1 00:00:00,080 --> 00:00:03,760 Speaker 1: I'm off my game today. No, you're not. People are 2 00:00:03,800 --> 00:00:05,640 Speaker 1: going to have to start making better content. I think 3 00:00:05,640 --> 00:00:07,160 Speaker 1: we're gonna be talking about this for a long time. 4 00:00:07,200 --> 00:00:10,200 Speaker 1: When you program for everyone, you programmed for no one. 5 00:00:10,200 --> 00:00:12,280 Speaker 1: I think it's a word purpose driven platform. Like we're 6 00:00:12,320 --> 00:00:15,640 Speaker 1: trying to get to substance. How was that? Are you 7 00:00:15,680 --> 00:00:19,160 Speaker 1: happy with that? This is marketing therapy right now? And 8 00:00:19,280 --> 00:00:23,840 Speaker 1: it really is? What's up on? Laura Currency and I'm 9 00:00:23,840 --> 00:00:27,640 Speaker 1: Alexa Kristen. Welcome back to at Landia Episode four. Here 10 00:00:27,680 --> 00:00:30,760 Speaker 1: we are. We're back this season of love, the season 11 00:00:30,800 --> 00:00:34,239 Speaker 1: of what Feb Feb this season of love. We're back 12 00:00:34,280 --> 00:00:36,599 Speaker 1: from the I A B. It was a really good 13 00:00:36,760 --> 00:00:39,760 Speaker 1: meeting a couple of days. We met some really cool 14 00:00:39,800 --> 00:00:44,159 Speaker 1: people and I be dropped some knowledge about DTC brands 15 00:00:44,560 --> 00:00:47,160 Speaker 1: and what they're doing in the space. And I think 16 00:00:47,479 --> 00:00:51,400 Speaker 1: for me at least, what was really interesting was this 17 00:00:51,920 --> 00:00:55,080 Speaker 1: very very clear kind of call out from the I 18 00:00:55,320 --> 00:01:02,160 Speaker 1: B about community, about content over advertising, and UM, we're 19 00:01:02,160 --> 00:01:04,360 Speaker 1: gonna have Randall Rothenberg on the show to kind of 20 00:01:04,560 --> 00:01:07,000 Speaker 1: walk through their findings because I thought that they were 21 00:01:07,000 --> 00:01:12,200 Speaker 1: really smart. But when we were talking to UM, Henry Davis, 22 00:01:12,280 --> 00:01:15,800 Speaker 1: the president and CEO of Glossier on stage the opening night. 23 00:01:16,600 --> 00:01:20,120 Speaker 1: One thing that Henry made really clear is, yes, we 24 00:01:20,280 --> 00:01:24,280 Speaker 1: use data and we're looking at certain signals with our consumers, 25 00:01:24,720 --> 00:01:27,880 Speaker 1: but if we are not in bed and we are 26 00:01:27,920 --> 00:01:30,840 Speaker 1: not part of the community, there's not a ton we 27 00:01:30,880 --> 00:01:34,600 Speaker 1: can do. And so how do we connect people around beauty? 28 00:01:34,760 --> 00:01:38,240 Speaker 1: How do we connect people around identities? And I'm I 29 00:01:38,280 --> 00:01:42,520 Speaker 1: think that that is not just for direct to consumer brands. 30 00:01:42,600 --> 00:01:45,280 Speaker 1: That's for everyone. And I think in not so subtle 31 00:01:45,319 --> 00:01:48,760 Speaker 1: away Henry said, and I'm paraphrasing, he said, you know, 32 00:01:49,080 --> 00:01:51,279 Speaker 1: kind of one of our next steps is to really 33 00:01:51,640 --> 00:01:55,559 Speaker 1: start building ways of having the community talk to each 34 00:01:55,560 --> 00:01:59,400 Speaker 1: other that and what does that mean? What does that mean? 35 00:01:59,480 --> 00:02:02,080 Speaker 1: Did they start becoming more of a technology brand or 36 00:02:02,160 --> 00:02:04,720 Speaker 1: on the side, I don't know. Yeah, what does it 37 00:02:04,760 --> 00:02:07,000 Speaker 1: mean when a beauty brand opens up a slack channel 38 00:02:07,040 --> 00:02:10,240 Speaker 1: where you know, or they becomes and whatnot are being shared, 39 00:02:10,520 --> 00:02:13,080 Speaker 1: or they become this lack of beauty right or they 40 00:02:13,080 --> 00:02:15,480 Speaker 1: could become a slack of you know, something like even 41 00:02:15,520 --> 00:02:19,040 Speaker 1: becoming the actual pipe. I think that starts getting really 42 00:02:19,080 --> 00:02:22,320 Speaker 1: interesting and then it also opens opportunities for new brands 43 00:02:22,360 --> 00:02:25,400 Speaker 1: to get in on and get away from a Facebook, 44 00:02:25,440 --> 00:02:29,200 Speaker 1: a Google, a YouTube, right and actually start interacting with 45 00:02:29,880 --> 00:02:34,280 Speaker 1: a community that a brand has created and communication channel 46 00:02:34,280 --> 00:02:37,200 Speaker 1: that they've created. It becomes an obsession, a place of obsession, 47 00:02:37,720 --> 00:02:39,880 Speaker 1: you know, where people you know, you're you're getting served 48 00:02:39,919 --> 00:02:43,000 Speaker 1: all the context as opposed to part of it. Yeah, 49 00:02:43,639 --> 00:02:46,120 Speaker 1: so we're going to have Melissa Habilei on who's the 50 00:02:46,160 --> 00:02:50,400 Speaker 1: CMO of okay Cupid? After the break and before we 51 00:02:50,440 --> 00:02:52,040 Speaker 1: get into that, one of the things that like I 52 00:02:52,040 --> 00:02:54,600 Speaker 1: think our minds are in the middle of the conversation 53 00:02:55,240 --> 00:02:58,679 Speaker 1: was around the incredible amount of data um and personal 54 00:02:58,840 --> 00:03:02,200 Speaker 1: personal details of at a apps are sitting on that 55 00:03:02,280 --> 00:03:05,040 Speaker 1: We were like, holy shit, how do you take this 56 00:03:05,919 --> 00:03:09,560 Speaker 1: and start to streamline insights and information back into the market. 57 00:03:09,800 --> 00:03:13,919 Speaker 1: That brings us to the next level, one layer deeper 58 00:03:14,400 --> 00:03:18,760 Speaker 1: into personas because the things that they're able to uncover 59 00:03:18,800 --> 00:03:21,480 Speaker 1: in terms of how you know persone wants to get 60 00:03:21,639 --> 00:03:23,880 Speaker 1: matched up with person B. I mean, those are the 61 00:03:23,880 --> 00:03:28,000 Speaker 1: most intimate parts of you. Where how where are they going? 