 00:06:42,560 --> 00:06:45,560 Speaker 1: just say that this paper is really amazing and very 121 00:06:45,680 --> 00:06:47,760 Speaker 1: very funny, and part of the thing that makes it 122 00:06:47,839 --> 00:06:50,119 Speaker 1: so special is it's sort of written in this very 123 00:06:50,240 --> 00:06:54,400 Speaker 1: dry way, and it includes sentences like, you know, men 124 00:06:54,480 --> 00:06:57,440 Speaker 1: struggle more in the dating market when young and overtime 125 00:06:57,480 --> 00:07:02,039 Speaker 1: adjust expectations as the market prices their deficiencies more shrewdly, 126 00:07:02,680 --> 00:07:06,600 Speaker 1: which is just an amazingly entertaining sentence. But I'm curious 127 00:07:06,720 --> 00:07:10,560 Speaker 1: when you started doing research for this paper, like how 128 00:07:10,640 --> 00:07:15,760 Speaker 1: much was anecdotal or based on your own experiences versus 129 00:07:15,920 --> 00:07:19,880 Speaker 1: sort of rigorous academic research. In other words, did you 130 00:07:19,920 --> 00:07:23,120 Speaker 1: go out and sort of do your own field research 131 00:07:23,200 --> 00:07:27,640 Speaker 1: for this one? Let's say, well, we wrote it. We 132 00:07:27,680 --> 00:07:29,480 Speaker 1: wrote it. We thought it was a very funny subject 133 00:07:29,480 --> 00:07:33,520 Speaker 1: matter to write. It's a strange topic to write about 134 00:07:33,560 --> 00:07:36,400 Speaker 1: in any sort of professional context, so we wanted to 135 00:07:36,440 --> 00:07:38,000 Speaker 1: write about it. We were gonna be funny to sort 136 00:07:38,000 --> 00:07:41,640 Speaker 1: of ironically write it very straight, and then um, you know, 137 00:07:41,680 --> 00:07:44,120 Speaker 1: put little jokes in there. Um, But yeah, all of 138 00:07:44,120 --> 00:07:46,280 Speaker 1: the above. I mean it started out. You know, the 139 00:07:46,320 --> 00:07:48,840 Speaker 1: interest in this started out because it's the way people 140 00:07:49,000 --> 00:07:52,240 Speaker 1: in my age age bracket date, and so everyone's sort 141 00:07:52,280 --> 00:07:56,480 Speaker 1: of commiserating about, um, their problems and their successes and 142 00:07:56,520 --> 00:07:59,320 Speaker 1: things like that. I've used all of these apps and 143 00:07:59,360 --> 00:08:03,240 Speaker 1: all of my into have and it's something that's frequently discussed. Um. 144 00:08:03,400 --> 00:08:05,480 Speaker 1: As those of you followed my Twitter will know, I'm 145 00:08:05,520 --> 00:08:07,520 Speaker 1: a bit of a comic, and so a lot of 146 00:08:07,520 --> 00:08:09,840 Speaker 1: people in the comedy community talk about It's just been 147 00:08:09,840 --> 00:08:13,440 Speaker 1: a frequent discussion. And so what I was interested interested 148 00:08:13,480 --> 00:08:15,600 Speaker 1: in was I was hearing a lot of opinions that 149 00:08:16,200 --> 00:08:19,640 Speaker 1: sort of up close, maybe conflicted, and a lot of 150 00:08:19,640 --> 00:08:23,360 Speaker 1: people on average were frustrated with the experience, and I 151 00:08:23,400 --> 00:08:27,000 Speaker 1: was I was fascinated to see everyone simultaneously be frustrated 152 00:08:27,040 --> 00:08:29,600 Speaker 1: and yet they continue to grow and grow and grow, 153 00:08:30,200 --> 00:08:32,160 Speaker 1: even though a lot of people would say, oh, you know, 154 00:08:32,200 --> 00:08:35,920 Speaker 1: I'm just generally disillusioned with using dating apps. And I've 155 00:08:35,960 --> 00:08:38,319 Speaker 1: also seen great successes. I know people have gotten married 156 00:08:38,320 --> 00:08:41,920 Speaker 1: off of Tender, which leads to amazing best man toasts 157 00:08:41,960 --> 00:08:45,000 Speaker 1: and things like that. And I've seen people have terrible experiences. 158 00:08:45,520 --> 00:08:47,800 Speaker 1: But it's one of the things where everyone seemed to 159 00:08:47,840 --> 00:08:50,040 Speaker 1: be talking about it, but I haven't seen any And 160 00:08:50,160 --> 00:08:53,080 Speaker 1: it's become a very serious day to day part of 161 00:08:53,200 --> 00:08:57,000 Speaker 1: almost everyone's lives who's under maybe thirty five and some over, 162 00:08:57,360 --> 00:08:59,440 Speaker 1: and yet there hasn't been a lot of serious research 163 00:08:59,520 --> 00:09:02,720 Speaker 1: done it lead in the financial economic community. So I said, okay, 164 00:09:02,720 --> 00:09:05,080 Speaker 1: what literature exists? So we first the first thing we 165 00:09:05,120 --> 00:09:06,800 Speaker 1: do when we're looking at any subjects at work is 166 00:09:06,840 --> 00:09:09,400 Speaker 1: we do a thorough literature review. So we've looked at, 167 00:09:09,800 --> 00:09:13,400 Speaker 1: you know, a number of nonprofit think tanks, university research entities, 168 00:09:13,400 --> 00:09:16,920 Speaker 1: and there's a lot of good sociological research done on 169 00:09:17,200 --> 00:09:20,000 Speaker 1: dating and health information, marriage and all of that. Divorce 170 00:09:20,840 --> 00:09:22,360 Speaker 1: and one of the things that was very interesting to 171 00:09:22,400 --> 00:09:25,400 Speaker 1: me was as we look through these papers, it was 172 00:09:25,480 --> 00:09:27,959 Speaker 1: kind of like, you know, at one point, we could 173 00:09:28,000 --> 00:09:30,800 Speaker 1: find a lot of data showing that online dating had 174 00:09:30,840 --> 00:09:33,840 Speaker 1: now become the dominant factor in dating, and at the 175 00:09:33,880 --> 00:09:37,120 Speaker 1: same time, all these papers still sort of treated it 176 00:09:37,200 --> 00:09:39,760 Speaker 1: like a footnote, it is kind of owned by the 177 00:09:39,800 --> 00:09:42,679 Speaker 1: way some people are dating online, even though eighty or 178 00:09:42,760 --> 00:09:45,680 Speaker 1: ninety percent of the data inputs into those papers were 179 00:09:45,679 --> 00:09:48,160 Speaker 1: being heavily influenced by that factor. So we said, that's 180 00:09:48,160 --> 00:09:50,960 Speaker 1: a really interesting set up for further research. So at 181 00:09:51,000 --> 00:09:53,200 Speaker 1: that point, we spoke to people at pretty much every 182 00:09:53,280 --> 00:09:57,120 Speaker 1: dating company you can imagine, ranging from e Harmony to Okay, 183 00:09:57,240 --> 00:10:01,880 Speaker 1: cubid to match too, Tender or Facebook dating, all of them, 184 00:10:02,000 --> 00:10:06,200 Speaker 1: and we also spoke to people that ran actual matchmaking 185 00:10:06,200 --> 00:10:08,640 Speaker 1: business is kind of old school and those tend to 186 00:10:08,640 --> 00:10:11,760 Speaker 1: be higher end. It was a very editive research process 187 00:10:11,760 --> 00:10:14,440 Speaker 1: where we kept having different hypothesies about how this market 188 00:10:14,520 --> 00:10:17,040 Speaker 1: was working, and then as we did more research, we 189 00:10:17,120 --> 00:10:19,240 Speaker 1: kind of kept invalidating them until he came to something 190 00:10:19,240 --> 00:10:21,440 Speaker 1: that made a lot of sense, and and then we 191 00:10:21,440 --> 00:10:24,280 Speaker 1: started going back out and when we had an idea 192 00:10:24,320 --> 00:10:25,880 Speaker 1: what we thought was going on, we started going and 193 00:10:25,880 --> 00:10:29,520 Speaker 1: doing specific polling UH and then looking in specific geographies 194 00:10:29,559 --> 00:10:31,880 Speaker 1: because we had a sort of view that essince you 195 00:10:31,960 --> 00:10:34,560 Speaker 1: what happens is an online dating site goes up, goes up. 196 00:10:35,200 --> 00:10:38,800 Speaker 1: Men immediately join it because dudes are going to do that. 197 00:10:39,120 --> 00:10:41,960 Speaker 1: Women slowly go onto the platform. There's a lack of 198 00:10:42,000 --> 00:10:46,240 Speaker 1: trust at the beginning, and over time what tends to 199 00:10:46,280 --> 00:10:49,200 Speaker 1: happen is the women are actually in a position of control. 200 00:10:49,280 --> 00:10:51,400 Speaker 1: Even though that that is what what would is initially 201 00:10:51,600 --> 00:10:54,400 Speaker 1: like scary about online dating, particularly for women, is the 202 00:10:54,480 --> 00:10:57,240 Speaker 1: unknowns and the lack of feeling safe and things like that. 203 00:10:57,720 --> 00:11:00,199 Speaker 1: But particularly looking at markets and the elite East in 204 00:11:00,280 --> 00:11:04,320 Speaker 1: an Asia where women have significantly less agency than they 205 00:11:04,360 --> 00:11:06,079 Speaker 1: do in the United States, we saw happen with this 206 00:11:06,280 --> 00:11:09,880 Speaker 1: very clever dynamic of women all of a sudden realizing, okay, wait, 207 00:11:10,040 --> 00:11:12,760 Speaker 1: I can see unlimited guys I might want to go 208 00:11:12,800 --> 00:11:15,360 Speaker 1: out with. I can say no to as many many 209 00:11:15,360 --> 00:11:18,640 Speaker 1: of them I want without any possible repercussions, and I 210 00:11:18,679 --> 00:11:21,319 Speaker 1: can be very very choosy about who I want to 211 00:11:21,360 --> 00:11:23,280 Speaker 1: go out with. But that also means I don't have 212 00:11:23,400 --> 00:11:26,160 Speaker 1: to go out with whoever my dad wants. Signatures introduced 213 00:11:26,160 --> 00:11:29,120 Speaker 1: me to I don't have to participate in these sort 214 00:11:29,160 --> 00:11:32,040 Speaker 1: of weird pseudo arrange structures that I don't really like. 215 00:11:32,559 --> 00:11:34,840 Speaker 1: And also instead of having to date within my immediate 216 00:11:34,880 --> 00:11:38,040 Speaker 1: social circle, which can have bad ramifications of things don't 217 00:11:38,040 --> 00:11:40,160 Speaker 1: work out, I can date everyone in this city or 218 00:11:40,200 --> 00:11:43,679 Speaker 1: everyone within fifty miles at least level the playing field, 219 00:11:43,720 --> 00:11:47,000 Speaker 1: if not put women in a dominant position, particularly in 220 00:11:47,000 --> 00:11:49,520 Speaker 1: those markets. And that's the first time that's ever happened 221 00:11:50,120 --> 00:11:52,600 Speaker 1: in you know, most of the Middle East, in a 222 00:11:52,600 --> 00:11:55,720 Speaker 1: lot of places. And we think that's a really interesting dynamic, 223 00:11:55,800 --> 