1 00:00:02,720 --> 00:00:10,559 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,600 --> 00:00:14,560 Speaker 1: Bloomberg Intelligence podcast. Catch us live weekdays at ten am 3 00:00:14,600 --> 00:00:17,880 Speaker 1: Eastern on Apple, Cocklay and Android Auto with the Bloomberg 4 00:00:17,920 --> 00:00:21,040 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,360 --> 00:00:23,080 Speaker 1: or watch us live on YouTube. 6 00:00:24,000 --> 00:00:26,760 Speaker 2: Tons of earnings coming out here, a lot of tech stuff, 7 00:00:26,800 --> 00:00:30,800 Speaker 2: a lot of user economy stuff. I'm looking at Airbnb, Instacart, 8 00:00:30,880 --> 00:00:33,640 Speaker 2: all kinds of stuff. Man Deep saying he covers all 9 00:00:33,760 --> 00:00:35,720 Speaker 2: the tech industry for Bloomberg Intelligence. 10 00:00:35,720 --> 00:00:37,199 Speaker 3: He's got the team which. 11 00:00:36,960 --> 00:00:40,120 Speaker 2: He manages all around the world for Bloomberg Intelligence. Mandee, 12 00:00:40,200 --> 00:00:43,760 Speaker 2: let's start with Airbnb. I've seen a stock trading up here. 13 00:00:43,800 --> 00:00:46,000 Speaker 2: There's some pretty good numbers. I was kind of surprised. 14 00:00:46,240 --> 00:00:48,639 Speaker 2: They're double digit revenue growth in twenty twenty six. What's 15 00:00:48,680 --> 00:00:49,240 Speaker 2: the story there. 16 00:00:50,800 --> 00:00:54,600 Speaker 4: Yeah, I think anytime you have a big event coming up, 17 00:00:54,640 --> 00:00:58,400 Speaker 4: which in this case it's the FIFA World Cup in 18 00:00:58,440 --> 00:01:02,280 Speaker 4: the summer, that's always good news for Airbnb, and that's 19 00:01:02,320 --> 00:01:03,160 Speaker 4: what you're seeing. 20 00:01:03,520 --> 00:01:03,880 Speaker 5: I think. 21 00:01:04,880 --> 00:01:09,480 Speaker 4: I mean, expectations were low, but clearly they're seeing some 22 00:01:09,680 --> 00:01:13,440 Speaker 4: lift from a big events, as well as the reserve 23 00:01:13,520 --> 00:01:16,959 Speaker 4: now pay later, which is another way to stimulate demand. 24 00:01:17,000 --> 00:01:19,960 Speaker 4: But overall supply growth seems to be improving, and they 25 00:01:20,440 --> 00:01:24,440 Speaker 4: want to expand into hotels and other areas. It may 26 00:01:24,920 --> 00:01:27,280 Speaker 4: compress their take rates a little bit, but there is 27 00:01:27,319 --> 00:01:29,880 Speaker 4: no doubt that they want to expand the footprint of 28 00:01:30,319 --> 00:01:32,680 Speaker 4: what they have to offer on the platform. 29 00:01:32,840 --> 00:01:36,119 Speaker 6: They've also, thanks to a lot of marketing, made clear 30 00:01:36,160 --> 00:01:38,760 Speaker 6: that they want to expand into services as well. For 31 00:01:38,920 --> 00:01:42,720 Speaker 6: guests we're seeing at Airbnb venues wherever they go. How 32 00:01:42,760 --> 00:01:45,280 Speaker 6: much is is that a meaningful contributor to revenue? 33 00:01:46,360 --> 00:01:47,240 Speaker 5: No, not yet. 34 00:01:47,720 --> 00:01:51,880 Speaker 4: I think all of that hotel services experiences is still 35 00:01:51,960 --> 00:01:57,120 Speaker 4: less than five percent and diluted to margins. But look, 36 00:01:57,560 --> 00:02:01,120 Speaker 4: the UI for these companies may change because of AI. 37 00:02:01,320 --> 00:02:03,720 Speaker 4: So one of the things that they got to ask 38 00:02:03,800 --> 00:02:06,320 Speaker 4: on the call is how are they preparing for that 39 00:02:06,520 --> 00:02:09,919 Speaker 4: UI change? And I think the mode over the years 40 00:02:10,000 --> 00:02:14,000 Speaker 4: for all of the marketplaces has been get bigger in 41 00:02:14,120 --> 00:02:18,000 Speaker 4: size and you know, have more frequency with the users. 42 00:02:18,040 --> 00:02:22,080 Speaker 4: And that's why experiences and hotels is just their way 43 00:02:22,120 --> 00:02:25,120 Speaker 4: of engaging more with their daily active users. 44 00:02:25,639 --> 00:02:29,040 Speaker 2: Mindy, what's the how's the market share kind of shaking 45 00:02:29,080 --> 00:02:32,560 Speaker 2: out here in the world of hospitality in terms of 46 00:02:32,760 --> 00:02:37,440 Speaker 2: the Airbnbs of the world versus the traditional hotel motel Here, 47 00:02:37,480 --> 00:02:40,080 Speaker 2: what's the market share, what's the split and are we 48 00:02:40,080 --> 00:02:41,160 Speaker 2: still seeing movement there? 49 00:02:42,800 --> 00:02:43,000 Speaker 5: Yeah? 50 00:02:43,040 --> 00:02:47,079 Speaker 4: I mean all of these big three OTA's Booking, Expedia, 51 00:02:47,240 --> 00:02:51,680 Speaker 4: and Airbnb, they do the majority of the booked room nights. 52 00:02:51,720 --> 00:02:54,240 Speaker 4: When you think about the global scale, these are the 53 00:02:54,320 --> 00:02:58,520 Speaker 4: three scale players. The differences in the profitability. Airbnb is 54 00:02:58,560 --> 00:03:02,040 Speaker 4: a lot more profitable and let's say Expedia, which is 55 00:03:02,040 --> 00:03:04,919 Speaker 4: why you see that kind of stock reaction today. And 56 00:03:05,680 --> 00:03:09,320 Speaker 4: I think what Airbnb has done well is really added 57 00:03:09,440 --> 00:03:13,760 Speaker 4: more fragmented supply. So the more fragmented the supply, the 58 00:03:13,840 --> 00:03:16,200 Speaker 4: harder it is to disrupt. Even if you get a 59 00:03:16,280 --> 00:03:19,840 Speaker 4: new UI tomorrow, because of you know, all the AI innovation, 60 00:03:20,360 --> 00:03:23,760 Speaker 4: how do you add the supply, you know, the host 61 00:03:23,840 --> 00:03:26,840 Speaker 4: that Airbnb has added over the years, It's very hard 62 00:03:26,880 --> 00:03:29,880 Speaker 4: to kind of disrupt that mode because that supply part 63 00:03:29,919 --> 00:03:32,480 Speaker 4: is the hardest part. When it comes to marketplaces. 