1 00:00:01,360 --> 00:00:05,680 Speaker 1: This is Bloomberg Business Wait inside from the reporters and 2 00:00:05,880 --> 00:00:09,440 Speaker 1: editors who bring you America's most trusted business magazine, plus 3 00:00:09,520 --> 00:00:13,680 Speaker 1: global business, finance and tech news. The Bloomberg Business Week 4 00:00:13,720 --> 00:00:19,000 Speaker 1: Podcast with Carol Messer and Tim Stenebeck from Bloomberg Radio. 5 00:00:19,880 --> 00:00:21,479 Speaker 2: I have to say on our planning call, when I 6 00:00:21,480 --> 00:00:23,520 Speaker 2: heard that Bradstone was going to join us on Amazon, 7 00:00:23,560 --> 00:00:25,720 Speaker 2: I was like, Okay, that's all I need, so let's 8 00:00:25,720 --> 00:00:28,240 Speaker 2: get to it. Brad, as you know, he is Bloomberg 9 00:00:28,280 --> 00:00:31,360 Speaker 2: New Senior Executive Editor of Global Technologies, the author of 10 00:00:31,400 --> 00:00:34,479 Speaker 2: two books on Amazon, Jeff Bezos and The Innovation of 11 00:00:34,479 --> 00:00:37,440 Speaker 2: a Global Empire, and of course The Everything Store. Brad 12 00:00:37,479 --> 00:00:39,760 Speaker 2: is there on zoom in San Francisco. Brad, thank you 13 00:00:39,800 --> 00:00:41,440 Speaker 2: so much. Luck going on, and I know you and 14 00:00:41,479 --> 00:00:45,160 Speaker 2: your team have been busy this week Amazon. Where should 15 00:00:45,200 --> 00:00:46,839 Speaker 2: we start? What do you think is the most important 16 00:00:47,200 --> 00:00:48,880 Speaker 2: in this release so far? Yeah? 17 00:00:49,080 --> 00:00:52,159 Speaker 3: I think the question that was lingering over the company 18 00:00:52,520 --> 00:00:56,160 Speaker 3: was whether it had slimmed itself down enough to boost profits, 19 00:00:56,200 --> 00:00:59,360 Speaker 3: whether with all the lafts nearly three thousand this year alone, 20 00:00:59,560 --> 00:01:02,200 Speaker 3: it made any progress and its effort to cut costs 21 00:01:02,200 --> 00:01:05,800 Speaker 3: and match this new era of slowing post pandemic growth 22 00:01:06,040 --> 00:01:08,240 Speaker 3: and Carol, you can see from a twelve percent after 23 00:01:08,520 --> 00:01:11,240 Speaker 3: market boost right now, investors are happy with what they're 24 00:01:11,240 --> 00:01:15,360 Speaker 3: seeing on operating income, net income and the durability of AWS. 25 00:01:16,080 --> 00:01:19,840 Speaker 4: Do you see the good results today feeding through for 26 00:01:20,080 --> 00:01:22,640 Speaker 4: Amazon through the end of the year, particularly as you 27 00:01:22,680 --> 00:01:26,560 Speaker 4: mentioned on the piece about cutting costs through cutting back 28 00:01:26,600 --> 00:01:29,959 Speaker 4: on the workforce. How does Amazon sustain that growth this year? 29 00:01:30,840 --> 00:01:33,600 Speaker 3: Yeah, I mean we don't know. I mean Amazon's performance 30 00:01:33,680 --> 00:01:37,319 Speaker 3: is so tethered to the macroeconomic climate, and obviously with 31 00:01:37,360 --> 00:01:40,320 Speaker 3: the growth report today, I mean, there are big questions 32 00:01:40,319 --> 00:01:42,640 Speaker 3: about the health of the economy. I think you know 33 00:01:42,680 --> 00:01:46,440 Speaker 3: what we're seeing with Jase's comments about machine learning making 34 00:01:46,440 --> 00:01:50,080 Speaker 3: the AD business better and how the AWS business, they're 35 00:01:50,160 --> 00:01:53,480 Speaker 3: really pitching it as a way to do AI deeper 36 00:01:53,480 --> 00:01:56,400 Speaker 3: and more efficiently. You know, they're trying to set this 37 00:01:56,480 --> 00:01:58,480 Speaker 3: company up not just for the next year, but for 38 00:01:58,600 --> 00:02:01,320 Speaker 3: kind of this next era Silicon Valley and say like 39 00:02:01,360 --> 00:02:04,320 Speaker 3: this is the smart play whatever happens to the economy, 40 00:02:04,560 --> 00:02:06,360 Speaker 3: this is the long term smart play on AI. 41 00:02:06,760 --> 00:02:08,720 Speaker 2: I mean, and the thing that we're highlighting on the 42 00:02:08,760 --> 00:02:11,320 Speaker 2: Bloomberg brad you know, they're talking about that second quarter 43 00:02:11,320 --> 00:02:13,680 Speaker 2: net sales one hundred and twenty seven two hundred and 44 00:02:13,680 --> 00:02:15,800 Speaker 2: thirty three billion. The estimate out there is one thirty. 45 00:02:15,840 --> 00:02:19,080 Speaker 2: I mean it's a sizeable, you know range there, but 46 00:02:19,160 --> 00:02:21,840 Speaker 2: it's upbeat, And so you do wonder about what they 47 00:02:21,880 --> 00:02:24,120 Speaker 2: are seeing about the outlook that gives them at least 48 00:02:24,320 --> 00:02:26,320 Speaker 2: comfort in putting this out here, or how do you 49 00:02:26,360 --> 00:02:28,000 Speaker 2: see it when they put out a forecast like that. 50 00:02:28,320 --> 00:02:31,560 Speaker 3: I mean, they always leave their forecasts large enough to 51 00:02:31,639 --> 00:02:34,480 Speaker 3: drive an Amazon delivery truck through, you know, so I 52 00:02:34,520 --> 00:02:37,120 Speaker 3: don't ever put put that much stock in it. But look, 53 00:02:37,200 --> 00:02:39,480 Speaker 3: I mean, this is like a beat across the board. 54 00:02:40,000 --> 00:02:43,520 Speaker 3: Even a physical store sales were a beat online store 55 00:02:43,560 --> 00:02:46,000 Speaker 3: sales or a beat, you know. So I think that 56 00:02:46,160 --> 00:02:48,320 Speaker 3: you know they're they're seeing not just to kind of 57 00:02:48,320 --> 00:02:50,560 Speaker 3: recover from the top line, but all the things they 58 00:02:50,560 --> 00:02:54,440 Speaker 3: have been working on for so many years, shorter delivery times, 59 00:02:54,440 --> 00:02:57,080 Speaker 3: more fulfillment centers closer to customers, that these things are 60 00:02:57,120 --> 00:03:00,800 Speaker 3: finally beginning to make a difference for customers and are 61 00:03:00,800 --> 00:03:04,640 Speaker 3: a little bit more of a differentiator for Amazon fast 62 00:03:04,720 --> 00:03:07,240 Speaker 3: oncoming competitors like Walmart, dot Com, et cetera. 63 00:03:07,760 --> 00:03:09,880 Speaker 4: Talk to me about the AI piece we have in here. 64 00:03:10,440 --> 00:03:13,960 Speaker 4: Some I see six on the word count for AI here. 65 00:03:15,320 --> 00:03:17,600 Speaker 4: Does that feel like enough to you? Does it feel 66 00:03:17,639 --> 00:03:20,040 Speaker 4: like they're leaning into AI in this earnings report? 67 00:03:20,560 --> 00:03:23,400 Speaker 3: I mean every company is right now, and I expect 68 00:03:23,400 --> 00:03:25,600 Speaker 3: it on the media call at the bottom of the 69 00:03:25,639 --> 00:03:27,560 Speaker 3: hour and the analyst call at the top of the hour. 70 00:03:27,680 --> 00:03:30,600 Speaker 3: It's going to be you know, I AI like all 71 00:03:30,680 --> 00:03:33,320 Speaker 3: these calls this week. But I mean the one explicit 72 00:03:33,440 --> 00:03:37,160 Speaker 3: thing that they don't have is a consumer facing you know, 73 00:03:37,840 --> 00:03:42,640 Speaker 3: arge language model that BOT help customers. You know, Alexa 74 00:03:42,720 --> 00:03:45,560 Speaker 3: with a version of that, but it's a little generation old. 75 00:03:45,840 --> 00:03:50,000 Speaker 3: And so they're pitching these these services to developers, like 76 00:03:50,160 --> 00:03:53,520 Speaker 3: one is called Bedrock, where you know, you can come 77 00:03:53,560 --> 00:03:56,120 Speaker 3: and like tailor your own So they're really seeing it 78 00:03:56,160 --> 00:03:58,880 Speaker 3: as a part right now at least of AWS and 79 00:03:58,920 --> 00:04:02,680 Speaker 3: making their business and their AWS customers business more efficient. 80 00:04:02,960 --> 00:04:04,760 Speaker 3: You know, we'll see how much of that is like 81 00:04:04,840 --> 00:04:07,400 Speaker 3: AI washing and how much is a real difference for 82 00:04:07,440 --> 00:04:09,560 Speaker 3: competitors for their customers. 83 00:04:09,680 --> 00:04:11,320 Speaker 2: I am blown away by the numbers, and I'm going 84 00:04:11,360 --> 00:04:13,520 Speaker 2: to go back to physical stores. I mean, I guess, 85 00:04:13,600 --> 00:04:15,280 Speaker 2: you know, because we all think about Amazon, we disorder 86 00:04:15,280 --> 00:04:17,719 Speaker 2: and it just shows up, you know, miraculously on a doorstep. 87 00:04:18,160 --> 00:04:21,719 Speaker 2: Four point now almost five billion dollars in sales. I mean, 88 00:04:21,960 --> 00:04:24,440 Speaker 2: is this something that they continue to invest in and 89 00:04:24,480 --> 00:04:26,839 Speaker 2: build out or is it just again very cautiously, but 90 00:04:27,120 --> 00:04:28,039 Speaker 2: that's some real money. 91 00:04:28,720 --> 00:04:31,160 Speaker 3: I mean, if anything, Carol, it's the reverse. I mean, 92 00:04:31,200 --> 00:04:33,480 Speaker 3: they've closed all the physical stores. So the number you're 93 00:04:33,520 --> 00:04:36,719 Speaker 3: seeing here is whole foods, I mean, by and large, 94 00:04:36,800 --> 00:04:39,839 Speaker 3: so you know they've been they've been cutting that business 95 00:04:39,839 --> 00:04:42,320 Speaker 3: a little bit. They've closed some stores. I think I 96 00:04:42,320 --> 00:04:45,000 Speaker 3: think that number shows like maybe some stability, like the 97 00:04:45,440 --> 00:04:49,000 Speaker 3: bookstores they've closed, the four Star stores. Amazon Go has 98 00:04:49,040 --> 00:04:51,480 Speaker 3: been whittled down to like a shadow of its former self, 99 00:04:51,600 --> 00:04:55,200 Speaker 3: so you know they're done cutting, and perhaps that's reflective 100 00:04:55,240 --> 00:04:57,839 Speaker 3: of maybe an overall sort of revival in just the 101 00:04:57,880 --> 00:04:58,960 Speaker 3: supermarket category. 102 00:04:59,600 --> 00:05:01,960 Speaker 4: Is there a anything else that you think Amazon needs 103 00:05:02,000 --> 00:05:04,560 Speaker 4: to do this year to control costs? Or does this 104 00:05:04,880 --> 00:05:08,719 Speaker 4: earnings outlook read to you as a company that can 105 00:05:08,880 --> 00:05:11,200 Speaker 4: happily continue to pour money back into itself. 