00:11:59,120 Speaker 1: just looking historically, because dating for women is so much 224 00:11:59,200 --> 00:12:01,280 Speaker 1: riskier than it is for men. And so we did 225 00:12:01,320 --> 00:12:04,280 Speaker 1: a lot of interviews with women using these apps in 226 00:12:04,280 --> 00:12:08,439 Speaker 1: different countries and their experiences. And I think that Americans 227 00:12:08,480 --> 00:12:10,600 Speaker 1: have a very Americans and Europeans probably have a very 228 00:12:10,640 --> 00:12:14,280 Speaker 1: skewed opinion of what dating is like globally, and I 229 00:12:14,280 --> 00:12:16,520 Speaker 1: also think men tend to have a very skewed opinion 230 00:12:16,559 --> 00:12:19,480 Speaker 1: of what dating is like just in general. So it 231 00:12:19,559 --> 00:12:21,840 Speaker 1: was this iterative process of you know, we've used them all, 232 00:12:21,960 --> 00:12:23,520 Speaker 1: We've talked to a lot of people, We've done the 233 00:12:23,559 --> 00:12:26,800 Speaker 1: academic research, we've talked to people at companies, uh, and 234 00:12:26,800 --> 00:12:29,560 Speaker 1: then we've kind of iterated that with question list we had, 235 00:12:29,640 --> 00:12:32,480 Speaker 1: and then we've tried to test our hypothesis against new 236 00:12:32,520 --> 00:12:35,199 Speaker 1: incoming data, and really we got to a point where 237 00:12:35,200 --> 00:12:38,240 Speaker 1: all the new incoming data was sort of confirming our model, 238 00:12:38,320 --> 00:12:40,920 Speaker 1: so to speak. And that was where we got very 239 00:12:40,920 --> 00:12:43,600 Speaker 1: comfortable with the overall thesis, and we shared the these 240 00:12:43,640 --> 00:12:46,240 Speaker 1: are the few people, and they everyone was very very 241 00:12:46,240 --> 00:12:48,520 Speaker 1: interested in most of the stuff we write about as 242 00:12:48,520 --> 00:12:50,959 Speaker 1: hedge fund guys nobody cares about, and so we made 243 00:12:50,960 --> 00:12:52,960 Speaker 1: a decision to publish it. We just wanted to put out, 244 00:12:53,559 --> 00:12:55,280 Speaker 1: you know, not a stock pick so much. It's just 245 00:12:55,400 --> 00:12:57,600 Speaker 1: here's our general framework on this market. We think it's 246 00:12:57,600 --> 00:13:00,160 Speaker 1: a very big deal, and we think people aren't really 247 00:13:00,160 --> 00:13:02,600 Speaker 1: appreciating that this is not a fad and this is 248 00:13:02,640 --> 00:13:04,680 Speaker 1: not a niche app. I mean, this is the number 249 00:13:04,679 --> 00:13:07,080 Speaker 1: one grossing app on the Apple Store and Google Play 250 00:13:07,160 --> 00:13:10,760 Speaker 1: for you know, forever, and it needs to be taken seriously. 251 00:13:10,840 --> 00:13:13,920 Speaker 1: And I think it's it's fascinating to me how I 252 00:13:13,920 --> 00:13:16,560 Speaker 1: think it's just psychological bias against something that is still 253 00:13:16,559 --> 00:13:20,959 Speaker 1: categorized as being sexual in nature that is causing people 254 00:13:21,000 --> 00:13:24,360 Speaker 1: not to really think big picture about what's going on here? 255 00:13:25,440 --> 00:13:29,839 Speaker 1: So you mentioned that if you look through existing literature, 256 00:13:29,920 --> 00:13:35,080 Speaker 1: sociological literature on household formation and so forth, that dating apps, 257 00:13:35,120 --> 00:13:38,040 Speaker 1: the rise of dating apps is often treated as a footnote, 258 00:13:38,440 --> 00:13:41,560 Speaker 1: even though much of the data and much of these 259 00:13:41,600 --> 00:13:45,520 Speaker 1: new households are being formed by dating apps, and so 260 00:13:45,559 --> 00:13:49,360 Speaker 1: they're being simultaneously they formed the core of the new information, 261 00:13:50,000 --> 00:13:53,840 Speaker 1: but also they're dismissed. What is the error that that 262 00:13:53,960 --> 00:13:58,000 Speaker 1: leads to when you see people dismissing the significance of 263 00:13:58,120 --> 00:14:02,199 Speaker 1: dating apps or treat partnerships relationships that form via dating 264 00:14:02,200 --> 00:14:06,320 Speaker 1: apps as being exactly equivalent to partnerships that formed via 265 00:14:06,400 --> 00:14:08,920 Speaker 1: any other form, whether it's meeting in a bar or 266 00:14:09,000 --> 00:14:13,040 Speaker 1: through churches or work or whatever. What kind of errors 267 00:14:13,080 --> 00:14:17,079 Speaker 1: does that lead to in terms of analysis? Yeah, So, 268 00:14:17,080 --> 00:14:20,640 Speaker 1: so it's really about if you think about any sort 269 00:14:20,680 --> 00:14:23,480 Speaker 1: of analysis of a process like this, there are gating items. 270 00:14:23,680 --> 00:14:27,880 Speaker 1: So before you get to a question of who somebody 271 00:14:27,960 --> 00:14:30,840 Speaker 1: might want to date, the first question is who is 272 00:14:30,840 --> 00:14:33,120 Speaker 1: the what is the available pool off of which they're 273 00:14:33,160 --> 00:14:37,120 Speaker 1: making those decisions. So, particularly in America, UM and in 274 00:14:37,600 --> 00:14:41,520 Speaker 1: other places you America is not a very densely populated country. 275 00:14:41,600 --> 00:14:45,120 Speaker 1: So in America, especially if you're dating within your social circle, 276 00:14:45,760 --> 00:14:50,200 Speaker 1: and you know, particularly before you know, seventies of the sixties, 277 00:14:50,520 --> 00:14:53,760 Speaker 1: people generally less mobile. The actual dating pool people are 278 00:14:53,760 --> 00:14:56,880 Speaker 1: selecting from is quite small, um, so it might be 279 00:14:56,920 --> 00:14:59,120 Speaker 1: a few hundred people, and then you filter for people 280 00:14:59,120 --> 00:15:01,960 Speaker 1: who are available, people in the appropriate age range, people 281 00:15:02,000 --> 00:15:05,320 Speaker 1: who are from good families, things like that, and there's 282 00:15:05,360 --> 00:15:07,600 Speaker 1: a lot of other variables that get upweighted around the 283 00:15:07,680 --> 00:15:11,760 Speaker 1: social standing within that given sort of click or tribe, 284 00:15:11,840 --> 00:15:13,600 Speaker 1: and so that's there's a lot of variables to get 285 00:15:13,640 --> 00:15:15,800 Speaker 1: thrown out. So the first effect that online dating happ 286 00:15:16,000 --> 00:15:19,920 Speaker 1: has is that your dating pool size effectively becomes unlimited. 287 00:15:19,920 --> 00:15:23,200 Speaker 1: So it's going from realistically several hundred people. I mean, 288 00:15:23,280 --> 00:15:25,080 Speaker 1: let's say it's the people at work, it's the people 289 00:15:25,120 --> 00:15:28,040 Speaker 1: at the bar after after work, it's your church, and 290 00:15:28,080 --> 00:15:30,280 Speaker 1: it's a couple of social activities you're not going to 291 00:15:30,360 --> 00:15:34,160 Speaker 1: interact with in any material way more than several dozen people. 292 00:15:34,200 --> 00:15:36,520 Speaker 1: It's not a few hundred people. People go through that 293 00:15:36,560 --> 00:15:39,040 Speaker 1: many people on a dating app in like an hour. 294 00:15:39,600 --> 00:15:42,560 Speaker 1: The average time somebody spends looking at another profile and 295 00:15:42,640 --> 00:15:45,720 Speaker 1: a dating app is two to three seconds. So the 296 00:15:45,760 --> 00:15:49,080 Speaker 1: initial pool being drawn upon goes up massively, and so 297 00:15:49,120 --> 00:15:51,680 Speaker 1: then the question is if somebody has millions of people 298 00:15:51,720 --> 00:15:54,320 Speaker 1: to choose from instead of a hundred, do the variables 299 00:15:54,360 --> 00:15:58,760 Speaker 1: they're selecting people on change? And most of the historical 300 00:15:59,440 --> 00:16:01,520 Speaker 1: um pay as we've seen, really try to take a 301 00:16:01,600 --> 00:16:04,640 Speaker 1: really really rational approach to dating. And I don't know 302 00:16:04,680 --> 00:16:06,640 Speaker 1: if either of you know anyone who's ever dated, but 303 00:16:06,720 --> 00:16:10,240 Speaker 1: it's not the most rational process. I've met people who 304 00:16:10,280 --> 00:16:12,680 Speaker 1: have dated. And so we've seen a lot of things 305 00:16:12,760 --> 00:16:15,960 Speaker 1: where these papers are sort of arguing that men and 306 00:16:16,000 --> 00:16:19,400 Speaker 1: women's create like a spreadsheet in their brain of Okay, 307 00:16:19,440 --> 00:16:21,640 Speaker 1: this person went to this college, this person has this 308 00:16:21,760 --> 00:16:25,000 Speaker 1: income power, they sorted and then they select based on that. 309 00:16:44,160 --> 00:16:47,680 Speaker 1: Most people have had very small actual available dating pools, 310 00:16:47,720 --> 00:16:50,560 Speaker 1: particularly in smaller towns. Of your work, you have your 311 00:16:50,560 --> 00:16:54,640 Speaker 1: afterwork activities, church, a few other things. Particularly historically, that 312 00:16:54,720 --> 00:16:57,160 Speaker 1: pool gets very small. You're talking a few hundred people 313 00:16:57,240 --> 00:17:00,480 Speaker 1: at most when you would justust for appropriate aid range 314 00:17:01,040 --> 00:17:04,040 Speaker 1: and uh, you know, correct gender for your preferences and 315 00:17:04,080 --> 00:17:06,639 Speaker 1: things like that. Online dating flip sets and now the 316 00:17:06,640 --> 00:17:09,120 Speaker 1: pool side is unlimited. In addition to that, a lot 317 00:17:09,119 --> 00:17:11,480 Speaker 1: of the historical studies and still a lot of studies 318 00:17:11,520 --> 00:17:15,200 Speaker 1: really focused on academic attainment and things like that, as 319 00:17:15,200 --> 00:17:17,720 Speaker 1: if people are using a ranking algorithm in their head 320 00:17:17,760 --> 00:17:20,000 Speaker 1: and that just tends to not be true. It can 321 00:17:20,160 --> 00:17:23,280 Speaker 1: give me true in certain populations in cities, which is 322 00:17:23,800 --> 00:17:26,080 Speaker 1: tends to be the people doing the academic studies, but 323 00:17:26,119 --> 00:17:30,159 Speaker 1: it doesn't really bear out over broad populations, with the 324 00:17:30,160 --> 00:17:33,560 Speaker 1: exception of sort of minimum gating items. So you know, 325 00:17:33,560 --> 00:17:35,879 