62 00:03:28,280 --> 00:03:31,800 Speaker 1: Like where is it happening? Both from a geographical standpoint, 63 00:03:31,919 --> 00:03:34,840 Speaker 1: but like what are the topics and things that people 64 00:03:34,840 --> 00:03:37,560 Speaker 1: are identifying with, which I think is really surprising when 65 00:03:37,560 --> 00:03:42,960 Speaker 1: she starts talking about identities and where totally and and 66 00:03:43,000 --> 00:03:44,680 Speaker 1: there are things that you we would we were like 67 00:03:44,760 --> 00:03:48,080 Speaker 1: what we would have never guessed. She dropped some really 68 00:03:48,080 --> 00:03:54,840 Speaker 1: interesting insights around UM relationships, UM and psychographics and politics 69 00:03:55,760 --> 00:03:58,960 Speaker 1: that I think any brand should be listening to and 70 00:03:59,080 --> 00:04:01,360 Speaker 1: any brand should be aware of. It's not even about 71 00:04:01,400 --> 00:04:04,160 Speaker 1: being in the dating space. It's about how people are 72 00:04:04,680 --> 00:04:08,560 Speaker 1: starting to come together in intimate relationships. Yeah. Well, if 73 00:04:08,560 --> 00:04:12,760 Speaker 1: I'm I'm Starbucks or Dunkin Donuts and I know that 74 00:04:13,200 --> 00:04:16,440 Speaker 1: you know, insert data point. Here are the types of 75 00:04:16,440 --> 00:04:18,599 Speaker 1: people that are coming to have their first day over 76 00:04:19,120 --> 00:04:22,960 Speaker 1: you know, uh latte, and they want to talk about 77 00:04:23,000 --> 00:04:25,159 Speaker 1: this that can completely shape the way I'm communicating to 78 00:04:25,200 --> 00:04:28,400 Speaker 1: those consumers totally. And there's twenty million of them globally. Yeah, 79 00:04:28,440 --> 00:04:30,680 Speaker 1: it's impressive. I mean, it's impressively and it's I was 80 00:04:30,800 --> 00:04:32,240 Speaker 1: really I mean, I think she said it was like 81 00:04:32,240 --> 00:04:35,760 Speaker 1: a three point six billion dollar industry right now and growing. 82 00:04:36,880 --> 00:04:39,200 Speaker 1: It's big UM and I think it's the new way. 83 00:04:39,240 --> 00:04:42,440 Speaker 1: And Bumble is definitely cued into this because it's the 84 00:04:42,480 --> 00:04:46,640 Speaker 1: new way people are meeting, not even in romantic relationships, 85 00:04:46,640 --> 00:04:51,599 Speaker 1: but Bumble has gone into Buble relationships full stop. Right, yeah, 86 00:04:51,640 --> 00:04:54,039 Speaker 1: so that we are really excited to have Melissa on 87 00:04:54,400 --> 00:04:56,560 Speaker 1: and we hope all of you ad Landias out there 88 00:04:56,640 --> 00:05:12,320 Speaker 1: finding love in one way or another. Welcome back. We're 89 00:05:12,320 --> 00:05:15,560 Speaker 1: in the studio with Okay Cupid CMO Melissa Habiley, who 90 00:05:15,600 --> 00:05:18,520 Speaker 1: is reinventing the way we think about DTF. Welcome to 91 00:05:18,560 --> 00:05:25,040 Speaker 1: the show, Melissa, Welcome in India. So there's a lot 92 00:05:25,120 --> 00:05:28,400 Speaker 1: of competition in the dating app world, right, So everything 93 00:05:28,520 --> 00:05:31,359 Speaker 1: from the o G s like match dot Com to 94 00:05:32,040 --> 00:05:35,320 Speaker 1: the new ones like Tinder and Hinge and ball and 95 00:05:35,640 --> 00:05:39,000 Speaker 1: all of these. Um, you obviously came out swinging with 96 00:05:39,040 --> 00:05:41,800 Speaker 1: this new campaign. Can you tell us where the point 97 00:05:41,839 --> 00:05:45,919 Speaker 1: of differentiation exists for okay Cupid and why this campaign now? Yeah, 98 00:05:45,960 --> 00:05:47,880 Speaker 1: and thanks again for having us on to talk about this. 99 00:05:47,920 --> 00:05:51,239 Speaker 1: I think what we wanted to do was not create 100 00:05:51,400 --> 00:05:54,560 Speaker 1: something in isolation of me too and time's up and 101 00:05:54,680 --> 00:05:57,600 Speaker 1: all these conversations we were having and and what a 102 00:05:57,680 --> 00:06:00,760 Speaker 1: year it's been for women, and uh, you know, we 103 00:06:00,920 --> 00:06:04,000 Speaker 1: talked about Okay, well what are women dealing with today? 104 00:06:04,240 --> 00:06:07,880 Speaker 1: And we had you know, this term DTF is almost 105 00:06:07,960 --> 00:06:11,400 Speaker 1: often used by guys to talk to other guys about girls. 106 00:06:11,440 --> 00:06:14,920 Speaker 1: You don't have uh, you don't have a place in that, 107 00:06:14,960 --> 00:06:17,080 Speaker 1: you don't have a say in that. It's a label 108 00:06:17,160 --> 00:06:19,679 Speaker 1: that you probably did not co opt into. And so 109 00:06:20,200 --> 00:06:23,919 Speaker 1: when we were thinking, okay, Cupid's never had a campaign, 110 00:06:23,960 --> 00:06:27,440 Speaker 1: which is so crazy, there this o G dating app 111 00:06:27,480 --> 00:06:30,320 Speaker 1: that grew organically and had a great story and they 112 00:06:30,320 --> 00:06:33,360 Speaker 1: were all about the data. So around like four years, 113 00:06:33,640 --> 00:06:35,280 Speaker 1: I thought it was like ten or fourteen years. And 114 00:06:35,520 --> 00:06:37,000 Speaker 1: then you know, the thing about that is we've learned 115 00:06:37,000 --> 00:06:39,640 Speaker 1: a lot along the way. We've learned a lot, and 116 00:06:39,640 --> 00:06:41,960 Speaker 1: that's why we're really good at matching people. We have 117 00:06:42,160 --> 00:06:45,120 Speaker 1: more New York Times vows features than any other dating 118 00:06:45,120 --> 00:06:50,400 Speaker 1: app by a factor three. So um, we know we 119 00:06:50,440 --> 00:06:53,039 Speaker 1: do the best job of getting people together. And with DTF, 120 00:06:53,160 --> 00:06:56,920 Speaker 1: we you know what we didn't like was there are 121 00:06:56,920 --> 00:07:00,400 Speaker 1: phrases out there that make women feel worse about the selves. 122 00:07:00,680 --> 00:07:03,200 Speaker 1: And so the idea was, let's change it. We worked 123 00:07:03,200 --> 00:07:06,960 Speaker 1: with an unbelievable team at widen um, in particular jessin 124 00:07:07,040 --> 00:07:10,040 Speaker 1: Ian who were um, you know, carl Oeil who are 125 00:07:10,120 --> 00:07:13,080 Speaker 1: who are on the team, And the idea is, let's 126 00:07:13,080 --> 00:07:16,360 Speaker 1: subvert reclaim DTF. The f is whatever the fuck you 127 00:07:16,360 --> 00:07:18,000 Speaker 1: want it to be and you could be down to 128 00:07:18,000 --> 00:07:20,120 Speaker 1: the fuck, but like you own that it can be 129 00:07:20,440 --> 00:07:23,240 Speaker 1: down to fall head over heels um. The campaign was 130 00:07:23,240 --> 00:07:26,160 Speaker 1: shot by Maritio Catalan, who's one of those talked about 131 00:07:26,200 --> 00:07:29,080 Speaker 1: artists of today, most recently The Golden Toilet, which you know, 132 00:07:29,120 --> 00:07:32,080 Speaker 1: the Googenheim, very cheeky and a very cheeky way offered 133 00:07:32,080 --> 00:07:35,280 Speaker 1: to the White House and the spector is my hero. 134 00:07:35,840 --> 00:07:39,280 Speaker 1: I mean, I mean that's modern cur When has anyone 135 00:07:39,320 --> 00:07:42,000 Speaker 1: talked about the Gouggenheim as much as they have over 136 00:07:42,040 --> 00:07:43,920 Speaker 1: the last two or three weeks. She put them on 137 00:07:43,920 --> 00:07:46,360 Speaker 1: the map. And you know when we sat down in 138 00:07:46,400 --> 00:07:51,680 Speaker 1: Marizio and Pierre Palos partner UM in Creativity UM and Widen, 139 00:07:51,760 --> 00:07:54,400 Speaker 1: we were all brainstorming the FS. We wanted to shoot 140 00:07:54,440 --> 00:07:56,840 Speaker 1: and we wanted to have something that we're political. There's 141 00:07:56,880 --> 00:08:00,559 Speaker 1: this unprecedented moment right now politics and the roller and dating. 