1 00:00:02,240 --> 00:00:05,520 Speaker 1: From the heart of where Innovation, money and power Colli 2 00:00:06,360 --> 00:00:10,879 Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with 3 00:00:10,960 --> 00:00:27,320 Speaker 1: Emily jay I remember my check in San Francisco, and 4 00:00:27,360 --> 00:00:30,080 Speaker 1: this is Bloomberg Technology coming up in the next hour. 5 00:00:30,240 --> 00:00:32,760 Speaker 1: This week marks the beginning of a new chapter in 6 00:00:32,800 --> 00:00:37,120 Speaker 1: the already long and twisty elon Musk Twitter saga, moves 7 00:00:37,200 --> 00:00:40,320 Speaker 1: from the Chief Twitter over the weekend, and what's next 8 00:00:41,040 --> 00:00:44,440 Speaker 1: Claus Pinterest's latest earnings beat was a welcome bright spot 9 00:00:44,440 --> 00:00:48,120 Speaker 1: compared to its peers like Snap Meta Alphabet. We'll catch 10 00:00:48,159 --> 00:00:50,520 Speaker 1: up with CEO Bill Ready to talk about its strategy 11 00:00:50,600 --> 00:00:55,240 Speaker 1: to reignite the platform. And in China and exitus of 12 00:00:55,320 --> 00:00:57,960 Speaker 1: workers has threatened to disrupt output at the world's largest 13 00:00:57,960 --> 00:01:01,200 Speaker 1: iPhone plant operated by fox On Now. The company is 14 00:01:01,200 --> 00:01:03,800 Speaker 1: said to be raising wages by as much as to 15 00:01:03,880 --> 00:01:06,679 Speaker 1: keep production going. We're gonna have all the details later 16 00:01:06,720 --> 00:01:10,480 Speaker 1: this hour. This week, of course, marks the beginning of 17 00:01:10,480 --> 00:01:12,800 Speaker 1: a new chapter in the Musk Twitter saga. In the 18 00:01:12,840 --> 00:01:15,360 Speaker 1: span of just two days, he has completed the acquisition, 19 00:01:15,720 --> 00:01:18,840 Speaker 1: fired Twitter's top executives, and taken over as Chief Twitter. 20 00:01:19,160 --> 00:01:21,679 Speaker 1: Joining us now for more. Mark Mhaney, Senior managing director 21 00:01:21,680 --> 00:01:23,959 Speaker 1: at Evercore, I s I who covered Twitter as a 22 00:01:24,000 --> 00:01:27,120 Speaker 1: public company, and our very own senior executive tech editor, 23 00:01:27,440 --> 00:01:30,440 Speaker 1: Brad Stone. So Brad, he's also dissolved the board. He's 24 00:01:30,480 --> 00:01:33,759 Speaker 1: the only board member as of now. What's actually happening 25 00:01:34,120 --> 00:01:36,800 Speaker 1: inside Twitter at this moment. I think there's a lot 26 00:01:36,800 --> 00:01:40,840 Speaker 1: of anxiety and confusion and speculation right now. Emily employees 27 00:01:40,840 --> 00:01:44,880 Speaker 1: are bracing for layoffs. They're swapping phone numbers, connecting on LinkedIn, 28 00:01:45,319 --> 00:01:47,600 Speaker 1: a lot of people assuming they're probably about to get 29 00:01:47,680 --> 00:01:50,080 Speaker 1: kicked out of the system. We know thanks to Mike 30 00:01:50,120 --> 00:01:52,680 Speaker 1: colleague Kurt Wagner, a lot of managers had to create 31 00:01:52,760 --> 00:01:55,600 Speaker 1: lists over the weekend of employees that they were planning 32 00:01:55,640 --> 00:01:58,520 Speaker 1: to let go today. Nothing's been announced, but it really 33 00:01:58,600 --> 00:02:01,640 Speaker 1: only seems a matter of time. And then other than that, 34 00:02:01,840 --> 00:02:03,640 Speaker 1: they're throwing a lot of things against the wall. You 35 00:02:03,720 --> 00:02:07,240 Speaker 1: heard this thing about maybe reviving Vine, Twitter's old video 36 00:02:07,280 --> 00:02:11,040 Speaker 1: sharing service that they closed in two thousand sixteen. Twitter 37 00:02:11,080 --> 00:02:14,120 Speaker 1: would have to rebuild it to convince creators to come back. 38 00:02:14,560 --> 00:02:16,880 Speaker 1: They haven't been able to make money on that when 39 00:02:16,880 --> 00:02:18,280 Speaker 1: they when they had it, so that would be a 40 00:02:18,320 --> 00:02:20,880 Speaker 1: big challenge. And then this idea of getting people to 41 00:02:20,960 --> 00:02:23,920 Speaker 1: pay for that blue check mark that we enjoy. Emily, 42 00:02:24,000 --> 00:02:28,239 Speaker 1: the verification um twenty dollars a month was floated. I 43 00:02:28,560 --> 00:02:31,200 Speaker 1: think they're throwing some things against the wall. We do 44 00:02:31,320 --> 00:02:34,600 Speaker 1: know that Ellen wants to revive subscriptions at Twitter, so 45 00:02:34,639 --> 00:02:37,359 Speaker 1: maybe that's one piece of a broader plan. But it's 46 00:02:37,360 --> 00:02:40,440 Speaker 1: still very early. Mark, I someone who covered the company 47 00:02:40,680 --> 00:02:44,240 Speaker 1: as an analyst four years, What do you make of it? 48 00:02:44,600 --> 00:02:46,960 Speaker 1: What of what? What kind of a proposition is this 49 00:02:47,080 --> 00:02:50,200 Speaker 1: really for investors today? Well, I think it's gonna be 50 00:02:50,280 --> 00:02:54,000 Speaker 1: a it's gonna be completely revamped over the next year too. 51 00:02:54,160 --> 00:02:57,600 Speaker 1: And um, you know, I listened to much very carefully 52 00:02:57,639 --> 00:03:00,200 Speaker 1: for the last six months. I didn't necessarily to hear 53 00:03:00,240 --> 00:03:02,720 Speaker 1: business plans. I think he had a lot of other 54 00:03:02,760 --> 00:03:05,600 Speaker 1: reasons for owning the asset, and so it's his now. 55 00:03:06,200 --> 00:03:08,359 Speaker 1: I think from a from if this were to come 56 00:03:08,360 --> 00:03:10,960 Speaker 1: out into the public markets again, I guess that this 57 00:03:11,040 --> 00:03:13,720 Speaker 1: business will be completely revampeded. But if I just step back, 58 00:03:13,720 --> 00:03:16,120 Speaker 1: Twitter didn't really do much in the public markets. She 59 00:03:16,240 --> 00:03:19,000 Speaker 1: was there for what seven years, and uh, it barely 60 00:03:19,040 --> 00:03:21,400 Speaker 1: moved over that course of that time. It is very volatile. 61 00:03:21,760 --> 00:03:26,800 Speaker 1: It um, it never really gained dramatic share amongst amongst 62 00:03:26,800 --> 00:03:30,400 Speaker 1: advertisers marketers. They generated reasonable a modern revenue five billion 63 00:03:30,480 --> 00:03:33,040 Speaker 1: a year, They had reasonable free cash flow, but they 64 00:03:33,040 --> 00:03:36,280 Speaker 1: could never really break through beyond being like a second 65 00:03:36,360 --> 00:03:39,440 Speaker 1: or even a third tier advertising platform. I haven't heard 66 00:03:39,440 --> 00:03:41,960 Speaker 1: anything from from us that suggests he's got a plan 67 00:03:42,080 --> 00:03:44,680 Speaker 1: to to break him out of that. I think subscriptions 68 00:03:44,680 --> 00:03:48,320 Speaker 1: are are limited as to long term strategy for Twitter. 69 00:03:48,440 --> 00:03:51,240 Speaker 1: Good strategy, but they don't dramatically move the needles. So 70 00:03:51,840 --> 00:03:55,000 Speaker 1: I'm sort of I'm skeptically watching this from a distance. 71 00:03:55,040 --> 00:03:57,920 Speaker 1: I hope he can improve the business model there, but 72 00:03:58,600 --> 00:04:00,440 Speaker 1: I'm not I'm not holding my breath on that. But 73 00:04:00,480 --> 00:04:03,120 Speaker 1: if he can, wonderful In the meantime, I think his 74 00:04:03,160 --> 00:04:06,600 Speaker 1: intentions were very different than improving the business, and you know, 75 00:04:06,640 --> 00:04:08,800 Speaker 1: I wish him good luck with the rest that he's 76 00:04:08,840 --> 00:04:12,160 Speaker 1: trying to do with the business. Brad We reported that 77 00:04:12,200 --> 00:04:16,000 Speaker 1: in the hours after his takeover, hate speech surged on 78 00:04:16,080 --> 00:04:18,359 Speaker 1: the platform. Twitter responded saying a lot of that was 79 00:04:18,440 --> 00:04:23,679 Speaker 1: inauthentic behavior. Over the weekend, Must also retweeted an article 80 00:04:23,880 --> 00:04:27,680 Speaker 1: with a conspiracy theory about the attack on now speaker 81 00:04:27,760 --> 00:04:31,560 Speaker 1: Nancy Policy's husband, obviously, this is a person with a 82 00:04:31,680 --> 00:04:36,960 Speaker 1: huge audience that obviously creates huge opportunities but also real dangers. 