Speaker 1: if you don't have a high school degree, or if 326 00:17:35,920 --> 00:17:38,600 Speaker 1: you're in a college educated area you don't have a 327 00:17:38,640 --> 00:17:41,440 Speaker 1: college degree, it does get harder. But beyond that you're 328 00:17:41,440 --> 00:17:43,520 Speaker 1: looking at now, so basically going from a few hundred 329 00:17:43,560 --> 00:17:46,760 Speaker 1: people being your choice set to millions. And then when 330 00:17:46,760 --> 00:17:49,240 Speaker 1: people are looking at profiles, they're spending between two and 331 00:17:49,320 --> 00:17:52,639 Speaker 1: three seconds deciding yes or no, And so that means 332 00:17:52,680 --> 00:17:55,600 Speaker 1: that that the decision about swiping it left or right, 333 00:17:55,640 --> 00:17:58,320 Speaker 1: are saying yes or no is a lot more about 334 00:17:58,960 --> 00:18:01,199 Speaker 1: kind of the visual element of the profile, and so 335 00:18:01,320 --> 00:18:03,800 Speaker 1: you can get there's different elements in there which might 336 00:18:03,840 --> 00:18:07,040 Speaker 1: correlate with college education, but it really comes down to 337 00:18:07,040 --> 00:18:09,760 Speaker 1: how can you present yourself with photographs in some text 338 00:18:10,040 --> 00:18:14,040 Speaker 1: Each platform, individual platform uses a slightly different user interface 339 00:18:14,560 --> 00:18:18,600 Speaker 1: so that people can either find different information about potential 340 00:18:18,640 --> 00:18:22,760 Speaker 1: matches they value or showcase and or showcase information they 341 00:18:22,760 --> 00:18:25,199 Speaker 1: think is valuable. So it's leading to kind of an 342 00:18:25,200 --> 00:18:31,040 Speaker 1: instagrammification of dating, people making very quick snap judgments and 343 00:18:31,040 --> 00:18:33,600 Speaker 1: then people chat. But the other thing is that the 344 00:18:34,040 --> 00:18:36,680 Speaker 1: match ratios for men and women are radically different. Women 345 00:18:36,720 --> 00:18:39,040 Speaker 1: are getting a minimum of five times and in many 346 00:18:39,080 --> 00:18:43,160 Speaker 1: markets twenty five times the inbound like that a male 347 00:18:43,160 --> 00:18:46,080 Speaker 1: account is getting, And so that introduces a lot of 348 00:18:46,119 --> 00:18:50,240 Speaker 1: other gamifying elements around Look, you could be the greatest 349 00:18:50,280 --> 00:18:53,159 Speaker 1: person ever, but if you if you come into some 350 00:18:53,240 --> 00:18:56,840 Speaker 1: of these methods Q and your forty back, you're probably 351 00:18:56,840 --> 00:18:59,800 Speaker 1: not going to get seen. So then it introduces elements 352 00:18:59,800 --> 00:19:02,480 Speaker 1: of a random chance around what time of day like 353 00:19:02,720 --> 00:19:04,920 Speaker 1: or a message is sent, and how do you really 354 00:19:04,960 --> 00:19:08,919 Speaker 1: draw attention? So also rewards behaviors that draw attention so 355 00:19:09,000 --> 00:19:11,960 Speaker 1: you can stand out because there's just so much volume, 356 00:19:12,160 --> 00:19:14,359 Speaker 1: and it's very similar to a lot of things in 357 00:19:14,400 --> 00:19:16,600 Speaker 1: markets right now. And you know a lot of people 358 00:19:16,640 --> 00:19:18,240 Speaker 1: right now are looking at you know, a few high 359 00:19:18,240 --> 00:19:21,800 Speaker 1: profile CEOs. They're doing some very flashy things and wos 360 00:19:21,840 --> 00:19:23,840 Speaker 1: what people saying? They're getting all of the attention and 361 00:19:23,880 --> 00:19:26,280 Speaker 1: that's really the same thing that's happening right now in 362 00:19:26,440 --> 00:19:28,800 Speaker 1: dating is if you are not able to draw attention 363 00:19:28,840 --> 00:19:31,119 Speaker 1: to yourself to stand out because the pool is so 364 00:19:31,200 --> 00:19:34,200 Speaker 1: much larger, you have a big problem. So that's leading 365 00:19:34,240 --> 00:19:37,480 Speaker 1: to people going on, people having to change their strategies 366 00:19:37,520 --> 00:19:39,399 Speaker 1: how to get dates. And then when you go on 367 00:19:39,440 --> 00:19:42,679 Speaker 1: the date, you have to stand out because everyone knows 368 00:19:42,680 --> 00:19:45,560 Speaker 1: that in ten seconds you can go on your phone 369 00:19:45,920 --> 00:19:47,679 Speaker 1: and you can have another date, or you may know 370 00:19:47,760 --> 00:19:50,639 Speaker 1: that you have five, ten, twenty alternatives waiting in the 371 00:19:50,640 --> 00:19:53,159 Speaker 1: wings on your phone. So if there's a red flag 372 00:19:53,240 --> 00:19:55,240 Speaker 1: on date one, there probably is not a date two. 373 00:19:55,320 --> 00:19:58,720 Speaker 1: People are not hanging around on Overall, in the whole population, 374 00:19:58,720 --> 00:20:02,280 Speaker 1: people are not hanging around in bad relationships as long. Wait, Dan, 375 00:20:02,359 --> 00:20:06,600 Speaker 1: can I ask a real quick question. But whether it's 376 00:20:06,840 --> 00:20:11,840 Speaker 1: on the profile itself, like on one's profile, or whether 377 00:20:11,880 --> 00:20:14,639 Speaker 1: it's showing up, is it smart strategy to be wearing 378 00:20:14,640 --> 00:20:17,919 Speaker 1: cargo shorts. I am an advocate of a cargo shorts 379 00:20:17,960 --> 00:20:21,920 Speaker 1: all the time, but my cargo short oriented dating app 380 00:20:22,000 --> 00:20:24,480 Speaker 1: is not doing that well. And I just think there's 381 00:20:24,520 --> 00:20:28,239 Speaker 1: a conspiracy against me at Apple from the top, and uh, 382 00:20:28,440 --> 00:20:31,200 Speaker 1: Tim Apple himself does not want this to happen, but 383 00:20:31,400 --> 00:20:33,800 Speaker 1: I think it's just an inevitability. Everyone's gonna wear nothing 384 00:20:33,800 --> 00:20:35,399 Speaker 1: but cargo shorts in the kind of huge I just 385 00:20:35,400 --> 00:20:38,679 Speaker 1: wanted to clear that up. Yeah, are you a B testing? 386 00:20:38,960 --> 00:20:42,000 Speaker 1: Like is there one profile where you're wearing cargo shorts 387 00:20:42,000 --> 00:20:44,240 Speaker 1: and another one where you aren't? You know you joke, 388 00:20:44,440 --> 00:20:47,440 Speaker 1: But we did several years ago do some a B 389 00:20:47,600 --> 00:20:50,800 Speaker 1: testing with dummy accounts, and I think one of them 390 00:20:50,840 --> 00:20:53,400 Speaker 1: did have cargo shorts on. We made an account called 391 00:20:53,480 --> 00:20:58,760 Speaker 1: Chad that was the worst person ever, and it did 392 00:20:59,040 --> 00:21:01,800 Speaker 1: way better than I thought it would. It was really offensive. 393 00:21:01,920 --> 00:21:04,919 Speaker 1: I think it actually outperformed my actual account, which is 394 00:21:05,000 --> 00:21:08,760 Speaker 1: just crushing um. But it comes back to like attention, 395 00:21:08,840 --> 00:21:10,240 Speaker 1: like if you make if you if you have like 396 00:21:10,240 --> 00:21:14,399 Speaker 1: a shirtless dude in cargo shorts, that the entire profile 397 00:21:14,440 --> 00:21:17,119 Speaker 1: is ridiculous, you're gonna get some percentage of people saying 398 00:21:17,200 --> 00:21:19,920 Speaker 1: yes because they say, oh that's funny. They're actually such 399 00:21:19,920 --> 00:21:21,600 Speaker 1: a thing. It's like a hate like some people will 400 00:21:21,640 --> 00:21:23,880 Speaker 1: match with somebody just to say mean things to them 401 00:21:23,880 --> 00:21:25,679 Speaker 1: in the d M. You know, you get a lot 402 00:21:25,720 --> 00:21:27,960 Speaker 1: of that, but yeah, you can. We did a bit 403 00:21:28,400 --> 00:21:31,960 Speaker 1: with cargo shorts. So before we get onto more of 404 00:21:32,000 --> 00:21:35,160 Speaker 1: the economic implications, I just wanted to ask you're you're 405 00:21:35,160 --> 00:21:40,320 Speaker 1: talking about online dating basically making the whole dating market 406 00:21:40,520 --> 00:21:44,720 Speaker 1: more efficient, so you have greater access to a bigger 407 00:21:44,800 --> 00:21:50,280 Speaker 1: pool of potential mates, which is a terrible word, but like, 408 00:21:50,440 --> 00:21:54,320 Speaker 1: I just wonder how much of that efficiency is actually 409 00:21:54,560 --> 00:22:00,919 Speaker 1: offset by having an enormous amount of or a number 410 00:22:00,920 --> 00:22:04,399 Speaker 1: of people to actually choose from and and having to 411 00:22:04,480 --> 00:22:07,399 Speaker 1: go on dates with with various people. In other words, like, 412 00:22:07,480 --> 00:22:11,160 Speaker 1: how much of the efficiency from online dating is actually 413 00:22:11,320 --> 00:22:16,679 Speaker 1: offset by the stress and burnout of doing this constantly? 414 00:22:17,119 --> 00:22:20,080 Speaker 1: Excellent questions. So I think it's important to understand that 415 00:22:20,280 --> 00:22:23,160 Speaker 1: stress and burnout is a huge factor in dating. That's 416 00:22:23,200 --> 00:22:25,840 Speaker 1: the least romantic thing to say, ever, But at some 417 00:22:25,960 --> 00:22:28,960 Speaker 1: point you're making a judgment of I really like this person, 418 00:22:30,040 --> 00:22:32,359 Speaker 1: you know, we're in loved at it up, but you know, 419 00:22:32,560 --> 00:22:35,720 Speaker 1: I think there might be somebody else that could convince 420 00:22:35,800 --> 00:22:38,399 Speaker 1: you to break up with them and go with somebody 421 00:22:38,400 --> 00:22:42,199 Speaker 1: else in a lot of circumstances, and historically, when you know, 422 00:22:42,240 --> 00:22:44,600 Speaker 1: if you live in a small town like I'm from Richard, Virginia, 423 00:22:45,200 --> 00:22:48,600 Speaker 1: if you know three people and there's really like twenty 424 00:22:48,720 --> 00:22:53,800 Speaker 1: that you think are potential long term life partners. At 425 00:22:53,800 --> 00:22:55,440 Speaker 1: a certain point, you're gonna say, do I really want 426 00:22:55,440 --> 00:22:58,199 Speaker 1: to risk this good thing for you know, five or 427 00:22:58,240 --> 00:23:01,480 Speaker 1: six other potential options? When the clock is starting to 428 00:23:01,560 --> 00:23:05,520 Speaker 1: run down, it starts to be an illogical, interrrational decision 429 00:23:06,040 --> 00:23:08,800 Speaker 1: the real differences, and so that still exists as you 430 00:23:08,840 --> 00:23:10,560 Speaker 1: get older, you get to a certain point, like at 431 00:23:10,600 --> 00:23:13,000 Speaker 1: some point you're gonna say, I'm really tired of playing 432 00:23:13,000 --> 00:23:15,879 Speaker 1: this game. I'd really like to you know not. And 433 00:23:15,920 --> 00:23:18,560 Speaker 1: that's not true for everybody. Some people enjoy dating. I 434 00:23:18,600 --> 00:23:21,560 Speaker 1: think that's insane. I think dating is stressful, especially early dating. 