106 00:05:11,680 --> 00:05:14,120 Speaker 3: I mean, we're you know, we're right in the middle 107 00:05:14,160 --> 00:05:16,600 Speaker 3: of the layoffs. I think this week was when they 108 00:05:16,640 --> 00:05:20,800 Speaker 3: started the aw A AWS layoffs, and the head of 109 00:05:20,800 --> 00:05:23,640 Speaker 3: AWS described it as one of the worst days for 110 00:05:24,000 --> 00:05:26,880 Speaker 3: the company. So I think they've probably announced most of 111 00:05:26,960 --> 00:05:30,320 Speaker 3: the cost cutting they're going to do. It's ongoing, it'll 112 00:05:30,360 --> 00:05:32,720 Speaker 3: it'll take place throughout the quarter, and at this at 113 00:05:32,720 --> 00:05:35,039 Speaker 3: this point, you know, and also yesterday, by the way, 114 00:05:35,200 --> 00:05:38,120 Speaker 3: they canceled another product, the Halo wristband, so one of 115 00:05:38,120 --> 00:05:41,520 Speaker 3: their health initiatives. So I think at this point, most 116 00:05:41,520 --> 00:05:44,240 Speaker 3: of the blood's probably on the floor. And you're right 117 00:05:44,320 --> 00:05:46,279 Speaker 3: that from from here on out it's going to be 118 00:05:46,320 --> 00:05:49,240 Speaker 3: a you know, maybe a more careful and curated set 119 00:05:49,240 --> 00:05:49,960 Speaker 3: of bets, you. 120 00:05:49,880 --> 00:05:51,880 Speaker 2: Know, or Ed Ludlow pointing out, and this caught my 121 00:05:52,200 --> 00:05:53,800 Speaker 2: uh caught me too when I was reading through the 122 00:05:53,800 --> 00:05:58,520 Speaker 2: press release. In terms of advertising, their advertising services business 123 00:05:58,760 --> 00:06:01,920 Speaker 2: sales coming in at twenty three percent year over year, 124 00:06:02,000 --> 00:06:04,560 Speaker 2: a thirty five and a half percent help performance relative 125 00:06:04,600 --> 00:06:08,600 Speaker 2: to consensus. You know, we keep worried about anything AD related, 126 00:06:08,640 --> 00:06:11,560 Speaker 2: AD connected. What is it that they are doing just 127 00:06:11,640 --> 00:06:14,200 Speaker 2: so writers it just because they are so huge, there's 128 00:06:14,279 --> 00:06:17,320 Speaker 2: such a big part of everybody's world, and they reach 129 00:06:17,560 --> 00:06:20,520 Speaker 2: so many individuals, if you will, that that makes sense 130 00:06:20,520 --> 00:06:22,040 Speaker 2: that they're really outperforming there. 131 00:06:22,880 --> 00:06:25,920 Speaker 3: Well, what they have said and what they want us 132 00:06:25,920 --> 00:06:29,479 Speaker 3: to believe is that their investments in machine learning help 133 00:06:29,680 --> 00:06:33,440 Speaker 3: match better matchup ads with customers when they're searching in 134 00:06:33,480 --> 00:06:36,880 Speaker 3: the Amazon search box. You know, my view as an 135 00:06:36,880 --> 00:06:40,599 Speaker 3: Amazon customer is that they're simply just flooding the zone. 136 00:06:40,800 --> 00:06:43,520 Speaker 3: I just think that they have thrown open the search 137 00:06:43,560 --> 00:06:47,920 Speaker 3: results to you know, to paid results to the highest bidder. 138 00:06:48,279 --> 00:06:50,520 Speaker 3: And maybe there's a little machine learning there, but it's 139 00:06:50,520 --> 00:06:54,960 Speaker 3: the increasing willingness in the post Jeff Bezos era to 140 00:06:55,080 --> 00:06:58,239 Speaker 3: really self search to the highest bidder that is mainly 141 00:06:58,400 --> 00:06:59,880 Speaker 3: powering that line. 142 00:07:00,520 --> 00:07:04,320 Speaker 2: Brad fast forward for me, which is a bummer for us, then, yes, 143 00:07:04,800 --> 00:07:07,600 Speaker 2: but anyway, but good for them, sorry, Maddie, No, no, no, no, no, it's. 144 00:07:07,600 --> 00:07:10,440 Speaker 4: It's an excellent point, Brad, fast forward to me for 145 00:07:10,560 --> 00:07:12,840 Speaker 4: me to the end of this earning season. Here when 146 00:07:12,840 --> 00:07:15,800 Speaker 4: we look at these Amazon earnings, is this going to 147 00:07:15,840 --> 00:07:20,000 Speaker 4: be the quote unquote bell weather for big tech fueling 148 00:07:20,360 --> 00:07:23,520 Speaker 4: continued gains in the S and P, you know, as 149 00:07:23,520 --> 00:07:24,880 Speaker 4: we wrap up this earning season. 150 00:07:25,720 --> 00:07:28,760 Speaker 3: I think it's consistent, Maddie, with what we've seen from Meta, 151 00:07:28,840 --> 00:07:31,120 Speaker 3: with what we've seen from ALPHAVT. Maybe I haven't been 152 00:07:31,120 --> 00:07:34,280 Speaker 3: paying attention. I'm curious about Snap earnings today. But you 153 00:07:34,320 --> 00:07:37,160 Speaker 3: know that we've been through a brutal period of you know, 154 00:07:37,240 --> 00:07:40,679 Speaker 3: regression in big tech stocks and a lot of cost cutting, 155 00:07:40,840 --> 00:07:45,800 Speaker 3: high unemployment now in Silicon Valley, or at least increasing unemployment, 156 00:07:46,160 --> 00:07:49,320 Speaker 3: and you know, a readjustment. Then maybe this this quarter 157 00:07:49,400 --> 00:07:51,880 Speaker 3: is going to mark kind of the turning point here 158 00:07:51,960 --> 00:07:54,120 Speaker 3: where where as I said, you know, most of the 159 00:07:54,160 --> 00:07:56,800 Speaker 3: pain has been endured, and these companies now with their 160 00:07:56,840 --> 00:08:00,160 Speaker 3: big bets on AI, are beginning to rekindle some They 161 00:08:00,160 --> 00:08:00,960 Speaker 3: were a momentum. 162 00:08:01,000 --> 00:08:04,080 Speaker 2: Brad, you mentioned Snap down twenty two percent in the aftermarket, 163 00:08:04,240 --> 00:08:07,400 Speaker 2: reported its first ever decline in quarterly revenue after making 164 00:08:07,400 --> 00:08:10,960 Speaker 2: some major changes to its advertising tools. So quarter first 165 00:08:11,000 --> 00:08:14,120 Speaker 2: quarter revenue fell seven percent to nine eighty eight point 166 00:08:14,120 --> 00:08:16,559 Speaker 2: six million, So it missed the average at analyst estimate 167 00:08:16,560 --> 00:08:19,840 Speaker 2: of about a billion. So yeah, not not good at all. 168 00:08:19,800 --> 00:08:22,400 Speaker 3: Very different, perhaps not consistent with the overall team. 169 00:08:22,480 --> 00:08:25,040 Speaker 4: Then it makes me wonder what Snap and Pinterest are 170 00:08:25,040 --> 00:08:28,400 Speaker 4: doing differently because they did not perform well, but Amazon, 171 00:08:28,480 --> 00:08:32,080 Speaker 4: Microsoft Meta all performed great about twenty second spread Any 172 00:08:32,080 --> 00:08:34,400 Speaker 4: thoughts on that, Well, it's. 173 00:08:34,240 --> 00:08:38,880 Speaker 3: A good question. There might it's probably the lack of 174 00:08:38,960 --> 00:08:42,560 Speaker 3: kind of topline user growth, I mean meta at Facebook 175 00:08:42,559 --> 00:08:45,720 Speaker 3: and Instagram added user. Snap has struggled with that and 176 00:08:47,559 --> 00:08:49,960 Speaker 3: you know, perhaps a little less global exposure than some 177 00:08:50,000 --> 00:08:50,800 Speaker 3: of their competitors. 178 00:08:50,880 --> 00:08:52,920 Speaker 2: Yeah, Snap had three hundred and eighty three million users 179 00:08:53,000 --> 00:08:56,280 Speaker 2: daily in the first quarter, in line with analyst estimates. Bradstone, 180 00:08:56,360 --> 00:08:58,320 Speaker 2: your gem I know you're busy, I know your team is. 181 00:08:58,360 --> 00:09:01,440 Speaker 2: We love it when you can join us. Bradstone there 182 00:09:01,720 --> 00:09:04,840 Speaker 2: in San Francisco or San Francisco bureau, joining us via Zoom. 183 00:09:05,120 --> 00:09:07,120 Speaker 2: Jeff Bezos and the Invention of a Global Empire and 184 00:09:07,120 --> 00:09:09,800 Speaker 2: the Everything stort. He knows so much about this company. 185 00:09:09,960 --> 00:09:12,400 Speaker 2: Those are two books he's written. Check it out Amazon's 186 00:09:12,400 --> 00:09:13,200 Speaker 2: app nine percent. 187 00:09:13,440 --> 00:09:17,000 Speaker 1: You're listening to the Bloomberg Business Week podcast. Catch us 188 00:09:17,000 --> 00:09:20,360 Speaker 1: live weekday afternoons from three to six Eastern Listen on 189 00:09:20,440 --> 00:09:24,480 Speaker 1: Bloomberg dot com, the iHeartRadio app and the Bloomberg Business app, 190 00:09:24,760 --> 00:09:27,040 Speaker 1: or watch us live on YouTube. 191 00:09:28,360 --> 00:09:31,480 Speaker 2: He did also mentioned Snap, which is getting hammered. It's 192 00:09:31,720 --> 00:09:34,000 Speaker 2: off its lows in the aftermarket, but still down about 193 00:09:34,040 --> 00:09:37,959 Speaker 2: nineteen percent. Let's get to it because some disappointments, certainly, 194 00:09:38,040 --> 00:09:41,280 Speaker 2: as you can see by the share trade here. Let's 195 00:09:41,280 --> 00:09:43,640 Speaker 2: get to it with Bloomberg News Technology Report to Alex Birinka. 196 00:09:43,920 --> 00:09:48,080 Speaker 2: She's on zoom in our La bureau covers his space. Alex, 197 00:09:48,160 --> 00:09:49,920 Speaker 2: A lot of disappointment. Want to walk us through the 198 00:09:50,000 --> 00:09:52,480 Speaker 2: quarter and why investors are so disappointed here? 199 00:09:53,240 --> 00:09:56,240 Speaker 5: Definitely a lot of disappointment, and I think that disappointment 200 00:09:56,280 --> 00:10:00,000 Speaker 5: really is kind of floating around this top line revenue 201 00:10:00,080 --> 00:10:02,760 Speaker 5: line for the first time ever for this company that's 202 00:10:02,760 --> 00:10:05,400 Speaker 5: always been seen kind of as a growth company. And 203 00:10:05,600 --> 00:10:08,000 Speaker 5: you know, there's a little bit of surprise here too, 204 00:10:08,200 --> 00:10:11,160 Speaker 5: because even though the company had guided for a revenue decrease, 205 00:10:11,800 --> 00:10:15,120 Speaker 5: they guided for a decrease in the first quarter. The 206 00:10:15,559 --> 00:10:19,080 Speaker 5: forecastle're giving for the second quarter is another consecutive quarter 207 00:10:19,200 --> 00:10:22,760 Speaker 5: of sales declines. Some of this is self inflicted too. 208 00:10:22,960 --> 00:10:26,000 Speaker 5: Snap told us three months ago that they're making a 209 00:10:26,000 --> 00:10:29,320 Speaker 5: lot of changes to their advertising tools and that would 210 00:10:29,400 --> 00:10:32,600 Speaker 5: impact revenue for the quarter. They didn't say that it 211 00:10:32,640 --> 00:10:34,080 Speaker 5: was going to kind of drag on for a while, 212 00:10:34,080 --> 00:10:37,480 Speaker 5: which seems like is what's happening here, And when you 213 00:10:37,520 --> 00:10:41,640 Speaker 5: kind of dig into layers deeper on the results I'm 214 00:10:41,679 --> 00:10:45,080 Speaker 5: seeing here, another really important number for investors is users. 