83 00:04:37,480 --> 00:04:39,520 Speaker 1: What does all of this tell you, Well, I mean, 84 00:04:39,520 --> 00:04:42,239 Speaker 1: there was a breathtaking lack of respect with that tweet 85 00:04:42,520 --> 00:04:44,960 Speaker 1: for the former Senator and First Lady Hillary Clinton, for 86 00:04:45,000 --> 00:04:47,359 Speaker 1: the Speaker of the House and her husband, for the 87 00:04:47,400 --> 00:04:49,720 Speaker 1: facts of the case which are now very well established 88 00:04:49,720 --> 00:04:52,840 Speaker 1: by the criminal complaint coming out of San Francisco. I mean, 89 00:04:53,440 --> 00:04:56,400 Speaker 1: really believe the conspiracy theories? I don't think so. What 90 00:04:56,440 --> 00:04:59,279 Speaker 1: it tells me is that like owning the lips, provoking 91 00:04:59,279 --> 00:05:03,280 Speaker 1: Democrats being contrariant, this is kind of the animating philosophy 92 00:05:03,400 --> 00:05:06,560 Speaker 1: right now, not only the right wing Republicans, but the 93 00:05:06,600 --> 00:05:10,120 Speaker 1: pro business moderates like Elon and David Sachs. They just 94 00:05:10,400 --> 00:05:14,440 Speaker 1: enjoy this pointless provocation. And you know this is penn 95 00:05:14,520 --> 00:05:17,000 Speaker 1: Elon m o on Twitter for quite some time now, 96 00:05:17,160 --> 00:05:20,200 Speaker 1: Jack Dorsey, We're just getting this headline, Jack Dorsey contributing 97 00:05:20,360 --> 00:05:25,680 Speaker 1: eighteen million Twitter shares to retain an indirect stake in 98 00:05:25,720 --> 00:05:30,080 Speaker 1: this company under Elon musk Mark. What do you make 99 00:05:30,120 --> 00:05:33,600 Speaker 1: of that? And what do potential advertisers who have been 100 00:05:33,600 --> 00:05:37,159 Speaker 1: working with Twitter for all these years make of what's 101 00:05:37,160 --> 00:05:39,880 Speaker 1: to come. I mean, clearly there's a lot of uncertainty. Well, 102 00:05:40,040 --> 00:05:43,560 Speaker 1: I'll just hit on the second part of the second question, Emily. 103 00:05:43,800 --> 00:05:45,320 Speaker 1: So this is this is key. I mean, this is 104 00:05:45,400 --> 00:05:49,440 Speaker 1: this is how of the revenue from Twitter and the 105 00:05:49,520 --> 00:05:52,200 Speaker 1: pass came from advertising. I find I don't really see 106 00:05:52,240 --> 00:05:54,800 Speaker 1: a business model in the future that doesn't still have 107 00:05:55,760 --> 00:05:57,920 Speaker 1: plus to the revenue come from advertising, like it does 108 00:05:58,000 --> 00:06:00,680 Speaker 1: with every other social media asset. There's nothing wrong with that. 109 00:06:00,720 --> 00:06:03,640 Speaker 1: It's a high margin business. Wonderful thing about social media 110 00:06:03,680 --> 00:06:05,760 Speaker 1: is that they don't have to pay the content providers 111 00:06:05,839 --> 00:06:08,799 Speaker 1: or play largely don't, so it's a very high margin business. 112 00:06:08,800 --> 00:06:11,120 Speaker 1: You just need to sell effectively adds against it. One 113 00:06:11,160 --> 00:06:12,440 Speaker 1: of the things that Twitter has been trying to do 114 00:06:12,480 --> 00:06:14,760 Speaker 1: for the last couple of years is moved beyond brand 115 00:06:14,760 --> 00:06:18,240 Speaker 1: advertising to direct response advertising, which has kind of always 116 00:06:18,240 --> 00:06:21,159 Speaker 1: been the power alley of Internet advertising. The problem is 117 00:06:21,200 --> 00:06:23,440 Speaker 1: that those dollars have gone to Google, and they've gone 118 00:06:23,440 --> 00:06:25,880 Speaker 1: to Facebook and a few other places, and they've only 119 00:06:25,920 --> 00:06:29,400 Speaker 1: trickled down to Twitter because in part because Twitter has 120 00:06:29,400 --> 00:06:32,000 Speaker 1: never really had great tools for direct response advertisers. So 121 00:06:32,200 --> 00:06:35,840 Speaker 1: maybe that's all part of the fix at Twitter. From 122 00:06:35,839 --> 00:06:37,960 Speaker 1: a business model perspective, that's not going to happen in 123 00:06:37,960 --> 00:06:40,160 Speaker 1: a quarter or two. That's a year or two slog 124 00:06:40,240 --> 00:06:42,880 Speaker 1: for that to happen. In the meantime. Marketers all this 125 00:06:43,040 --> 00:06:47,560 Speaker 1: debate about whether there's um uh censorship or not on 126 00:06:47,560 --> 00:06:50,080 Speaker 1: on Twitter. Marketers, I think they just want something that's 127 00:06:50,120 --> 00:06:53,400 Speaker 1: relatively well regulated. They don't want their brands put against 128 00:06:53,880 --> 00:06:57,200 Speaker 1: nasty content, whether that's whether that's a verbal or whether 129 00:06:57,240 --> 00:07:00,960 Speaker 1: it's graphic. Uh and um so I think uh if 130 00:07:01,000 --> 00:07:04,719 Speaker 1: something changes in the marketplace that makes it less user friendly, 131 00:07:05,080 --> 00:07:08,600 Speaker 1: makes it makes it if there's more vulgarity on the site, 132 00:07:08,640 --> 00:07:11,120 Speaker 1: I think advertisers will pull back from that. So there's 133 00:07:11,120 --> 00:07:13,800 Speaker 1: a real tough balancing act here between what must he 134 00:07:13,880 --> 00:07:16,280 Speaker 1: is trying to do and what marketers want. And you know, 135 00:07:16,320 --> 00:07:18,800 Speaker 1: I saw his tweets to market to marketers over the weekend. 136 00:07:19,040 --> 00:07:21,120 Speaker 1: He said he would try to avoid the place becoming 137 00:07:21,120 --> 00:07:24,720 Speaker 1: a hellscape. I think he does that for personal philosophical reasons, 138 00:07:24,720 --> 00:07:26,720 Speaker 1: but also for business reasons, because if it does become 139 00:07:26,760 --> 00:07:30,560 Speaker 1: a healthscape, advertisers will flee. Rad Curious what your take 140 00:07:30,680 --> 00:07:32,880 Speaker 1: is on these Jack Dorsey filings. We're getting this all 141 00:07:32,960 --> 00:07:36,320 Speaker 1: from a third ten d that Jack Dorrisey still retaining 142 00:07:36,680 --> 00:07:40,080 Speaker 1: an indirect stake in Twitter. I mean Jack Dorsey is 143 00:07:40,520 --> 00:07:45,360 Speaker 1: the author of this whole situation. He personally solicited Ellen 144 00:07:45,520 --> 00:07:48,920 Speaker 1: to come by the company. He long felt that Twitter 145 00:07:49,280 --> 00:07:52,680 Speaker 1: would do better as a private company. He helped taking 146 00:07:52,680 --> 00:07:55,640 Speaker 1: a public with one of the company's big mistakes. So 147 00:07:55,800 --> 00:07:57,880 Speaker 1: you know, it doesn't surprise me. He's a big fan 148 00:07:57,920 --> 00:08:01,240 Speaker 1: of Elon's. He wants to be a small part of 149 00:08:01,240 --> 00:08:04,320 Speaker 1: of Twitter's makeover. He cares deeply for the company. Uh, 150 00:08:04,360 --> 00:08:07,320 Speaker 1: so you know he's putting his money where his mouth is. Um, 151 00:08:07,320 --> 00:08:10,440 Speaker 1: it'll be interesting to see if he has any operational 152 00:08:10,520 --> 00:08:12,840 Speaker 1: or advisory role in the new Twitter. Of course, it's 153 00:08:12,960 --> 00:08:15,000 Speaker 1: it's too soon to tell. But no, this doesn't surprise 154 00:08:15,040 --> 00:08:17,120 Speaker 1: me at all. Well, speaking of that, I'm curious what 155 00:08:17,160 --> 00:08:20,920 Speaker 1: you think about him surrounding himself Elon Musk surrounding himself 156 00:08:20,920 --> 00:08:24,840 Speaker 1: with people like David Sacks and Jason Calcannis, both of 157 00:08:24,920 --> 00:08:27,800 Speaker 1: the All In Pod, both with a point of view. 158 00:08:27,920 --> 00:08:30,920 Speaker 1: You've also got Amy Klobuchar, Senator Amy Klobuchar out there 159 00:08:31,120 --> 00:08:33,960 Speaker 1: saying that she's worried that hate speeches an even bigger 160 00:08:34,000 --> 00:08:39,480 Speaker 1: liability now on Twitter. Um, you know, clearly we're still 161 00:08:39,480 --> 00:08:43,120 Speaker 1: waiting for the plans to form. But you know, how 162 00:08:43,600 --> 00:08:46,400 Speaker 1: what sort of conclusions are we supposed to draw here 163 00:08:46,440 --> 00:08:50,480 Speaker 1: about what kind of company he's going to be running. Well, well, look, 164 00:08:51,280 --> 00:08:54,520 Speaker 1: I think everybody was bracing for Donald Trump to be 165 00:08:54,640 --> 00:08:58,520 Speaker 1: reinstated onto Twitter at the very first day of Elan 166 00:08:58,600 --> 00:09:01,040 Speaker 1: owning the company, and it did happen. You know, I 167 00:09:01,040 --> 00:09:04,160 Speaker 1: feel a little sheepish praising Ellen here for exercising restraint. 