64 00:03:33,240 --> 00:03:35,920 Speaker 6: I'm kind of surprised that Airbnb is now offering rooms 65 00:03:35,920 --> 00:03:38,960 Speaker 6: at boutique hotels in New York, LA and San Francisco, 66 00:03:39,160 --> 00:03:41,560 Speaker 6: Like that feels like it's going into the market that 67 00:03:41,760 --> 00:03:45,240 Speaker 6: intended to disrupt and the hotel companies are teaming up 68 00:03:45,240 --> 00:03:47,200 Speaker 6: with it. How did that come about and does this 69 00:03:47,280 --> 00:03:48,800 Speaker 6: become a bigger part of its business. 70 00:03:50,720 --> 00:03:53,120 Speaker 4: I won't say it will become a bigger part, but 71 00:03:53,800 --> 00:03:58,440 Speaker 4: those smaller independent boutique hotels, we're looking for additional distribution. 72 00:03:59,120 --> 00:04:01,840 Speaker 4: And AIRBNBA as a platform obviously has a lot of 73 00:04:01,880 --> 00:04:05,480 Speaker 4: direct traffic. So I think it made sense for Airbnb 74 00:04:05,640 --> 00:04:08,760 Speaker 4: to boost their supply because they are sort of plateauing 75 00:04:08,840 --> 00:04:12,360 Speaker 4: out when it comes to the vacation rentals, especially in 76 00:04:12,760 --> 00:04:16,599 Speaker 4: developed markets, and so from that perspective, supplying growth is 77 00:04:16,720 --> 00:04:20,520 Speaker 4: very essential for a marketplace, and adding independent boutique hotels 78 00:04:20,640 --> 00:04:24,320 Speaker 4: does add to, you know, that supply, and overall, if 79 00:04:24,320 --> 00:04:27,240 Speaker 4: it helps them boost frequency and engagement on the platform, 80 00:04:27,279 --> 00:04:29,040 Speaker 4: I think that's what they're looking for. 81 00:04:29,080 --> 00:04:32,719 Speaker 2: You all right, well we got you Mandy pinterest stocks 82 00:04:32,760 --> 00:04:33,839 Speaker 2: down twenty one percent? 83 00:04:33,920 --> 00:04:34,920 Speaker 3: What is going on there? 84 00:04:36,320 --> 00:04:38,799 Speaker 4: I mean that's when Meta you know, when they guide 85 00:04:38,839 --> 00:04:42,000 Speaker 4: it to thirty percent top line growth in the first quarter, 86 00:04:42,839 --> 00:04:45,520 Speaker 4: it had to be at the expense of you know, 87 00:04:45,560 --> 00:04:49,000 Speaker 4: the smaller companies, and we saw Reddit do well, but 88 00:04:49,400 --> 00:04:54,120 Speaker 4: clearly snap Pinterests, these guys are exposed to the same 89 00:04:54,360 --> 00:04:58,159 Speaker 4: advertisers as Meta is, and last night Pinterest called out 90 00:04:58,240 --> 00:05:01,320 Speaker 4: you know, tariffs being one of the reasons for advertisers 91 00:05:01,320 --> 00:05:05,920 Speaker 4: pulling back on their platform. Retailers, you know, clearly are 92 00:05:05,920 --> 00:05:08,200 Speaker 4: spending a lot more on Meta even though Meta is 93 00:05:08,240 --> 00:05:11,880 Speaker 4: the scale player. These companies are not getting the advertising 94 00:05:11,920 --> 00:05:15,080 Speaker 4: dollars at the scale that Meta is getting, and that's 95 00:05:15,080 --> 00:05:16,880 Speaker 4: why you're seeing that slowdown in growth. 96 00:05:17,680 --> 00:05:18,920 Speaker 3: Does AI save the day? 97 00:05:19,200 --> 00:05:23,640 Speaker 6: Pints says it's launched Pinterest Assistant its first and of 98 00:05:23,680 --> 00:05:26,760 Speaker 6: course this is marketing jargon first, AI powered, visual first 99 00:05:26,760 --> 00:05:28,200 Speaker 6: collaborator for online shopping. 100 00:05:29,600 --> 00:05:31,960 Speaker 4: I mean, the problem is, you know, no matter what 101 00:05:32,040 --> 00:05:35,520 Speaker 4: you do, you're competing with a scale player like Meta, 102 00:05:35,600 --> 00:05:38,719 Speaker 4: which is allocating one hundred and thirty five billion dollars 103 00:05:38,800 --> 00:05:43,680 Speaker 4: in capex this year building their infrastructure using that for AI. 104 00:05:43,880 --> 00:05:46,719 Speaker 4: And that's where I think competition is very tough for 105 00:05:46,920 --> 00:05:49,120 Speaker 4: all the smaller players on that side. 106 00:05:49,720 --> 00:05:52,840 Speaker 3: Stay with us. More from Bloomberg Intelligence coming up after this. 107 00:05:56,720 --> 00:06:01,080 Speaker 1: You're listening to the Bloomberg Intelligence podcast live weekdays at 108 00:06:01,080 --> 00:06:04,039 Speaker 1: ten am Eastern on Apple Cocklay and Android Auto with 109 00:06:04,120 --> 00:06:07,240 Speaker 1: the Bloomberg Business app. Listen on demand wherever you get 110 00:06:07,279 --> 00:06:10,080 Speaker 1: your podcasts or watch us live on YouTube. 