215 00:10:45,440 --> 00:10:48,040 Speaker 5: User growth came in right an analyss essment, so there's 216 00:10:48,040 --> 00:10:51,040 Speaker 5: no kind of upside to offset that downside that you're 217 00:10:51,040 --> 00:10:52,160 Speaker 5: seeing on the top line. 218 00:10:52,440 --> 00:10:55,760 Speaker 4: Talk to us about the ad space and specifically Snap 219 00:10:55,840 --> 00:10:58,720 Speaker 4: kind of tweaking the design of its direct response ads. 220 00:10:58,760 --> 00:11:02,360 Speaker 4: You mentioned the impact of that. To what extent are 221 00:11:02,400 --> 00:11:07,280 Speaker 4: these earnings and the market reaction about the ad space 222 00:11:07,320 --> 00:11:08,560 Speaker 4: in particular for Snap. 223 00:11:09,520 --> 00:11:12,719 Speaker 5: For Snap, it's all about that ad space. They are 224 00:11:12,800 --> 00:11:15,120 Speaker 5: a smaller player in the ad world. They have much 225 00:11:15,200 --> 00:11:18,160 Speaker 5: less share than say Alphabet or Meta, but the vast 226 00:11:18,200 --> 00:11:21,960 Speaker 5: majority of their dollars come from advertising revenue, and historically 227 00:11:22,040 --> 00:11:25,640 Speaker 5: Snap has been stronger in something called brand advertising, which 228 00:11:25,679 --> 00:11:28,000 Speaker 5: is kind of telling the big picture story of your brand, 229 00:11:28,000 --> 00:11:30,600 Speaker 5: and less on what you mentioned, which is direct response ads, 230 00:11:30,800 --> 00:11:32,840 Speaker 5: those ads where you see something, you click on it, 231 00:11:32,840 --> 00:11:35,760 Speaker 5: and you buy it right there. In the current economic environment, 232 00:11:35,880 --> 00:11:39,319 Speaker 5: marketers are really preferring those direct response ads because they 233 00:11:39,320 --> 00:11:42,400 Speaker 5: can directly tie return on investment. They can prove out 234 00:11:42,480 --> 00:11:45,920 Speaker 5: saying somebody clicked on this dress video and bought this 235 00:11:46,040 --> 00:11:48,720 Speaker 5: dress versus you know, someone likes the brands better because 236 00:11:48,760 --> 00:11:51,760 Speaker 5: of the brand advertisement. So to have Snap kind of 237 00:11:51,800 --> 00:11:54,760 Speaker 5: playing around with those direct response ads, a lot of 238 00:11:54,760 --> 00:11:56,920 Speaker 5: marketers have backed away, and it's clear that they're not 239 00:11:56,960 --> 00:11:59,719 Speaker 5: spending on the platform now. The company will say they 240 00:11:59,800 --> 00:12:02,640 Speaker 5: have to make these changes, this will improve their business 241 00:12:02,679 --> 00:12:05,640 Speaker 5: in the long run. But it does seem like there 242 00:12:05,720 --> 00:12:08,200 Speaker 5: is quite a bit at least twenty percent downward pressure 243 00:12:08,240 --> 00:12:11,320 Speaker 5: on the stock of Impatients from investors in terms of 244 00:12:11,360 --> 00:12:12,640 Speaker 5: the story that they're telling today. 245 00:12:12,760 --> 00:12:15,240 Speaker 2: All right, So, as you note in your story, and 246 00:12:15,280 --> 00:12:17,400 Speaker 2: I'm looking at this was a stock that back in 247 00:12:17,440 --> 00:12:20,000 Speaker 2: September of twenty twenty one was above eighty three dollars 248 00:12:20,040 --> 00:12:22,600 Speaker 2: a share. We're now just under eleven dollars. Okay, so 249 00:12:22,960 --> 00:12:27,560 Speaker 2: a very different world and certainly in terms of market value. 250 00:12:27,760 --> 00:12:29,760 Speaker 2: You write a new story, though, Alex. You talk about 251 00:12:29,760 --> 00:12:33,480 Speaker 2: how they have also been looking for new streams of revenue, 252 00:12:33,960 --> 00:12:37,240 Speaker 2: and there's things about you know, trying and close virtually 253 00:12:38,280 --> 00:12:42,280 Speaker 2: and other things. Is this something that could ultimately move 254 00:12:42,360 --> 00:12:45,679 Speaker 2: that revenue needle and be a big driver of growth 255 00:12:45,720 --> 00:12:46,360 Speaker 2: going forward? 256 00:12:47,120 --> 00:12:50,280 Speaker 5: It potentially could. I actually chatted to Snap CEO about 257 00:12:50,280 --> 00:12:54,240 Speaker 5: a year a week ago, talking at his product conference, 258 00:12:54,920 --> 00:12:57,720 Speaker 5: you know, saying, hey, Snap looks like a very different company. 259 00:12:57,720 --> 00:12:57,880 Speaker 6: Now. 260 00:12:57,920 --> 00:13:01,040 Speaker 5: They're doing things like selling subscription, and they're doing things 261 00:13:01,080 --> 00:13:04,800 Speaker 5: like selling software to businesses. It's a really interesting moment 262 00:13:04,840 --> 00:13:06,800 Speaker 5: for them. So there's potential there. But these things are 263 00:13:06,880 --> 00:13:09,319 Speaker 5: so early days that they're not upsetting the losses they're 264 00:13:09,320 --> 00:13:10,439 Speaker 5: seeing from the ad business. 265 00:13:11,480 --> 00:13:14,560 Speaker 4: I want to talk about the Meta piece because they 266 00:13:14,600 --> 00:13:16,640 Speaker 4: had a big win yesterday, and they also had a 267 00:13:16,640 --> 00:13:19,559 Speaker 4: big win when it came to their ads and their 268 00:13:19,600 --> 00:13:22,040 Speaker 4: AD revenue, which was critical to watch as it was 269 00:13:22,080 --> 00:13:25,520 Speaker 4: with Snap today. Does the win for Meta yesterday make 270 00:13:25,840 --> 00:13:30,640 Speaker 4: the results today from Snap even worse for investors? 271 00:13:30,640 --> 00:13:32,960 Speaker 5: Sort of? So Meta story is a little bit different 272 00:13:32,960 --> 00:13:35,440 Speaker 5: because of how big they are. They have certainly been 273 00:13:35,559 --> 00:13:40,040 Speaker 5: challenged by kind of the general dismalness of the ad business, 274 00:13:40,040 --> 00:13:42,760 Speaker 5: by marketers pulling back spending, But their business is so 275 00:13:42,920 --> 00:13:45,720 Speaker 5: much bigger, and Snap is so much more of a 276 00:13:45,840 --> 00:13:49,720 Speaker 5: kind of real true growth company that that's all Snap 277 00:13:49,840 --> 00:13:52,160 Speaker 5: kind of has the ability to rely on. Snap has 278 00:13:52,200 --> 00:13:54,440 Speaker 5: also cut costs, They've done a lot of the things 279 00:13:54,480 --> 00:13:57,640 Speaker 5: we've seen from the bigger players. But because folks really 280 00:13:57,760 --> 00:14:00,120 Speaker 5: kind of bet on them for that kind of all 281 00:14:00,160 --> 00:14:03,760 Speaker 5: in growth one hundred percent quarter over quarter in past years, 282 00:14:04,120 --> 00:14:06,360 Speaker 5: to see that number fall makes it a little bit 283 00:14:06,440 --> 00:14:09,079 Speaker 5: challenging With Meta, you know, the big question for them 284 00:14:09,160 --> 00:14:11,920 Speaker 5: has been Okay, you have this big core ad business, 285 00:14:12,080 --> 00:14:14,079 Speaker 5: are you spending enough time there to make sure it's 286 00:14:14,080 --> 00:14:17,079 Speaker 5: still going well in this challenge ad environment? And also 287 00:14:17,160 --> 00:14:19,720 Speaker 5: what else are you spending on? This whole metaverse thing 288 00:14:19,800 --> 00:14:22,400 Speaker 5: is not something that we will realize in the next 289 00:14:22,440 --> 00:14:25,160 Speaker 5: decade or so, And are those dollars actually going to 290 00:14:25,200 --> 00:14:27,120 Speaker 5: things that are going to increase the value of the business. 291 00:14:27,160 --> 00:14:30,680 Speaker 5: So kind of similar kind of wins affecting both of 292 00:14:30,720 --> 00:14:33,080 Speaker 5: those companies, But I think they're just kind of size 293 00:14:33,480 --> 00:14:35,800 Speaker 5: and status in the ad market makes it a little 294 00:14:35,840 --> 00:14:36,960 Speaker 5: bit of a different tale. 295 00:14:37,160 --> 00:14:39,600 Speaker 2: Well, you know, alex, I always think about, you know, 296 00:14:39,880 --> 00:14:42,960 Speaker 2: more broadly, what's going on in social media and just 297 00:14:43,280 --> 00:14:46,400 Speaker 2: all the things, whether it's apps, whether it's streaming services, 298 00:14:46,440 --> 00:14:49,760 Speaker 2: everything competing for our attention. At some point there's got 299 00:14:49,800 --> 00:14:51,280 Speaker 2: to be a little bit of a bust I think 300 00:14:51,320 --> 00:14:54,640 Speaker 2: of this. I caught up with Alexis Ohanian this week, right, 301 00:14:54,720 --> 00:14:57,360 Speaker 2: the co founder of Reddit, you know, and he too said, 302 00:14:57,400 --> 00:15:00,640 Speaker 2: you know, social media, you know, culturally made be going 303 00:15:00,720 --> 00:15:02,880 Speaker 2: to go through a rethink, if you will, how do 304 00:15:02,960 --> 00:15:05,600 Speaker 2: you look at it? And so is it a case 305 00:15:05,640 --> 00:15:07,200 Speaker 2: of some of the smaller guys are going to fall 306 00:15:07,240 --> 00:15:09,720 Speaker 2: to the wayside, or I don't know, how do you 307 00:15:09,760 --> 00:15:12,720 Speaker 2: think of a big picture and then how do investors 308 00:15:12,760 --> 00:15:14,560 Speaker 2: need to think about it? Maybe for some shifts that 309 00:15:14,640 --> 00:15:15,760 Speaker 2: might be to come. 310 00:15:16,640 --> 00:15:19,200 Speaker 5: It's a really interesting moment, and I'll actually use metas 311 00:15:19,200 --> 00:15:22,160 Speaker 5: Earnings to kind of illustrate this. For you know, as 312 00:15:22,160 --> 00:15:24,640 Speaker 5: long as we've had social it's really been about who 313 00:15:24,680 --> 00:15:27,880 Speaker 5: follows you and kind of developing that following and choosing 314 00:15:27,880 --> 00:15:30,560 Speaker 5: the people you follow. When TikTok kind of smashed on 315 00:15:30,600 --> 00:15:32,680 Speaker 5: the scene, they changed the game. They made it about 316 00:15:32,920 --> 00:15:35,920 Speaker 5: what content is best and what content's going to resonate 317 00:15:36,240 --> 00:15:39,400 Speaker 5: with the user's interests instead of with the people that 318 00:15:39,400 --> 00:15:44,000 Speaker 5: that user will follow. Meta YouTube they've all copied kind 319 00:15:44,040 --> 00:15:47,280 Speaker 5: of that TikTok idea, where now your feed is full 320 00:15:47,360 --> 00:15:49,400 Speaker 5: of things they think you might be interested in that's 321 00:15:49,400 --> 00:15:52,880 Speaker 5: selected for you by an algorithm less so your friends 322 00:15:52,960 --> 00:15:55,920 Speaker 5: and family, and so Meta and alphabet have been trying 323 00:15:55,960 --> 00:15:58,880 Speaker 5: to kind of figure out how to match ads with 324 00:15:58,960 --> 00:16:02,000 Speaker 5: those interest groups on this new kind of world where 325 00:16:02,040 --> 00:16:04,520 Speaker 5: a snap has taken a little bit of a different approach. 