168 00:09:04,360 --> 00:09:06,600 Speaker 1: But to go back to Mark's point, I think he's 169 00:09:06,600 --> 00:09:09,240 Speaker 1: now got to balance some of his rhetoric with the 170 00:09:09,280 --> 00:09:12,760 Speaker 1: realities of running a company and keeping the advertising base 171 00:09:12,840 --> 00:09:16,400 Speaker 1: and keeping advertisers happy and and fostering you know, kind 172 00:09:16,400 --> 00:09:20,400 Speaker 1: of kind of reasonably safe dialogue on the on the surface. 173 00:09:20,720 --> 00:09:23,000 Speaker 1: You know they've talked about in oversight board. We don't 174 00:09:23,200 --> 00:09:25,120 Speaker 1: there's a lot we don't know. Is that, like Facebook's 175 00:09:25,160 --> 00:09:29,559 Speaker 1: oversight board, a sort of kind of veto appellate body, 176 00:09:30,280 --> 00:09:32,800 Speaker 1: or is it more than management of the company. You know, 177 00:09:32,920 --> 00:09:36,520 Speaker 1: these are all real serious, hard questions that Ellen and 178 00:09:36,640 --> 00:09:39,760 Speaker 1: his his friends now who all have other jobs, by 179 00:09:39,760 --> 00:09:42,440 Speaker 1: the way, have to have to determine. And you know, 180 00:09:42,520 --> 00:09:45,280 Speaker 1: I wish them well. These are these are tough decisions. 181 00:09:45,400 --> 00:09:48,640 Speaker 1: Are who knows that's CEO position, according to Ellen is open. 182 00:09:48,720 --> 00:09:53,079 Speaker 1: He's just the chief twit for now, Bloomberg's Bradstone. Thank 183 00:09:53,080 --> 00:09:55,520 Speaker 1: you so much. Mark Mahaney of ever Card, Mark, you're 184 00:09:55,520 --> 00:09:57,760 Speaker 1: going to stick with us and help us break down 185 00:09:58,280 --> 00:10:00,080 Speaker 1: some of the big tech results we've seen of the 186 00:10:00,160 --> 00:10:04,000 Speaker 1: last couple of weeks. Sticking with Twitter, Democratic Senator Chris 187 00:10:04,120 --> 00:10:07,680 Speaker 1: Murphy said Musque's purchase of the platform should be scrutinized. 188 00:10:07,720 --> 00:10:11,040 Speaker 1: Murphy tweeting today, I'm requesting the Committee on Foreign Investment 189 00:10:11,120 --> 00:10:14,760 Speaker 1: to conduct an investigation into the national security implications of 190 00:10:14,760 --> 00:10:19,200 Speaker 1: Saudi Arabia's purchase of Twitter. Now, among the investors backing 191 00:10:19,280 --> 00:10:21,960 Speaker 1: must take over, Saudi Prince Alwa lead been to lall 192 00:10:22,080 --> 00:10:24,680 Speaker 1: through the Kingdom holding Company and his private office, which 193 00:10:24,679 --> 00:10:28,280 Speaker 1: agreed to roll over nearly thirty five million Twitter shares 194 00:10:28,280 --> 00:10:41,199 Speaker 1: worth about one point nine billion dollars. Back now with 195 00:10:41,400 --> 00:10:44,240 Speaker 1: Mark Mahoney of Avercor to talk about big tech results. Mark, 196 00:10:44,280 --> 00:10:47,040 Speaker 1: I gotta start with Meta. It's sold off more than 197 00:10:47,120 --> 00:10:50,400 Speaker 1: sevent so far this year. I just checked its market cap, 198 00:10:50,679 --> 00:10:53,400 Speaker 1: less than two hundred fifty million dollars. We're back to 199 00:10:53,480 --> 00:10:59,280 Speaker 1: October levels. I mean, would you have ever thought this 200 00:11:00,000 --> 00:11:04,320 Speaker 1: could be possible? Um, after this company has achieved such 201 00:11:04,400 --> 00:11:08,520 Speaker 1: historic high I didn't think it would be possible. Um Well, 202 00:11:08,559 --> 00:11:10,040 Speaker 1: I guess I thought it was possible, but I didn't 203 00:11:10,040 --> 00:11:11,800 Speaker 1: think it was probable, or else I would have had 204 00:11:11,840 --> 00:11:13,760 Speaker 1: a buy on it. Mikel has been dead wrong on 205 00:11:13,800 --> 00:11:16,320 Speaker 1: this for the last twelve months or even longer. This 206 00:11:16,360 --> 00:11:19,640 Speaker 1: company hit this buzz saw of these Apple privacy changes, 207 00:11:20,559 --> 00:11:26,040 Speaker 1: competition from from TikTok, and now an advertising economic recession, 208 00:11:26,520 --> 00:11:29,520 Speaker 1: and then this fourth kind of spoiler alert issue or 209 00:11:29,559 --> 00:11:32,280 Speaker 1: spoiler issue, which is what really came up last week, 210 00:11:32,320 --> 00:11:34,960 Speaker 1: which is that the market wants them to cut out 211 00:11:35,040 --> 00:11:38,440 Speaker 1: the spend on the metaverse, slash it in half, rain 212 00:11:38,559 --> 00:11:42,280 Speaker 1: and expenses. It's a recession. When when that happens, you're 213 00:11:42,280 --> 00:11:45,800 Speaker 1: supposed to kind of marry down, ratchet down expenses and 214 00:11:45,840 --> 00:11:49,120 Speaker 1: investments to kind of kind of match up with with 215 00:11:49,240 --> 00:11:52,240 Speaker 1: the deteriorating revenue. And the company is sort of refusing 216 00:11:52,280 --> 00:11:54,720 Speaker 1: to do that. Zuckerberger's refusing to do that. And I 217 00:11:54,720 --> 00:11:57,240 Speaker 1: think this last part is really just fight selling on 218 00:11:57,280 --> 00:11:59,760 Speaker 1: a part of investors who were saying you know, the 219 00:11:59,800 --> 00:12:02,720 Speaker 1: It's wasn't the revenue results. People expected softness there. It 220 00:12:02,840 --> 00:12:05,920 Speaker 1: was that they that the clinging to this aggressive investment 221 00:12:05,920 --> 00:12:08,480 Speaker 1: horizon in this environment, and the market has said no, 222 00:12:09,080 --> 00:12:11,640 Speaker 1: that too much. It's no mosque, We're out of here. 223 00:12:11,640 --> 00:12:14,080 Speaker 1: We're selling now. There were a couple of companies that 224 00:12:14,200 --> 00:12:19,160 Speaker 1: had strong quarters Apple Pinterest, which is interesting given their 225 00:12:19,240 --> 00:12:24,040 Speaker 1: role in the advertising business. But of course Alphabet, Meta, Microsoft, Amazon, 226 00:12:24,240 --> 00:12:29,040 Speaker 1: all having a really tough quarter reporting. What's the common 227 00:12:29,080 --> 00:12:32,440 Speaker 1: thread here, Well, just the only thing I uh equivabal 228 00:12:32,520 --> 00:12:36,320 Speaker 1: with you on is Pinterest. Pinterest revenue results actually deteriorated. Now, 229 00:12:36,559 --> 00:12:39,480 Speaker 1: the expectations have been set low enough that results came 230 00:12:39,520 --> 00:12:41,120 Speaker 1: in a little bit better than expected. By the way 231 00:12:41,200 --> 00:12:43,599 Speaker 1: they did with Meta too, ad revenue came in a 232 00:12:43,640 --> 00:12:46,520 Speaker 1: smidgin better than expected. So it wasn't a revenue problem. 233 00:12:46,720 --> 00:12:48,920 Speaker 1: Is that people just don't want them investing out, particularly 234 00:12:48,920 --> 00:12:51,240 Speaker 1: they don't want them investing in the metaverse with their 235 00:12:51,280 --> 00:12:54,640 Speaker 1: return on that investment dollar is so uncertain. What's happening 236 00:12:54,720 --> 00:12:57,600 Speaker 1: is demanded softening across the board. So the two most 237 00:12:57,640 --> 00:13:01,040 Speaker 1: interesting parts to me, Emily were Google. This was the 238 00:13:01,080 --> 00:13:03,400 Speaker 1: first quarter that Google said there was weakness and search. 