435 00:23:22,000 --> 00:23:25,280 Speaker 1: But um, there are people who like that. But what's 436 00:23:25,280 --> 00:23:28,639 Speaker 1: important understand is that it's more about during like specifically 437 00:23:28,720 --> 00:23:32,840 Speaker 1: during your twenties and early thirties. This is providing at 438 00:23:32,880 --> 00:23:34,800 Speaker 1: any point in time, you have an escape pass you 439 00:23:34,800 --> 00:23:37,720 Speaker 1: can pull, you can always go, and you have hundreds, 440 00:23:37,720 --> 00:23:40,680 Speaker 1: if not thousands, of potential options. And so you're gonna 441 00:23:40,800 --> 00:23:42,920 Speaker 1: you're gonna try on this is not bad. You're gonna 442 00:23:42,960 --> 00:23:45,200 Speaker 1: try on more pants. You're gonna you're gonna have more 443 00:23:45,240 --> 00:23:47,920 Speaker 1: options to try out. You're gonna go on more first 444 00:23:48,000 --> 00:23:50,640 Speaker 1: dates that are gonna end badly. And I think what's 445 00:23:50,640 --> 00:23:52,800 Speaker 1: happening is that's allowing people to sort of build a 446 00:23:52,880 --> 00:23:56,600 Speaker 1: database of what their deal breakers are, which you know, 447 00:23:56,600 --> 00:23:58,840 Speaker 1: I'm gonna include all thirty Rock references in that because 448 00:23:58,840 --> 00:24:01,239 Speaker 1: I love that show. You you're gonna figure out that 449 00:24:01,280 --> 00:24:03,320 Speaker 1: doesn't work for me, that doesn't work for me. This 450 00:24:03,400 --> 00:24:05,960 Speaker 1: is a problem. And now of those ethics are going 451 00:24:06,040 --> 00:24:08,000 Speaker 1: to be good. But you're not going to stick around 452 00:24:08,040 --> 00:24:10,160 Speaker 1: in a relationship if there's a clear red flag off 453 00:24:10,160 --> 00:24:12,320 Speaker 1: the bat, because you can be on another day tomorrow, 454 00:24:12,680 --> 00:24:14,520 Speaker 1: So you're not gonna go out with, you know, a 455 00:24:14,520 --> 00:24:17,800 Speaker 1: sketchy person two or three or four times again. Overall, obviously, 456 00:24:17,840 --> 00:24:20,720 Speaker 1: individual people will make terrible decisions. It's what America is 457 00:24:20,720 --> 00:24:24,720 Speaker 1: all about. But it's the massive increase in alternatives and 458 00:24:24,760 --> 00:24:27,720 Speaker 1: so as you go through more and more dates, and 459 00:24:27,720 --> 00:24:29,479 Speaker 1: one of the things that's been studied quite a bit. 460 00:24:29,480 --> 00:24:32,040 Speaker 1: I'm gonna post some more papers about this is that 461 00:24:32,440 --> 00:24:36,720 Speaker 1: between about the nineteen nineteen fifties and now, the median 462 00:24:36,840 --> 00:24:41,000 Speaker 1: person when they get married is having seven to twelve 463 00:24:41,080 --> 00:24:44,160 Speaker 1: times as much dating experiences as their parents. I think 464 00:24:44,160 --> 00:24:47,280 Speaker 1: that numbers low balls. I think people still, uh I 465 00:24:47,359 --> 00:24:51,000 Speaker 1: don't want to sound promiscuous. So people are when they 466 00:24:51,000 --> 00:24:54,239 Speaker 1: are making a decision to get married, they're coming in 467 00:24:54,240 --> 00:24:57,520 Speaker 1: with way more information, They've seen a lot more. They're 468 00:24:57,560 --> 00:24:59,920 Speaker 1: also more aware of how stressful it is to date, 469 00:25:00,040 --> 00:25:01,879 Speaker 1: so there isn't that factor of, oh, I wonder what 470 00:25:01,920 --> 00:25:03,480 Speaker 1: else is out there. You're like, no, I know what 471 00:25:03,560 --> 00:25:06,560 Speaker 1: else is out there. I'm really good, Like this is solid. 472 00:25:07,040 --> 00:25:09,679 Speaker 1: So you're just making a more informed purchasing decision, if 473 00:25:09,680 --> 00:25:12,600 Speaker 1: you want to sound like an economist about it. And 474 00:25:12,640 --> 00:25:15,639 Speaker 1: that's really really changing things. And as a result, I 475 00:25:15,680 --> 00:25:18,520 Speaker 1: think this is driving a reduction and divorce. The other 476 00:25:18,560 --> 00:25:23,120 Speaker 1: issue is that absolute marriage rates, particularly marriage rates below 477 00:25:23,200 --> 00:25:25,840 Speaker 1: twenty five, are going down a lot, and in my 478 00:25:25,920 --> 00:25:29,520 Speaker 1: personal opinions might offend some people. I think getting divorced 479 00:25:29,560 --> 00:25:32,200 Speaker 1: before your brain is fully formed around twenty five years 480 00:25:32,200 --> 00:25:34,880 Speaker 1: old is kind of crazy because you have very little 481 00:25:34,880 --> 00:25:38,320 Speaker 1: life experience. You said getting divorced before, did you mean 482 00:25:38,320 --> 00:25:42,280 Speaker 1: getting married before? I mean both, but yeah, I mean yeah, 483 00:25:42,280 --> 00:25:47,200 Speaker 1: getting married before is statistically a worse idea because you're 484 00:25:47,240 --> 00:25:48,560 Speaker 1: not at a point where you're not a point of 485 00:25:48,600 --> 00:25:51,560 Speaker 1: stability personally. You don't have a lot of life experience. 486 00:25:51,640 --> 00:25:53,919 Speaker 1: You haven't all the dating experience. You're making a huge 487 00:25:53,920 --> 00:25:57,280 Speaker 1: decision with very little information going in. You're gonna generally 488 00:25:57,640 --> 00:26:01,440 Speaker 1: be unable to withstand kind of shocks better than you know. 489 00:26:01,480 --> 00:26:03,119 Speaker 1: We could wield miss team to Leven here and he 490 00:26:03,160 --> 00:26:04,919 Speaker 1: could explain it, but you're not gonna be able to 491 00:26:04,920 --> 00:26:07,480 Speaker 1: withstand shocks very well. One of the things that's happening 492 00:26:07,480 --> 00:26:09,840 Speaker 1: as a result of that is that people are are 493 00:26:09,920 --> 00:26:12,800 Speaker 1: are dating a little bit longer. People are also moving 494 00:26:12,800 --> 00:26:16,479 Speaker 1: in together more, and the probability that if you live together, 495 00:26:16,520 --> 00:26:19,200 Speaker 1: if you cohabitate, you do get married is dropping because 496 00:26:19,240 --> 00:26:21,479 Speaker 1: people are moving in for six months, twelve months, two 497 00:26:21,560 --> 00:26:24,160 Speaker 1: years and just saying, okay, can we actually live together. 498 00:26:24,200 --> 00:26:26,359 Speaker 1: We might really love each other, but are we going 499 00:26:26,400 --> 00:26:28,199 Speaker 1: to kill each other if we live together? Which is 500 00:26:28,200 --> 00:26:31,040 Speaker 1: an important question to ask, uh if you think of 501 00:26:31,160 --> 00:26:34,359 Speaker 1: getting married, So you're seeing you know, you're just seeing 502 00:26:34,400 --> 00:26:37,400 Speaker 1: a lot more trials, and so you could you could 503 00:26:37,480 --> 00:26:39,280 Speaker 1: comp that to the market and say you're seeing a 504 00:26:39,280 --> 00:26:42,240 Speaker 1: lot more trading volume, which tends to lead to more 505 00:26:42,240 --> 00:26:44,840 Speaker 1: efficient pricing. And so what we think is happening is 506 00:26:44,840 --> 00:26:47,080 Speaker 1: people are basically going on more bad dates, figuring out 507 00:26:47,160 --> 00:26:49,439 Speaker 1: more of what doesn't work for them. They're living with 508 00:26:49,440 --> 00:26:51,000 Speaker 1: people before they get married, and then when they do 509 00:26:51,080 --> 00:26:53,800 Speaker 1: get married, and all of that up until the marriage 510 00:26:53,840 --> 00:26:56,359 Speaker 1: decision is is can be very stressful and hard, and 511 00:26:56,680 --> 00:26:59,040 Speaker 1: that I think that's why all the dissatisfaction is there. 512 00:26:59,560 --> 00:27:02,360 Speaker 1: But when do actually finally find somebody, they have way 513 00:27:02,359 --> 00:27:05,560 Speaker 1: more information. They're making a much more informed decision overall, 514 00:27:06,320 --> 00:27:10,720 Speaker 1: and you're seeing better marriage outcomes where people are actually 515 00:27:10,840 --> 00:27:12,879 Speaker 1: you know, they know what they're getting into and they 516 00:27:12,920 --> 00:27:15,920 Speaker 1: actually can make it. They're making an educated decision about 517 00:27:15,960 --> 00:27:17,520 Speaker 1: whether or not they think this is gonna work. I 518 00:27:17,520 --> 00:27:20,640 Speaker 1: think it's important to note that on a statistical basis, 519 00:27:20,640 --> 00:27:23,120 Speaker 1: marriage is a lot more about downside risk and upside. 