111 00:06:10,920 --> 00:06:13,000 Speaker 6: All right, let's shift gears and talk a little bit 112 00:06:13,040 --> 00:06:16,280 Speaker 6: about what's been happening in techland. Software companies have had 113 00:06:16,320 --> 00:06:19,880 Speaker 6: a rough, rough week, rough couple of weeks, to be honest, 114 00:06:20,160 --> 00:06:22,719 Speaker 6: it hasn't been limited to this week. On our Rana 115 00:06:22,760 --> 00:06:27,240 Speaker 6: is our Bloomberg Intelligence technology analyst and hon Our talk 116 00:06:27,279 --> 00:06:29,640 Speaker 6: to us a little bit here about how management is 117 00:06:29,680 --> 00:06:33,560 Speaker 6: dealing with the AI scare. That's just you know, taking 118 00:06:33,720 --> 00:06:37,520 Speaker 6: every part of the economy by storm. It's kind of 119 00:06:37,600 --> 00:06:41,160 Speaker 6: rolling through different sectors and everyone seems to need to 120 00:06:41,200 --> 00:06:43,600 Speaker 6: be able to answer for how they're going to survive 121 00:06:43,880 --> 00:06:44,839 Speaker 6: the on sought of AI. 122 00:06:46,839 --> 00:06:48,960 Speaker 7: And this kind of skate is very different than anything 123 00:06:49,000 --> 00:06:51,200 Speaker 7: we have seen in the past, because, you know, in 124 00:06:51,240 --> 00:06:54,440 Speaker 7: the previous downtowns or whenever we saw big sell off, 125 00:06:54,680 --> 00:06:57,800 Speaker 7: the question was the near term demand is an issue 126 00:06:57,920 --> 00:07:01,520 Speaker 7: or save some bal issue with someone. In this particular case, 127 00:07:01,680 --> 00:07:04,760 Speaker 7: the case is that there is no need for software 128 00:07:04,880 --> 00:07:07,760 Speaker 7: a few years from now, not today or tomorrow, what 129 00:07:08,200 --> 00:07:10,160 Speaker 7: a few years from now. So what that does is 130 00:07:10,280 --> 00:07:14,160 Speaker 7: when you're doing discounted cash flow analysis, the terminal value 131 00:07:14,200 --> 00:07:16,800 Speaker 7: of that particular company or a stock, you know, they're 132 00:07:16,800 --> 00:07:19,160 Speaker 7: saying is going to be close to zero, and that's 133 00:07:19,200 --> 00:07:21,960 Speaker 7: an argument it's so difficult to deal with because that 134 00:07:22,040 --> 00:07:26,160 Speaker 7: event hasn't happened. It's all you could say a thesis 135 00:07:26,280 --> 00:07:29,080 Speaker 7: of a particular group of investors that says saying that 136 00:07:29,160 --> 00:07:32,000 Speaker 7: there is no need for a lot of these companies 137 00:07:32,040 --> 00:07:36,240 Speaker 7: that depend on the intellectual capital of software developers people 138 00:07:36,280 --> 00:07:38,440 Speaker 7: who are using it, and we could all do this 139 00:07:38,560 --> 00:07:41,520 Speaker 7: in house. And I think that's the big fear everybody's 140 00:07:41,560 --> 00:07:45,080 Speaker 7: grappling with. And every time you see somebody say, well, 141 00:07:45,120 --> 00:07:48,040 Speaker 7: this particular software can go out into something in the 142 00:07:48,120 --> 00:07:50,840 Speaker 7: legal world, all the stocks that are part of the 143 00:07:50,920 --> 00:07:53,200 Speaker 7: data network or the software that sells it to it, 144 00:07:53,480 --> 00:07:56,560 Speaker 7: you know, sell off. So it's really a big dilemma 145 00:07:56,680 --> 00:07:58,520 Speaker 7: for even management teams as to what do you even 146 00:07:58,560 --> 00:07:59,160 Speaker 7: do right now? 147 00:07:59,560 --> 00:08:00,160 Speaker 5: Yeah, us. 148 00:08:00,200 --> 00:08:02,800 Speaker 2: What would be frustrating for investors in some of these 149 00:08:02,880 --> 00:08:06,360 Speaker 2: software names is like AI. We don't even know what 150 00:08:06,440 --> 00:08:09,360 Speaker 2: AI is going to be and what the use cases 151 00:08:09,360 --> 00:08:11,680 Speaker 2: are going to be. So I think what's happening is 152 00:08:11,760 --> 00:08:14,760 Speaker 2: people are just spitting out the worst case scenarios that 153 00:08:15,480 --> 00:08:17,160 Speaker 2: you know, and that's what I'm seeing in some of 154 00:08:17,160 --> 00:08:19,000 Speaker 2: these stocks that are off thirty forty percent and these 155 00:08:19,000 --> 00:08:23,280 Speaker 2: are real companies with real earnings. Is this something that 156 00:08:23,320 --> 00:08:26,400 Speaker 2: plays out over time or how do you get trains? 157 00:08:27,240 --> 00:08:30,240 Speaker 7: Yeah, the fear of the terminal value going to zero. 158 00:08:30,720 --> 00:08:33,079 Speaker 7: You cannot undo it in the next few months. It's 159 00:08:33,120 --> 00:08:36,199 Speaker 7: going to take several, I mean honestly years to play out. 160 00:08:36,559 --> 00:08:38,679 Speaker 7: What you have to figure out is do you have 161 00:08:38,720 --> 00:08:41,320 Speaker 7: a framework under which you are thinking about, you know, 162 00:08:41,360 --> 00:08:44,400 Speaker 7: what kind of companies are better protected than the others. So, 163 00:08:44,480 --> 00:08:47,679 Speaker 7: for example, you know, one could argue that cybersecurity companies 164 00:08:47,720 --> 00:08:50,920 Speaker 7: have a better presence there. Second place that we are 165 00:08:51,040 --> 00:08:55,480 Speaker 7: arguing is companies that sell into really large enterprises that 166 00:08:55,600 --> 00:09:00,000 Speaker 7: have domain expertise, Companies that are critical to you running 167 00:09:00,040 --> 00:09:03,679 Speaker 7: your daily operation, your P and L, your human resources. 168 00:09:04,160 --> 00:09:06,400 Speaker 7: Those are the ones that are a far more sticky 169 00:09:06,440 --> 00:09:09,640 Speaker 7: product than the point product companies that are selling into 170 00:09:09,880 --> 00:09:13,480 Speaker 7: the smaller of the medium size enterprise. But you know, 171 00:09:13,559 --> 00:09:15,800 Speaker 7: who knows, maybe that theory goes out of the water 172 00:09:15,880 --> 00:09:18,280 Speaker 7: as well. So I think you have to have some 173 00:09:18,480 --> 00:09:22,800 Speaker 7: framework under which you are you know, gauging these companies 174 00:09:22,840 --> 00:09:25,440 Speaker 7: not so much anymore by the financials, but by the 175 00:09:25,480 --> 00:09:27,720 Speaker 7: business model and where the impact could. 