239 00:13:03,559 --> 00:13:05,320 Speaker 1: They hadn't said that in March, they hadn't said that 240 00:13:05,400 --> 00:13:07,400 Speaker 1: in June quarter. They said that in the September quarter. 241 00:13:07,720 --> 00:13:10,760 Speaker 1: And search is usually considered to be the most not 242 00:13:11,120 --> 00:13:14,400 Speaker 1: recession proof, but recession resilient of all the ad platforms. 243 00:13:14,480 --> 00:13:16,640 Speaker 1: So if Google seeing it in search, you can you 244 00:13:16,679 --> 00:13:19,520 Speaker 1: can be pretty sure that just about every other company 245 00:13:19,559 --> 00:13:21,800 Speaker 1: is seeing it. And then there's Amazon. Amazon, and the 246 00:13:21,920 --> 00:13:24,920 Speaker 1: June quarter was specifically asked whether they've seen any signs 247 00:13:24,920 --> 00:13:27,840 Speaker 1: of consumer softness in the CEFO said no, Well things 248 00:13:27,840 --> 00:13:30,480 Speaker 1: have changed now they're starting to see softness, and they 249 00:13:30,520 --> 00:13:33,040 Speaker 1: saw it in Europe maybe not surprisingly, and now I'm 250 00:13:33,040 --> 00:13:35,320 Speaker 1: starting to bleed over to the US. So the real 251 00:13:35,400 --> 00:13:37,560 Speaker 1: question is how much worse could it get? We know 252 00:13:37,640 --> 00:13:39,720 Speaker 1: what's getting softer, will it continue to get softer and 253 00:13:39,800 --> 00:13:42,640 Speaker 1: for how long? And that's that's a really hard one 254 00:13:42,679 --> 00:13:44,240 Speaker 1: to know. But it's a macro call. And I think 255 00:13:44,240 --> 00:13:46,800 Speaker 1: all of these companies, especially they have exposure to the consumer, 256 00:13:46,920 --> 00:13:50,320 Speaker 1: but even Microsoft and and Amazon with a WS are 257 00:13:50,440 --> 00:13:53,079 Speaker 1: are saying that enterprises are starting to slow down to 258 00:13:53,440 --> 00:13:56,680 Speaker 1: we're heading into recession demand trends or softening across the board, 259 00:13:56,920 --> 00:13:59,280 Speaker 1: and any company who tells you that that's not the case. 260 00:13:59,360 --> 00:14:01,599 Speaker 1: It's probably be either doesn't know their business or is 261 00:14:01,640 --> 00:14:04,880 Speaker 1: not being honest. Interesting point you made about Pinterest. Bill Ready, 262 00:14:04,880 --> 00:14:07,400 Speaker 1: the new CEO is going to be on the show 263 00:14:07,840 --> 00:14:09,800 Speaker 1: in in in a few minutes. I'm gonna put your 264 00:14:09,840 --> 00:14:12,319 Speaker 1: point to him. I do want to ask about the 265 00:14:12,360 --> 00:14:15,520 Speaker 1: broader advertising landscape and what your outlook is. You know, 266 00:14:15,600 --> 00:14:19,200 Speaker 1: you also cover Netflix, which reversed the decline and subscribers 267 00:14:19,240 --> 00:14:21,200 Speaker 1: for the first time in a while. You've got now 268 00:14:21,240 --> 00:14:24,160 Speaker 1: the streamers going after a piece of the advertising pie 269 00:14:24,240 --> 00:14:27,440 Speaker 1: in addition to the social media companies going after the 270 00:14:27,520 --> 00:14:30,760 Speaker 1: advertising pie. How is this all going to play out well? 271 00:14:30,960 --> 00:14:33,360 Speaker 1: By the way I think Pinterest is maybe really will 272 00:14:33,440 --> 00:14:36,240 Speaker 1: set up here. You know, you've got a turnaround story, 273 00:14:36,440 --> 00:14:40,680 Speaker 1: um executive with a very good execution track record, asset 274 00:14:40,720 --> 00:14:42,800 Speaker 1: that may not have been run that well in the past. 275 00:14:42,880 --> 00:14:45,040 Speaker 1: So there's a turnaround story. By the way, there's sort 276 00:14:45,080 --> 00:14:46,880 Speaker 1: of is a Netflix too, which is why the stock 277 00:14:46,920 --> 00:14:50,360 Speaker 1: has been a monster stock to the upside finally over 278 00:14:50,360 --> 00:14:53,040 Speaker 1: the last couple of months, because there's this new revenue 279 00:14:53,080 --> 00:14:55,040 Speaker 1: team that they're going to go from zero to a huntred. 280 00:14:55,240 --> 00:14:58,000 Speaker 1: Question is just how quickly. But you know there there's 281 00:14:58,240 --> 00:15:04,640 Speaker 1: there's enormous demand for from advertisers for access to Netflix's base. 282 00:15:04,800 --> 00:15:06,920 Speaker 1: I mean two or your twenty million people who use 283 00:15:07,000 --> 00:15:09,040 Speaker 1: the site, you know, an hour or two hours a day. 284 00:15:09,040 --> 00:15:11,960 Speaker 1: So you've got reach, you've got frequency, and you've got 285 00:15:12,000 --> 00:15:14,680 Speaker 1: almost like a primetime audience. You know that that prime 286 00:15:14,720 --> 00:15:18,240 Speaker 1: audience I meant like Amazon Prime s. The average household 287 00:15:18,240 --> 00:15:22,560 Speaker 1: probably rescuse middle to upper middle income globally for Netflix. 288 00:15:22,600 --> 00:15:25,400 Speaker 1: So there's just a lot that brand advertisers can tap into. 289 00:15:25,440 --> 00:15:28,280 Speaker 1: For the first time ever, you can own Netflix inventory, 290 00:15:28,400 --> 00:15:31,320 Speaker 1: so that that's what there's something new. If you don't, 291 00:15:31,360 --> 00:15:33,320 Speaker 1: if you don't have something new, brand new in your 292 00:15:33,360 --> 00:15:35,560 Speaker 1: in your fundamentals, they are going to get weaker in 293 00:15:35,600 --> 00:15:38,080 Speaker 1: the back half year and going into next year. That's 294 00:15:38,080 --> 00:15:40,600 Speaker 1: the advantage that Netflix has right here. I like Netflix 295 00:15:40,680 --> 00:15:43,360 Speaker 1: is one of my topics, so is Meta. I just didn't. 296 00:15:43,440 --> 00:15:46,320 Speaker 1: I just thought Metal was gonna show more cost and 297 00:15:46,480 --> 00:15:50,720 Speaker 1: investment discipline than than they've led on mark human covering 298 00:15:50,800 --> 00:15:55,400 Speaker 1: tech for two decades. Do you think we're seeing a 299 00:15:55,400 --> 00:15:58,560 Speaker 1: real inflection point here? Is there further to fall? And 300 00:15:58,600 --> 00:16:01,400 Speaker 1: how how long does it take before this turns around well, 301 00:16:01,560 --> 00:16:03,680 Speaker 1: so to two thoughts, Um and I love the way 302 00:16:03,720 --> 00:16:05,320 Speaker 1: you set up the question. So yeah, we have a 303 00:16:05,360 --> 00:16:08,320 Speaker 1: negative inflection here. These are tech is bigger than it 304 00:16:08,400 --> 00:16:10,880 Speaker 1: was during the last cycle O eight oh nine with 305 00:16:10,960 --> 00:16:14,680 Speaker 1: the great housing, great financial crisis, Great housing, great financial crisis. 306 00:16:14,720 --> 00:16:17,480 Speaker 1: Those are the same thing, and so it's much bigger. 307 00:16:17,480 --> 00:16:20,080 Speaker 1: So it's more cyclical than it was back then. Look, 308 00:16:20,080 --> 00:16:22,440 Speaker 1: our our our firm aber Coorien size call is that 309 00:16:22,600 --> 00:16:25,880 Speaker 1: overall advertising is going to decline mid single digits next year, 310 00:16:26,040 --> 00:16:28,640 Speaker 1: which probably means to digital advertising is going to be 311 00:16:29,080 --> 00:16:31,960 Speaker 1: flat up five percent. There's another inflection point yield that 312 00:16:31,960 --> 00:16:33,920 Speaker 1: I'm super interested in. We'll have to come back to it. 313 00:16:33,960 --> 00:16:37,920 Speaker 1: But that's AI. So what Facebook and Google are doing, 314 00:16:38,000 --> 00:16:42,160 Speaker 1: met and alphabet they're spending seventy billion dollars combined next 315 00:16:42,200 --> 00:16:45,920 Speaker 1: year on capex related to AI, artificial intelligence and machine learning. 