520 00:27:23,119 --> 00:27:24,679 Speaker 1: I mean, you you can't really predict if you're going 521 00:27:24,720 --> 00:27:27,359 Speaker 1: to be the most happy you've ever been, but you 522 00:27:27,400 --> 00:27:30,000 Speaker 1: can probably predict if, like this person is going to 523 00:27:30,119 --> 00:27:31,840 Speaker 1: kill you with an AX. So you need to really 524 00:27:31,960 --> 00:27:34,400 Speaker 1: you want to avoid the ax murder situation as much 525 00:27:34,440 --> 00:27:36,800 Speaker 1: as possible, more than you want to have like the 526 00:27:36,880 --> 00:27:40,600 Speaker 1: notebook happen. Right. That's yeah, it's really like kind of 527 00:27:40,880 --> 00:27:44,919 Speaker 1: depressing and unromantic though that like, okay, yes, maybe there 528 00:27:44,920 --> 00:27:50,520 Speaker 1: are fewer divorces now. But basically that's just about eliminating 529 00:27:50,560 --> 00:27:53,040 Speaker 1: the left side of the tail. Basically, it's not that 530 00:27:53,119 --> 00:27:55,600 Speaker 1: marriages are per se better, it's just that there are 531 00:27:55,600 --> 00:27:58,280 Speaker 1: fewer of the really bad sounds like yeah, but I 532 00:27:58,280 --> 00:28:00,359 Speaker 1: mean I think you know, I'm from a only that 533 00:28:00,400 --> 00:28:03,120 Speaker 1: had I'm from a divorced family, and I can tell 534 00:28:03,119 --> 00:28:06,600 Speaker 1: you that you know, the left tail is not fun. 535 00:28:07,400 --> 00:28:11,879 Speaker 1: And people getting into these decisions of like where like 536 00:28:12,440 --> 00:28:15,199 Speaker 1: you see this a lot investing people optimize, people in 537 00:28:15,200 --> 00:28:18,880 Speaker 1: their head optimize to this dream scenario that it's really 538 00:28:18,920 --> 00:28:20,960 Speaker 1: really dangerous. It's kind of a siren song. You're thinking 539 00:28:21,000 --> 00:28:24,040 Speaker 1: about perfection. You're not thinking about something that is consistently 540 00:28:24,080 --> 00:28:28,119 Speaker 1: good and consistently positive. And I think overall it's better 541 00:28:28,160 --> 00:28:30,639 Speaker 1: for people, and people are happier if they have something 542 00:28:30,640 --> 00:28:35,640 Speaker 1: that is consistently good. Then if they make these moonshot bets. Now, 543 00:28:35,680 --> 00:28:37,560 Speaker 1: I will say that the moon shot bet thing is 544 00:28:37,640 --> 00:28:41,000 Speaker 1: huge in this because because the dating pools are so large, 545 00:28:41,360 --> 00:28:44,840 Speaker 1: people are a lot pickier, particularly women when they're under 546 00:28:44,880 --> 00:28:48,640 Speaker 1: call at twenty five. Everyone is trying no matter you know, 547 00:28:49,000 --> 00:28:51,800 Speaker 1: who you are, what you look like, whatever, everyone is 548 00:28:51,840 --> 00:28:54,880 Speaker 1: trying to punch above their weight because statistically, it will 549 00:28:54,920 --> 00:28:59,000 Speaker 1: probably happen given you have unlimited swipes, right, so you 550 00:28:59,080 --> 00:29:01,600 Speaker 1: have unlimited at at that's never been the case before, 551 00:29:02,120 --> 00:29:04,320 Speaker 1: and so everyone is trying to punch above their weight, 552 00:29:04,480 --> 00:29:07,320 Speaker 1: and that's actually causing there to be more competition in 553 00:29:07,360 --> 00:29:10,360 Speaker 1: the market. But people tend to find that that doesn't 554 00:29:10,360 --> 00:29:12,959 Speaker 1: actually work so well, that doesn't you know, you're probably 555 00:29:12,960 --> 00:29:14,840 Speaker 1: going to get to go on a few dates with 556 00:29:14,920 --> 00:29:17,719 Speaker 1: people that are way out of your league, and you know, 557 00:29:17,920 --> 00:29:21,520 Speaker 1: if you make that happen, great for you. But over time, 558 00:29:21,560 --> 00:29:25,480 Speaker 1: people sort of, you know, get their expectations, your expectations 559 00:29:25,520 --> 00:29:28,000 Speaker 1: get priced to a reasonable level in the market over time, 560 00:29:28,400 --> 00:29:30,560 Speaker 1: and all this sounds very, very unromantic. I'm just kind 561 00:29:30,560 --> 00:29:32,880 Speaker 1: of describing what's happening dispatched. I think that's part of 562 00:29:32,880 --> 00:29:35,200 Speaker 1: the issue also, is it's very hard for people to 563 00:29:35,240 --> 00:29:39,480 Speaker 1: describe this market is passionately because it says something about you. 564 00:29:39,680 --> 00:29:42,920 Speaker 1: I don't want to sound like a psychopath describing people 565 00:29:43,360 --> 00:29:46,960 Speaker 1: falling in love as a pricing function, but the data 566 00:29:47,040 --> 00:29:48,840 Speaker 1: looks the hell of a lot like a pricing function, 567 00:29:49,400 --> 00:29:51,680 Speaker 1: and using a pricing function is the only way we've 568 00:29:51,680 --> 00:29:54,280 Speaker 1: been able to actually solve this. So I kind of 569 00:29:54,280 --> 00:29:56,680 Speaker 1: got to, you know, put on my psychopath hat and 570 00:29:56,680 --> 00:29:58,760 Speaker 1: and talk like one for a minute to understand what's 571 00:29:58,800 --> 00:30:01,320 Speaker 1: going on. I'm but then there are strategies, you know, 572 00:30:01,360 --> 00:30:04,120 Speaker 1: you can use to get outcomes that you're happy with. Here. 573 00:30:04,160 --> 00:30:06,120 Speaker 1: I mean, it's not this is not a circumstance where 574 00:30:06,120 --> 00:30:08,480 Speaker 1: everybody's doomed. It's just people are going to go through 575 00:30:08,480 --> 00:30:10,800 Speaker 1: a period of struggle and then the bright side is 576 00:30:10,840 --> 00:30:13,360 Speaker 1: people are finding what they're looking for. And then the 577 00:30:13,520 --> 00:30:15,640 Speaker 1: great thing about online dating also is that there are 578 00:30:15,680 --> 00:30:18,680 Speaker 1: all the big properties, but there's increasingly more and more 579 00:30:18,800 --> 00:30:22,680 Speaker 1: deep niche categories where people can find very specific traits 580 00:30:22,720 --> 00:30:24,720 Speaker 1: if they want a certain type of partnership. So it 581 00:30:24,800 --> 00:30:28,000 Speaker 1: might be considered abnormal or or or interest oriented, or 582 00:30:28,040 --> 00:30:31,840 Speaker 1: ethnicity oriented or something like that. People can select into that, 583 00:30:31,960 --> 00:30:33,680 Speaker 1: you know. So for example, you know, we have a 584 00:30:33,680 --> 00:30:37,200 Speaker 1: friend of the firm is Orthodox Jewish family, and he 585 00:30:37,240 --> 00:30:39,280 Speaker 1: was talking about how, you know, when he was a kid, 586 00:30:39,280 --> 00:30:42,320 Speaker 1: it was all family introductions and now all the kids 587 00:30:42,320 --> 00:30:44,320 Speaker 1: are on you know, Jase Wipe and things like that, 588 00:30:44,400 --> 00:30:46,680 Speaker 1: and it's it's like, it's weird because I don't understand 589 00:30:46,720 --> 00:30:49,080 Speaker 1: it at all. But there's still dating within the pool 590 00:30:49,160 --> 00:30:51,280 Speaker 1: that i'd like them to date with so great. So 591 00:30:51,480 --> 00:30:53,840 Speaker 1: you know, people are getting the outcomes that they want 592 00:30:54,160 --> 00:30:56,800 Speaker 1: and they are limiting the left tail. So it's kind 593 00:30:56,800 --> 00:30:59,160 Speaker 1: of like it reminds me a lot of when people 594 00:30:59,440 --> 00:31:02,680 Speaker 1: get into an investing and they start thinking, Okay, I'm 595 00:31:02,720 --> 00:31:04,840 Speaker 1: going to pick some genius stock. I'm gonna be the 596 00:31:04,840 --> 00:31:07,080 Speaker 1: guy who buys Amazon at a dollar a share, and 597 00:31:07,080 --> 00:31:10,920 Speaker 1: I'm gonna make all this money, and they realize over time, like, 598 00:31:11,040 --> 00:31:15,520 Speaker 1: you know, if I can do a solid like on 599 00:31:15,600 --> 00:31:19,040 Speaker 1: my retirement portfolio over thirty or forty years, like that's great, 600 00:31:19,160 --> 00:31:22,840 Speaker 1: But that's not a fun process of adjusting your expectations, 601 00:31:22,960 --> 00:31:25,920 Speaker 1: you know. And I think it's a lot like that. Well, 602 00:31:26,160 --> 00:31:30,520 Speaker 1: since you're talking about dating um from a slightly psychopathic, 603 00:31:31,200 --> 00:31:37,440 Speaker 1: numbers based slash investing strategy perspective, I'm wondering, given that 604 00:31:37,520 --> 00:31:40,880 Speaker 1: online dating is sort of the dominant form of dating now, 605 00:31:41,080 --> 00:31:45,800 Speaker 1: is is real life dating where the alpha is Like, 606 00:31:46,000 --> 00:31:49,000 Speaker 1: is that where you could maybe find some interesting matches 607 00:31:49,080 --> 00:31:53,480 Speaker 1: and maybe outperform the broader market? If that makes sense? 608 00:31:54,000 --> 00:31:56,600 Speaker 1: I think so. If I'm gonna just put my hypocrite 609 00:31:56,640 --> 00:31:58,920 Speaker 1: hat on here for a second, but my girlfriend I 610 00:31:58,960 --> 00:32:03,080 Speaker 1: actually met offline, but it's happening less And I think 611 00:32:03,120 --> 00:32:04,960 Speaker 1: one of the things is, you know, every one of 612 00:32:05,000 --> 00:32:07,320 Speaker 1: the common comments about millennials, you go to a barner, 613 00:32:07,360 --> 00:32:10,520 Speaker 1: everybody's on their phone, So there are less people who 614 00:32:10,560 --> 00:32:14,800 Speaker 1: actually have the conversational skill to you know, strike up 615 00:32:14,840 --> 00:32:17,120 Speaker 1: conversation form of connection. The other thing is, as I said, 616 00:32:17,160 --> 00:32:19,200 Speaker 1: when you're on the apps, people are spending two to 617 00:32:19,320 --> 00:32:23,560 Speaker 1: three seconds at most on average on each profile. So 618 00:32:23,600 --> 00:32:26,080 Speaker 1: if you can actually start a conversation and then you 619 00:32:26,120 --> 00:32:28,640 Speaker 1: and that person are going to share you know, let's 620 00:32:28,640 --> 00:32:31,640 Speaker 1: take two or three or four minutes of mutual attention, 621 00:32:31,920 --> 00:32:35,120 Speaker 1: that's giving you, you know, hundreds of times the exposure 622 00:32:35,160 --> 00:32:37,800 Speaker 1: that you're getting otherwise. So I definitely think that if 623 00:32:37,840 --> 00:32:41,080 Speaker 1: there our way, if you can do that without being creepy, 624 00:32:41,360 --> 00:32:43,640 Speaker 1: there's definitely a lot of you know, alpha there. I 625 00:32:43,680 --> 00:32:46,600 Speaker 1: think that things like a friend of friend introductions and 626 00:32:46,640 --> 00:32:53,000 Speaker 1: family introductions are likely structurally dead because the risk there's 627 00:32:53,000 --> 00:32:55,560 Speaker 1: such a big risk factor there that now is not necessary. 