326 00:16:04,920 --> 00:16:07,680 Speaker 5: They have always had kind of the core feature of 327 00:16:07,760 --> 00:16:11,040 Speaker 5: Snapchat being person to person communication, that kind. 328 00:16:10,840 --> 00:16:11,800 Speaker 3: Of closed loop. 329 00:16:11,920 --> 00:16:14,480 Speaker 5: But I will say it's really interesting. In the last 330 00:16:14,520 --> 00:16:16,760 Speaker 5: few weeks here, Snap has announced that more people can 331 00:16:16,760 --> 00:16:20,600 Speaker 5: now post content publicly, so you're seeing some kind of changes, 332 00:16:20,640 --> 00:16:22,760 Speaker 5: And I think there's this really interesting tension right now 333 00:16:22,800 --> 00:16:25,920 Speaker 5: between folks wanting to stay connected with friends and family 334 00:16:26,000 --> 00:16:28,200 Speaker 5: and a lot of the platforms starting to move away 335 00:16:28,240 --> 00:16:30,600 Speaker 5: from that in favor of showing you things that are 336 00:16:30,640 --> 00:16:34,320 Speaker 5: maybe more entertaining, maybe more in the taking screen time 337 00:16:34,360 --> 00:16:36,760 Speaker 5: from the Netflixes and Hulas of the world. But it's 338 00:16:36,840 --> 00:16:39,400 Speaker 5: less about you know, your your aunts in Texas or 339 00:16:39,400 --> 00:16:40,840 Speaker 5: your friend who's living in New York City. 340 00:16:40,960 --> 00:16:43,640 Speaker 2: Yeah that's really funny. Yeah, no, it's so true, and 341 00:16:43,760 --> 00:16:45,240 Speaker 2: spending a little bit like for the first time, I'm 342 00:16:45,240 --> 00:16:47,240 Speaker 2: finally like checking out TikTok. I know I'm a little 343 00:16:47,240 --> 00:16:49,120 Speaker 2: bit slow to the game, but kind of playing around 344 00:16:49,160 --> 00:16:51,760 Speaker 2: with that more than like sitting down for hours, you know, 345 00:16:52,320 --> 00:16:53,520 Speaker 2: binging on a series. 346 00:16:53,720 --> 00:16:55,880 Speaker 4: Yeah no, I do it sometimes when I don't have 347 00:16:55,880 --> 00:16:58,320 Speaker 4: the energy to pick a show. Alex, I want to 348 00:16:58,440 --> 00:17:01,080 Speaker 4: end on your story about big tech being obsessed with 349 00:17:01,120 --> 00:17:04,080 Speaker 4: cost cutting, except for when it comes to AI, tell 350 00:17:04,080 --> 00:17:05,000 Speaker 4: me what's going on there? 351 00:17:05,600 --> 00:17:05,879 Speaker 1: Yeah. 352 00:17:06,040 --> 00:17:08,000 Speaker 5: I kind of made the argument in our newsletter today 353 00:17:08,000 --> 00:17:10,439 Speaker 5: that AAI is coming for your jobs, just not the 354 00:17:10,440 --> 00:17:14,720 Speaker 5: way you thought. Meta, Alphabet, Microsoft, They've all come out 355 00:17:14,800 --> 00:17:16,119 Speaker 5: kind of promising. 356 00:17:15,640 --> 00:17:17,639 Speaker 3: These big cost cuts while. 357 00:17:17,440 --> 00:17:20,880 Speaker 5: Also kind of emphatically reminding investors that they're spending tons 358 00:17:20,920 --> 00:17:23,800 Speaker 5: of money on AI. So where is that money coming from? 359 00:17:24,320 --> 00:17:26,919 Speaker 5: You can look back to the forty thousand positions that 360 00:17:26,960 --> 00:17:30,239 Speaker 5: they've eliminated over the past few months to kind of 361 00:17:30,400 --> 00:17:34,600 Speaker 5: keep those savings and reinvest those funds into artificial intelligence. 362 00:17:34,640 --> 00:17:37,199 Speaker 5: So in this kind of big AI arms race that 363 00:17:37,240 --> 00:17:39,959 Speaker 5: we're in right now, a lot of that's being interestingly 364 00:17:40,000 --> 00:17:42,879 Speaker 5: funded by big tech from the dollars that are not 365 00:17:42,960 --> 00:17:45,439 Speaker 5: going to headcount, that are not going to offices, that 366 00:17:45,480 --> 00:17:47,399 Speaker 5: are only going to kind of the products that are 367 00:17:47,400 --> 00:17:51,000 Speaker 5: getting folks really excited and leaving a lot of former 368 00:17:51,040 --> 00:17:52,640 Speaker 5: employees kind of out to drive. 369 00:17:53,440 --> 00:17:57,320 Speaker 2: Good to be a programmer right now? Really, you know, hey, 370 00:17:57,720 --> 00:18:00,520 Speaker 2: really quickly fifteen seconds, what would you ask Snap on 371 00:18:00,560 --> 00:18:01,280 Speaker 2: the earnings call? 372 00:18:02,240 --> 00:18:04,439 Speaker 5: I want to know at what point revenue turns around 373 00:18:04,520 --> 00:18:06,840 Speaker 5: the changes that they're making, when do those kick in, 374 00:18:06,920 --> 00:18:09,959 Speaker 5: and when do they start luring advertisers to keep that 375 00:18:10,480 --> 00:18:12,359 Speaker 5: top line from continuing to slip? 376 00:18:12,400 --> 00:18:15,120 Speaker 2: All right, great stuff, as oways our Alex Birinka, Bloomberg 377 00:18:15,119 --> 00:18:19,399 Speaker 2: News Technology reporter there in La and check out her newsletter. 378 00:18:19,560 --> 00:18:22,640 Speaker 2: You can find it Bloomberg Tech Daily Newsletter. Just sign 379 00:18:22,720 --> 00:18:24,560 Speaker 2: up at Bloomberg dot com Slash Technology. 380 00:18:26,359 --> 00:18:29,960 Speaker 1: You're listening to the Bloomberg Business Week podcast. Catch us 381 00:18:29,960 --> 00:18:34,000 Speaker 1: live weekday afternoons from three to six Easter on Bloomberg Radio, 382 00:18:34,200 --> 00:18:37,480 Speaker 1: the Bloomberg Business app, and YouTube. You can also listen 383 00:18:37,560 --> 00:18:40,680 Speaker 1: live on Amazon Alexa from our flagship New York station. 384 00:18:41,119 --> 00:18:43,919 Speaker 1: Just say Alexa play Bloomberg eleven thirty. 385 00:18:45,720 --> 00:18:48,400 Speaker 2: Pressure is building on President Buying to respond after House 386 00:18:48,440 --> 00:18:50,919 Speaker 2: Republicans unified on a set of demands to vert a 387 00:18:50,920 --> 00:18:54,480 Speaker 2: contest a catastrophic US debt default in the coming weeks. 388 00:18:54,920 --> 00:18:57,720 Speaker 2: So there's pressure on the President to really sit down 389 00:18:57,720 --> 00:19:01,560 Speaker 2: with Speaker Kevin McCarthy. Well, Bloomberg watched correspondent Amory Hordern 390 00:19:01,840 --> 00:19:03,840 Speaker 2: did sit down at the Speaker of the House to 391 00:19:03,840 --> 00:19:05,960 Speaker 2: talk about where we are. Check it out, everybody. 392 00:19:07,119 --> 00:19:09,719 Speaker 4: Many people doubted you were going to be able to 393 00:19:09,800 --> 00:19:12,560 Speaker 4: get this bill passed through the floor. You prove them wrong. 394 00:19:12,600 --> 00:19:15,600 Speaker 4: You successfully got it through the floor two hundred and 395 00:19:15,640 --> 00:19:19,120 Speaker 4: seventeen voting in favor of you. Parsident Biden, though, says 396 00:19:19,160 --> 00:19:21,560 Speaker 4: he's only going to meet with you if you separate 397 00:19:22,119 --> 00:19:26,240 Speaker 4: the fiscal spending, cuts the budget with the debt ceiling. 398 00:19:26,320 --> 00:19:27,720 Speaker 4: So what comes next. 399 00:19:28,160 --> 00:19:30,520 Speaker 6: Well, I don't know, because it was eighty five days ago. 400 00:19:30,560 --> 00:19:33,240 Speaker 7: I sat down with the President February first, talking about 401 00:19:33,280 --> 00:19:36,639 Speaker 7: finding a sensible, responsible way to raise the debt limit 402 00:19:36,960 --> 00:19:40,399 Speaker 7: and make us less dependent on China, curve inflation, and 403 00:19:40,640 --> 00:19:43,560 Speaker 7: bring growth to this economy. And that's exactly what we 404 00:19:43,600 --> 00:19:45,240 Speaker 7: just did. The President then said he wasn't going to 405 00:19:45,280 --> 00:19:47,439 Speaker 7: meet with me until we showed him a plan. So 406 00:19:47,480 --> 00:19:49,640 Speaker 7: then I showed him a plan, and then we passed it. 407 00:19:50,080 --> 00:19:52,679 Speaker 7: You know, the way government works is the House passes 408 00:19:52,720 --> 00:19:54,679 Speaker 7: the bill, the Senate passes a bill, and then you 409 00:19:54,760 --> 00:19:57,600 Speaker 7: conference together and the President can sign decide whether he 410 00:19:57,680 --> 00:20:00,480 Speaker 7: signs it or not. The challenge here is the Senate's nothing. 411 00:20:00,920 --> 00:20:02,040 Speaker 6: But I shouldn't be rude. 412 00:20:02,119 --> 00:20:05,600 Speaker 7: They did name March Maine maple syrup, but they did 413 00:20:05,600 --> 00:20:07,520 Speaker 7: get that done, but they haven't done anything on the 414 00:20:07,560 --> 00:20:10,120 Speaker 7: debt sitting, and the President has ignored this problem. He's 415 00:20:10,200 --> 00:20:14,680 Speaker 7: actually putting the economy of America in jeopardy by not 416 00:20:14,720 --> 00:20:18,560 Speaker 7: doing anything because only the House has raised the debt limit. 417 00:20:18,640 --> 00:20:21,080 Speaker 7: Passed the bill to do that and at the same. 418 00:20:20,880 --> 00:20:22,639 Speaker 6: Time grow the economy. 419 00:20:22,680 --> 00:20:25,200 Speaker 7: And we did it with ideas that he has voted. 420 00:20:24,880 --> 00:20:28,160 Speaker 6: For work requirements. He voted for that as a Senator. 421 00:20:28,160 --> 00:20:31,280 Speaker 7: But more importantly, just a couple months ago in Wisconsin 422 00:20:31,320 --> 00:20:33,520 Speaker 7: it passed with eighty two percent of the vote to 423 00:20:33,600 --> 00:20:35,879 Speaker 7: limit our growth in the future so government doesn't get 424 00:20:35,920 --> 00:20:38,760 Speaker 7: out of control. Well, that's an idea from Joe Manchin. 425 00:20:39,280 --> 00:20:42,840 Speaker 7: We help the supply chain, We repel eighty seven thousand 426 00:20:42,840 --> 00:20:46,800 Speaker 7: IRS agents, We make America energy independent. We cut the 427 00:20:46,840 --> 00:20:49,920 Speaker 7: red tape so we could build things again in America. 428 00:20:50,000 --> 00:20:51,320 Speaker 6: I don't think that's radical. 429 00:20:51,359 --> 00:20:52,880 Speaker 7: And the words that are coming out of the White 430 00:20:52,880 --> 00:20:55,680 Speaker 7: House that we are going to melt children's bones, we're 431 00:20:55,680 --> 00:20:58,639 Speaker 7: going to create asthma, there's nothing in the build that 432 00:20:58,760 --> 00:21:02,560 Speaker 7: does that. It actually text veterans protects our military, makes 433 00:21:02,560 --> 00:21:06,439 Speaker 7: his a stronger case for the future. 