316 00:16:46,120 --> 00:16:49,480 Speaker 1: I'm fascinating And Bill Ready has been uh, very thoughtful 317 00:16:49,520 --> 00:16:52,000 Speaker 1: on this topic too. I'm fascinated by what's gonna come 318 00:16:52,000 --> 00:16:54,040 Speaker 1: out of this. The market is assuming that there's very 319 00:16:54,040 --> 00:16:58,160 Speaker 1: little return on that AI investment, that AI capital expenditures. 320 00:16:58,640 --> 00:17:00,800 Speaker 1: My guess is at Google and and men have probably 321 00:17:00,800 --> 00:17:02,360 Speaker 1: know what they're doing, and we're going to see some 322 00:17:02,440 --> 00:17:04,840 Speaker 1: sort of return on it. But but and so when 323 00:17:04,880 --> 00:17:06,560 Speaker 1: we see that, I don't think that's pricing. I think 324 00:17:06,560 --> 00:17:09,800 Speaker 1: that creates some wonderful long term buying opportunities on these 325 00:17:09,840 --> 00:17:12,119 Speaker 1: two stocks. What I fear is that the stocks are 326 00:17:12,160 --> 00:17:14,720 Speaker 1: first going to go down because of macro and recession 327 00:17:14,960 --> 00:17:18,439 Speaker 1: before they start moving up because of artificial intelligence. All Right, 328 00:17:18,600 --> 00:17:21,399 Speaker 1: we're gonna have to dig in to artificial intelligence with 329 00:17:21,440 --> 00:17:23,840 Speaker 1: you next time you're back on the show. Markmahenny of 330 00:17:23,840 --> 00:17:26,119 Speaker 1: ever Core, I s, I always appreciate your perspective, and 331 00:17:26,200 --> 00:17:30,439 Speaker 1: especially your historical perspective. Given how many years you've been 332 00:17:30,480 --> 00:17:33,120 Speaker 1: doing this, We're gonna have much more ahead. Stay with us. 333 00:17:33,280 --> 00:17:50,600 Speaker 1: This is Bloomberg, another story we're continuing to watch. Electronic 334 00:17:50,680 --> 00:17:54,200 Speaker 1: Arts will develop three video games inspired by Marvel comic 335 00:17:54,280 --> 00:17:57,240 Speaker 1: book characters. That gives the company access to the most 336 00:17:57,240 --> 00:18:00,800 Speaker 1: popular entertainment franchise in the world. The scheme e A 337 00:18:01,160 --> 00:18:03,720 Speaker 1: is making is based on Iron Man, that is, the 338 00:18:03,760 --> 00:18:06,760 Speaker 1: billionaire inventor and superhero who was the main character in 339 00:18:06,800 --> 00:18:17,800 Speaker 1: one of the first hit Marvel movies. Welcome back to 340 00:18:17,840 --> 00:18:20,199 Speaker 1: Bloomberg Technology and Emily Changing in San Francisco. Let's get 341 00:18:20,240 --> 00:18:23,040 Speaker 1: back to the markets and social media stocks on the move. 342 00:18:23,280 --> 00:18:26,440 Speaker 1: Bloomberg's at Ludlow is back and take it away. Yeah, 343 00:18:26,440 --> 00:18:28,240 Speaker 1: there was a pocket of weakness in the market when 344 00:18:28,240 --> 00:18:30,360 Speaker 1: it comes to social media shares. We talked about how 345 00:18:30,359 --> 00:18:34,440 Speaker 1: Meta closed its lowest level since October. There were reports 346 00:18:34,760 --> 00:18:38,440 Speaker 1: from down to detect to seven thousand incidences of people 347 00:18:38,520 --> 00:18:42,639 Speaker 1: saying that Instagram had crashed and was having some glitches 348 00:18:42,680 --> 00:18:44,680 Speaker 1: and was down. But you would suspect that a lot 349 00:18:44,680 --> 00:18:47,280 Speaker 1: of the pressure on this stock stems from that disappointing 350 00:18:47,640 --> 00:18:50,240 Speaker 1: earnings report last week. Snap caught up with that down 351 00:18:50,240 --> 00:18:53,520 Speaker 1: one point sent Pinterest Interesting had its best day in 352 00:18:53,560 --> 00:18:56,320 Speaker 1: more than two months last Friday after strong earnings. I 353 00:18:56,320 --> 00:18:58,720 Speaker 1: think the street really liked what they saw, but giving 354 00:18:58,800 --> 00:19:01,840 Speaker 1: up some of those gains in Monday session down one 355 00:19:01,840 --> 00:19:05,480 Speaker 1: Pinterest really interesting stories. We look at the stock year 356 00:19:05,520 --> 00:19:08,119 Speaker 1: to day relative to met Her and Snap. We know 357 00:19:08,160 --> 00:19:11,960 Speaker 1: about softness and the advertizing space, but actually relative to 358 00:19:12,000 --> 00:19:14,680 Speaker 1: its peers, Pinterest is held up really well. I'm really 359 00:19:14,680 --> 00:19:16,960 Speaker 1: interested in what the story is here and what invests 360 00:19:17,040 --> 00:19:20,600 Speaker 1: see in Pinterest relative to a Meta, relative to a Snap. 361 00:19:20,640 --> 00:19:23,719 Speaker 1: That said, of course, it is still down pretty significantly 362 00:19:23,760 --> 00:19:26,399 Speaker 1: year today, and I'm hoping that you can ask which 363 00:19:26,440 --> 00:19:30,520 Speaker 1: direction the stock goes from here? All right, I will 364 00:19:30,560 --> 00:19:35,119 Speaker 1: indeed thank you. Pinterest has been out pacing its peers, 365 00:19:35,119 --> 00:19:37,439 Speaker 1: as I mentioned, posting strong third quarter results with an 366 00:19:37,480 --> 00:19:41,480 Speaker 1: uptick and monthly active users after three straight quarters of declines. 367 00:19:41,960 --> 00:19:44,520 Speaker 1: This as the social media industry grapples with a decrease 368 00:19:44,560 --> 00:19:49,000 Speaker 1: in digital ad spend while marketers worry about economic uncertainty. 369 00:19:49,200 --> 00:19:52,040 Speaker 1: Joining me now for more on this bi already, Pinterest 370 00:19:52,040 --> 00:19:54,880 Speaker 1: CEO has been on the job since late June. So 371 00:19:55,240 --> 00:19:58,280 Speaker 1: how is it that Pinterest seemed to buck the ad 372 00:19:58,400 --> 00:20:02,520 Speaker 1: media spiral we saw with Snap and Meta and others. 373 00:20:02,680 --> 00:20:05,960 Speaker 1: Bill Well, first of all, thanks for having me Emily. 374 00:20:06,160 --> 00:20:08,920 Speaker 1: Always a pleasure, UM, And I feel really great about 375 00:20:08,920 --> 00:20:11,280 Speaker 1: how our team performed in Q three. I think you 376 00:20:11,320 --> 00:20:13,680 Speaker 1: know we're we're doing some things that are fundingly different 377 00:20:13,720 --> 00:20:16,040 Speaker 1: than the rest of social media, and I think you're 378 00:20:16,040 --> 00:20:18,920 Speaker 1: seeing that start to cut through with advertisers, uh, and 379 00:20:18,920 --> 00:20:21,280 Speaker 1: and with users. We grew teen percent year on year 380 00:20:21,320 --> 00:20:25,119 Speaker 1: on a constant currency basis. UH, really outpacing a decelerating 381 00:20:25,160 --> 00:20:26,920 Speaker 1: market and growing faster than a lot of our peers, 382 00:20:26,960 --> 00:20:29,640 Speaker 1: which means we're taking share. Uh. And I think part 383 00:20:29,640 --> 00:20:32,359 Speaker 1: of that is that, you know, number one, we're a 384 00:20:32,400 --> 00:20:34,480 Speaker 1: positive platform. We're not a place where people go to 385 00:20:34,480 --> 00:20:37,760 Speaker 1: shout about their politics or to present their seemly perfect 386 00:20:37,760 --> 00:20:40,440 Speaker 1: life that makes others feel negative. Uh. It's it's a 387 00:20:40,440 --> 00:20:43,040 Speaker 1: place where people go to find inspiration. UH. It's a 388 00:20:43,040 --> 00:20:45,320 Speaker 1: place where people go with an intent and a purpose. 389 00:20:45,960 --> 00:20:49,320 Speaker 1: And that's a very unique thing in the space, both 390 00:20:49,359 --> 00:20:52,360 Speaker 1: for what the users get as well as what advertisers get. 391 00:20:52,400 --> 00:20:56,080 Speaker 1: It's a full funnel ADS solution in the advertisers can 392 00:20:56,080 --> 00:20:59,600 Speaker 1: connect at the upper, mid and lower funnel and really 393 00:20:59,640 --> 00:21:02,280 Speaker 1: meet you. There's a multiple points along their journey. And 394 00:21:02,320 --> 00:21:04,800 Speaker 1: so the brand safe nature of the platform, paired with 395 00:21:04,840 --> 00:21:07,960 Speaker 1: the full funnel nature of it, UH, user growth returning, 396 00:21:08,280 --> 00:21:10,560 Speaker 1: these things are all starting to really cut through. UH. 397 00:21:10,600 --> 00:21:12,400 Speaker 1: And I think you see it demonstrated in our results. 