142 00:08:00,600 --> 00:08:02,560 Speaker 1: So we have down to filter out the far right, 143 00:08:02,600 --> 00:08:04,720 Speaker 1: which by the way, some places will not let us run. 144 00:08:05,040 --> 00:08:07,800 Speaker 1: We have down to um fight about the president. We 145 00:08:07,880 --> 00:08:10,560 Speaker 1: have romantic ones like down to fall ahead of our heels, 146 00:08:10,640 --> 00:08:13,000 Speaker 1: down to farmers market, down to floss together, because those 147 00:08:13,040 --> 00:08:14,280 Speaker 1: are some of the things that you do and you're 148 00:08:14,320 --> 00:08:16,680 Speaker 1: like early in the relationship, like an floss in front 149 00:08:16,680 --> 00:08:19,480 Speaker 1: of him. Um. And then we have things that are 150 00:08:19,600 --> 00:08:22,520 Speaker 1: you know, talking about this girl and you know people 151 00:08:22,560 --> 00:08:24,840 Speaker 1: are doing like down to fire up the kilns. People 152 00:08:24,840 --> 00:08:28,520 Speaker 1: are into that, down to focus on my chakras. Uh, 153 00:08:28,560 --> 00:08:30,280 Speaker 1: down to finish my novel because you've got a side 154 00:08:30,360 --> 00:08:32,679 Speaker 1: hustle and that's what your f is. And we just 155 00:08:32,760 --> 00:08:35,600 Speaker 1: want to affirm you. And you talked about, you know, 156 00:08:35,920 --> 00:08:40,199 Speaker 1: this idea of dating being in this world of substance 157 00:08:40,240 --> 00:08:44,040 Speaker 1: over selfies. Why do you think that's changed and how 158 00:08:44,040 --> 00:08:46,560 Speaker 1: do you see Okay Cupid helping to elevate that in 159 00:08:46,559 --> 00:08:49,480 Speaker 1: the dating world. What we notice is people are connecting 160 00:08:49,480 --> 00:08:52,280 Speaker 1: on issues and so we just started leaning into that. UM. 161 00:08:52,280 --> 00:08:55,719 Speaker 1: We noticed that both men and women started talking politics 162 00:08:55,720 --> 00:08:58,600 Speaker 1: in their profile. So there's been a one thousand percent 163 00:08:58,720 --> 00:09:02,120 Speaker 1: increase in political terms used in your profile in just 164 00:09:02,320 --> 00:09:04,760 Speaker 1: two years. What are some of those words, so it 165 00:09:04,760 --> 00:09:09,360 Speaker 1: could be progressive, liberal, republican, politically active, some of the 166 00:09:09,360 --> 00:09:14,640 Speaker 1: ones that you might expect, voting, UM, activists. Those are 167 00:09:14,840 --> 00:09:18,720 Speaker 1: all phrases that we're seeing people use. The Women's March 168 00:09:19,440 --> 00:09:21,800 Speaker 1: became a really popular price for women to put their 169 00:09:21,800 --> 00:09:25,640 Speaker 1: profile picture. And that is really important because you're signaling 170 00:09:25,640 --> 00:09:30,439 Speaker 1: what you're about this isdies. Yeah, And isn't it cool 171 00:09:30,520 --> 00:09:33,439 Speaker 1: that people are connecting not just and are you attractive 172 00:09:33,600 --> 00:09:35,000 Speaker 1: and do you want to make out with them or 173 00:09:35,040 --> 00:09:37,080 Speaker 1: take their clothes off? But are you like attracted to 174 00:09:37,080 --> 00:09:39,760 Speaker 1: their mind? Their brain? And that stuff is a really 175 00:09:39,800 --> 00:09:43,080 Speaker 1: good starting point. What's what we're noticing is when people 176 00:09:43,120 --> 00:09:45,439 Speaker 1: are upfront about I'm really passion about climate change, I'm 177 00:09:45,440 --> 00:09:49,760 Speaker 1: really passionate about voter rights, I'm I'm passionate about women's 178 00:09:49,840 --> 00:09:51,760 Speaker 1: right to choose, whatever those issues are. We see that 179 00:09:51,840 --> 00:09:54,520 Speaker 1: both sides are connecting over that. How many people are 180 00:09:54,559 --> 00:09:58,800 Speaker 1: on last year we had twenty million users. Now that's 181 00:09:58,800 --> 00:10:01,600 Speaker 1: around the world, that's globe. Our biggest audience is in 182 00:10:02,120 --> 00:10:04,480 Speaker 1: in the US. You know, it's interesting as you're talking, 183 00:10:04,520 --> 00:10:07,439 Speaker 1: you know, the idea that people are coming forth with 184 00:10:07,480 --> 00:10:10,600 Speaker 1: this information in such an intimate place, right, So, as 185 00:10:10,640 --> 00:10:12,880 Speaker 1: you think about audience personas, and we talk a lot 186 00:10:12,920 --> 00:10:16,760 Speaker 1: about use cases of data and how brands stand to 187 00:10:16,800 --> 00:10:19,200 Speaker 1: be able to actually monetize that or use it in 188 00:10:19,240 --> 00:10:23,200 Speaker 1: a way that is providing value or insight back into 189 00:10:23,240 --> 00:10:27,320 Speaker 1: our industry. Right. So, yeah, the data that you're aggregating 190 00:10:27,760 --> 00:10:32,439 Speaker 1: is essentially more intimate, seemingly truthful and real because it's 191 00:10:32,480 --> 00:10:35,200 Speaker 1: the most personal part of you. And so are you 192 00:10:35,320 --> 00:10:37,680 Speaker 1: doing anything with a lot of this data that you're 193 00:10:37,760 --> 00:10:42,240 Speaker 1: curating and um, that would be provocative and insightful to 194 00:10:42,280 --> 00:10:44,160 Speaker 1: the marketing industry at large? Do you plan to kind 195 00:10:44,200 --> 00:10:45,880 Speaker 1: of come out with anything that talks about That's a 196 00:10:46,000 --> 00:10:49,280 Speaker 1: great question. Right now, we only use it to better 197 00:10:49,400 --> 00:10:52,720 Speaker 1: understand how do we get more people together? Um. We 198 00:10:52,920 --> 00:10:56,920 Speaker 1: certainly have been able to use that for good in 199 00:10:56,960 --> 00:11:00,920 Speaker 1: a few ways, like drawing attention to votes that would 200 00:11:00,920 --> 00:11:05,559 Speaker 1: have impacted health care for women, you know, right, so 201 00:11:05,960 --> 00:11:08,640 Speaker 1: we're able to see things like when you know your 202 00:11:08,760 --> 00:11:11,560 Speaker 1: dating app is the app you are using probably the 203 00:11:11,559 --> 00:11:13,280 Speaker 1: most on your phone and as you said, the most 204 00:11:13,280 --> 00:11:17,480 Speaker 1: personal and most vulnerable, the most intimate. Uh. Um, we 205 00:11:17,920 --> 00:11:20,200 Speaker 1: right now we're really used man Tower just again understand 206 00:11:20,200 --> 00:11:22,839 Speaker 1: how people are getting together? How do we help you? Right? 