434 00:21:07,040 --> 00:21:09,240 Speaker 2: All right, That, of course, was the US Speaker of 435 00:21:09,280 --> 00:21:11,840 Speaker 2: the House, Kevin McCarthy catching up with our Bloomberg Washington 436 00:21:11,840 --> 00:21:14,560 Speaker 2: correspondent and Marie Horden. If you want to hear more 437 00:21:14,560 --> 00:21:16,720 Speaker 2: of the interview, just get to Bloomberg dot Com or 438 00:21:16,800 --> 00:21:21,240 Speaker 2: check it out on the Bloomberg Terminal. This is Bloomberg Radio. 439 00:21:28,480 --> 00:21:31,960 Speaker 2: Well things can maybe get for the over one hundred 440 00:21:31,960 --> 00:21:35,960 Speaker 2: million obesion overweight individuals in the United States. Uh, there 441 00:21:36,000 --> 00:21:38,280 Speaker 2: is a story in the new issue Bloomberg BusinessWeek. It's 442 00:21:38,280 --> 00:21:41,200 Speaker 2: out on newsstands, online at Bloomberg dot com, slash BusinessWeek, 443 00:21:41,240 --> 00:21:44,080 Speaker 2: and on the Bloomberg Terminal. And many of these individuals 444 00:21:44,160 --> 00:21:46,639 Speaker 2: would love to lose a bunch of weight to improve 445 00:21:46,680 --> 00:21:49,240 Speaker 2: their health situation. And you know what, there's a bunch 446 00:21:49,280 --> 00:21:51,600 Speaker 2: of drugs out there that can do that. The big 447 00:21:51,600 --> 00:21:54,280 Speaker 2: problem though, is the cost and having to use the 448 00:21:54,320 --> 00:21:56,520 Speaker 2: drug for the rest of your life. All right, let's 449 00:21:56,520 --> 00:21:58,760 Speaker 2: get into it with our Bloomberg News healthcare reporting team 450 00:21:58,800 --> 00:22:01,719 Speaker 2: who wrote the story of Emma Court and Bob Langreth. 451 00:22:02,119 --> 00:22:04,359 Speaker 2: They are both here in our Interactive Broker studio. So 452 00:22:04,359 --> 00:22:06,840 Speaker 2: excited to have both of you with us. Emma, why 453 00:22:06,840 --> 00:22:08,359 Speaker 2: don't you kick it off with us and tell us 454 00:22:08,359 --> 00:22:11,119 Speaker 2: about this class of drugs which they were mentioned at 455 00:22:11,160 --> 00:22:14,080 Speaker 2: the Oscars. Comedians talk about them. I think Elon Musk 456 00:22:14,119 --> 00:22:16,520 Speaker 2: has talked about them. Tell us what we're talking about. 457 00:22:17,000 --> 00:22:18,879 Speaker 8: Yeah, Well, first of all, thank you so much for 458 00:22:18,920 --> 00:22:21,360 Speaker 8: having us on. We're really excited about the story. It's 459 00:22:21,400 --> 00:22:26,560 Speaker 8: the cover story this week, so we're thrilled. These new 460 00:22:26,680 --> 00:22:30,520 Speaker 8: drugs are called effectively glp ones. They're named after a 461 00:22:30,640 --> 00:22:34,560 Speaker 8: hormone they mimic that essentially helps people feel fuller, they 462 00:22:34,560 --> 00:22:37,400 Speaker 8: have less appetite, they eat less, and they lose weight. 463 00:22:38,160 --> 00:22:41,080 Speaker 8: What's interesting about these drugs is they're not all that new. 464 00:22:41,240 --> 00:22:44,240 Speaker 8: This class has been around for diabetes for many years, 465 00:22:44,720 --> 00:22:48,720 Speaker 8: but more recently pharma companies have been developing them specifically 466 00:22:48,760 --> 00:22:51,720 Speaker 8: for obesity. There's a couple of different names for them. 467 00:22:51,760 --> 00:22:54,960 Speaker 8: People are very familiar by now with ozembic, which is 468 00:22:55,040 --> 00:22:57,920 Speaker 8: a diabetes drug. That's the one that Jimmy Kimmel joked 469 00:22:57,920 --> 00:23:01,520 Speaker 8: about at the oscars. But they're are also drugs called. 470 00:23:01,359 --> 00:23:04,440 Speaker 2: If everybody laughed or whether it was like deadpan, because 471 00:23:04,480 --> 00:23:08,440 Speaker 2: it was like hitting too. 472 00:23:08,520 --> 00:23:12,480 Speaker 8: Go ahead, they're well. There are a number of perhaps 473 00:23:12,560 --> 00:23:16,040 Speaker 8: less well known drugs, including a new one called Munjaro 474 00:23:16,119 --> 00:23:18,920 Speaker 8: that hasn't been formally approved for obesity but likely will 475 00:23:18,920 --> 00:23:21,679 Speaker 8: in the next year. There's also a drug called Wigovi, 476 00:23:21,840 --> 00:23:24,920 Speaker 8: which was the first sort of highly effective obesity drug 477 00:23:25,040 --> 00:23:28,439 Speaker 8: approved in the US. And what's really interesting about them is, 478 00:23:28,880 --> 00:23:32,480 Speaker 8: you know, these are drugs that are helping people lose 479 00:23:32,600 --> 00:23:35,640 Speaker 8: up to fifty pounds in some cases. So they're way 480 00:23:35,680 --> 00:23:38,040 Speaker 8: more effective than anything that had been available for weight 481 00:23:38,040 --> 00:23:41,199 Speaker 8: loss before, and it's getting a lot of doctors and 482 00:23:41,240 --> 00:23:42,399 Speaker 8: patients excited about it. 483 00:23:42,680 --> 00:23:45,280 Speaker 4: So Bob, come in here, because we've all, i think, 484 00:23:45,359 --> 00:23:48,080 Speaker 4: heard in our lifetimes about a variety of different diet 485 00:23:48,160 --> 00:23:51,520 Speaker 4: pills and ways to lose weight. Certainly as a woman 486 00:23:51,560 --> 00:23:53,640 Speaker 4: growing up in the nineties heard about plenty of them. 487 00:23:53,960 --> 00:23:56,800 Speaker 4: How is ozemba weegov, how is it different? And what 488 00:23:56,840 --> 00:23:59,600 Speaker 4: are the risks and the some of the benefits I'm. 489 00:23:59,640 --> 00:24:01,960 Speaker 9: Talking to Yeah, one of the really interesting things for 490 00:24:02,080 --> 00:24:04,399 Speaker 9: me as I've been covering drug industry for decades and 491 00:24:05,200 --> 00:24:07,320 Speaker 9: you know, a b City weight loss that was kind 492 00:24:07,320 --> 00:24:10,359 Speaker 9: of always like a graveyard for drugs. Drugnacity had been 493 00:24:10,400 --> 00:24:12,320 Speaker 9: trying for a long time to come up with drugs. 494 00:24:12,320 --> 00:24:14,160 Speaker 9: There was the kind of there are a whole bunch 495 00:24:14,240 --> 00:24:16,880 Speaker 9: of safety v calls. One of the most famous ones 496 00:24:17,000 --> 00:24:19,560 Speaker 9: or infamous ones was fen fen back in the late nineties, 497 00:24:19,560 --> 00:24:23,160 Speaker 9: where one of the components caused heart problems. Uh so 498 00:24:24,000 --> 00:24:26,440 Speaker 9: BC drugs for a long time at a bad reputation, 499 00:24:26,680 --> 00:24:29,040 Speaker 9: and these ones, you know, sort of came a little 500 00:24:29,040 --> 00:24:30,960 Speaker 9: bit almost out of left field. As MS said, they 501 00:24:30,960 --> 00:24:34,439 Speaker 9: were developed for diabetes, and drug companies increasingly started you know, 502 00:24:34,520 --> 00:24:37,399 Speaker 9: noting noticing the weight loss effects they were seeing. And 503 00:24:37,440 --> 00:24:41,919 Speaker 9: as I started testing the drugs uh in people that 504 00:24:42,040 --> 00:24:46,520 Speaker 9: didn't have diabetes there that were uh suffered from a 505 00:24:46,520 --> 00:24:49,919 Speaker 9: b CD but didn't have diabetes, they started seeing even larger. 506 00:24:49,640 --> 00:24:50,800 Speaker 6: Amounts of weight loss. 507 00:24:51,320 --> 00:24:55,080 Speaker 9: Uh So, the safety track record and diabetes is pretty good. 508 00:24:55,119 --> 00:24:56,960 Speaker 9: Like all drugs are not without risks, you know, but 509 00:24:57,040 --> 00:24:59,880 Speaker 9: they do have a number of side effects, including non 510 00:25:00,480 --> 00:25:03,320 Speaker 9: in vomiting and diarrhea potentially, so do you have a bunch 511 00:25:03,359 --> 00:25:05,399 Speaker 9: of gi side effects and you actually have to tightrate 512 00:25:05,440 --> 00:25:07,680 Speaker 9: them up slowly. These are injectable drugs. It's not a 513 00:25:07,720 --> 00:25:09,880 Speaker 9: simple pill. You have to inject them, most. 514 00:25:09,720 --> 00:25:10,520 Speaker 6: Of them weekly. 515 00:25:10,880 --> 00:25:11,240 Speaker 1: Most of that. 516 00:25:11,400 --> 00:25:14,200 Speaker 9: Yeah, the new ones are weekly. And what's happened is 517 00:25:14,280 --> 00:25:17,560 Speaker 9: as they've gone to sort of more potent, long acting ones, 518 00:25:17,560 --> 00:25:21,160 Speaker 9: they've seen the anti obesity effect increase, and that's when 519 00:25:21,160 --> 00:25:23,920 Speaker 9: they've started to get some of these dramatic weight loss. 520 00:25:24,040 --> 00:25:27,360 Speaker 9: And the Eli Lilomanjaro drug, which is like the newest one. 521 00:25:27,800 --> 00:25:30,640 Speaker 9: It's only approved for diabetes, but Eli Lilly is very 522 00:25:30,680 --> 00:25:33,360 Speaker 9: soon going to seek approval for obesity. That's the one 523 00:25:33,359 --> 00:25:35,680 Speaker 9: that's showing some of the most dramatic weight loss effects 524 00:25:35,720 --> 00:25:38,720 Speaker 9: so far, and they just had another positive study out today. 525 00:25:39,040 --> 00:25:40,200 Speaker 2: Why is it so expensive? 526 00:25:41,400 --> 00:25:42,960 Speaker 8: It's the billion dollar question. 527 00:25:43,160 --> 00:25:45,399 Speaker 2: I feel like we asked this so often about drugs, 528 00:25:45,440 --> 00:25:47,520 Speaker 2: and I know we do, but why is it especially 529 00:25:47,560 --> 00:25:49,840 Speaker 2: it's been around for a while, right, I'm just curious, 530 00:25:50,040 --> 00:25:51,160 Speaker 2: why is it so expensive? 531 00:25:51,760 --> 00:25:53,800 Speaker 8: So some of these drugs are newer, and they are 532 00:25:53,840 --> 00:25:56,360 Speaker 8: the most expensive ones, so they they are new, they 533 00:25:56,359 --> 00:25:58,399 Speaker 8: can't say they've been around for many years. 534 00:25:58,880 --> 00:25:59,080 Speaker 6: You know. 535 00:25:59,240 --> 00:26:02,040 Speaker 8: It's a difficult question, and we certainly asked the companies 536 00:26:02,080 --> 00:26:04,679 Speaker 8: about it, and we didn't get a super straight answer 537 00:26:04,720 --> 00:26:06,720 Speaker 8: on it. I would say, I'm curious what Bob thinks 538 00:26:06,760 --> 00:26:07,280 Speaker 8: about those. 539 00:26:08,040 --> 00:26:10,960 Speaker 9: Well, I've been asking drug companies about their pricing. 540 00:26:10,680 --> 00:26:11,800 Speaker 6: Forever, druggies, forever. 