398 00:21:12,640 --> 00:21:15,760 Speaker 1: Let's talk about what advertisers get, because obviously we're seeing 399 00:21:15,760 --> 00:21:18,320 Speaker 1: a broader ad pullback. What is your outlook as we 400 00:21:18,320 --> 00:21:21,320 Speaker 1: head into three and how much of that you know, 401 00:21:21,400 --> 00:21:25,520 Speaker 1: pinterest gains? Do you do potentially gain ad market share 402 00:21:25,760 --> 00:21:30,240 Speaker 1: or not As we head into a potentially pronounced long 403 00:21:30,320 --> 00:21:33,479 Speaker 1: term economic downturn. Yeah, well, I think it's clear when 404 00:21:33,480 --> 00:21:35,640 Speaker 1: you look at our performance relative. Here's this past quarter 405 00:21:36,240 --> 00:21:39,119 Speaker 1: that we've been gaining share, uh and where a smaller 406 00:21:39,119 --> 00:21:40,280 Speaker 1: player than many of the others, and so I think 407 00:21:40,320 --> 00:21:42,640 Speaker 1: there's a lot more opportunity for us to pick up share. 408 00:21:43,200 --> 00:21:45,919 Speaker 1: That said, we know we outran a decelerating ad market 409 00:21:45,920 --> 00:21:48,520 Speaker 1: this past quarter, and you know the market looks to 410 00:21:48,560 --> 00:21:50,480 Speaker 1: still be choppy, and so we're looking to make sure 411 00:21:50,520 --> 00:21:54,080 Speaker 1: that we show up with really great value for our advertisers. 412 00:21:54,119 --> 00:21:56,840 Speaker 1: And we're doing that through you know, a number of dimensions. 413 00:21:56,880 --> 00:21:59,760 Speaker 1: You know, a couple of which I mentioned around really 414 00:21:59,800 --> 00:22:02,480 Speaker 1: help helping the advertisers meet the users throughout the full funnel. 415 00:22:02,480 --> 00:22:04,600 Speaker 1: I think that's quite unique when you compare us to 416 00:22:04,640 --> 00:22:07,800 Speaker 1: other social media platforms. Most of them have the user 417 00:22:07,840 --> 00:22:10,480 Speaker 1: and sort of a lean back entertainment mode where the 418 00:22:10,600 --> 00:22:13,119 Speaker 1: user is there for some other purpose, whether it's to 419 00:22:13,240 --> 00:22:15,480 Speaker 1: watch a funny dance video or to view pictures of 420 00:22:15,520 --> 00:22:19,240 Speaker 1: their friends. People come on Pinterest looking for products. More 421 00:22:19,240 --> 00:22:21,720 Speaker 1: than half of them are there to shop, and so 422 00:22:22,600 --> 00:22:24,800 Speaker 1: they're there with an intent and a purpose. And the 423 00:22:24,840 --> 00:22:27,960 Speaker 1: fact that we get users at the upper, mid and 424 00:22:28,040 --> 00:22:30,399 Speaker 1: lower stage of their journeys means that we're able to 425 00:22:30,480 --> 00:22:33,480 Speaker 1: help the advertiser connect across those and really meet users 426 00:22:33,480 --> 00:22:35,680 Speaker 1: at this sort of magic moment where they have an idea, 427 00:22:36,160 --> 00:22:38,359 Speaker 1: a general idea of what they want, but they haven't 428 00:22:38,359 --> 00:22:41,280 Speaker 1: decided what to buy yet, and so that's really cutting through. 429 00:22:41,520 --> 00:22:44,760 Speaker 1: And then finally, I just say, you know, every CMO 430 00:22:44,840 --> 00:22:47,120 Speaker 1: out there has been approached by their CFO saying Okay, 431 00:22:47,119 --> 00:22:50,040 Speaker 1: you've got to go drive performance, and sometimes that results 432 00:22:50,040 --> 00:22:53,840 Speaker 1: in a bit of a Sophie's choice where that means 433 00:22:53,880 --> 00:22:56,679 Speaker 1: that they oftentimes rushed to last click, but it means 434 00:22:56,720 --> 00:22:58,560 Speaker 1: they're not getting to tell their brand story. And what 435 00:22:58,640 --> 00:23:02,760 Speaker 1: pinterest is delivering that we're finding really resonant with advertisers 436 00:23:02,880 --> 00:23:05,280 Speaker 1: is the ability to tell their brand story in a 437 00:23:05,359 --> 00:23:08,520 Speaker 1: performant way because we do have the lower funnel aspect 438 00:23:08,520 --> 00:23:11,280 Speaker 1: of that as well, and and can connect across that 439 00:23:11,280 --> 00:23:13,919 Speaker 1: that user journey. Let's talk a little bit about users, 440 00:23:13,960 --> 00:23:19,000 Speaker 1: because obviously investors are excited about the reignition of growth. 441 00:23:19,000 --> 00:23:22,639 Speaker 1: Here we had Mark Mhaney, who covers pinterest on earlier 442 00:23:22,680 --> 00:23:24,720 Speaker 1: in the show, he said, to be fair, expectations for 443 00:23:24,760 --> 00:23:27,399 Speaker 1: Pinterests were low, though he is very optimistic about you 444 00:23:27,480 --> 00:23:31,080 Speaker 1: coming in and you know, bringing a new perspective on 445 00:23:31,119 --> 00:23:33,919 Speaker 1: how to manage this company. What are you doing to 446 00:23:34,040 --> 00:23:37,480 Speaker 1: attract gen z and how and what is the evidence 447 00:23:37,680 --> 00:23:41,399 Speaker 1: that that is working. Yeah, so you know, we return 448 00:23:41,440 --> 00:23:43,360 Speaker 1: to user growth this quarter. We stabilize the user based 449 00:23:43,560 --> 00:23:46,440 Speaker 1: based return to user growth, and we really doing doing 450 00:23:46,480 --> 00:23:50,280 Speaker 1: that by leaning into the uniqueness of the platform. When 451 00:23:50,280 --> 00:23:52,040 Speaker 1: you think about it as a positive place and a 452 00:23:52,080 --> 00:23:54,760 Speaker 1: place where people go with intent and purpose, it really 453 00:23:54,800 --> 00:23:57,760 Speaker 1: is unique across social media. It's also quite unique and 454 00:23:57,800 --> 00:24:00,000 Speaker 1: that it's a place where people go to express their creativity. 455 00:24:00,760 --> 00:24:03,600 Speaker 1: And so we're leveraging those things, leaning into them more, 456 00:24:04,400 --> 00:24:07,000 Speaker 1: drawing the contrast from the rest of social media, and 457 00:24:07,520 --> 00:24:11,080 Speaker 1: you know, really leveraging the unique human curation that happens 458 00:24:11,080 --> 00:24:15,000 Speaker 1: on our platform to drive better and more personalized experiences 459 00:24:15,040 --> 00:24:17,840 Speaker 1: for our users. To give you a tangible example of that, 460 00:24:18,200 --> 00:24:20,159 Speaker 1: you know, you can go lots of places to find 461 00:24:20,359 --> 00:24:23,320 Speaker 1: a great new dress, but if you think about how 462 00:24:23,320 --> 00:24:26,199 Speaker 1: to put together a great outfit and what handbag and 463 00:24:26,240 --> 00:24:28,520 Speaker 1: shoes and accessories might go really well with that dress. 464 00:24:29,119 --> 00:24:31,520 Speaker 1: M Yes, we're doing a lot with machine learning, as 465 00:24:31,520 --> 00:24:34,359 Speaker 1: many others are, but machine learning is only as good 466 00:24:34,400 --> 00:24:36,840 Speaker 1: as a signal that is acting upon, and we have 467 00:24:37,000 --> 00:24:39,320 Speaker 1: hundreds of millions of pinners that come to our platform 468 00:24:39,760 --> 00:24:42,879 Speaker 1: and curate boards that tell us what kind of accessories 469 00:24:42,960 --> 00:24:44,920 Speaker 1: might go well with that dress. So when you get 470 00:24:44,960 --> 00:24:48,080 Speaker 1: recommendations here, it's not just from really great machine learning, 471 00:24:48,280 --> 00:24:51,719 Speaker 1: it's really great machine learning acting upon signals from hundreds 472 00:24:51,720 --> 00:24:54,600 Speaker 1: of millions of pinners that are telling us what things 473 00:24:54,640 --> 00:24:56,800 Speaker 1: go well together, whether it's putting together an outfit, or 474 00:24:56,800 --> 00:24:59,000 Speaker 1: putting together a room, or thinking about how to put 475 00:24:59,040 --> 00:25:02,200 Speaker 1: together really great holiday plans for what a great meal 