207 00:11:22,920 --> 00:11:25,360 Speaker 1: So one of the things we we introduced this tool 208 00:11:25,400 --> 00:11:28,280 Speaker 1: where you could actually search around passions. We're kind of 209 00:11:28,280 --> 00:11:30,120 Speaker 1: famous for these questions that you have to answer to 210 00:11:30,120 --> 00:11:32,000 Speaker 1: on board, and we have three thousand them. You have 211 00:11:32,040 --> 00:11:34,719 Speaker 1: to answer fifteen and some of those are political. You 212 00:11:34,720 --> 00:11:36,520 Speaker 1: can skip them until you get questions you want and 213 00:11:36,520 --> 00:11:39,760 Speaker 1: you tell us how important those are. And so we 214 00:11:39,840 --> 00:11:42,040 Speaker 1: had seen you know, we dropped in a question and 215 00:11:42,120 --> 00:11:44,160 Speaker 1: me too, would you ever date someone that didn't support 216 00:11:44,200 --> 00:11:49,559 Speaker 1: me to not? Surprisingly? You know women would not you know. Um, 217 00:11:49,640 --> 00:11:51,880 Speaker 1: So when we we were asking questions about like how 218 00:11:51,880 --> 00:11:53,199 Speaker 1: do you feel about what's happening out there? How do 219 00:11:53,200 --> 00:11:54,920 Speaker 1: you feel at the conversations that are taking place? And 220 00:11:54,920 --> 00:11:58,280 Speaker 1: that helped us inform the DTF campaign. Are you updating 221 00:11:58,280 --> 00:12:03,880 Speaker 1: those questions like all you have some and so what 222 00:12:03,960 --> 00:12:06,280 Speaker 1: how do it? What? What's the scale of saying I'm 223 00:12:06,320 --> 00:12:08,760 Speaker 1: gonna we're gonna bring in me to questions like what's 224 00:12:08,800 --> 00:12:10,959 Speaker 1: that scale? When do you decide? Do you know what's 225 00:12:11,000 --> 00:12:13,600 Speaker 1: so cool? And this is why the culture okay cup, 226 00:12:13,640 --> 00:12:17,400 Speaker 1: it is great. At seven am we'll say, hey, you 227 00:12:17,400 --> 00:12:19,400 Speaker 1: know we slat we should we need to drop this 228 00:12:19,480 --> 00:12:22,319 Speaker 1: question in um and use this to help connect people. 229 00:12:22,960 --> 00:12:26,760 Speaker 1: And by seven thirty it's in. Wow, it's it's if 230 00:12:26,760 --> 00:12:29,200 Speaker 1: this okay cube. It is a really fast moving operation. 231 00:12:29,280 --> 00:12:32,559 Speaker 1: And what's lovely is you make decisions quickly. We don't 232 00:12:32,600 --> 00:12:34,440 Speaker 1: let time kill the Yeah, well you kind of have 233 00:12:34,480 --> 00:12:36,480 Speaker 1: to because these are the conversations people are having on 234 00:12:36,520 --> 00:12:39,840 Speaker 1: their days over drink. Yeah, that's exactly right, Like, shouldn't 235 00:12:39,840 --> 00:12:42,360 Speaker 1: your dating app be reflecting like what the conversations you're 236 00:12:42,360 --> 00:12:45,440 Speaker 1: having at bars? Or I think you're in a really 237 00:12:45,440 --> 00:12:48,400 Speaker 1: interesting position as you think about dating and sort of 238 00:12:48,440 --> 00:12:51,080 Speaker 1: the conversations that are happening as a part of this 239 00:12:51,240 --> 00:12:56,440 Speaker 1: culture or really what's informing society and vice versa. And 240 00:12:56,520 --> 00:12:59,280 Speaker 1: so you're kind of at this interesting intersection where you're 241 00:12:59,320 --> 00:13:01,559 Speaker 1: really in the in the thick of it, where other 242 00:13:01,559 --> 00:13:03,240 Speaker 1: people are like, should we go there? Should we not? 243 00:13:03,280 --> 00:13:04,640 Speaker 1: Like you, you don't really have a choice, do you, 244 00:13:04,880 --> 00:13:07,440 Speaker 1: We don't have a choice, And frankly, we think listen. 245 00:13:07,520 --> 00:13:09,640 Speaker 1: Let's also be totally clear. I mean, you guys are 246 00:13:09,800 --> 00:13:12,880 Speaker 1: the experts on this stuff. It's a good brand decision, right. 247 00:13:12,920 --> 00:13:15,240 Speaker 1: If you are talking to everybody, you're talking to nobody 248 00:13:15,280 --> 00:13:21,559 Speaker 1: and so so be distinctive and like right, and so 249 00:13:22,080 --> 00:13:24,920 Speaker 1: you know, you you've got to you've got to tell 250 00:13:25,000 --> 00:13:27,840 Speaker 1: people what you're about. And you know, like yesterday I 251 00:13:27,880 --> 00:13:30,800 Speaker 1: was like getting coffee and like Starbucks is grant behemous 252 00:13:30,800 --> 00:13:33,120 Speaker 1: and people feel whatever, But you know, I love about Starbucks. 253 00:13:33,200 --> 00:13:35,360 Speaker 1: Their benefits are great. You know, the benefits are because 254 00:13:35,840 --> 00:13:37,640 Speaker 1: comes from a blue collar family. His father broke his 255 00:13:37,720 --> 00:13:40,000 Speaker 1: ankle or something and his family couldn't eat for a 256 00:13:40,080 --> 00:13:42,360 Speaker 1: few months because of that. And they provide I V 257 00:13:42,679 --> 00:13:45,160 Speaker 1: for women. So I'm like, I'm happy to support that. 258 00:13:45,160 --> 00:13:49,520 Speaker 1: Even so, what what? What matters to people more so 259 00:13:49,640 --> 00:13:51,600 Speaker 1: than ever, You guys are doing a really good job 260 00:13:51,720 --> 00:13:54,720 Speaker 1: talking about it is what your brand cares about, what 261 00:13:54,760 --> 00:13:56,559 Speaker 1: they get behind and if they make a statement or 262 00:13:56,600 --> 00:13:59,320 Speaker 1: not does matter, And it matters if I'm going to 263 00:13:59,440 --> 00:14:01,720 Speaker 1: choose you or someone else. By the way, Okay, Cupid 264 00:14:01,800 --> 00:14:05,280 Speaker 1: is free, so you know, we have a premium service, um, 265 00:14:05,280 --> 00:14:06,760 Speaker 1: which is great and that's where a lot of our 266 00:14:06,760 --> 00:14:10,679 Speaker 1: revenue comes from. But um, you know, you've got to 267 00:14:10,720 --> 00:14:14,640 Speaker 1: take some bold moves and tell people what you care about. 268 00:14:14,760 --> 00:14:17,320 Speaker 1: We were the first big dating app to create non 269 00:14:17,360 --> 00:14:20,000 Speaker 1: binary gender options. We're one of the first big dating 270 00:14:20,040 --> 00:14:22,520 Speaker 1: apps to create a great experience for l g B 271 00:14:22,640 --> 00:14:25,760 Speaker 1: t Q. And is there a business case for creating 272 00:14:25,760 --> 00:14:28,440 Speaker 1: not We have twenty two gender options. The the amount 273 00:14:28,440 --> 00:14:33,200 Speaker 1: of time and money and two gender options, there's no 274 00:14:33,240 --> 00:14:36,680 Speaker 1: business case that would ever justify what we invested in that. 275 00:14:36,760 --> 00:14:40,320 Speaker 1: But it's the right thing to do. Our ecosystems care 276 00:14:40,400 --> 00:14:42,360 Speaker 1: that we do that, they care that their friends who 277 00:14:42,440 --> 00:14:44,240 Speaker 1: are in those scenarios where you know, one of our 278 00:14:44,280 --> 00:14:47,680 Speaker 1: hero images from DTF is two women in an embrace 279 00:14:47,960 --> 00:14:51,960 Speaker 1: and and like, you know, the big business opportunities of 280 00:14:52,040 --> 00:14:56,520 Speaker 1: the heterosexual audience, but our audience cares that we support that. 281 00:14:57,040 --> 00:14:58,600 Speaker 1: I loved that because what you see now is when 282 00:14:58,600 --> 00:15:00,960 Speaker 1: Cecili Richards is posting, she's saying about Black Lives Matter, 283 00:15:01,000 --> 00:15:07,000 Speaker 1: she's posting about many issues beyond the issue of women's health. 