541 00:26:12,000 --> 00:26:14,240 Speaker 9: You know that that is one question when you ask, 542 00:26:14,400 --> 00:26:18,520 Speaker 9: it's very very difficult to get. Like my senses, they 543 00:26:18,520 --> 00:26:20,560 Speaker 9: don't really tell you the real answer, like what happened 544 00:26:20,760 --> 00:26:22,879 Speaker 9: in the back room when they decided. 545 00:26:22,920 --> 00:26:24,879 Speaker 2: I have a brother who was in pharmacuticals for over 546 00:26:24,960 --> 00:26:26,720 Speaker 2: twenty years, and he was always like, listen, we do 547 00:26:26,760 --> 00:26:28,199 Speaker 2: so much R and D, and I'm like, did I 548 00:26:28,200 --> 00:26:30,760 Speaker 2: ever come on? You also make a ton of money 549 00:26:30,800 --> 00:26:31,280 Speaker 2: on stuff. 550 00:26:31,320 --> 00:26:33,639 Speaker 9: So but basically in the US, you know, it's a 551 00:26:33,680 --> 00:26:36,080 Speaker 9: free market. Drug companies and price their drugs at kind 552 00:26:36,119 --> 00:26:38,800 Speaker 9: of whatever price they want. And these when they came 553 00:26:38,840 --> 00:26:42,320 Speaker 9: on the market as diabetes drugs, they were priced, you know, 554 00:26:42,440 --> 00:26:46,320 Speaker 9: fairly high. And they and some of the pricing. There's 555 00:26:46,320 --> 00:26:48,480 Speaker 9: one that will Govi drug, which is a higher dose 556 00:26:48,600 --> 00:26:51,119 Speaker 9: version of a zempic that Nova Nordi sells her obesity. 557 00:26:51,160 --> 00:26:55,280 Speaker 9: They priced out it even higher price than nozempic. It's 558 00:26:55,400 --> 00:26:59,480 Speaker 9: exact different doses of the exact same you know, chemical compound, 559 00:27:00,080 --> 00:27:01,400 Speaker 9: but one is a higher price. 560 00:27:01,480 --> 00:27:03,480 Speaker 6: The abcity one is a higher price. 561 00:27:03,600 --> 00:27:06,399 Speaker 8: The second interesting aspect of this is like when you 562 00:27:06,480 --> 00:27:08,520 Speaker 8: look at the sheer number of people who would be 563 00:27:08,600 --> 00:27:11,000 Speaker 8: eligible for these drugs in the US, it's more than 564 00:27:11,000 --> 00:27:13,560 Speaker 8: one hundred million people, right, So it's like it's massive. 565 00:27:13,680 --> 00:27:16,280 Speaker 8: Why are the prices so high given that the market 566 00:27:16,320 --> 00:27:19,280 Speaker 8: opportunity is huge? And we actually talked to one of 567 00:27:19,280 --> 00:27:22,200 Speaker 8: the sort of foundational scientists in this field. His name 568 00:27:22,280 --> 00:27:25,080 Speaker 8: is Dan Drucker, and he was one of the guys 569 00:27:25,080 --> 00:27:28,440 Speaker 8: who helped discover these hormones in the body many many 570 00:27:28,480 --> 00:27:31,080 Speaker 8: years ago. And he said, you know, he's asked companies 571 00:27:31,119 --> 00:27:32,840 Speaker 8: over the years, why don't you just do, you know, 572 00:27:32,960 --> 00:27:35,119 Speaker 8: be the McDonald's in the space, Which is kind of 573 00:27:35,119 --> 00:27:38,199 Speaker 8: an ironic comparison if you think about it, But you know, 574 00:27:38,240 --> 00:27:41,679 Speaker 8: why don't you come out with really cheaper versions of 575 00:27:41,720 --> 00:27:43,640 Speaker 8: these drugs and lots of people take them and you'll 576 00:27:43,680 --> 00:27:44,800 Speaker 8: still make a bunch of money. 577 00:27:45,119 --> 00:27:47,440 Speaker 2: And you're talking about one in three how many was 578 00:27:47,480 --> 00:27:48,480 Speaker 2: our population. 579 00:27:49,480 --> 00:27:51,639 Speaker 6: Of adults in the US of obesity. 580 00:27:51,760 --> 00:27:54,360 Speaker 2: Yeah, so what's interesting too, And I feel like there's 581 00:27:54,359 --> 00:27:58,560 Speaker 2: a bigger, broader conversation when it comes to healthcare, right, 582 00:27:58,760 --> 00:28:01,480 Speaker 2: I mean being overweight so in COVID like that could 583 00:28:01,560 --> 00:28:04,320 Speaker 2: make you more susceptible to not having a great outcome. 584 00:28:04,640 --> 00:28:08,440 Speaker 2: I mean, being overweight for most people causes all these 585 00:28:08,440 --> 00:28:10,760 Speaker 2: other problems. We know, it's a big reason why there's 586 00:28:10,800 --> 00:28:14,439 Speaker 2: so much diabetes. Where is the medical community, where's the 587 00:28:14,480 --> 00:28:17,600 Speaker 2: insurance community. I'm thinking about if we can get people 588 00:28:17,640 --> 00:28:20,800 Speaker 2: to be not so overweight that it's just better for 589 00:28:20,840 --> 00:28:24,080 Speaker 2: their health, come, their their healthcare, their outcomes and also 590 00:28:24,119 --> 00:28:25,080 Speaker 2: their health care costs. 591 00:28:25,200 --> 00:28:28,439 Speaker 8: Well. One really important and interesting aspect of this is 592 00:28:28,520 --> 00:28:31,119 Speaker 8: we often blame weight for a lot of things in 593 00:28:31,160 --> 00:28:34,600 Speaker 8: our society, and it's interesting to look at this idea 594 00:28:34,600 --> 00:28:36,919 Speaker 8: of BMI and realize it's kind of imprecise. 595 00:28:37,000 --> 00:28:37,359 Speaker 3: Right, it was. 596 00:28:37,320 --> 00:28:40,440 Speaker 8: Supposed to be kind of a population level measure, and 597 00:28:40,480 --> 00:28:43,160 Speaker 8: instead it's been applied to individuals, So like, if someone 598 00:28:43,200 --> 00:28:46,040 Speaker 8: has a certain weight, regardless of what their health looks 599 00:28:46,080 --> 00:28:49,520 Speaker 8: like in other aspects, they are obese just because of 600 00:28:49,560 --> 00:28:50,240 Speaker 8: their BMI. 601 00:28:50,440 --> 00:28:50,600 Speaker 3: Right. 602 00:28:50,640 --> 00:28:52,680 Speaker 8: If you think about that, it's kind of an interesting aspect, 603 00:28:52,800 --> 00:28:55,600 Speaker 8: Like you could be totally healthy, have no diabetes, have 604 00:28:55,680 --> 00:28:58,880 Speaker 8: no high cholesterol, whatever, and you're still ill by some 605 00:28:59,000 --> 00:29:01,720 Speaker 8: of these kind of modern standard So it is kind 606 00:29:01,720 --> 00:29:05,160 Speaker 8: of a nuanced, complicated topic. While higher weights have been 607 00:29:05,200 --> 00:29:08,560 Speaker 8: really highly associated with lots of different diseases, it's important 608 00:29:08,600 --> 00:29:10,480 Speaker 8: to note that there are a lot of shades of 609 00:29:10,480 --> 00:29:14,160 Speaker 8: gray here. Another interesting aspect of this is like, how. 610 00:29:14,040 --> 00:29:16,200 Speaker 2: Does that mean not as many people would really kind 611 00:29:16,240 --> 00:29:18,240 Speaker 2: of be eligible for these. 612 00:29:18,360 --> 00:29:20,480 Speaker 8: Well, that's the kind million, right, So if you think 613 00:29:20,520 --> 00:29:24,480 Speaker 8: about it, maybe not everyone who qualifies as overweight or 614 00:29:24,520 --> 00:29:27,600 Speaker 8: obese is necessarily going to be the best candidate for 615 00:29:27,640 --> 00:29:30,680 Speaker 8: these drugs. There's a big kind of murky middle of 616 00:29:30,760 --> 00:29:33,480 Speaker 8: people who where it's not totally clear how big a 617 00:29:33,640 --> 00:29:34,960 Speaker 8: danger than they are we impose it. 618 00:29:35,320 --> 00:29:38,080 Speaker 9: This is a really important question here. So like the 619 00:29:38,200 --> 00:29:43,440 Speaker 9: risks of of you know, suffering from obesity, you know, 620 00:29:44,680 --> 00:29:46,520 Speaker 9: as opposed to someone's normal way. A lot of that 621 00:29:46,560 --> 00:29:49,680 Speaker 9: comes from epidemiological studies. You know, what's not been proven 622 00:29:49,800 --> 00:29:52,960 Speaker 9: over the long terms. If you take the weight off 623 00:29:53,320 --> 00:29:56,360 Speaker 9: with one of these drugs, you know, do you eliminate 624 00:29:56,440 --> 00:29:59,160 Speaker 9: all these like actual like risks like the risk of 625 00:29:59,280 --> 00:30:02,160 Speaker 9: heart disease and strokes and other like concrete you know, 626 00:30:02,320 --> 00:30:05,120 Speaker 9: does it makenal downsides? They haven't actually proven that in 627 00:30:05,160 --> 00:30:08,440 Speaker 9: trials right now. It's not necessarily the case that you know, 628 00:30:08,480 --> 00:30:12,360 Speaker 9: you'll get all that benefit because these are epidemiology studies 629 00:30:12,360 --> 00:30:14,800 Speaker 9: and your communit you're comparing risk factors and there might 630 00:30:14,840 --> 00:30:16,920 Speaker 9: be other things that are different, you know, when they 631 00:30:17,040 --> 00:30:20,080 Speaker 9: when they do these complicated comparisons. So the companies, that's 632 00:30:20,120 --> 00:30:22,440 Speaker 9: the that's what I'm sure that's what they say. This 633 00:30:22,560 --> 00:30:25,080 Speaker 9: is not proven. There's only really proven to take off 634 00:30:25,080 --> 00:30:27,160 Speaker 9: a lot of way. You haven't proven that it prevents 635 00:30:27,160 --> 00:30:29,400 Speaker 9: a heart attack or a stroke five years from now, 636 00:30:29,520 --> 00:30:29,960 Speaker 9: and you have. 637 00:30:29,920 --> 00:30:33,360 Speaker 4: To take it forever, seemingly to prevent the heart disease. 638 00:30:33,440 --> 00:30:35,880 Speaker 8: So what the That's what the pharma companies are saying, 639 00:30:35,880 --> 00:30:38,080 Speaker 8: that's what the doctors are saying. There have been studies 640 00:30:38,080 --> 00:30:40,680 Speaker 8: of this new drug, WIGOVI that show when people quit 641 00:30:40,720 --> 00:30:43,600 Speaker 8: the drug after a year the way it comes back 642 00:30:43,680 --> 00:30:47,680 Speaker 8: for most people. So that is a big issue about 643 00:30:48,280 --> 00:30:51,960 Speaker 8: such an expensive drug like this is possibly a lifelong thing, 644 00:30:52,400 --> 00:30:54,320 Speaker 8: and it does raise questions about, well, what is the 645 00:30:54,320 --> 00:30:56,640 Speaker 8: side effect profile here? We're not talking about taking something 646 00:30:56,640 --> 00:30:58,280 Speaker 8: for a few months or years. 647 00:30:57,880 --> 00:31:01,760 Speaker 4: Forever potentially does does it insurance tend to cover it? 648 00:31:01,840 --> 00:31:05,280 Speaker 4: If you are at that BMI, then what's the spread? 