176 00:09:27,559 --> 00:09:31,000 Speaker 6: Be domain expertise. That's a term that I've heard pop 177 00:09:31,120 --> 00:09:33,280 Speaker 6: up over and over again on our What does that 178 00:09:33,320 --> 00:09:35,320 Speaker 6: mean in the context of software companies? 179 00:09:36,440 --> 00:09:39,040 Speaker 7: So think about it this way. We you know, when 180 00:09:39,080 --> 00:09:41,560 Speaker 7: there is an issue that we have internally while we 181 00:09:41,600 --> 00:09:43,960 Speaker 7: are working, we put in a ticket to figure get 182 00:09:43,960 --> 00:09:47,520 Speaker 7: our HR system fixed or our computer fixed. That falls 183 00:09:47,559 --> 00:09:50,560 Speaker 7: into a realm of a thing called it service management. 184 00:09:50,920 --> 00:09:53,199 Speaker 7: There's a company called service now that has forty percent 185 00:09:53,280 --> 00:09:55,839 Speaker 7: market share in that area. You look at somebody like 186 00:09:55,880 --> 00:09:58,599 Speaker 7: an a SAP, they pretty much control the finance and 187 00:09:58,640 --> 00:10:01,360 Speaker 7: accounting software that's out there. You look at a company 188 00:10:01,440 --> 00:10:05,200 Speaker 7: like Workday, they can they control the HR software market 189 00:10:05,320 --> 00:10:08,200 Speaker 7: or the HR systems people use. That's the kind of 190 00:10:08,200 --> 00:10:11,640 Speaker 7: domain expertise I'm talking about, because that's something only these 191 00:10:11,679 --> 00:10:15,000 Speaker 7: guys do, and they do it very well for larger companies. 192 00:10:15,120 --> 00:10:18,079 Speaker 7: And there are you know, smaller companies that target the 193 00:10:18,520 --> 00:10:20,959 Speaker 7: lower end of the market, but these are the ones 194 00:10:21,000 --> 00:10:23,439 Speaker 7: that they'll deal with it. I'll tell you another one. Shopify, 195 00:10:23,520 --> 00:10:26,480 Speaker 7: for example. Shopify is something that does a digital commerce 196 00:10:26,480 --> 00:10:28,880 Speaker 7: better than any company out there, and they probably have 197 00:10:29,040 --> 00:10:31,520 Speaker 7: one third of the overall market right now, and they're 198 00:10:31,559 --> 00:10:34,320 Speaker 7: growing at you know, twenty five thirty percent. But guess 199 00:10:34,360 --> 00:10:37,440 Speaker 7: when they reported didn't matter, stock still went down after that. 200 00:10:38,320 --> 00:10:41,040 Speaker 2: This if you're you know, an investor with high level 201 00:10:41,040 --> 00:10:46,120 Speaker 2: of conviction, this is a once in a career type 202 00:10:46,160 --> 00:10:49,760 Speaker 2: opportunity potentially. Do you talk to some I'm not going 203 00:10:49,800 --> 00:10:51,160 Speaker 2: to call it smart money, but you already talk to 204 00:10:51,320 --> 00:10:54,280 Speaker 2: people that have some experience that are saying this is it. 205 00:10:54,760 --> 00:10:56,960 Speaker 2: I'm backing it up. I'm loading up on some of 206 00:10:57,000 --> 00:10:59,160 Speaker 2: these names where I feel I have a high level 207 00:10:59,200 --> 00:11:01,280 Speaker 2: of conviction in their cash flows. Are you hearing any 208 00:11:01,320 --> 00:11:01,800 Speaker 2: of that yet? 209 00:11:02,640 --> 00:11:05,120 Speaker 7: Yeah. I haven't had that many incoming inquiries to talk 210 00:11:05,160 --> 00:11:07,640 Speaker 7: about software stock in many years because they were very 211 00:11:07,679 --> 00:11:09,720 Speaker 7: expensive at that time. I think if you go out 212 00:11:09,720 --> 00:11:13,120 Speaker 7: and read the article the Amazon aws, you know the 213 00:11:13,240 --> 00:11:15,440 Speaker 7: head he comes out and says, you know, this is 214 00:11:15,559 --> 00:11:18,240 Speaker 7: just overblown at this point. So you have like somebody 215 00:11:18,320 --> 00:11:21,559 Speaker 7: like Amazon Web Services CEO talking about it in the 216 00:11:21,400 --> 00:11:23,760 Speaker 7: in the market, so you know there is and then 217 00:11:23,800 --> 00:11:25,280 Speaker 7: then you know, on the other side, there is an 218 00:11:25,360 --> 00:11:28,439 Speaker 7: argument that, you know, all these jobs would be automated 219 00:11:28,480 --> 00:11:30,320 Speaker 7: in the next two years or so. So it is 220 00:11:30,360 --> 00:11:33,480 Speaker 7: that these two fears, and we all know when you 221 00:11:33,640 --> 00:11:36,200 Speaker 7: have a fear in the market, people shoot first. And 222 00:11:36,240 --> 00:11:38,719 Speaker 7: they think later. And that's kind of the dilemma, or 223 00:11:38,800 --> 00:11:40,640 Speaker 7: that's that's kind of the market where we are right. 224 00:11:41,320 --> 00:11:43,720 Speaker 6: Has that fear dissipated a little bit as we gotten 225 00:11:43,720 --> 00:11:45,080 Speaker 6: towards the end of the week or is it still 226 00:11:45,120 --> 00:11:47,080 Speaker 6: just as intense as it was a few weeks ago? 227 00:11:47,120 --> 00:11:50,040 Speaker 7: On rog I think it gets worse every week. I 228 00:11:50,120 --> 00:11:52,800 Speaker 7: mean I started looking at this the you know, the 229 00:11:52,880 --> 00:11:55,560 Speaker 7: second half of last year, and every time I would 230 00:11:55,640 --> 00:11:57,480 Speaker 7: talk about it and no, this is you know, there 231 00:11:57,520 --> 00:12:00,280 Speaker 7: is just two overblown and this doesn't make sense. You know, 232 00:12:00,320 --> 00:12:02,480 Speaker 7: next week you come in, everything is down five to 233 00:12:02,520 --> 00:12:05,240 Speaker 7: seven percent. Again, I mean as in total. There are 234 00:12:05,280 --> 00:12:07,600 Speaker 7: certain companies, as I said, you know, look at Shopify. 