284 00:15:07,240 --> 00:15:10,520 Speaker 1: And you see that out of a number of movements, um, 285 00:15:10,560 --> 00:15:12,840 Speaker 1: you know, people supporting each other. And so we want 286 00:15:12,880 --> 00:15:15,600 Speaker 1: to play in that space as much as we can 287 00:15:15,640 --> 00:15:19,680 Speaker 1: authentically do that. Does Okay Cupid or does any dating 288 00:15:19,680 --> 00:15:23,920 Speaker 1: app go too far? And having perspective like I don't 289 00:15:23,920 --> 00:15:25,840 Speaker 1: think they go far enough, you know, I think that 290 00:15:25,960 --> 00:15:28,120 Speaker 1: I really don't. I don't think enough brands are going 291 00:15:28,120 --> 00:15:31,360 Speaker 1: far enough, you know, um several years ago. But this 292 00:15:31,440 --> 00:15:34,320 Speaker 1: is here's what's really awesome about my position is okay, 293 00:15:34,400 --> 00:15:36,440 Speaker 1: keep it as a track record of this. When the 294 00:15:36,440 --> 00:15:40,480 Speaker 1: then CEO of Mozilla made home of comments, we immediately 295 00:15:40,720 --> 00:15:43,800 Speaker 1: said you were not participating. We will not be able 296 00:15:43,840 --> 00:15:46,440 Speaker 1: to use this the Mozilla argument. Earlier this year, we 297 00:15:46,480 --> 00:15:48,080 Speaker 1: had a white supremacist on this site, one of the 298 00:15:48,160 --> 00:15:51,480 Speaker 1: Charlotte organizers, and we booted him out very quickly. It 299 00:15:51,520 --> 00:15:54,080 Speaker 1: was in corporate and we had a hundred sixty thousand 300 00:15:54,120 --> 00:15:58,200 Speaker 1: tweets in like ten hours. And so we are unapologetic 301 00:15:58,280 --> 00:16:00,520 Speaker 1: about some of this stuff. I think I think more 302 00:16:00,520 --> 00:16:02,840 Speaker 1: brands and companies need to take some I think it's 303 00:16:02,960 --> 00:16:06,800 Speaker 1: easier for you. It is easier, No, but it but 304 00:16:06,960 --> 00:16:10,080 Speaker 1: acknowledging that it is easier, you should do it. I 305 00:16:10,120 --> 00:16:13,720 Speaker 1: think you know how to brands start stepping into owning 306 00:16:14,120 --> 00:16:16,960 Speaker 1: their perspective. How how do you you know outside of 307 00:16:16,960 --> 00:16:20,320 Speaker 1: how does a CpG start to do that? It's a 308 00:16:20,360 --> 00:16:22,560 Speaker 1: really tough It's a tough Wait. Who do you guys 309 00:16:22,600 --> 00:16:24,440 Speaker 1: think is doing a good job at that? I think 310 00:16:24,480 --> 00:16:29,280 Speaker 1: done amazing job. Teen Folk. I think teen freaking Vogue 311 00:16:29,360 --> 00:16:33,560 Speaker 1: and like what Elaine um Walter Ross did when she 312 00:16:33,720 --> 00:16:39,200 Speaker 1: was at the editor, Holy sh it ll All of 313 00:16:39,240 --> 00:16:42,400 Speaker 1: a sudden, teen Vogue went from play cating and trying 314 00:16:42,440 --> 00:16:45,720 Speaker 1: to sell advertising really at the end of the day 315 00:16:46,160 --> 00:16:50,360 Speaker 1: too tweens and teens to having a perspective and rooting 316 00:16:50,360 --> 00:16:53,600 Speaker 1: themselves in issues and conversations that we're actually being had, 317 00:16:53,720 --> 00:16:56,560 Speaker 1: which you are doing. You know, I think we have 318 00:16:56,600 --> 00:16:59,720 Speaker 1: an opportunity but also responsibility. I think you're dating episode, 319 00:16:59,760 --> 00:17:02,840 Speaker 1: you're vulnerable, it's like you're falling in love. You've got 320 00:17:02,920 --> 00:17:06,280 Speaker 1: to be connected to what people are talking about and 321 00:17:06,280 --> 00:17:09,800 Speaker 1: and you know that's where the opportunity is. You mentioned 322 00:17:09,800 --> 00:17:12,439 Speaker 1: that you're a free service, which means you have to 323 00:17:13,119 --> 00:17:18,160 Speaker 1: revenue dollars. So as somebody who is taking these provocative 324 00:17:18,920 --> 00:17:24,040 Speaker 1: um stances around, you know, different thematics and culture, society, 325 00:17:24,080 --> 00:17:29,400 Speaker 1: et cetera, how are brands reacting that need to reach 326 00:17:29,480 --> 00:17:31,480 Speaker 1: this audience and advertise on your site. Yeah, that's a 327 00:17:31,520 --> 00:17:34,879 Speaker 1: great question because this isn't for everyone. And as we 328 00:17:35,000 --> 00:17:39,560 Speaker 1: become sharper about who we are for and what we're 329 00:17:39,600 --> 00:17:42,000 Speaker 1: about and what we're gonna put our time and energy into, um, 330 00:17:42,040 --> 00:17:44,200 Speaker 1: some folks are gonna say that's not for us. And 331 00:17:44,720 --> 00:17:46,800 Speaker 1: I'm really blessed to be in a position where you know, 332 00:17:46,840 --> 00:17:51,720 Speaker 1: we're supported in doing that. Um. But yeah, it's not 333 00:17:51,720 --> 00:17:53,679 Speaker 1: going to be for everyone. Who's who's like one of 334 00:17:53,720 --> 00:17:56,040 Speaker 1: your you don't have to name the brand, but category 335 00:17:56,119 --> 00:18:01,000 Speaker 1: who's like category wise top advertiser. Okay, Cuban, you know, 336 00:18:01,480 --> 00:18:05,920 Speaker 1: um we it's interesting because it's changed a lot, and 337 00:18:05,960 --> 00:18:07,280 Speaker 1: I think it's going to change a lot in the 338 00:18:07,320 --> 00:18:09,640 Speaker 1: next few years. I think what we're seeing our brands 339 00:18:09,640 --> 00:18:14,200 Speaker 1: that you guys have talked about who care about uh 340 00:18:14,400 --> 00:18:17,200 Speaker 1: more than just having the best product in ex category. 341 00:18:17,280 --> 00:18:22,600 Speaker 1: They care about consumers and what they're doing and and 342 00:18:22,800 --> 00:18:25,520 Speaker 1: having a point of view on that stuff. So, um, 343 00:18:25,640 --> 00:18:27,119 Speaker 1: you know, I'll tell you who I love to have 344 00:18:27,520 --> 00:18:29,959 Speaker 1: you just you see with them the Cards against Humanity 345 00:18:30,000 --> 00:18:32,919 Speaker 1: people did the wall and then you could get anyway. 