649 00:31:05,600 --> 00:31:08,080 Speaker 9: It's all over the place right now. We do a 650 00:31:08,120 --> 00:31:10,520 Speaker 9: lot of reporting this. It's all over the place right now, 651 00:31:10,560 --> 00:31:12,760 Speaker 9: and you know, whether you have access to one of 652 00:31:12,760 --> 00:31:15,080 Speaker 9: these drugs may kind of just depend on the luck 653 00:31:15,080 --> 00:31:17,400 Speaker 9: of the drawer and what your particular insurance company you 654 00:31:17,480 --> 00:31:21,560 Speaker 9: have to you end up at. But like basically three 655 00:31:21,680 --> 00:31:25,080 Speaker 9: quarters of state we surveyed all fifty states state medicaid programs, 656 00:31:25,120 --> 00:31:29,000 Speaker 9: three quarters the states have very little coverage for obesity drugs, 657 00:31:29,040 --> 00:31:31,880 Speaker 9: and you're roughly approx. Give or take a few three 658 00:31:31,960 --> 00:31:36,600 Speaker 9: quarters of private insurance generally don't cover obesity drugs either. 659 00:31:36,680 --> 00:31:39,560 Speaker 9: Now the coverage we've found signs that the coverage is 660 00:31:39,600 --> 00:31:42,800 Speaker 9: starting to increase. For example, in Medicaid, eight different states 661 00:31:42,880 --> 00:31:45,320 Speaker 9: told us they're considering it. But this is like, this 662 00:31:45,400 --> 00:31:46,880 Speaker 9: is like the big battle that's going to be going 663 00:31:46,880 --> 00:31:49,560 Speaker 9: on the next year between the drug companies and the 664 00:31:49,600 --> 00:31:53,440 Speaker 9: doctors that favor more coverage and insurance companies. 665 00:31:53,520 --> 00:31:54,840 Speaker 6: That's like, that's like the big battle. 666 00:31:55,040 --> 00:31:57,440 Speaker 8: It was amazing to see how much coverage ranged in 667 00:31:57,480 --> 00:32:00,560 Speaker 8: this fifty state survey of Medicaid plans, which met kitas 668 00:32:00,560 --> 00:32:03,719 Speaker 8: covers low income folks for health insurance. I mean, there 669 00:32:03,800 --> 00:32:06,000 Speaker 8: was one state that literally told us we will pay 670 00:32:06,040 --> 00:32:09,800 Speaker 8: for you know, some obesity drugs for people under the 671 00:32:09,840 --> 00:32:12,720 Speaker 8: age of twenty one, for young people, but not adults. 672 00:32:13,160 --> 00:32:16,160 Speaker 8: We're like, what, Like, there's so much. 673 00:32:16,320 --> 00:32:18,200 Speaker 2: That, I mean, what would make it much more clear? 674 00:32:18,240 --> 00:32:20,200 Speaker 2: I just got about thirty seconds. Is it some study 675 00:32:20,200 --> 00:32:21,920 Speaker 2: that needs to be like, what is it? That would 676 00:32:22,160 --> 00:32:24,280 Speaker 2: be like health insurans would be like, yeah, we got 677 00:32:24,320 --> 00:32:25,240 Speaker 2: to be in on this or not. 678 00:32:25,360 --> 00:32:27,800 Speaker 9: The big studies, The most important studies that are coming 679 00:32:27,960 --> 00:32:30,360 Speaker 9: is that both Eli Lilly and Nova Noordis, which they 680 00:32:30,360 --> 00:32:33,720 Speaker 9: are the two makers. They're studying their drugs in people 681 00:32:33,720 --> 00:32:35,960 Speaker 9: with a BC to show they can prevent heart attacks 682 00:32:35,960 --> 00:32:38,080 Speaker 9: and strokes. And you know, if they do that, if 683 00:32:38,120 --> 00:32:40,320 Speaker 9: those studies succeed, it's going to be much much harder 684 00:32:40,360 --> 00:32:41,720 Speaker 9: for insurance to deny coverage. 685 00:32:41,800 --> 00:32:43,840 Speaker 8: Yeah, and that's going to be a big, big thing 686 00:32:43,880 --> 00:32:45,800 Speaker 8: that's going to come in the next couple of months. 687 00:32:45,960 --> 00:32:48,520 Speaker 8: Heart disease is the leading killer of Americans. So this 688 00:32:48,560 --> 00:32:50,040 Speaker 8: is something with really high stakes. 689 00:32:50,120 --> 00:32:53,040 Speaker 2: All right, great story, guys. It is the cover of 690 00:32:53,320 --> 00:32:56,200 Speaker 2: Bloomberg Business Week. As we said, it is out on newsstands. 691 00:32:56,240 --> 00:32:58,600 Speaker 2: It's already on the Bloomberg terminal and online at Bloomberg 692 00:32:58,640 --> 00:33:02,160 Speaker 2: dot com Slash BusinessWeek, The Court and Bob Langreth, both 693 00:33:02,280 --> 00:33:04,560 Speaker 2: healthcare reporters here at Bloomberg News, joining us here in 694 00:33:04,600 --> 00:33:06,960 Speaker 2: our interactive broker story. Be sure to check it out. 695 00:33:07,000 --> 00:33:09,040 Speaker 2: It's also going to be in our weekend show on 696 00:33:09,160 --> 00:33:15,400 Speaker 2: Bloomberg Radio. This is Bloomberg Business Week. I'm brother Marco, 697 00:33:17,320 --> 00:33:20,040 Speaker 2: a journal How about you let me drive? 698 00:33:20,560 --> 00:33:25,640 Speaker 1: No, no, no, no, honey, please, how do the riding gravel? 699 00:33:26,200 --> 00:33:27,000 Speaker 6: Let's mate, I. 700 00:33:27,000 --> 00:33:28,880 Speaker 2: Want to try it. 701 00:33:29,840 --> 00:33:30,760 Speaker 10: It's a good question. 702 00:33:31,480 --> 00:33:37,160 Speaker 2: Try This is the Drive to the Clothes dot Com 703 00:33:37,200 --> 00:33:39,600 Speaker 2: tm me think we'll buy around to other on I'm 704 00:33:39,720 --> 00:33:43,360 Speaker 2: on Bloomberg Radio. All right, everybody, we have just under 705 00:33:43,360 --> 00:33:45,920 Speaker 2: eighteen minutes left in today's trading session, getting ready to 706 00:33:45,920 --> 00:33:48,600 Speaker 2: wrap up the Thursday trade. We've got big earnings coming, 707 00:33:48,720 --> 00:33:52,040 Speaker 2: as Charlie mentioned, Amazon, Intel, a few others after the 708 00:33:52,040 --> 00:33:54,120 Speaker 2: Clothes holding out to gain sell on the equity side 709 00:33:54,120 --> 00:33:56,160 Speaker 2: of things. So let's get to it. Our Drive to 710 00:33:56,200 --> 00:33:59,320 Speaker 2: the Close guest on this Thursday is Shanil Ramsey, Senior 711 00:33:59,360 --> 00:34:02,440 Speaker 2: investment Manager. You're at Picta Asset Management here in our 712 00:34:02,480 --> 00:34:06,000 Speaker 2: Bloomberg Interactive Broker studio with Maddie and myself. Nice to 713 00:34:06,080 --> 00:34:06,600 Speaker 2: have you here. 714 00:34:06,760 --> 00:34:08,840 Speaker 10: How are you Yeah, very good, Thanks for having me. 715 00:34:08,960 --> 00:34:09,879 Speaker 10: Nice to be in New York? 716 00:34:10,080 --> 00:34:12,600 Speaker 2: Yeah, oh good. Where are you typically based in London? 717 00:34:12,760 --> 00:34:16,280 Speaker 2: In London? All right, so tell me mood difference between 718 00:34:16,280 --> 00:34:17,080 Speaker 2: London and here. 719 00:34:17,800 --> 00:34:21,240 Speaker 10: Well, firstly, the weather is not as good in London, 720 00:34:21,320 --> 00:34:23,640 Speaker 10: let me tell you that much. But now it's like 721 00:34:23,719 --> 00:34:25,359 Speaker 10: it's lovely to be back in New York. Haven't been 722 00:34:25,400 --> 00:34:27,680 Speaker 10: back for several years and the buzz is great. 723 00:34:27,960 --> 00:34:30,759 Speaker 2: It does feel like the energy when you're in London, though, 724 00:34:31,000 --> 00:34:34,040 Speaker 2: is what is the conversation you think most that you 725 00:34:34,080 --> 00:34:36,200 Speaker 2: guys talk about at work versus like when you come 726 00:34:36,200 --> 00:34:38,000 Speaker 2: over to the US and you're talking to different clients. 727 00:34:38,080 --> 00:34:39,840 Speaker 2: Is it a little bit different? Is it the same stuff? 728 00:34:40,160 --> 00:34:43,040 Speaker 10: Yeah? In the US it's typically quite US focused. You know, 729 00:34:43,080 --> 00:34:46,000 Speaker 10: we have a much global, much more global view in London, 730 00:34:46,120 --> 00:34:49,160 Speaker 10: and it's always the US versus the rest. Right Where 731 00:34:49,400 --> 00:34:52,439 Speaker 10: when are we going to see performance come through from 732 00:34:52,480 --> 00:34:55,360 Speaker 10: the rest of the world. And we do see that 733 00:34:55,520 --> 00:34:57,600 Speaker 10: coming to the for this year and in some ways 734 00:34:58,160 --> 00:35:01,279 Speaker 10: with European innses doing quite well this year, uh and 735 00:35:01,640 --> 00:35:05,240 Speaker 10: the reopening of China really starting to drive some investment decisions. 736 00:35:05,239 --> 00:35:08,200 Speaker 10: So coming coming to YES this week, I think this 737 00:35:08,280 --> 00:35:10,400 Speaker 10: is what people have been asking about. 738 00:35:10,560 --> 00:35:13,759 Speaker 4: Are you monitoring every single potential data point that could 739 00:35:13,760 --> 00:35:16,960 Speaker 4: impact the fed's moves as much as we are here, you'd. 740 00:35:16,719 --> 00:35:19,600 Speaker 10: Be surprised that in Europe we care a lot about 741 00:35:19,600 --> 00:35:22,680 Speaker 10: that too, right, So we we are, you know, watching 742 00:35:23,120 --> 00:35:27,360 Speaker 10: each and every statement also, but we try and trying 743 00:35:27,360 --> 00:35:30,480 Speaker 10: to have that more applicable to what's going on elsewhere. 744 00:35:30,520 --> 00:35:32,520 Speaker 10: What is the ECB, what is the BOE, what is 745 00:35:32,520 --> 00:35:34,280 Speaker 10: the bo J what is the Chinese? 746 00:35:34,640 --> 00:35:35,280 Speaker 6: Uh people? 747 00:35:35,520 --> 00:35:38,319 Speaker 10: Yeah, so how how are they responding to what the 748 00:35:38,360 --> 00:35:40,680 Speaker 10: FED is doing? But you know, the FED is still 749 00:35:41,000 --> 00:35:43,239 Speaker 10: the big the big guy in the room, and we 750 00:35:43,320 --> 00:35:46,279 Speaker 10: really need to know what Jay, Paul and co. Are 751 00:35:46,320 --> 00:35:47,720 Speaker 10: going to do well. 752 00:35:47,800 --> 00:35:50,800 Speaker 2: So, having said that, you do to take a global perspective, 753 00:35:50,960 --> 00:35:53,880 Speaker 2: and lucky for us, you've shared something else with our producers. 754 00:35:53,920 --> 00:35:57,040 Speaker 2: So we know that you do like non US equities 755 00:35:57,440 --> 00:35:59,840 Speaker 2: more than you like US equities from what I understand, 756 00:36:00,080 --> 00:36:00,760 Speaker 2: make that case. 757 00:36:01,080 --> 00:36:03,000 Speaker 10: So at the moment, we know that the valuations in 758 00:36:03,000 --> 00:36:04,960 Speaker 10: the US are quite high with this thing s and 759 00:36:05,000 --> 00:36:07,520 Speaker 10: people have one hundred is about eighteen times. When we 760 00:36:07,600 --> 00:36:10,720 Speaker 10: look elsewhere around the world, we think looking at much 761 00:36:10,800 --> 00:36:14,080 Speaker 10: lower valuations twelve times in Europe, ten times in the UK, 762 00:36:14,280 --> 00:36:17,160 Speaker 10: much lower in parts of Asia. So we can say, 763 00:36:17,160 --> 00:36:19,880 Speaker 10: for on a valuation case that this is interesting. But 764 00:36:20,000 --> 00:36:22,000 Speaker 10: we know that the rest of the world's always been 765 00:36:22,400 --> 00:36:26,080 Speaker 10: cheaper in general. So why now? Why do we think now? 766 00:36:26,160 --> 00:36:30,000 Speaker 10: So firstly, we think there's a desynchronization in the global economy. 