628 00:32:55,960 --> 00:32:57,760 Speaker 1: You know, it's always been the case that well you 629 00:32:57,840 --> 00:33:00,960 Speaker 1: introduce somebody within your friend circle, be does it may 630 00:33:01,040 --> 00:33:03,560 Speaker 1: strengthen you know, loyalty within the tribe over time, but 631 00:33:03,600 --> 00:33:06,400 Speaker 1: if it doesn't work, then it's a really bad thing 632 00:33:06,640 --> 00:33:08,280 Speaker 1: and it's gonna be awkward as hell, and it's gonna 633 00:33:08,320 --> 00:33:10,760 Speaker 1: make Christmas parties terrible. And I think everybody has been 634 00:33:10,760 --> 00:33:13,760 Speaker 1: through that experience. And so because there's unlimited dating alternative, 635 00:33:13,800 --> 00:33:15,400 Speaker 1: if nobody's gonna do that anymore. But I do think 636 00:33:15,400 --> 00:33:18,120 Speaker 1: there's there are a lot of opportunities to you know, 637 00:33:18,240 --> 00:33:20,480 Speaker 1: do better than you might on the apps by being 638 00:33:20,520 --> 00:33:23,360 Speaker 1: proactive in real life. And the other thing that you know, 639 00:33:23,400 --> 00:33:25,200 Speaker 1: we point out is we we joked in the paper 640 00:33:25,200 --> 00:33:27,080 Speaker 1: about don't ask us about dating advice, and I really 641 00:33:27,080 --> 00:33:28,920 Speaker 1: don't want a bunch of people ask me about dating advice, 642 00:33:28,960 --> 00:33:32,000 Speaker 1: but I do have some dating advice. Finally, this is good. 643 00:33:32,120 --> 00:33:34,800 Speaker 1: This is probably gonna be one of the first actionable 644 00:33:34,880 --> 00:33:37,440 Speaker 1: things on odd logever because you know, you we don't 645 00:33:37,480 --> 00:33:40,920 Speaker 1: normally are in the business of investing or trading advice 646 00:33:41,000 --> 00:33:43,520 Speaker 1: or anything, but finally someone is going to offer something 647 00:33:44,000 --> 00:33:47,760 Speaker 1: substance these apps spark. In many cases, the engineers at 648 00:33:47,800 --> 00:33:50,800 Speaker 1: the dating app companies are actually programmers who are coming 649 00:33:50,880 --> 00:33:55,040 Speaker 1: from slot machine programming jobs like gaming relays a Less 650 00:33:55,120 --> 00:33:59,120 Speaker 1: Vegas like that, so they are incredibly good at manipulating 651 00:33:59,120 --> 00:34:02,120 Speaker 1: these quick dopen feedback loops basically like you know, the 652 00:34:02,160 --> 00:34:06,200 Speaker 1: Stanford Marshmallow test thing, and everyone fails it, and everyone 653 00:34:06,240 --> 00:34:08,319 Speaker 1: fails it, particularly if it has anything to do with sex. 654 00:34:08,360 --> 00:34:11,560 Speaker 1: It just overrides everything else and you're you're competing against 655 00:34:11,600 --> 00:34:13,600 Speaker 1: your lizard brain. You're gonna lose. So it's very hard 656 00:34:13,640 --> 00:34:15,920 Speaker 1: to draw attention stand out. One of the ways that 657 00:34:15,960 --> 00:34:17,840 Speaker 1: you can, it seems like you can get around that 658 00:34:17,920 --> 00:34:20,279 Speaker 1: is if you can target or if you're if you're 659 00:34:20,280 --> 00:34:24,120 Speaker 1: targeting audiences that have a demonstrated ability to resist that. 660 00:34:24,680 --> 00:34:26,359 Speaker 1: And I think a good proxy for that is people 661 00:34:26,360 --> 00:34:28,560 Speaker 1: who are very passionate about something or some sort of 662 00:34:28,600 --> 00:34:31,759 Speaker 1: intense hobby or something like that where they're very very 663 00:34:31,760 --> 00:34:35,120 Speaker 1: focused on you know, long term skill development things like that, 664 00:34:35,239 --> 00:34:38,319 Speaker 1: so you know, athletes, artists, things like that, people who 665 00:34:38,360 --> 00:34:41,760 Speaker 1: are very very focused on kind of not immediate payoff 666 00:34:41,800 --> 00:34:43,719 Speaker 1: work and things like that. So I think a lot 667 00:34:43,760 --> 00:34:48,279 Speaker 1: of people are having very positive experiences meeting people. You know, 668 00:34:48,680 --> 00:34:49,799 Speaker 1: a lot of people when they go to a new 669 00:34:49,800 --> 00:34:51,239 Speaker 1: city are talking to me. They're like, well, how do 670 00:34:51,239 --> 00:34:52,480 Speaker 1: I meet people in a new city. I'm like, well, 671 00:34:52,480 --> 00:34:54,880 Speaker 1: you can do their dating apps. That's gonna work overall, 672 00:34:55,520 --> 00:34:58,160 Speaker 1: but you know, join a club, go do you know, 673 00:34:58,719 --> 00:35:00,160 Speaker 1: not to be too share as I go to a 674 00:35:00,280 --> 00:35:03,320 Speaker 1: cross fit class, go to yoga, go to an art class, 675 00:35:03,360 --> 00:35:06,239 Speaker 1: go like go do an activity, join some sort of 676 00:35:06,320 --> 00:35:09,799 Speaker 1: club where it's centered around everybody really enjoying that thing 677 00:35:09,800 --> 00:35:12,239 Speaker 1: and being very passionate about that. And that could be 678 00:35:12,320 --> 00:35:14,319 Speaker 1: a good place where again you can meet people in 679 00:35:14,360 --> 00:35:17,360 Speaker 1: real life who may share similar character traits that you 680 00:35:17,520 --> 00:35:20,319 Speaker 1: value and you can do well that way. But you've 681 00:35:20,320 --> 00:35:21,759 Speaker 1: really got to put yourself out there. And I think 682 00:35:21,760 --> 00:35:24,440 Speaker 1: the other thing is for people who are especially young professionals, 683 00:35:24,440 --> 00:35:25,920 Speaker 1: who are trying to you know, make it, and they're 684 00:35:25,960 --> 00:35:28,160 Speaker 1: grinding and they've got all these things going on. You know, 685 00:35:28,320 --> 00:35:30,480 Speaker 1: it is a lot of work. Very easy to hop 686 00:35:30,520 --> 00:35:32,640 Speaker 1: on your phone and just go swipe slight slip, swipe, 687 00:35:32,920 --> 00:35:35,160 Speaker 1: and then you've got a date versus you know, spending 688 00:35:35,200 --> 00:35:39,080 Speaker 1: several hours finding an activity, going to activity, you know, 689 00:35:39,120 --> 00:35:41,760 Speaker 1: going out and doing something and and so that's that's 690 00:35:41,800 --> 00:35:43,440 Speaker 1: a strategy that can work. It just takes a lot 691 00:35:43,440 --> 00:35:45,920 Speaker 1: of work. It's similar to doing kind of fundamental investing. 692 00:35:45,920 --> 00:35:48,080 Speaker 1: It You're gonna have to do an enormous amount of work. 693 00:35:48,480 --> 00:35:50,160 Speaker 1: And you're gonna feel really stupid about it a lot 694 00:35:50,160 --> 00:35:52,560 Speaker 1: of the time. You know, this is not an efficient 695 00:35:52,560 --> 00:35:55,080 Speaker 1: market in the sense that you can't achieve your desired 696 00:35:55,120 --> 00:35:58,600 Speaker 1: outcomes and you can't you know, find somebody. Everybody finds 697 00:35:58,600 --> 00:36:01,799 Speaker 1: somebody eventually. But I do think that focusing on people 698 00:36:01,840 --> 00:36:05,920 Speaker 1: who have kind of established delay gratification skills is a really, 699 00:36:06,000 --> 00:36:08,920 Speaker 1: really good strategy. And then I also think that you know, 700 00:36:09,000 --> 00:36:11,399 Speaker 1: time of day of when you're when you're using these 701 00:36:11,440 --> 00:36:14,440 Speaker 1: apps is very important given the queuing dynamics. And I 702 00:36:14,480 --> 00:36:16,560 Speaker 1: also I also think people should try out multiple apps 703 00:36:16,560 --> 00:36:18,000 Speaker 1: and figure out which ones they like, so you know, 704 00:36:18,040 --> 00:36:21,400 Speaker 1: for example, okay Cube, it provides a lot more information 705 00:36:21,440 --> 00:36:24,480 Speaker 1: about users. You're getting several pages of text about somebody 706 00:36:24,480 --> 00:36:27,040 Speaker 1: and you can respond, you can write something in any 707 00:36:27,080 --> 00:36:29,880 Speaker 1: case you actually care, and it's a lot slower of 708 00:36:29,920 --> 00:36:33,800 Speaker 1: a dynamic. Tender is a very quick lottery type dynamic 709 00:36:33,920 --> 00:36:36,520 Speaker 1: that really and like I think, unless you're like an 710 00:36:36,520 --> 00:36:39,000 Speaker 1: eight or above, I don't know why you're on tender personally, 711 00:36:39,160 --> 00:36:42,240 Speaker 1: You're just you have no shot TINGE has a different dynamic, 712 00:36:42,320 --> 00:36:46,040 Speaker 1: J swipe, different dynamic, you know, E harmony, things like that, 713 00:36:46,320 --> 00:36:49,040 Speaker 1: and some of these are really optimized for long term relationships, 714 00:36:49,040 --> 00:36:50,800 Speaker 1: and some of these are optimized to make you swipe, 715 00:36:51,239 --> 00:36:52,879 Speaker 1: And so I think you need to, like, you can't 716 00:36:52,960 --> 00:36:57,120 Speaker 1: judge the entire category by just doing one, and I 717 00:36:57,160 --> 00:36:59,080 Speaker 1: would just you know, encourage people to experiment with a 718 00:36:59,080 --> 00:37:00,840 Speaker 1: lot of them if if that's what they're looking for, 719 00:37:01,040 --> 00:37:04,080 Speaker 1: because they're very very different experiences app to app. Well, 720 00:37:04,200 --> 00:37:09,400 Speaker 1: this has been obviously some very useful insight into dating 721 00:37:09,480 --> 00:37:12,919 Speaker 1: and how to produce Alpha book. But we can't end 722 00:37:13,760 --> 00:37:17,560 Speaker 1: without talking at least a little bit about how you're 723 00:37:17,640 --> 00:37:20,960 Speaker 1: actually using your research. I mean, there's only so many 724 00:37:21,320 --> 00:37:24,600 Speaker 1: you know, obviously there's publicly traded online dating companies, but 725 00:37:24,640 --> 00:37:27,440 Speaker 1: not many like Matches one of them. What big picture, 726 00:37:27,600 --> 00:37:29,960 Speaker 1: this is research that you've done as part of your 727 00:37:30,000 --> 00:37:33,600 Speaker 1: fund and you talk about investing in dynamics that are 728 00:37:33,640 --> 00:37:36,319 Speaker 1: going to change the world over the next five to 729 00:37:36,360 --> 00:37:39,600 Speaker 1: ten years. So as you continue to build on this research, 730 00:37:40,120 --> 00:37:43,560 Speaker 1: where are the areas that people might look to see 731 00:37:43,920 --> 00:37:48,719 Speaker 1: the ramifications of the change in dating or mating habits 732 00:37:49,040 --> 00:37:52,720 Speaker 1: show up in the world of in the investable universe. 