346 00:18:32,960 --> 00:18:36,680 Speaker 1: I just thought, you know they are Actually that would 347 00:18:36,680 --> 00:18:40,120 Speaker 1: be such a fun partnership with you guys, so fun. Um. 348 00:18:40,200 --> 00:18:43,360 Speaker 1: We have partnership with Rosetta Stone interestingly, But the idea 349 00:18:43,480 --> 00:18:46,760 Speaker 1: was about we're seeing people as being different languages. As 350 00:18:46,840 --> 00:18:50,240 Speaker 1: border walls go up, people are more open and interested 351 00:18:50,280 --> 00:18:53,960 Speaker 1: than ever before in connecting with people that aren't from 352 00:18:54,000 --> 00:18:59,119 Speaker 1: that um from UM they're saying geography, background, et cetera. 353 00:18:59,240 --> 00:19:01,040 Speaker 1: So there's a fast extady that came out this year, 354 00:19:01,160 --> 00:19:04,240 Speaker 1: UM from like really similar people at like Nancy Colleges. Uh. 355 00:19:04,280 --> 00:19:06,719 Speaker 1: And the study was way sort of thing. The study 356 00:19:06,840 --> 00:19:09,640 Speaker 1: was there has been an unpresident arise in interracial marriages, 357 00:19:09,680 --> 00:19:13,119 Speaker 1: and that exactly correlates to when we saw dating apps 358 00:19:13,119 --> 00:19:16,920 Speaker 1: come onto the scene, and that is so exciting. Community borders. 359 00:19:16,960 --> 00:19:18,960 Speaker 1: It breaks down to ours exactly and you know, so 360 00:19:19,000 --> 00:19:21,440 Speaker 1: we we have we work with some really um clever 361 00:19:21,520 --> 00:19:23,399 Speaker 1: social scientists and people that are wet silier than us 362 00:19:23,440 --> 00:19:26,359 Speaker 1: and say, hey, so why are we attracted to attracted to? Right? Like, 363 00:19:26,400 --> 00:19:28,959 Speaker 1: that's one of the most basic questions. It's fascinating. One 364 00:19:29,000 --> 00:19:31,240 Speaker 1: of the elements, one of the ingredients, if you will, 365 00:19:31,440 --> 00:19:36,520 Speaker 1: of attraction is familiarity. Um, most people are attracted to 366 00:19:36,560 --> 00:19:40,119 Speaker 1: what they grew up with because it's familiar, and we 367 00:19:40,119 --> 00:19:43,360 Speaker 1: don't understand, you know, subconsciously why we attracted what we attracted. 368 00:19:43,359 --> 00:19:45,560 Speaker 1: But that's one of the drivers. So what happens is 369 00:19:45,600 --> 00:19:49,640 Speaker 1: in a dating app, you may not may you will 370 00:19:49,720 --> 00:19:53,320 Speaker 1: be exposed to more people than, um, what you grew 371 00:19:53,400 --> 00:19:56,479 Speaker 1: up with, and you start to break down kind of 372 00:19:56,520 --> 00:19:59,720 Speaker 1: the paranters that maybe you had. My husband's Asian If 373 00:19:59,720 --> 00:20:00,920 Speaker 1: you ever might I have been married to an Asian 374 00:20:00,960 --> 00:20:03,480 Speaker 1: Australian guy as a girl growing up in Indiana, I 375 00:20:03,480 --> 00:20:08,920 Speaker 1: would have said that sounds fun. I guess, like, you know, um, 376 00:20:09,320 --> 00:20:13,040 Speaker 1: and and that's awesome. Less in ten percent of people 377 00:20:13,040 --> 00:20:15,920 Speaker 1: and okay, Cupid even use a race or an ethnic 378 00:20:16,000 --> 00:20:20,159 Speaker 1: filters and ten percent, isn't that great? We're all and 379 00:20:20,200 --> 00:20:22,679 Speaker 1: we don't we we do not let you tell us 380 00:20:22,680 --> 00:20:24,800 Speaker 1: here's the eye color and the hair color that we 381 00:20:24,800 --> 00:20:29,240 Speaker 1: don't we don't allow that. We don't want to encourage that. Um. 382 00:20:29,400 --> 00:20:31,840 Speaker 1: I want to be about the story and are they 383 00:20:31,880 --> 00:20:34,639 Speaker 1: funny and all these things. UM, So we're seeing some 384 00:20:34,800 --> 00:20:38,720 Speaker 1: very really really fascinating shifts. Um you know, okay, cue, 385 00:20:38,720 --> 00:20:40,760 Speaker 1: but it's the most interesting because we have such a 386 00:20:40,760 --> 00:20:43,439 Speaker 1: a thriving presence in city. So you can san do 387 00:20:43,440 --> 00:20:45,920 Speaker 1: you guys work with like anyone in like on a 388 00:20:46,280 --> 00:20:50,399 Speaker 1: on a like n GEO level government level. Like some 389 00:20:50,480 --> 00:20:55,480 Speaker 1: of this data is freaking fascinating. Is rightly different type 390 00:20:55,520 --> 00:20:58,119 Speaker 1: of census data. It's it's fascinating. It's interesting. We we 391 00:20:58,160 --> 00:21:00,600 Speaker 1: did it. We did a big debate this week actually 392 00:21:00,920 --> 00:21:04,360 Speaker 1: um on our dating apps killing romance. And by the way, 393 00:21:04,359 --> 00:21:06,200 Speaker 1: we won the debate in a bit. And and they 394 00:21:06,200 --> 00:21:08,480 Speaker 1: take these very seriously deep Ac Chopra and Peter Teal 395 00:21:08,680 --> 00:21:11,400 Speaker 1: and Malcolm Gladwell all these people do this debate called 396 00:21:11,400 --> 00:21:17,760 Speaker 1: intelligence square and and we looked at we can't share 397 00:21:17,880 --> 00:21:20,600 Speaker 1: our data unless you know or we have to be 398 00:21:20,640 --> 00:21:23,040 Speaker 1: very careful to and when we are. But UM, one 399 00:21:23,080 --> 00:21:25,680 Speaker 1: of the allow of the day points ruling as the 400 00:21:25,800 --> 00:21:30,280 Speaker 1: rising number of marriages and the rates of divorce are falling. 401 00:21:30,480 --> 00:21:32,919 Speaker 1: No one's saying that. No one's talked because people are 402 00:21:32,920 --> 00:21:35,800 Speaker 1: getting married later and they're going for substance over selfie. 403 00:21:35,800 --> 00:21:38,560 Speaker 1: And this is one of the biggest impacts is because 404 00:21:38,600 --> 00:21:41,119 Speaker 1: women are working, so they and their identity is no 405 00:21:41,200 --> 00:21:43,919 Speaker 1: longer like maybe our moms. There the AGENTA was largely 406 00:21:43,960 --> 00:21:48,680 Speaker 1: about family, family, wife, mom, whatever. You're making decisions based 407 00:21:48,720 --> 00:21:50,240 Speaker 1: on a lot more than that. You're working, so you're 408 00:21:50,240 --> 00:21:54,440 Speaker 1: waiting longer. But what's also cool is people that are 409 00:21:55,760 --> 00:21:58,480 Speaker 1: relationships are coming from dating apps now and and we're 410 00:21:58,480 --> 00:22:01,080 Speaker 1: seeing there was again another study from not like the 411 00:22:01,119 --> 00:22:03,960 Speaker 1: match groups putting out the study, another study from UM. 412 00:22:04,000 --> 00:22:06,879 Speaker 1: I think the National Academy Science has said that UM 413 00:22:07,000 --> 00:22:11,280 Speaker 1: relationships that started on a dating app outlast traditional relationships, 414 00:22:11,320 --> 00:22:13,640 Speaker 1: and I don't I think that's partly with the dating app. 415 00:22:13,640 --> 00:22:15,000 Speaker 1: I think it's a lot of that has to do 416 00:22:15,080 --> 00:22:19,320 Speaker 1: with your meeting later. You're taking your time, you're focusing 417 00:22:19,359 --> 00:22:22,360 Speaker 1: on what are you into, what are you gonna talk about? 