767 00:36:30,280 --> 00:36:33,440 Speaker 10: We see the US economy is slowing. We saw today's 768 00:36:33,440 --> 00:36:38,239 Speaker 10: GDP number a bit slower, bit more inflation, And when 769 00:36:38,280 --> 00:36:40,359 Speaker 10: we look at the rest of the world. Having had 770 00:36:40,400 --> 00:36:43,680 Speaker 10: the big energy scare that we saw at the end 771 00:36:43,680 --> 00:36:45,719 Speaker 10: of the last year in Europe and thinking that we 772 00:36:45,719 --> 00:36:47,759 Speaker 10: were going to have a big recession in Europe first 773 00:36:47,840 --> 00:36:50,560 Speaker 10: quarter this year, that didn't materialize, and we're getting a 774 00:36:50,600 --> 00:36:54,480 Speaker 10: cyclical upswing in Europe. But that's also aided by the 775 00:36:54,520 --> 00:36:58,239 Speaker 10: fact that China reopened, right, So the China reopening has 776 00:36:58,360 --> 00:37:03,000 Speaker 10: helped look at non US growth being a little bit 777 00:37:03,040 --> 00:37:06,759 Speaker 10: better than US growth, and that's turning into some positives 778 00:37:06,760 --> 00:37:09,240 Speaker 10: for earnings, not just in China but elsewhere. 779 00:37:09,320 --> 00:37:12,960 Speaker 2: There's Europe. In Europe's a pretty big area region. What 780 00:37:13,080 --> 00:37:16,600 Speaker 2: specifically are there certain markets, are there certain types of industries, 781 00:37:16,640 --> 00:37:17,440 Speaker 2: certain companies. 782 00:37:17,640 --> 00:37:22,120 Speaker 10: Absolutely so in Europe, we really like the consumer sectors, 783 00:37:22,160 --> 00:37:25,600 Speaker 10: the consumer cyclicals. But really in a world where we 784 00:37:25,680 --> 00:37:28,480 Speaker 10: know that there's this inflation pressure, we think the high 785 00:37:28,560 --> 00:37:31,360 Speaker 10: end consumer is doing the best right. The affluent consumer 786 00:37:32,640 --> 00:37:34,799 Speaker 10: has the ability to spend more. So when we look 787 00:37:34,800 --> 00:37:37,520 Speaker 10: at those premium brands, when we look at those luxury companies, 788 00:37:37,760 --> 00:37:42,920 Speaker 10: they continue to grow their revenue base. They are interesting 789 00:37:42,960 --> 00:37:46,080 Speaker 10: companies in the sense that so like you'r lvmators, Absolutely 790 00:37:46,560 --> 00:37:52,440 Speaker 10: LVMH is the the LVMH, for example, encompasses all those 791 00:37:52,520 --> 00:37:55,080 Speaker 10: luxury brands, and we think there are many of them 792 00:37:55,360 --> 00:37:57,880 Speaker 10: in Europe, and that's what Europe does best. You know, 793 00:37:57,920 --> 00:38:00,000 Speaker 10: we know that those are some of the best companies 794 00:38:00,080 --> 00:38:02,520 Speaker 10: in Europe. Those those luxury. 795 00:38:02,160 --> 00:38:05,560 Speaker 2: Cots are US luxury brands. We love you, even if 796 00:38:07,880 --> 00:38:09,880 Speaker 2: I'm just kidding. Yeah, no, I mean it's but I 797 00:38:09,880 --> 00:38:11,520 Speaker 2: know what you're saying. And we've talked about that. We've 798 00:38:11,520 --> 00:38:14,239 Speaker 2: done a lot of reporting that as these results come in, 799 00:38:14,600 --> 00:38:17,239 Speaker 2: the luxury names have really been out performing, and we 800 00:38:17,320 --> 00:38:20,000 Speaker 2: are talking about the China reopening as one of the reasons. 801 00:38:20,000 --> 00:38:23,000 Speaker 2: But US shoppers are buying too, certainly US high end shoppers. 802 00:38:23,520 --> 00:38:26,160 Speaker 4: Yeah, why do you think that US high end shoppers 803 00:38:26,480 --> 00:38:31,719 Speaker 4: are more susceptible to headwinds than European high end shoppers. 804 00:38:32,000 --> 00:38:34,480 Speaker 10: I think the high the US high end, the consumer 805 00:38:34,560 --> 00:38:37,400 Speaker 10: is also going to be quite resilient. We've seen the 806 00:38:37,520 --> 00:38:41,600 Speaker 10: numbers today on the consumption being still quite strong, right, 807 00:38:41,680 --> 00:38:44,400 Speaker 10: so we know that the consumer in the US has 808 00:38:44,840 --> 00:38:45,279 Speaker 10: been good. 809 00:38:45,320 --> 00:38:48,360 Speaker 2: And those are January numbers, as are Mike McKee reminded us, 810 00:38:48,400 --> 00:38:50,040 Speaker 2: and we'll get March I think tomorrow. So it was 811 00:38:50,120 --> 00:38:53,280 Speaker 2: kind of before the banking, you know, kind of meltdown 812 00:38:53,280 --> 00:38:55,399 Speaker 2: of a few names, So it'll be interesting to see 813 00:38:55,440 --> 00:38:56,600 Speaker 2: if it continues to hold up. 814 00:38:56,719 --> 00:38:58,920 Speaker 10: But even if we look at travel, for example, travel 815 00:38:58,960 --> 00:39:02,640 Speaker 10: in leisure, when we look at the hotel hotel chain numbers, 816 00:39:02,640 --> 00:39:04,880 Speaker 10: when we look at the airline numbers, these numbers have 817 00:39:04,920 --> 00:39:08,160 Speaker 10: been pretty good. So we know that the consumers are 818 00:39:08,200 --> 00:39:11,640 Speaker 10: spending on what they hold deer and right now what 819 00:39:11,640 --> 00:39:14,200 Speaker 10: they hold dear is some of those luxury brands and 820 00:39:14,239 --> 00:39:17,520 Speaker 10: also the travel and leisure that they that they care 821 00:39:17,520 --> 00:39:18,040 Speaker 10: about most. 822 00:39:18,160 --> 00:39:19,880 Speaker 2: So you know, how much would you suggest for an 823 00:39:19,880 --> 00:39:23,160 Speaker 2: investor to have of their portfolio with non US exposure 824 00:39:23,160 --> 00:39:24,240 Speaker 2: at this point at. 825 00:39:24,080 --> 00:39:27,880 Speaker 10: The moment, just in that luxury consumer discretion era, the 826 00:39:27,920 --> 00:39:30,280 Speaker 10: portfolio that we built for clients has about five percent 827 00:39:30,800 --> 00:39:33,840 Speaker 10: in those areas, and we think that that's just because 828 00:39:34,160 --> 00:39:37,600 Speaker 10: the consumer is the driver right now in the global economy. 829 00:39:37,880 --> 00:39:41,520 Speaker 10: We do think, however, that that will slow over time. 830 00:39:42,000 --> 00:39:45,640 Speaker 10: And what we see in that desynchronization that I mentioned 831 00:39:45,840 --> 00:39:48,840 Speaker 10: is also desynchronization in the sectors of the economy that 832 00:39:48,880 --> 00:39:51,439 Speaker 10: are working. And one of those sectors that we think 833 00:39:51,600 --> 00:39:54,880 Speaker 10: could have some better performance in the second half of 834 00:39:54,880 --> 00:39:58,440 Speaker 10: the year now is the more manufacturing or industrial sector, 835 00:39:58,920 --> 00:40:01,600 Speaker 10: and we are seeing some of those numbers. 836 00:40:01,239 --> 00:40:03,959 Speaker 2: Come out for over Europe or more broadly. 837 00:40:03,719 --> 00:40:06,480 Speaker 10: More more broadly, more globally, and I think the European 838 00:40:06,680 --> 00:40:09,520 Speaker 10: story in terms of the industrials, we see earning revisions 839 00:40:09,560 --> 00:40:12,040 Speaker 10: pick up, and that's partly due to some of the 840 00:40:12,040 --> 00:40:15,680 Speaker 10: fiscal stimus that we see around some of the environmental 841 00:40:15,719 --> 00:40:18,360 Speaker 10: spend that's going on. Look at the either the IRA 842 00:40:18,640 --> 00:40:22,400 Speaker 10: or what this similar policies in Europe. These are spending 843 00:40:22,560 --> 00:40:25,319 Speaker 10: that governments are doing that are going to benefit some 844 00:40:25,400 --> 00:40:28,720 Speaker 10: of these industrial companies and their auder books are already 845 00:40:29,200 --> 00:40:29,640 Speaker 10: showing that. 846 00:40:30,120 --> 00:40:32,719 Speaker 4: But a lot of consumer discretionary companies in the US 847 00:40:32,840 --> 00:40:37,279 Speaker 4: are having amazing earnings. I'm thinking about McDonald's, PEPSI, so maybe. 848 00:40:37,000 --> 00:40:40,239 Speaker 2: Not just the high drum their global names. Yeah, absolutely, 849 00:40:40,239 --> 00:40:41,960 Speaker 2: So we got about thirty seconds left. 850 00:40:42,560 --> 00:40:47,120 Speaker 10: When we look at those those global US companies, they 851 00:40:47,160 --> 00:40:50,040 Speaker 10: have been having good numbers. And for example, I think 852 00:40:50,440 --> 00:40:53,160 Speaker 10: Clad said some of their coffee shops in China were 853 00:40:53,239 --> 00:40:56,640 Speaker 10: rarely showing positive earnings, so you know, you know it's 854 00:40:56,680 --> 00:40:59,400 Speaker 10: open when people are going out to coffee shops, So 855 00:40:59,560 --> 00:41:01,759 Speaker 10: you know, these are some of the data that we 856 00:41:01,800 --> 00:41:04,759 Speaker 10: look at so it's not just European companies, right, you 857 00:41:04,800 --> 00:41:08,320 Speaker 10: are right, it is also American companies. But we think 858 00:41:08,560 --> 00:41:11,239 Speaker 10: the consumer generally is the place for you, all. 859 00:41:11,200 --> 00:41:13,560 Speaker 2: Right, that we're certain to see that and as you said, 860 00:41:13,640 --> 00:41:16,600 Speaker 2: higher end in particular. Nil, thank you so much, really 861 00:41:16,600 --> 00:41:19,720 Speaker 2: appreciate it. Shamiel Ramchi, He's senior investment manager at Picta 862 00:41:19,800 --> 00:41:22,480 Speaker 2: Asset Management, joining us here in our Bloomberg in Directive 863 00:41:22,480 --> 00:41:23,200 Speaker 2: Brokers studio. 864 00:41:24,520 --> 00:41:28,360 Speaker 1: This is the Bloomberg Business Week podcast of a Little Apple, 865 00:41:28,600 --> 00:41:30,279 Speaker 1: Spotify and anywhere else you. 866 00:41:30,360 --> 00:41:31,480 Speaker 6: Get your podcasts. 867 00:41:31,840 --> 00:41:35,360 Speaker 1: Listen live weekday afternoons from three to six Eastern on 868 00:41:35,480 --> 00:41:38,800 Speaker 1: Bloomberg dot com, the iHeartRadio app, tune In, and the 869 00:41:38,880 --> 00:41:41,839 Speaker 1: Bloomberg Business App. You can also watch us live every 870 00:41:41,880 --> 00:41:45,240 Speaker 1: weekday on YouTube and always on the Bloomberg terminal