733 00:37:53,000 --> 00:37:55,880 Speaker 1: So obviously there's the publicly traded dating companies and you 734 00:37:55,920 --> 00:37:58,200 Speaker 1: know full disclosure we're long one of them. It's not 735 00:37:58,320 --> 00:38:01,040 Speaker 1: hard to guess which one. But I think one of 736 00:38:01,040 --> 00:38:02,960 Speaker 1: the things that really drew me into this subject to 737 00:38:03,040 --> 00:38:05,080 Speaker 1: dig into it deeper, and we're gonna be putting out 738 00:38:05,080 --> 00:38:08,840 Speaker 1: more research on this is household formation as a concept 739 00:38:08,920 --> 00:38:12,920 Speaker 1: has been a major driver of economic spending, you know, 740 00:38:13,080 --> 00:38:18,160 Speaker 1: purchasing a house, having kids, buying all this stuff, and 741 00:38:18,400 --> 00:38:21,520 Speaker 1: this is changing that dynamic. It's not eliminating it, but 742 00:38:21,560 --> 00:38:23,600 Speaker 1: it's changing it. And one of the things you've seen 743 00:38:23,600 --> 00:38:24,680 Speaker 1: in the last few year is that you know, a 744 00:38:24,719 --> 00:38:28,640 Speaker 1: lot of people comment on online all the time, is okay, 745 00:38:28,640 --> 00:38:30,960 Speaker 1: why are people getting married at different ages? And a 746 00:38:31,000 --> 00:38:32,719 Speaker 1: lot of people have jumped straight to oh, well, it's 747 00:38:32,760 --> 00:38:35,960 Speaker 1: just economic uncertainty, And no doubt it is one of 748 00:38:35,960 --> 00:38:39,120 Speaker 1: the variables in that equation is is economic uncertainty. But 749 00:38:39,160 --> 00:38:42,920 Speaker 1: I think online dating is actually very underappreciated factors. So 750 00:38:43,000 --> 00:38:45,680 Speaker 1: it might be a one percent waiting, but people might 751 00:38:45,719 --> 00:38:47,279 Speaker 1: have it in one percent waiting, but I think it's 752 00:38:47,320 --> 00:38:50,520 Speaker 1: probably more like a twenty or waiting because I think 753 00:38:50,520 --> 00:38:52,279 Speaker 1: when people get in a position where they're looking to 754 00:38:52,280 --> 00:38:55,520 Speaker 1: get married, that priorities reshift a lot. So I think 755 00:38:55,680 --> 00:38:59,520 Speaker 1: adding online dating in with what the income distribution the 756 00:38:59,560 --> 00:39:02,799 Speaker 1: United States really looks like, particularly among young people, and 757 00:39:02,840 --> 00:39:06,200 Speaker 1: particularly around housing prices and certain geographies is a very 758 00:39:06,280 --> 00:39:09,920 Speaker 1: very important explanatory variable. And so we're very focused on 759 00:39:10,040 --> 00:39:12,200 Speaker 1: another secular theme that we're very focused on. It will 760 00:39:12,239 --> 00:39:14,239 Speaker 1: probably be one of our next papers. I'm not sure 761 00:39:14,239 --> 00:39:15,680 Speaker 1: if it will be the first one or you know, 762 00:39:15,680 --> 00:39:17,560 Speaker 1: but it really coming out in the near future is 763 00:39:17,600 --> 00:39:21,080 Speaker 1: around affordable housing. There's a massive structural shortage of affordable 764 00:39:21,120 --> 00:39:23,759 Speaker 1: housing in the United States, and you could argue it's 765 00:39:23,800 --> 00:39:25,640 Speaker 1: ten to thirty million people, and you could argue that 766 00:39:25,680 --> 00:39:28,319 Speaker 1: it's growing. That shortage is growing at twenty to thirty 767 00:39:28,360 --> 00:39:31,279 Speaker 1: percent a year, and if that isn't solved in the 768 00:39:31,320 --> 00:39:34,120 Speaker 1: next five years, it's the only issue in every election. 769 00:39:34,160 --> 00:39:37,040 Speaker 1: And I'm baffled that this is not a bigger discussion. 770 00:39:37,520 --> 00:39:40,080 Speaker 1: So we think looking at the affordable housing shortage in 771 00:39:40,160 --> 00:39:44,640 Speaker 1: conjunction with people getting married later and also is going 772 00:39:44,680 --> 00:39:46,760 Speaker 1: to be a huge huge issue in terms of Okay, 773 00:39:46,760 --> 00:39:50,960 Speaker 1: how do families actually form, and then how many kids 774 00:39:50,960 --> 00:39:52,400 Speaker 1: are people having and what does that do to the 775 00:39:52,440 --> 00:39:56,560 Speaker 1: demographic kalens the United States, especially with our immigration policy 776 00:39:56,600 --> 00:39:59,480 Speaker 1: being fairly restrictive, right Now in addition to that, I think, 777 00:39:59,480 --> 00:40:02,560 Speaker 1: as I said, it is an instagrammification of dating. And 778 00:40:02,600 --> 00:40:05,640 Speaker 1: so you're seeing massive shifts and consumer trends. And I 779 00:40:05,640 --> 00:40:07,279 Speaker 1: don't know if you guys have noticed this, but there's 780 00:40:07,320 --> 00:40:09,960 Speaker 1: a huge boom and male cosmetics. And I don't mean 781 00:40:10,000 --> 00:40:11,680 Speaker 1: like just makeup. I mean there's a makeup brand I 782 00:40:11,719 --> 00:40:13,760 Speaker 1: was told about that's for men. It's called war Paint, 783 00:40:14,280 --> 00:40:15,880 Speaker 1: which I don't know an think about it beyond that, 784 00:40:15,960 --> 00:40:18,600 Speaker 1: but I think that's amazing branding. But you're seeing like 785 00:40:18,680 --> 00:40:20,560 Speaker 1: all these you know, I think they begin with beards. 786 00:40:20,600 --> 00:40:23,880 Speaker 1: There's been all these beard oils and waxes, and you know, 787 00:40:23,880 --> 00:40:27,359 Speaker 1: there's some company called Manscape is selling a male hair 788 00:40:27,440 --> 00:40:30,720 Speaker 1: trimmer and they have these hilarious ads. And now there's 789 00:40:30,840 --> 00:40:33,000 Speaker 1: the number of different male moisturizer brands. I was in 790 00:40:33,040 --> 00:40:35,200 Speaker 1: a target yesterday. There was an entire aisle of just 791 00:40:35,360 --> 00:40:38,480 Speaker 1: male skincare stuff. And to see that in a target 792 00:40:38,480 --> 00:40:40,719 Speaker 1: and risk in Virginia five or ten years ago is 793 00:40:40,760 --> 00:40:43,880 Speaker 1: completely unthinkable. I mean, it's ridiculous. And so I think 794 00:40:43,880 --> 00:40:47,520 Speaker 1: you're staying huge trends in particularly the startup market in 795 00:40:47,880 --> 00:40:51,560 Speaker 1: CPGs based off of people needing to look better on 796 00:40:51,719 --> 00:40:55,759 Speaker 1: camera to find somebody, and I think it's changing everything else. 797 00:40:55,800 --> 00:40:57,160 Speaker 1: And I think one of the other things that's not 798 00:40:57,160 --> 00:40:59,920 Speaker 1: appreciated is, you know, when you look at something like 799 00:41:00,080 --> 00:41:02,160 Speaker 1: match Group, you know, there's an argument you made that 800 00:41:02,440 --> 00:41:05,400 Speaker 1: they have a dominant position in that market. They just 801 00:41:05,440 --> 00:41:07,879 Speaker 1: did a partnership with Open Table, and so what they're 802 00:41:07,920 --> 00:41:09,840 Speaker 1: doing is they're going to partner with Open Table and 803 00:41:09,880 --> 00:41:13,600 Speaker 1: they're gonna place dates at restaurants. The margin that a 804 00:41:13,680 --> 00:41:17,560 Speaker 1: restaurant earns from somebody who is just going in and 805 00:41:17,600 --> 00:41:21,200 Speaker 1: buying a few drinks is astronomical compared to any other 806 00:41:21,200 --> 00:41:23,920 Speaker 1: type of customer they have, so they can actually pay 807 00:41:24,000 --> 00:41:26,040 Speaker 1: quite a bit for that. So what I'm also interested 808 00:41:26,080 --> 00:41:28,239 Speaker 1: to see, Okay, what other types of business models come 809 00:41:28,280 --> 00:41:31,400 Speaker 1: out of online dating. Did they start selling these cosmetics directly? 810 00:41:31,480 --> 00:41:35,520 Speaker 1: They start selling seats at bars, they start selling event tickets. 811 00:41:35,880 --> 00:41:37,680 Speaker 1: Did they start doing them your curated thing. One of 812 00:41:37,680 --> 00:41:39,319 Speaker 1: the questions that I had that I looked at a 813 00:41:39,320 --> 00:41:41,759 Speaker 1: lot when I was thinking about starting one was why 814 00:41:41,840 --> 00:41:43,880 Speaker 1: is there not an app that kind of continues to 815 00:41:43,920 --> 00:41:46,160 Speaker 1: work with you as you date. Why don't they Because 816 00:41:46,160 --> 00:41:48,200 Speaker 1: they'll they'll do a promotion and say Hey, you know, 817 00:41:48,320 --> 00:41:51,480 Speaker 1: five dollars off movie tickets or something. But why are 818 00:41:51,480 --> 00:41:54,360 Speaker 1: they not continuing to provide data date ideas? Why is 819 00:41:54,400 --> 00:41:56,920 Speaker 1: it not you know, the wine and painting thing, or 820 00:41:57,440 --> 00:41:59,799 Speaker 1: you know, go to Trapez on the West Side and 821 00:41:59,840 --> 00:42:02,200 Speaker 1: you or or something like that. I think there's a 822 00:42:02,239 --> 00:42:07,040 Speaker 1: lot of ways that products will be marketed through these 823 00:42:07,080 --> 00:42:10,080 Speaker 1: online dating platforms. So the online dating platforms are going 824 00:42:10,120 --> 00:42:12,960 Speaker 1: to change consumer demands. It's going to change how houseful 825 00:42:12,960 --> 00:42:15,520 Speaker 1: information is working. I think people are gonna start to 826 00:42:15,640 --> 00:42:18,399 Speaker 1: route a lot of products through online dating because it's 827 00:42:18,440 --> 00:42:23,000 Speaker 1: becoming a central nexus. And I think people below you know, thirty, 828 00:42:23,080 --> 00:42:25,439 Speaker 1: I think more of them are using Tender and things 829 00:42:25,480 --> 00:42:27,680 Speaker 1: like that on a daily basis and are using Facebook. 