418 00:22:22,480 --> 00:22:24,639 Speaker 1: And sometimes people don't get Cupid you're matching on more 419 00:22:24,680 --> 00:22:27,159 Speaker 1: than the superficial hopefully and also just even front like 420 00:22:27,200 --> 00:22:29,440 Speaker 1: people who just meet through fronts, that doesn't actually mean 421 00:22:29,480 --> 00:22:31,920 Speaker 1: that that's going to be a relationship that lasts. You 422 00:22:31,960 --> 00:22:36,080 Speaker 1: were talking earlier about the diversity obviously based on the 423 00:22:36,119 --> 00:22:38,200 Speaker 1: city demographics that you have, and as you were talking, 424 00:22:38,320 --> 00:22:40,679 Speaker 1: this thought spurred to me. As marketers, we think a 425 00:22:40,680 --> 00:22:46,359 Speaker 1: lot of about lookalike targeting, and what's interesting to me is, okay, 426 00:22:46,400 --> 00:22:50,720 Speaker 1: Cupid actually makes me challenge that thought and thinking about 427 00:22:50,840 --> 00:22:53,840 Speaker 1: you were talking about familiarity and this idea that like, 428 00:22:54,359 --> 00:22:59,199 Speaker 1: do brands actually want to engage and lookalike targeting? Because 429 00:22:59,200 --> 00:23:03,280 Speaker 1: the things that we based that on, right, so if 430 00:23:03,359 --> 00:23:05,919 Speaker 1: you know you like this TV show and I like 431 00:23:06,040 --> 00:23:07,720 Speaker 1: this TV show, well then we should be targeting the 432 00:23:07,760 --> 00:23:09,800 Speaker 1: same product. Is clearly we're of the same mindset. But 433 00:23:09,840 --> 00:23:13,159 Speaker 1: the reality is people's personas and profiles are so much 434 00:23:13,200 --> 00:23:15,639 Speaker 1: more complex and substantive than that. And so just as 435 00:23:15,640 --> 00:23:17,560 Speaker 1: you were bringing that up, it's just an interesting thoughts, 436 00:23:17,640 --> 00:23:20,040 Speaker 1: like you break down borders and you allow communication to 437 00:23:20,119 --> 00:23:23,199 Speaker 1: kind of get beyond the iron hair color, Like, do 438 00:23:23,280 --> 00:23:25,240 Speaker 1: we have it wrong when it comes to look like targeting. 439 00:23:25,800 --> 00:23:28,520 Speaker 1: I think you're totally right. That's such an amazing point. 440 00:23:28,600 --> 00:23:31,040 Speaker 1: I think you are. This is why we have a 441 00:23:31,040 --> 00:23:33,640 Speaker 1: lot of advertisers that come to okay Cupid because we're 442 00:23:33,640 --> 00:23:37,280 Speaker 1: able to hyper target and we truly know more about 443 00:23:37,359 --> 00:23:40,040 Speaker 1: people than anyone else because of the nature of what 444 00:23:40,119 --> 00:23:44,840 Speaker 1: we're doing. Have you thought about building out okay Cupid experiences? 445 00:23:44,880 --> 00:23:46,600 Speaker 1: So is there a part where you match the people 446 00:23:46,600 --> 00:23:48,239 Speaker 1: and then there's a partner that's going to help you 447 00:23:48,320 --> 00:23:51,040 Speaker 1: execute the first dage. Yeah, that's such a good question, 448 00:23:51,040 --> 00:23:53,960 Speaker 1: and we have thought about that. I think, um, listen, 449 00:23:54,000 --> 00:23:56,040 Speaker 1: we're in the software business, which is a high margin, 450 00:23:56,200 --> 00:23:59,840 Speaker 1: great business to be and when you start to look 451 00:23:59,840 --> 00:24:02,840 Speaker 1: in to experience and things, that becomes difficult to scale 452 00:24:03,040 --> 00:24:06,920 Speaker 1: and the business is less exciting. So we think about 453 00:24:06,960 --> 00:24:09,800 Speaker 1: that stuff. But we you know, for now, there's no plans. 454 00:24:10,080 --> 00:24:11,720 Speaker 1: But you know, we hear from advertisers and brands all 455 00:24:11,720 --> 00:24:13,560 Speaker 1: the time, and we are doing more events with people 456 00:24:13,680 --> 00:24:15,240 Speaker 1: like I want to get in front of folks. I 457 00:24:15,280 --> 00:24:18,240 Speaker 1: want to you know, we know that you are. You know, 458 00:24:18,280 --> 00:24:20,320 Speaker 1: a lot of people know could keep it our entities 459 00:24:20,400 --> 00:24:23,679 Speaker 1: there do you do I r L meetups, we do 460 00:24:24,080 --> 00:24:27,960 Speaker 1: UM and listen. We're innovating in a lot of exciting ways. 461 00:24:28,080 --> 00:24:30,280 Speaker 1: So you can come back in a few months. And 462 00:24:32,600 --> 00:24:35,240 Speaker 1: I think I love the exclusive I think I think 463 00:24:35,320 --> 00:24:37,240 Speaker 1: that there's such a huge place that I know you 464 00:24:37,280 --> 00:24:41,600 Speaker 1: said you are serious about the data side, UM and privacy, Yeah, 465 00:24:41,960 --> 00:24:44,560 Speaker 1: got it. But I think that if okay, Cupid had 466 00:24:44,600 --> 00:24:47,000 Speaker 1: to be two B side in your business, that you 467 00:24:47,040 --> 00:24:50,639 Speaker 1: would fucking kill. But you guys have insights, like no 468 00:24:50,680 --> 00:24:54,000 Speaker 1: one has insights. You have everything right, well it's so intimate, 469 00:24:54,000 --> 00:24:55,720 Speaker 1: but you have location base, you have this, you have that. 470 00:24:55,760 --> 00:24:58,239 Speaker 1: I mean like, holy moly, if you could go in 471 00:24:58,320 --> 00:25:01,800 Speaker 1: and go and talk to brand some publishers about you know, 472 00:25:02,160 --> 00:25:06,159 Speaker 1: major kind of future forecasting. But also think about it. 473 00:25:06,240 --> 00:25:08,040 Speaker 1: We need all these commercials that you see out there, 474 00:25:08,080 --> 00:25:10,359 Speaker 1: like oh we get people together, we get together, we 475 00:25:10,359 --> 00:25:13,159 Speaker 1: get we actually know what gets you together. We know 476 00:25:13,240 --> 00:25:15,280 Speaker 1: the brand, you know the place from the time of day. 477 00:25:15,480 --> 00:25:18,520 Speaker 1: Like publishers. Publishers they actually need, like almost the more 478 00:25:18,560 --> 00:25:21,960 Speaker 1: traditional publishers, they need some of these insights. They need 479 00:25:22,040 --> 00:25:24,680 Speaker 1: some of the insights around like how are people connecting, 480 00:25:25,119 --> 00:25:27,920 Speaker 1: what are topics what's the new