476 00:25:02,280 --> 00:25:06,240 Speaker 1: might be. All these things. We have great human curation 477 00:25:06,280 --> 00:25:08,800 Speaker 1: that happens on the platform at scale. They're just completely 478 00:25:08,840 --> 00:25:10,360 Speaker 1: unique across the space. I don't think you really see 479 00:25:10,359 --> 00:25:12,720 Speaker 1: it happening any place else. And we pair that with 480 00:25:12,800 --> 00:25:16,560 Speaker 1: great machine learning, great advertising capabilities. It's really cutting through 481 00:25:16,600 --> 00:25:19,119 Speaker 1: to drive user growth and revenue growth. Now, even the 482 00:25:19,119 --> 00:25:21,879 Speaker 1: point that Pinteresque you see as as being very different 483 00:25:21,920 --> 00:25:25,119 Speaker 1: from other social media platforms, I'm so curious what you 484 00:25:25,160 --> 00:25:28,640 Speaker 1: think about what's happening at Twitter. You know, it's unclear 485 00:25:28,760 --> 00:25:30,880 Speaker 1: what the business model is even going to be unclear 486 00:25:30,960 --> 00:25:34,240 Speaker 1: whether advertisers are going to stick around. Is Twitter under 487 00:25:34,280 --> 00:25:37,960 Speaker 1: Elon Musk, possibly an opportunity for pinterrests to take some 488 00:25:38,119 --> 00:25:41,000 Speaker 1: of those ad dollars or even to take some of 489 00:25:41,040 --> 00:25:45,400 Speaker 1: that mind share, or is it a totally different proposition. Well, 490 00:25:45,440 --> 00:25:47,919 Speaker 1: I mean, I can't comment on any one specific player, 491 00:25:47,960 --> 00:25:50,000 Speaker 1: but I would say that when you compare pinterest to 492 00:25:50,080 --> 00:25:53,240 Speaker 1: social media more broadly, Uh, First, I'd say, you know 493 00:25:53,240 --> 00:25:57,080 Speaker 1: where this really unique intersection between social search and commerce, 494 00:25:57,440 --> 00:25:59,920 Speaker 1: which is totally different than other platforms. I think when 495 00:26:00,040 --> 00:26:02,359 Speaker 1: add on to that the positive nature of our platform, 496 00:26:02,480 --> 00:26:05,720 Speaker 1: which we tune for intentionally, uh, and we hear from 497 00:26:05,800 --> 00:26:09,040 Speaker 1: users that it's a place that they feel uplifted, they 498 00:26:09,040 --> 00:26:12,479 Speaker 1: feel inspired, whereas oftentimes on other platforms they're you know, 499 00:26:12,560 --> 00:26:16,399 Speaker 1: seeing people shout about their politics or you know, you 500 00:26:16,400 --> 00:26:19,640 Speaker 1: know generally activity that you can lead them feeling leave 501 00:26:19,680 --> 00:26:21,840 Speaker 1: them feeling anxious or depressed or these kinds of things. 502 00:26:22,200 --> 00:26:24,239 Speaker 1: And they feel lifted up on our platform. And so 503 00:26:24,280 --> 00:26:26,520 Speaker 1: we're leaning into that, and as we do that, it 504 00:26:26,560 --> 00:26:29,160 Speaker 1: makes it a brand safe space for advertisers. And so 505 00:26:29,600 --> 00:26:32,600 Speaker 1: that's something that advertisers understood about Penchess for some time. 506 00:26:32,920 --> 00:26:34,640 Speaker 1: We're leaning more and more into that and we're seeing 507 00:26:34,680 --> 00:26:36,720 Speaker 1: it cut through more and more versus the rest of 508 00:26:36,720 --> 00:26:40,960 Speaker 1: social media. How has your Google commerce background come into 509 00:26:41,000 --> 00:26:43,840 Speaker 1: play thus far and have you had any sort of 510 00:26:43,920 --> 00:26:46,840 Speaker 1: light bulb moments about how to make that connection from 511 00:26:46,840 --> 00:26:49,439 Speaker 1: something you see on pinter as to something that you 512 00:26:49,600 --> 00:26:54,520 Speaker 1: buy much more concrete? Well, this is a great question 513 00:26:54,600 --> 00:26:59,080 Speaker 1: because while Pinterest is a full funnel platform, uh, you know, 514 00:26:59,280 --> 00:27:01,800 Speaker 1: his historically been stronger in the upper and mid funnel, 515 00:27:01,800 --> 00:27:03,480 Speaker 1: where people would find a lot of things they found 516 00:27:03,520 --> 00:27:07,160 Speaker 1: interesting on Pinterest, but then they have to go somewhere 517 00:27:07,200 --> 00:27:10,000 Speaker 1: else to go act upon that. And part of what 518 00:27:10,040 --> 00:27:12,960 Speaker 1: we're doing is making sure that as people find things 519 00:27:12,960 --> 00:27:15,600 Speaker 1: on Pinterest, that we're leaning into that intent to action, 520 00:27:15,640 --> 00:27:17,560 Speaker 1: making things much more actionable. So I talked about on 521 00:27:17,600 --> 00:27:19,840 Speaker 1: our earnings call. We want to make it so that 522 00:27:20,359 --> 00:27:22,800 Speaker 1: every image of every product that you encounter on Pinterest 523 00:27:22,920 --> 00:27:26,320 Speaker 1: becomes shoppable, whether you find that in a scene or 524 00:27:26,359 --> 00:27:28,840 Speaker 1: in user generated content. When you see a great product, 525 00:27:29,320 --> 00:27:31,520 Speaker 1: even if it's you know, some celebrity that's wearing it, 526 00:27:31,560 --> 00:27:33,280 Speaker 1: you say, oh, I want that product or I want 527 00:27:33,320 --> 00:27:35,919 Speaker 1: that same look. Uh. That we're making that more and 528 00:27:35,920 --> 00:27:39,040 Speaker 1: more shoppable for people. And as we do that, connecting 529 00:27:39,040 --> 00:27:41,679 Speaker 1: that intent to action strengthens the lower funnel part of 530 00:27:41,680 --> 00:27:44,600 Speaker 1: our business, and we think there's a lot more opportunity 531 00:27:45,080 --> 00:27:47,359 Speaker 1: to go there. I think it's historically again been a 532 00:27:47,400 --> 00:27:50,160 Speaker 1: place where the platform wasn't as strong, and we're making 533 00:27:50,160 --> 00:27:52,639 Speaker 1: that much stronger over time. And there's good progress already. 534 00:27:52,720 --> 00:27:54,879 Speaker 1: I talked about shopping as being up fifty year on 535 00:27:55,000 --> 00:27:59,480 Speaker 1: year conversions, so really good progress there, but a lot 536 00:27:59,520 --> 00:28:01,800 Speaker 1: more to do there and as we do it that 537 00:28:01,920 --> 00:28:04,720 Speaker 1: will be better and better engagement for users and also 538 00:28:04,960 --> 00:28:09,160 Speaker 1: really great advertising opportunities for our partners. Now, your collage 539 00:28:09,280 --> 00:28:13,160 Speaker 1: making app, Shuffles, has seen really good traction, I know, 540 00:28:13,920 --> 00:28:18,960 Speaker 1: especially in the United States, helping with engagement and active users. 541 00:28:19,840 --> 00:28:24,080 Speaker 1: What's the longer term vision there and how can you 542 00:28:24,119 --> 00:28:26,240 Speaker 1: integrate sort of what you're learning from Shuffles into the 543 00:28:26,240 --> 00:28:30,879 Speaker 1: broader experience. Yeah, so great question, Emily, Shuffles. We've been, 544 00:28:31,359 --> 00:28:33,919 Speaker 1: you know, quite excited by the progress with Shuffles. There 545 00:28:33,920 --> 00:28:37,000 Speaker 1: are college making app that has just really resonated with 546 00:28:37,080 --> 00:28:40,640 Speaker 1: gen Z and I think it's indicative of how there 547 00:28:40,680 --> 00:28:43,280 Speaker 1: are a number of adjacent use cases that we can 548 00:28:43,320 --> 00:28:46,680 Speaker 1: explore with Pinterest. They really lean into the unique nature 549 00:28:46,680 --> 00:28:48,320 Speaker 1: of our platform where we do have people in that 550 00:28:48,440 --> 00:28:51,840 Speaker 1: lean forward mode looking to express our creativity. So I 551 00:28:51,840 --> 00:28:54,080 Speaker 1: think we have license to bring those kinds of experiences 552 00:28:54,080 --> 00:28:56,840 Speaker 1: to users. Shuffles is one example of that, and I 553 00:28:56,920 --> 00:28:58,880 Speaker 1: also say it's just one example of how we're cutting 554 00:28:58,920 --> 00:29:02,600 Speaker 1: through with gen