235 00:12:08,080 --> 00:12:11,959 Speaker 7: They blew out their quarter crew thirty percent. Next quarter 236 00:12:11,960 --> 00:12:14,960 Speaker 7: consensus was twenty five percent. They said next quarter they 237 00:12:14,960 --> 00:12:18,239 Speaker 7: can do thirty percent, and they have a massive agentic 238 00:12:19,320 --> 00:12:22,520 Speaker 7: you could say, strategy that nobody else has. Stock was 239 00:12:22,559 --> 00:12:25,320 Speaker 7: down both times. I mean, it didn't matter. So it's 240 00:12:25,440 --> 00:12:28,400 Speaker 7: very difficult to you know, put rational thoughts at that point. 241 00:12:29,640 --> 00:12:32,800 Speaker 3: Stay with us. More from Bloomberg Intelligence coming up after this. 242 00:12:36,679 --> 00:12:40,360 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us Live 243 00:12:40,480 --> 00:12:43,559 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 244 00:12:43,559 --> 00:12:46,880 Speaker 1: Auto with the Bloomberg Business app, Listen on demand wherever 245 00:12:46,920 --> 00:12:50,040 Speaker 1: you get your podcasts, or watch us live on YouTube. 246 00:12:50,800 --> 00:12:52,960 Speaker 3: We went to we want to go to Ireland. 247 00:12:53,880 --> 00:12:57,200 Speaker 2: We ask this kid who is a tech geek, Hey, 248 00:12:57,200 --> 00:12:58,280 Speaker 2: we're thinking about going to Ireland. 249 00:12:58,320 --> 00:12:59,480 Speaker 3: He asked this a couple of questions. 250 00:13:00,080 --> 00:13:03,320 Speaker 2: Teen minutes later he comes back with a full itinerary 251 00:13:03,840 --> 00:13:04,440 Speaker 2: that he got. 252 00:13:04,320 --> 00:13:05,960 Speaker 3: Off of chat GPT. 253 00:13:06,080 --> 00:13:07,560 Speaker 2: I said, oh boy, what does this mean for the 254 00:13:07,600 --> 00:13:12,880 Speaker 2: travel agents? The OTAs not good. Nicole Desusa joins the 255 00:13:12,920 --> 00:13:15,719 Speaker 2: season Internet and software equity analysts for Bloomberg Intelligence. I'm 256 00:13:15,720 --> 00:13:18,240 Speaker 2: thinking about the expedies of the world, Nick Nicole, all 257 00:13:18,240 --> 00:13:21,559 Speaker 2: those types of things. What's going on with that business? 258 00:13:21,840 --> 00:13:23,400 Speaker 2: Is that could be one of those business that's really 259 00:13:23,400 --> 00:13:24,640 Speaker 2: disrupted with AI. 260 00:13:24,920 --> 00:13:26,480 Speaker 8: Yeah, so I think you bring up a great point. 261 00:13:26,559 --> 00:13:30,120 Speaker 8: Now travelers instead of going to booking Expedia, trip Advisor, 262 00:13:30,400 --> 00:13:32,800 Speaker 8: they're just working with chatchibt, so they don't even really 263 00:13:32,920 --> 00:13:36,200 Speaker 8: have to see the back end. So they are looking at, 264 00:13:36,280 --> 00:13:39,640 Speaker 8: you know, not just now planning on an AI product, 265 00:13:39,679 --> 00:13:42,080 Speaker 8: but they're also potentially going to be booking through an 266 00:13:42,080 --> 00:13:45,160 Speaker 8: AI product, So they will ask chatchibt. You know, this 267 00:13:45,240 --> 00:13:46,480 Speaker 8: is where I want to go, this is what I 268 00:13:46,480 --> 00:13:48,200 Speaker 8: want to see, what I want to do. It'll give 269 00:13:48,200 --> 00:13:50,320 Speaker 8: them an itinerary and then it'll work with the supply 270 00:13:50,400 --> 00:13:52,199 Speaker 8: partners directly to book everything. 271 00:13:52,360 --> 00:13:54,920 Speaker 2: Wow, because I mean again, this kid came back with 272 00:13:54,960 --> 00:13:57,599 Speaker 2: an agenda. Gets twenty eight years old, came back with 273 00:13:57,679 --> 00:14:01,320 Speaker 2: an agenda that was this is where you're staying, this 274 00:14:01,360 --> 00:14:04,080 Speaker 2: is where you're going to eat, cars, book, We're going 275 00:14:04,120 --> 00:14:06,640 Speaker 2: to get a card, do here's your flights, recommended flights, 276 00:14:06,640 --> 00:14:07,240 Speaker 2: blah blah blah. 277 00:14:07,320 --> 00:14:11,360 Speaker 3: Yeah, and then the next step would be booking it. Yes, wow, yes, 278 00:14:11,440 --> 00:14:15,360 Speaker 3: all right. So if the Expedias of the world, what 279 00:14:15,400 --> 00:14:16,120 Speaker 3: am I doing here? 280 00:14:16,640 --> 00:14:19,440 Speaker 8: So they are rolling out their own AI products, it's 281 00:14:19,560 --> 00:14:21,240 Speaker 8: a little too early to tell if they'll really be 282 00:14:21,320 --> 00:14:25,040 Speaker 8: able to compete with something like chat GBT. Expedia has 283 00:14:25,080 --> 00:14:27,440 Speaker 8: like a really interesting product where you can take uh 284 00:14:27,640 --> 00:14:30,640 Speaker 8: social media, like a real from Instagram, put it into 285 00:14:30,760 --> 00:14:34,160 Speaker 8: Expedia's AI product, and it'll create an itinerary based off 286 00:14:34,200 --> 00:14:36,640 Speaker 8: of what you're seeing on Instagram. So it's kind of 287 00:14:36,680 --> 00:14:39,920 Speaker 8: like you go from just having inspiration for a potential 288 00:14:39,960 --> 00:14:43,520 Speaker 8: trip and then it gives you the exact flights, hotels, everything. 289 00:14:44,400 --> 00:14:46,360 Speaker 3: Expedia just reported some results. 290 00:14:46,400 --> 00:14:51,040 Speaker 8: How were they They were actually pretty solid. So the 291 00:14:51,080 --> 00:14:53,440 Speaker 8: real overhang on Expedia for the last year has been 292 00:14:53,480 --> 00:14:57,200 Speaker 8: the US travel market, which has been pretty stagnant that 293 00:14:57,280 --> 00:15:00,520 Speaker 8: has been recovering. Expedia is primarily exposed to the US market. 