830 00:42:28,120 --> 00:42:30,560 Speaker 1: The opportunity to sell through there is huge, and so 831 00:42:30,600 --> 00:42:32,680 Speaker 1: it's gonna be this kind of nexus point between all 832 00:42:32,760 --> 00:42:35,160 Speaker 1: these big drivers. And maybe it's not that big of 833 00:42:35,200 --> 00:42:37,200 Speaker 1: a dollar category right now, but I think when you 834 00:42:37,200 --> 00:42:40,280 Speaker 1: think about it demographically going forward, particularly if you assume 835 00:42:40,360 --> 00:42:42,440 Speaker 1: that you know, people are not going to stop online 836 00:42:42,520 --> 00:42:44,880 Speaker 1: dating as they get older, if they're single again or 837 00:42:45,080 --> 00:42:47,279 Speaker 1: remain single, And that's what we're saying is they're seeing 838 00:42:47,280 --> 00:42:50,120 Speaker 1: older in order cohorts get online dating. So if you 839 00:42:50,120 --> 00:42:52,839 Speaker 1: think that this is gonna be the way people date 840 00:42:52,880 --> 00:42:55,680 Speaker 1: twenty years from now, and I do, then this is 841 00:42:55,680 --> 00:42:58,960 Speaker 1: going to be a massively important area to watch because 842 00:42:58,960 --> 00:43:01,799 Speaker 1: it's gonna give you leading indicators on household formation, it's 843 00:43:01,800 --> 00:43:04,960 Speaker 1: going to give you leading indicators on consumer brands. It's 844 00:43:04,960 --> 00:43:07,479 Speaker 1: gonna give you leading indicators on you know, what's cool 845 00:43:07,560 --> 00:43:09,640 Speaker 1: what's not cool. I mean you can see this on 846 00:43:09,680 --> 00:43:12,879 Speaker 1: Instagram all the time. People on Instagram are showing off 847 00:43:12,960 --> 00:43:15,200 Speaker 1: what they think are cool products, are cool things to do, 848 00:43:15,280 --> 00:43:17,880 Speaker 1: or this that or whatever. But online dating is a 849 00:43:17,920 --> 00:43:20,360 Speaker 1: super condensed version of that. You're not putting a picture 850 00:43:20,360 --> 00:43:23,279 Speaker 1: of yourself or content of yourself on an online dating 851 00:43:23,280 --> 00:43:26,239 Speaker 1: platform unless you think that is attractive to people. So 852 00:43:26,280 --> 00:43:28,680 Speaker 1: it's very very interesting the data and the insights that 853 00:43:28,680 --> 00:43:30,080 Speaker 1: can come out of this, and I think it has 854 00:43:30,120 --> 00:43:33,919 Speaker 1: huge implications for most of not all sectors. And it's 855 00:43:33,920 --> 00:43:36,440 Speaker 1: one of my favorite macro indicators actually looking at what's 856 00:43:36,440 --> 00:43:38,319 Speaker 1: going on in this dating market, not on a short 857 00:43:38,440 --> 00:43:40,360 Speaker 1: term basis, but I mean on a long term agrift 858 00:43:40,360 --> 00:43:42,600 Speaker 1: demographic basis. And I think it's also going to completely 859 00:43:42,680 --> 00:43:46,719 Speaker 1: reshape the entire societies in more conservative areas of the world, 860 00:43:46,719 --> 00:43:48,399 Speaker 1: where women are going to be able to step out 861 00:43:49,000 --> 00:43:52,759 Speaker 1: from behind a patriarchal society and have agency around their sexuality, 862 00:43:52,800 --> 00:43:55,719 Speaker 1: agency around their dating, agency around their marriage. You know, 863 00:43:55,880 --> 00:43:58,400 Speaker 1: it's not gonna happen all at once, and it's not 864 00:43:58,440 --> 00:44:00,520 Speaker 1: going to allow them to immediately snap the fingers and 865 00:44:00,560 --> 00:44:03,319 Speaker 1: be all good, but it's going to have this net 866 00:44:03,360 --> 00:44:05,799 Speaker 1: effect of starting a ripple process. It's just not going 867 00:44:05,840 --> 00:44:08,040 Speaker 1: to stop. And so I think that what's the biggest 868 00:44:08,080 --> 00:44:09,880 Speaker 1: point about online dating this interesting to me is what 869 00:44:09,960 --> 00:44:11,759 Speaker 1: is it going to do to emerging markets? And so 870 00:44:11,800 --> 00:44:14,000 Speaker 1: a lot of the big these emerging markets right now 871 00:44:14,160 --> 00:44:17,080 Speaker 1: is basically, other than plumbing, which is a huge issue, 872 00:44:17,719 --> 00:44:20,920 Speaker 1: smartphones are having this completely revolutionary idea. A lot of 873 00:44:20,920 --> 00:44:24,520 Speaker 1: people look at protests and things like that and they say, oh, well, 874 00:44:24,920 --> 00:44:27,840 Speaker 1: these protests are happening because the people are tired of 875 00:44:27,840 --> 00:44:29,560 Speaker 1: the corruption, and you know, I think they've been tired 876 00:44:29,600 --> 00:44:31,719 Speaker 1: of the coruption for a long time. The reason they're 877 00:44:31,719 --> 00:44:34,360 Speaker 1: protesting is they can coordinate, so they have smartphones. So 878 00:44:34,480 --> 00:44:37,440 Speaker 1: smartphones this vector that's changing every country in the world, 879 00:44:37,440 --> 00:44:39,560 Speaker 1: in the US as well, but not as much as 880 00:44:39,600 --> 00:44:43,480 Speaker 1: it's changing other countries. And I think that the specific 881 00:44:43,560 --> 00:44:47,600 Speaker 1: subvector within smartphones that's mattering the most emerging markets is 882 00:44:47,640 --> 00:44:50,960 Speaker 1: actually online dating, because it's going to unlock the value 883 00:44:51,000 --> 00:44:53,480 Speaker 1: and the agency and all the power of all the women, 884 00:44:53,520 --> 00:44:56,120 Speaker 1: which is half the damn population, and it's just gonna 885 00:44:56,160 --> 00:44:58,000 Speaker 1: be it's gonna be a much bigger issue. This is 886 00:44:58,040 --> 00:45:01,680 Speaker 1: not about people looking go out get laid at the bar. 887 00:45:01,960 --> 00:45:06,160 Speaker 1: This is a huge deal. Dan McMurtry, that was great. 888 00:45:06,360 --> 00:45:11,080 Speaker 1: Really enjoyed that conversation so much richer and thought provoking 889 00:45:11,440 --> 00:45:14,080 Speaker 1: than I had previously thought about the subject, which I 890 00:45:14,120 --> 00:45:16,520 Speaker 1: guess is kind of the whole reason you got into this. 891 00:45:16,560 --> 00:45:20,239 Speaker 1: But really appreciate you joining us. Thank you guys so much, 892 00:45:20,239 --> 00:45:22,839 Speaker 1: Really appreciate it. Happy to come on anytime. Thanks Dan. 893 00:45:23,120 --> 00:45:38,759 Speaker 1: Thanks Dan. That was great. Tracy. That really was, as 894 00:45:38,800 --> 00:45:41,719 Speaker 1: I said at the end, sort of far more interesting 895 00:45:41,960 --> 00:45:46,040 Speaker 1: in terms of the ramifications and follow on effects of 896 00:45:46,120 --> 00:45:49,080 Speaker 1: online dating than I had ever really thought about before. 897 00:45:49,520 --> 00:45:51,080 Speaker 1: I don't know about you, but it kind of has 898 00:45:51,120 --> 00:45:54,800 Speaker 1: me thinking about what my Tinder, my hypothetical Tinder profile 899 00:45:54,920 --> 00:45:57,520 Speaker 1: would actually look like. And I think, based on Dan's 900 00:45:57,600 --> 00:46:00,480 Speaker 1: observations and his dating advice, I would have to put 901 00:46:00,560 --> 00:46:05,040 Speaker 1: something about like I'm really good at delayed gratifications skills, 902 00:46:05,040 --> 00:46:07,960 Speaker 1: like that's what he might. Oh wait, that actually sounds 903 00:46:07,960 --> 00:46:11,000 Speaker 1: really bad. No. I think the idea is to demonstrate 904 00:46:11,520 --> 00:46:15,200 Speaker 1: that you have to pursuit right. Oh yes, that's right, 905 00:46:15,400 --> 00:46:21,160 Speaker 1: demonstrates that that attracts people who have delayed gratifications. So 906 00:46:21,680 --> 00:46:24,040 Speaker 1: the other thing that comes through from it is just 907 00:46:24,440 --> 00:46:27,839 Speaker 1: he mentioned the gamification of the entire dating strategy, which 908 00:46:27,880 --> 00:46:30,520 Speaker 1: is why, like they say, for guys on Tinder, you're 909 00:46:30,560 --> 00:46:34,279 Speaker 1: just supposed to swipe right constantly just to increase your 910 00:46:34,360 --> 00:46:37,319 Speaker 1: chances of getting a match. I didn't realize that the 911 00:46:37,520 --> 00:46:39,960 Speaker 1: time at which the time of day at which you 912 00:46:40,040 --> 00:46:42,400 Speaker 1: do it actually matters as well. That I was wondering 913 00:46:42,440 --> 00:46:44,200 Speaker 1: about that too, because maybe that would be my one 914 00:46:44,280 --> 00:46:46,480 Speaker 1: edge because I always get up at four am, So 915 00:46:46,520 --> 00:46:48,400 Speaker 1: I was thinking like, well, if I were getting up 916 00:46:48,440 --> 00:46:50,200 Speaker 1: at four am, I wonder if that would help me. 917 00:46:50,320 --> 00:46:53,600 Speaker 1: Like in the queue, you also have to wonder what 918 00:46:53,680 --> 00:46:57,319 Speaker 1: kind of people you're matching with it four am, I 919 00:46:57,360 --> 00:47:01,520 Speaker 1: can only imagine. But on his areous note, I mean 920 00:47:01,680 --> 00:47:05,600 Speaker 1: this notion that our economic models aren't really taking to 921 00:47:05,960 --> 00:47:09,520 Speaker 1: taking into account. What is a sweeping change to the 922 00:47:09,560 --> 00:47:12,440 Speaker 1: way society works. I think is a really interesting one, 923 00:47:12,480 --> 00:47:15,080 Speaker 1: and Dan made a very very good case for why 924 00:47:15,600 --> 00:47:18,640 Speaker 1: it matters in the broader economy and in the broader 925 00:47:18,680 --> 00:47:22,040 Speaker 1: consumer market as well. Yeah. Absolutely people should read the 926 00:47:22,080 --> 00:47:25,759 Speaker 1: paper and follow him. Yeah, for sure. The paper is 927 00:47:25,840 --> 00:47:31,280 Speaker 1: highly amusing. As mentioned earlier, this has been another edition 928 00:47:31,360 --> 00:47:34,120 Speaker 1: of the Odd Thoughts podcast. I'm Tracy Alloway. You can 929 00:47:34,160 --> 00:47:37,600 Speaker 1: follow me on Twitter at Tracy Alloway and I'm Joe 930 00:47:37,640 --> 00:47:40,000 Speaker 1: Why Isn't All? You could follow me on Twitter at 931 00:47:40,040 --> 00:47:43,920 Speaker 1: the Stalwart and you should definitely follow our guest today, 932 00:47:44,040 --> 00:47:49,200 Speaker 1: Dan McMurtry. He's at super Mugatu on Twitter. He's really 933 00:47:49,239 --> 00:47:52,080 Speaker 1: great because actually for a long time he was tseudonymous 934 00:47:52,120 --> 00:47:54,360 Speaker 1: and then at the time that he unveiled his dating paper, 935 00:47:54,440 --> 00:47:57,719 Speaker 1: he revealed his name to the public. Everyone should go 936 00:47:57,800 --> 00:48:00,000 Speaker 1: check it out. You could find links to the paper 937 00:48:00,080 --> 00:48:02,040 Speaker 1: or is there and all the other insights, all of 938 00:48:02,040 --> 00:48:05,320 Speaker 1: which are worth following. Be sure to follow our producer 939 00:48:05,440 --> 00:48:09,040 Speaker 1: on Twitter, Laura Carlson. She's at Laura M. Carlson, and 940 00:48:09,239 --> 00:48:13,239 Speaker 1: follow all of the Bloomberg podcast on Twitter at podcasts. 941 00:48:13,480 --> 00:48:14,200 Speaker 1: Thanks for listening.