language, what's this? What's 481 00:25:28,240 --> 00:25:29,760 Speaker 1: I mean? You can do it from a surface level, 482 00:25:29,800 --> 00:25:32,640 Speaker 1: but getting down to some of these more like detailed 483 00:25:32,720 --> 00:25:35,720 Speaker 1: understandings of like what's happening and what are the conversations 484 00:25:35,760 --> 00:25:39,399 Speaker 1: and what are the drivers and identities and you know, 485 00:25:39,600 --> 00:25:45,359 Speaker 1: that's amazing for for anyone that's creating content. Anyone. Yeah, well, 486 00:25:45,400 --> 00:25:49,920 Speaker 1: that said, it's time to play our favorite game. I'm 487 00:25:49,960 --> 00:25:52,720 Speaker 1: like excited for your answers. Well, I would okay with 488 00:25:52,840 --> 00:25:55,800 Speaker 1: d I y Amazon, because when I'd be the richest 489 00:25:55,880 --> 00:25:58,240 Speaker 1: person in the history of the world with Jeff Bezos, 490 00:25:58,440 --> 00:26:00,720 Speaker 1: they know that's the new record, which is ever we 491 00:26:00,760 --> 00:26:02,480 Speaker 1: need to we need to look back and say how 492 00:26:02,520 --> 00:26:05,880 Speaker 1: many on the show. I'm like, yeah, sure, yeah, that's 493 00:26:06,320 --> 00:26:09,080 Speaker 1: he's coming on the show. I would I gotta say this. 494 00:26:09,119 --> 00:26:12,280 Speaker 1: I would kill bad dating behavior, kill that. I would 495 00:26:12,320 --> 00:26:14,800 Speaker 1: kill the hay because a lot of guys they say, 496 00:26:14,840 --> 00:26:16,879 Speaker 1: they say hey, and the girls like they roll their 497 00:26:16,920 --> 00:26:21,600 Speaker 1: eyes like okay, kill they kill that. I would buy 498 00:26:22,480 --> 00:26:25,240 Speaker 1: real estate in downtown New York. But like in the sixties, 499 00:26:25,880 --> 00:26:30,840 Speaker 1: in the sixties, yeah it was cheap. N oh, yeah, 500 00:26:30,520 --> 00:26:35,439 Speaker 1: oh you are up there. That's not downtown, all right, 501 00:26:35,520 --> 00:26:37,680 Speaker 1: that's yeah, that's good. I would build Amazons and I 502 00:26:37,720 --> 00:26:39,800 Speaker 1: owned it, so we see that money motivates you. But hey, 503 00:26:39,840 --> 00:26:44,639 Speaker 1: annoys you all right? Oh I like the psychology answers around. 504 00:26:44,760 --> 00:26:48,760 Speaker 1: Very good, Melissa, This was so fun so much. You 505 00:26:48,760 --> 00:26:50,439 Speaker 1: guys are so cool. I'm gonna have you back on 506 00:26:50,480 --> 00:26:52,440 Speaker 1: and you're gonna talk about some of the fact you're doing. 507 00:26:53,160 --> 00:26:55,840 Speaker 1: So Melissa, if people want to find you, how did 508 00:26:55,880 --> 00:26:59,000 Speaker 1: they find you? And please reach out because we're just 509 00:26:59,080 --> 00:27:01,480 Speaker 1: doing some crazy cool things now and we work really 510 00:27:01,520 --> 00:27:04,040 Speaker 1: really fast. Um hobbily at okay Cupid, h O b 511 00:27:04,480 --> 00:27:06,760 Speaker 1: l e y at okay cupid dot com awesome or 512 00:27:06,800 --> 00:27:11,520 Speaker 1: the usual social places. You guys are awesome, Thank you much. Yes, 513 00:27:11,800 --> 00:27:15,360 Speaker 1: love and smart love like smart love. We are dad 514 00:27:15,480 --> 00:27:19,440 Speaker 1: to fucking hang out with you. Anything than sorry Dad 515 00:27:19,480 --> 00:27:28,840 Speaker 1: again from the language All right, all right, big thanks 516 00:27:28,840 --> 00:27:32,480 Speaker 1: Melissa happily from Okay Cupid, Cameron Drew's. We know you're 517 00:27:32,480 --> 00:27:34,240 Speaker 1: looking for love and all the wrong places, but we 518 00:27:34,320 --> 00:27:37,119 Speaker 1: give you lots of things. Andy Bowers, Matt Turk and 519 00:27:37,160 --> 00:27:39,520 Speaker 1: all of our friends and family at Panoply, and we 520 00:27:39,600 --> 00:27:41,800 Speaker 1: will be back in two weeks to tell you about 521 00:27:41,920 --> 00:27:44,359 Speaker 1: served over Sound, our new dinner series Go kill it 522 00:27:44,440 --> 00:27:54,360 Speaker 1: at Landia full disclosure, our opinions, our own How are 523 00:27:54,359 --> 00:27:56,959 Speaker 1: people going on dates? Like what are the popular like 524 00:27:57,160 --> 00:28:02,000 Speaker 1: first spots question? So so, um, it depends on your city, 525 00:28:02,160 --> 00:28:04,960 Speaker 1: is the first thing. So depending on where you are. 526 00:28:05,480 --> 00:28:09,400 Speaker 1: You are. So in Austin, you know Austin, like Austin's 527 00:28:09,440 --> 00:28:13,280 Speaker 1: food truck scene is so sick um. And you know, 528 00:28:13,280 --> 00:28:14,720 Speaker 1: we've been spending all the time in Austin because we 529 00:28:14,720 --> 00:28:17,200 Speaker 1: want to understand what people are doing. Like food trucks 530 00:28:17,240 --> 00:28:19,600 Speaker 1: are like that's like a good day in Austin because 531 00:28:19,600 --> 00:28:21,760 Speaker 1: they're great and like listen, if you're young, you don't 532 00:28:21,760 --> 00:28:24,359 Speaker 1: want the guy to drop. Actually, did a food truck? 533 00:28:25,480 --> 00:28:28,440 Speaker 1: Did a catfish food truck to talk about how you 534 00:28:28,560 --> 00:28:31,920 Speaker 1: can't be catfished? Yeah? Yeah, we thought that that was clever. 535 00:28:32,280 --> 00:28:34,919 Speaker 1: That was clever. Um. You know people don't catfish on 536 00:28:34,960 --> 00:28:37,240 Speaker 1: Okay cube it as much because we make you go 537 00:28:37,280 --> 00:28:42,240 Speaker 1: through a more rigorous profile. But anyway, um, what are 538 00:28:42,280 --> 00:28:47,000 Speaker 1: a little up? Oh it's a head to have the competition, right, Um. So, 539 00:28:47,000 --> 00:28:48,920 Speaker 1: so it depends on your city. Um, in New York, 540 00:28:49,160 --> 00:28:52,120 Speaker 1: it's bars right because we don't have to no one's driving, 541 00:28:52,280 --> 00:28:55,480 Speaker 1: so it's really easy. UM. San Francisco, you'll see more 542 00:28:55,520 --> 00:28:56,720 Speaker 1: things like, oh, do you want to go to this, 543 00:28:57,120 --> 00:28:59,640 Speaker 1: like tech stars meet up or like this. You know 544 00:28:59,680 --> 00:29:03,240 Speaker 1: people will do business centric dates more than other cities. 545 00:29:03,920 --> 00:29:08,200 Speaker 1: Actually everyone's hustling, so you know they might both be 546 00:29:08,200 --> 00:29:11,640 Speaker 1: going to some lecture or something like that. UM. In 547 00:29:11,800 --> 00:29:15,280 Speaker 1: places like Portland's craft beer is so big, so a 548 00:29:15,280 --> 00:29:18,120 Speaker 1: lot of breweries, but you'll see like like there's also 549 00:29:18,200 --> 00:29:21,680 Speaker 1: like hikes or you know, a cooking class like