294 00:15:00,520 --> 00:15:02,360 Speaker 8: They don't have as big of a global presence as 295 00:15:02,360 --> 00:15:06,440 Speaker 8: booking dot Com and Expedia. As a results, we're pretty solid, 296 00:15:06,480 --> 00:15:10,800 Speaker 8: strong execution pointing to a recovering US travel market. So 297 00:15:10,800 --> 00:15:14,120 Speaker 8: we were pretty pleased just with their execution over the 298 00:15:14,200 --> 00:15:14,680 Speaker 8: last quarter. 299 00:15:14,800 --> 00:15:18,360 Speaker 2: When I look at Expedia trip Advisor bookings, are they 300 00:15:18,600 --> 00:15:21,920 Speaker 2: kind of the same, totally the same, or they differentiated? 301 00:15:22,320 --> 00:15:25,480 Speaker 8: So Trip I would say, is differentiated. They've actually changed 302 00:15:25,480 --> 00:15:27,600 Speaker 8: their platform a lot in the last few quarters. They 303 00:15:27,600 --> 00:15:31,920 Speaker 8: are now focusing on becoming an experiences booking platform. So 304 00:15:32,000 --> 00:15:34,960 Speaker 8: if you are looking to book you know, a cooking 305 00:15:35,000 --> 00:15:37,680 Speaker 8: class or a wine tasting or a walking tour, you 306 00:15:37,720 --> 00:15:41,920 Speaker 8: can book that directly on trip platform. So a little 307 00:15:41,920 --> 00:15:43,960 Speaker 8: bit different than kind of what booking Expedia to do 308 00:15:44,000 --> 00:15:45,440 Speaker 8: with hotels and flights. 309 00:15:45,720 --> 00:15:47,960 Speaker 3: What's that? How's that industry? 310 00:15:47,960 --> 00:15:51,000 Speaker 2: What's the percentage now that people book through these OTAs 311 00:15:51,480 --> 00:15:54,520 Speaker 2: versus going to Marriott dot com or something like that. 312 00:15:54,920 --> 00:15:58,600 Speaker 8: So we have definitely seen an increase in direct bookings. 313 00:15:58,640 --> 00:16:02,880 Speaker 8: It's actually Hotel Hell partners now are incentivized to maybe 314 00:16:02,920 --> 00:16:06,000 Speaker 8: work directly with AI partners instead of Booking and Expedia 315 00:16:06,360 --> 00:16:08,920 Speaker 8: because if they go direct, if they have a direct booking, 316 00:16:08,920 --> 00:16:10,640 Speaker 8: they don't have to pay that fifteen to twenty percent 317 00:16:10,640 --> 00:16:12,080 Speaker 8: commission to OTAs. 318 00:16:12,520 --> 00:16:17,840 Speaker 2: So there's another So it's so the technology AI, chat, GPT, 319 00:16:17,960 --> 00:16:21,760 Speaker 2: whatever you're using that actually works in I guess in 320 00:16:21,800 --> 00:16:25,240 Speaker 2: favor of the actual hotel, the airline and all that 321 00:16:25,280 --> 00:16:25,840 Speaker 2: type of stuff. 322 00:16:25,920 --> 00:16:29,520 Speaker 8: Yes, so they now don't need the visibility per se 323 00:16:29,560 --> 00:16:30,440 Speaker 8: on booking. 324 00:16:30,200 --> 00:16:31,640 Speaker 3: Ex Yeah, that sounds scary to me. 325 00:16:31,720 --> 00:16:33,400 Speaker 2: So as I look at the year to date stock 326 00:16:33,400 --> 00:16:38,160 Speaker 2: price performance, Expedia down twenty five percent, Trip down thirty 327 00:16:38,200 --> 00:16:41,840 Speaker 2: two percent, Booking down twenty two percent. Yes, the market's 328 00:16:41,880 --> 00:16:47,120 Speaker 2: definitely telling you that they're concerned. Is there a less 329 00:16:47,160 --> 00:16:49,240 Speaker 2: bare case than that, because I mean, right now we're 330 00:16:49,240 --> 00:16:51,520 Speaker 2: in an environment where people are throwing everything out the window. 331 00:16:51,600 --> 00:16:54,200 Speaker 2: Software related Yes, because you don't know where AA is 332 00:16:54,240 --> 00:16:56,520 Speaker 2: going to go. Here's an example, here's an where you 333 00:16:56,560 --> 00:16:57,840 Speaker 2: can see it. 334 00:16:58,040 --> 00:17:00,280 Speaker 8: Yes, and I think, I mean we are definitely very 335 00:17:00,280 --> 00:17:03,160 Speaker 8: early in these AI products, so even the bookings product, 336 00:17:03,200 --> 00:17:05,919 Speaker 8: We've seen examples from Google and from Chat GVT, but 337 00:17:05,960 --> 00:17:08,320 Speaker 8: they're not necessarily in a place yet where they're going 338 00:17:08,359 --> 00:17:10,520 Speaker 8: to have a real impact on revenue at least in 339 00:17:10,560 --> 00:17:13,199 Speaker 8: maybe the next six to twelve months. And I do 340 00:17:13,280 --> 00:17:14,960 Speaker 8: think we are seeing, you know, an uptick in the 341 00:17:15,040 --> 00:17:17,840 Speaker 8: overall travel market. So US travel has been improving. We 342 00:17:17,920 --> 00:17:20,480 Speaker 8: have things like the Winter Olympics the World Cup later 343 00:17:20,520 --> 00:17:23,040 Speaker 8: this year which are going to kind of boost travel. 344 00:17:23,320 --> 00:17:25,000 Speaker 8: So I think there is kind of a case for 345 00:17:25,000 --> 00:17:29,159 Speaker 8: at least short term growth, but there is, you know, 346 00:17:29,200 --> 00:17:30,240 Speaker 8: the AI overhang still. 347 00:17:30,600 --> 00:17:32,440 Speaker 3: So is Airbnb. 348 00:17:32,520 --> 00:17:35,239 Speaker 2: Are they seeing like World Cup stuff like I can 349 00:17:35,320 --> 00:17:37,639 Speaker 2: rent out my New Jersey home for World Cup for 350 00:17:37,680 --> 00:17:38,280 Speaker 2: the finals. 351 00:17:38,400 --> 00:17:40,200 Speaker 8: Yeah, I think, I mean, I do think the World Cup, 352 00:17:40,280 --> 00:17:43,320 Speaker 8: especially for US travel, will have a pretty significant impact. 353 00:17:43,560 --> 00:17:45,400 Speaker 8: I think we're going to look at you know, Expedia 354 00:17:45,440 --> 00:17:48,800 Speaker 8: is probably the most exposed to the US travel market, 355 00:17:48,960 --> 00:17:51,480 Speaker 8: so if we keep seeing solid execution from them, we 356 00:17:51,520 --> 00:17:53,680 Speaker 8: could have a next a strong couple of quarters. 357 00:17:56,720 --> 00:17:59,160 Speaker 3: Stay with us. More from Bloomberg Intelligence coming. 358 00:17:59,000 --> 00:17:59,880 Speaker 5: Up there for this. 359 00:18:02,880 --> 00:18:06,560 Speaker 1: You're listening to the Bloomberg Intelligence podcast Catch us Live 360 00:18:06,640 --> 00:18:09,720 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 361 00:18:09,760 --> 00:18:13,040 Speaker 1: Auto with the Bloomberg Business app. Listen on demand wherever 362 00:18:13,119 --> 00:18:16,200 Speaker 1: you get your podcasts, or watch us live on YouTube. 363 00:18:17,080 --> 00:18:17,400 Speaker 2: All right. 364 00:18:18,040 --> 00:18:21,080 Speaker 6: One of my favorite groups on Facebook is the MX 365 00:18:21,160 --> 00:18:25,200 Speaker 6: Platinum Card Benefits and Offers Group. It's a private group. 366 00:18:25,240 --> 00:18:28,240 Speaker 6: It's got about seventy one thousand members, but everyone exchanges 367 00:18:28,280 --> 00:18:30,440 Speaker 6: tips on how to get the most out of their plot. 368 00:18:30,520 --> 00:18:32,520 Speaker 3: Really, yes, you're so, you're one of those people that's 369 00:18:32,560 --> 00:18:33,160 Speaker 3: really into it. 370 00:18:33,440 --> 00:18:35,560 Speaker 6: I started to become really into it because I didn't 371 00:18:35,600 --> 00:18:37,440 Speaker 6: like the refresh on the Chase staffire cards, so I 372 00:18:37,520 --> 00:18:38,920 Speaker 6: wanted to find out the other options. 373 00:18:39,160 --> 00:18:40,040 Speaker 3: What's the refreshman? 374 00:18:40,200 --> 00:18:42,760 Speaker 6: They raise the rate the annual fee and then they 375 00:18:42,840 --> 00:18:45,439 Speaker 6: like change the benefits okay, and so then you have 376 00:18:45,480 --> 00:18:46,120 Speaker 6: to do a deep diver. 377 00:18:46,240 --> 00:18:46,560 Speaker 3: Yeah, I know. 378 00:18:46,760 --> 00:18:49,320 Speaker 2: Like my daughter and her friends, they are all into 379 00:18:49,359 --> 00:18:51,840 Speaker 2: maximizing the points and oh so she knows she travels 380 00:18:51,880 --> 00:18:53,960 Speaker 2: all over the world and like she's like Charlie Pellett 381 00:18:54,080 --> 00:18:54,880 Speaker 2: and doesn't pay for anything. 382 00:18:54,880 --> 00:18:58,240 Speaker 6: Oh, Charlie Pellett is like the master guy when it 383 00:18:58,280 --> 00:18:59,320 Speaker 6: comes to these reward points. 384 00:18:59,359 --> 00:18:59,639 Speaker 3: Okay. 385 00:19:00,000 --> 00:19:05,200 Speaker 6: Bringing Edward Nigerian, he is a Bloomberg industry Bloomberg Intelligence 386 00:19:05,200 --> 00:19:08,440 Speaker 6: industry analysts who covers a consumer finance and his team 387 00:19:08,480 --> 00:19:11,119 Speaker 6: has just written a report on the Platinum Card and 388 00:19:11,160 --> 00:19:13,680 Speaker 6: the fee economics there, and we'd tell us a little 389 00:19:13,720 --> 00:19:16,480 Speaker 6: bit more about what you learn, because twenty twenty six 390 00:19:16,680 --> 00:19:20,200 Speaker 6: was the start of MS rolling out its increased fee 391 00:19:20,880 --> 00:19:23,280 Speaker 6: for the Platinum Card, and we're starting to get some 392 00:19:23,880 --> 00:19:25,280 Speaker 6: understanding of what it might look like. 393 00:19:27,119 --> 00:19:27,359 Speaker 5: Right. 394 00:19:27,480 --> 00:19:31,200 Speaker 9: So, I mean, when they reported the quarter, great quarter, 395 00:19:32,880 --> 00:19:35,480 Speaker 9: everything kind of in line with expectations or in some 396 00:19:35,640 --> 00:19:39,440 Speaker 9: areas better and gave great guidance in terms of mid 397 00:19:39,440 --> 00:19:43,560 Speaker 9: teens EPs growth for twenty twenty six, and you know, 398 00:19:43,920 --> 00:19:46,119 Speaker 9: a lot a lot of conversation about the refresh and 399 00:19:46,160 --> 00:19:49,320 Speaker 9: how great the refresh is going and acquiring you know, 400 00:19:49,920 --> 00:19:51,879 Speaker 9: lots of new customers. 401 00:19:52,000 --> 00:19:54,359 Speaker 5: But generally there were two things that. 402 00:19:54,320 --> 00:19:57,200 Speaker 9: Sort of analysts picked on in the quarter when you're 403 00:19:57,240 --> 00:19:59,920 Speaker 9: when you're trading that sort of a high multiple financial 404 00:20:00,720 --> 00:20:04,280 Speaker 9: and those two things were. Number one, that new card, 405 00:20:04,359 --> 00:20:06,960 Speaker 9: the new card acquisition rate kind of went down a 406 00:20:07,000 --> 00:20:09,760 Speaker 9: little bit relative to last year and relative to the 407 00:20:09,800 --> 00:20:14,320 Speaker 9: third quarter. And initially all the money that they're spending 408 00:20:14,359 --> 00:20:19,280 Speaker 9: on rewards and services and all of what they call variable, 409 00:20:19,320 --> 00:20:22,280 Speaker 9: customer engagement expenses went up a lot, a little too 410 00:20:22,359 --> 00:20:26,280 Speaker 9: much in some people's opinions. So what we kind of 411 00:20:26,359 --> 00:20:30,440 Speaker 9: learned recently was sort of some supporting data around two things. 412 00:20:30,480 --> 00:20:32,640 Speaker 5: And the big thing was while the. 413 00:20:33,359 --> 00:20:35,840 Speaker 9: Number of new cards acquired went down a little bit, 414 00:20:36,600 --> 00:20:38,960 Speaker 9: the fee per new card went up from one hundred 415 00:20:39,000 --> 00:20:41,760 Speaker 9: and ninety six in the third quarter to two hundred 416 00:20:41,800 --> 00:20:44,320 Speaker 9: and eighty two, now, so huge jump. 417 00:20:44,359 --> 00:20:45,160 Speaker 5: Now why is that? 418 00:20:45,160 --> 00:20:48,399 Speaker 9: That's because a lot of the much bigger percentage of 419 00:20:48,400 --> 00:20:52,199 Speaker 9: those new cards came from new Platinum customers, which is 420 00:20:52,280 --> 00:20:55,240 Speaker 9: much better than just a regular customers. So even though 421 00:20:55,280 --> 00:20:58,160 Speaker 9: a little little less customers acquired, you're getting many more 422 00:20:58,200 --> 00:21:01,040 Speaker 9: new platinum customers, much better economics. 423 00:21:01,720 --> 00:21:02,960 Speaker 5: So that's sort of one thing. 424 00:21:03,000 --> 00:21:07,560 Speaker 9: And then talked a lot about how they're absorbing all 425 00:21:07,640 --> 00:21:12,760 Speaker 9: of those extra reward costs if you will. But still 426 00:21:12,880 --> 00:21:16,439 Speaker 9: that's and that's fine because it's enhancing revenue growth, and 427 00:21:16,520 --> 00:21:20,040 Speaker 9: sort of the revenue growth benefit of that offsets the 428 00:21:20,080 --> 00:21:22,639 Speaker 9: reward cost more than offsets that reward cost. 429 00:21:22,840 --> 00:21:25,680 Speaker 6: Okay, Edward, one thing that I've noticed from these Facebook 430 00:21:25,720 --> 00:21:28,479 Speaker 6: groups is that people get a platinum card that's you know, 431 00:21:28,640 --> 00:21:30,479 Speaker 6: for the sign up bonus and everything else. But then 432 00:21:30,480 --> 00:21:33,080 Speaker 6: they start branching out and they get the Gold card 433 00:21:33,119 --> 00:21:35,879 Speaker 6: because there's more reward points for groceries there. They start 434 00:21:35,920 --> 00:21:39,000 Speaker 6: to compile a lot of Amex cards, so a lot 435 00:21:39,040 --> 00:21:41,320 Speaker 6: of the users have multiple cards, don't they. 436 00:21:42,760 --> 00:21:44,840 Speaker 5: Yeah, no question about that. 437 00:21:45,040 --> 00:21:47,960 Speaker 9: And obviously you've got to you know, a lot of 438 00:21:48,040 --> 00:21:50,720 Speaker 9: sort of families on the Platinum card, so there's sort 439 00:21:50,720 --> 00:21:54,520 Speaker 9: of a primary Platinum card owner and then issuer of 440 00:21:54,640 --> 00:21:57,720 Speaker 9: multiple cards related to that. So you sort of have 441 00:21:57,840 --> 00:22:01,520 Speaker 9: this this sort of network of effect of the Platinum 442 00:22:01,560 --> 00:22:05,040 Speaker 9: card that just keeps building and to some extent, you know, 443 00:22:05,119 --> 00:22:07,439 Speaker 9: if you can, you know, when you come back to 444 00:22:07,440 --> 00:22:10,080 Speaker 9: the JP Morgan Sapphire card, if you can, you know, 445 00:22:10,640 --> 00:22:15,359 Speaker 9: build that reward and service infrastructure even bigger and better. 446 00:22:15,760 --> 00:22:17,439 Speaker 9: You know, you create the you know, sort of the 447 00:22:17,440 --> 00:22:19,560 Speaker 9: mode effect, which is what they're trying to do and 448 00:22:19,680 --> 00:22:20,560 Speaker 9: seems to be working. 449 00:22:21,200 --> 00:22:24,280 Speaker 3: Hey, ed the I have the Green card I got 450 00:22:24,440 --> 00:22:27,000 Speaker 3: the day I graduated college. I kept it all. 451 00:22:27,040 --> 00:22:30,439 Speaker 2: But Scarlet and other folks, I understand they go crazy 452 00:22:30,480 --> 00:22:34,200 Speaker 2: for these really expensive cards and all the points and managing. 453 00:22:34,560 --> 00:22:37,320 Speaker 5: You need to go Platinum, Paul, No, I just can't. 454 00:22:37,400 --> 00:22:38,720 Speaker 3: I can't do it. 455 00:22:39,119 --> 00:22:42,200 Speaker 2: How big of a business is that for these card companies? 456 00:22:42,240 --> 00:22:44,840 Speaker 2: Is that really the value driver? The scarlet foods of 457 00:22:44,840 --> 00:22:45,440 Speaker 2: the world. 458 00:22:46,600 --> 00:22:47,040 Speaker 5: That's it. 459 00:22:47,280 --> 00:22:50,119 Speaker 9: Yeah, they care much more about scarlet than they care 460 00:22:50,160 --> 00:22:50,520 Speaker 9: about you. 461 00:22:50,560 --> 00:22:51,520 Speaker 5: I have to say, yes. 462 00:22:52,680 --> 00:22:55,359 Speaker 9: She's going She's about to pay eight hundred and ninety 463 00:22:55,359 --> 00:22:57,879 Speaker 9: five dollars a year, up from six hundred and ninety 464 00:22:57,880 --> 00:22:58,800 Speaker 9: five dollars a year. 465 00:23:00,359 --> 00:23:01,760 Speaker 5: They're gonna give her a heck of a lot of 466 00:23:01,800 --> 00:23:03,199 Speaker 5: rewards and services for that. 467 00:23:04,119 --> 00:23:06,080 Speaker 9: But I had a big sign a bump on average. 468 00:23:06,160 --> 00:23:10,160 Speaker 9: Now I hope this is not completely true, but on average, 469 00:23:10,600 --> 00:23:13,400 Speaker 9: she one of the Platinum card members, spends about ten 470 00:23:13,480 --> 00:23:15,160 Speaker 9: times as much on her card as you do. 471 00:23:16,720 --> 00:23:21,399 Speaker 1: This is the Bloomberg Intelligence podcast, available on Apple, Spotify, 472 00:23:21,600 --> 00:23:25,080 Speaker 1: and anywhere else you get your podcasts. 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