Z. Even separate from Shuffles, our gen 555 00:29:02,720 --> 00:29:06,360 Speaker 1: Z user base has more than doubled since Q three 556 00:29:06,360 --> 00:29:09,640 Speaker 1: of nineteen, and for this quarter it was our fastest 557 00:29:09,680 --> 00:29:14,719 Speaker 1: growing demographic. So Pinterests is cutting through with gen Z users, 558 00:29:14,880 --> 00:29:16,240 Speaker 1: and I think for a lot of the reasons that 559 00:29:16,440 --> 00:29:19,760 Speaker 1: I shared already that it is a positive place. It's 560 00:29:19,840 --> 00:29:22,520 Speaker 1: a bit of an oasis in the world of social 561 00:29:22,520 --> 00:29:26,239 Speaker 1: media for free users, where uh, it's a it's a 562 00:29:26,280 --> 00:29:28,680 Speaker 1: smaller circle. It's a place where the who you know 563 00:29:28,760 --> 00:29:33,160 Speaker 1: collaborate with closer friends versus you know, having to worry 564 00:29:33,160 --> 00:29:35,880 Speaker 1: about being shouted down or these kinds of things. Uh. 565 00:29:35,920 --> 00:29:39,080 Speaker 1: It's just felt as a safer and more inspiring space 566 00:29:39,200 --> 00:29:42,560 Speaker 1: by many users. And so that's really resonating with gen Z, 567 00:29:42,680 --> 00:29:45,160 Speaker 1: and as we give them more and more tools like Shuffles, 568 00:29:45,680 --> 00:29:47,080 Speaker 1: we think there's a lot more we can do to 569 00:29:47,120 --> 00:29:49,880 Speaker 1: serve that as a great up and coming demographic. Alright, 570 00:29:50,040 --> 00:29:53,120 Speaker 1: pinterest CEO Bill already, Bill, thank you so much for 571 00:29:53,200 --> 00:29:57,200 Speaker 1: joining us as always created from you. Appreciate the extended conversation. 572 00:29:57,280 --> 00:29:59,320 Speaker 1: All right, coming up, getting a second look. A new 573 00:29:59,360 --> 00:30:02,080 Speaker 1: team is taking a crack and investigating Tether and whether 574 00:30:02,120 --> 00:30:06,080 Speaker 1: the stable coin executives committed a crime. That is next. 575 00:30:06,440 --> 00:30:25,760 Speaker 1: This is Bloomberg, a Justice Department probe into the stable 576 00:30:25,760 --> 00:30:28,040 Speaker 1: coin Tether is getting a fresh pair of eyes after 577 00:30:28,040 --> 00:30:31,400 Speaker 1: struggling to reach a conclusion. Joining us now our Bloomber 578 00:30:31,440 --> 00:30:34,880 Speaker 1: crypto reporter Matt Robinson And Matt, it's very unusual to 579 00:30:35,000 --> 00:30:38,440 Speaker 1: redirect an investigation like this. What exactly is the d 580 00:30:38,520 --> 00:30:42,480 Speaker 1: o J looking into? Right? So, the Justice Department has 581 00:30:42,520 --> 00:30:44,880 Speaker 1: long been looking into Tether the last few years about 582 00:30:45,200 --> 00:30:48,040 Speaker 1: a variety of its statements, for for instance, how much 583 00:30:48,280 --> 00:30:51,240 Speaker 1: money they have to back the stable coin, also to 584 00:30:51,400 --> 00:30:54,080 Speaker 1: what they told banks when they were transacting. So this 585 00:30:54,160 --> 00:31:01,160 Speaker 1: investigation started with Maine justin has moved to prosecutors in Manhattan. UM. 586 00:31:01,200 --> 00:31:03,200 Speaker 1: So they're looking to see if any sort of you know, 587 00:31:03,400 --> 00:31:06,400 Speaker 1: if there's bank fraud violations. Uh, you know, given the 588 00:31:06,480 --> 00:31:11,360 Speaker 1: size of um Tether, it's the third largest cryptocurrency beyond 589 00:31:11,600 --> 00:31:15,320 Speaker 1: excuse me, behind bitcoin and Ethereum they want to make 590 00:31:15,320 --> 00:31:17,760 Speaker 1: sure that those uh, you know, what they've told the 591 00:31:17,760 --> 00:31:22,719 Speaker 1: banks and is accurate. Remind us what is tether. This 592 00:31:22,800 --> 00:31:26,960 Speaker 1: is the third largest cryptocurrency. The creators have said it's 593 00:31:27,040 --> 00:31:30,640 Speaker 1: backed by the US dollar. What does it actually mean 594 00:31:30,680 --> 00:31:33,920 Speaker 1: to the crypto ecosystem. It's it's very important. It's very 595 00:31:33,960 --> 00:31:38,080 Speaker 1: unusual part of the excuse me, crypto ecosystem because it's 596 00:31:38,160 --> 00:31:40,360 Speaker 1: it's designed as a stable coin. It's it's like a 597 00:31:40,400 --> 00:31:44,680 Speaker 1: digital uh stand in for dollars. They get started. You know, 598 00:31:44,760 --> 00:31:47,280 Speaker 1: this was time in the industry where you know, there 599 00:31:47,320 --> 00:31:49,480 Speaker 1: wasn't a lot that was stable. They wanted to keep 600 00:31:49,640 --> 00:31:51,760 Speaker 1: your cash or you wanted to keep your dollars and 601 00:31:51,920 --> 00:31:55,000 Speaker 1: something that you know, I wasn't going to move, you know, 602 00:31:55,200 --> 00:31:59,080 Speaker 1: dramatically overnight. So it became just a crucial part of 603 00:31:59,240 --> 00:32:03,200 Speaker 1: the excuse me of the market because often folks, oftentimes 604 00:32:03,240 --> 00:32:06,120 Speaker 1: folks are going to be trading Bitcoin with Tether or 605 00:32:06,400 --> 00:32:09,280 Speaker 1: you know, ethereum and tether. And so it's grown to 606 00:32:09,360 --> 00:32:12,880 Speaker 1: almost seventy billion dollars um, you know, a massive fund 607 00:32:12,920 --> 00:32:16,520 Speaker 1: and and you know, the company has come into some 608 00:32:16,600 --> 00:32:20,520 Speaker 1: other regulatory probes from from other agencies. For instance, the 609 00:32:20,560 --> 00:32:24,600 Speaker 1: CFTC over the amount of money, the amount of cash 610 00:32:24,800 --> 00:32:29,400 Speaker 1: backing their stable coin. So it's an enormously important part 611 00:32:29,400 --> 00:32:32,520 Speaker 1: of the market and how it functions, um, you know, 612 00:32:32,560 --> 00:32:35,520 Speaker 1: with traders being able to use it to to make 613 00:32:35,560 --> 00:32:39,880 Speaker 1: speculative bets on on other cryptocurrencies. What's the likelihood map 614 00:32:39,960 --> 00:32:43,840 Speaker 1: that criminal charges actually happened here? Uh, you know that's 615 00:32:43,880 --> 00:32:47,240 Speaker 1: that's obviously up for d o J to decide. Um. 616 00:32:47,280 --> 00:32:49,800 Speaker 1: You know that, as we reported, the tether is looking 617 00:32:49,800 --> 00:32:54,520 Speaker 1: for declination letters, which is basically the Justice Department saying 618 00:32:54,600 --> 00:32:56,920 Speaker 1: you know, we we've looked at this and now you 619 00:32:56,960 --> 00:33:00,760 Speaker 1: know we're we're declining to pursue any charges. So that 620 00:33:00,760 --> 00:33:03,480 Speaker 1: that's you know, that remains to be seen, all right, 621 00:33:03,560 --> 00:33:06,240 Speaker 1: Bloomberg's Matt Robinson, Matt, thank you so much for that. 622 00:33:06,880 --> 00:33:09,400 Speaker 1: We will follow your reporting to stay up to date 623 00:33:09,440 --> 00:33:21,360 Speaker 1: on this investigation. Workers at a fox Con production plant 624 00:33:21,360 --> 00:33:24,600 Speaker 1: in central China, the largest iPhone factory in the world, 625 00:33:24,920 --> 00:33:28,280 Speaker 1: are walking off the job, hitching rides and dipping into 626 00:33:28,320 --> 00:33:31,760 Speaker 1: their savings to escape another COVID lockdown. Bloomberg's Debby Woo 627 00:33:32,200 --> 00:33:34,680 Speaker 1: has all of the details for us. Debbie, in your story, 628 00:33:34,720 --> 00:33:38,240 Speaker 1: you profile woman named Dong Wan Wan who is literally 629 00:33:38,280 --> 00:33:41,960 Speaker 1: walked I believe twenty five miles um and quit the 630 00:33:42,080 --> 00:33:44,400 Speaker 1: job to get out of there. Tell us more about 631 00:33:44,400 --> 00:33:47,840 Speaker 1: what is happening. So what is happening is COVID recently 632 00:33:47,920 --> 00:33:52,760 Speaker 1: yells right through well Fox comes up two people's site 633 00:33:52,800 --> 00:33:57,440 Speaker 1: in central China that makes the world's most iPhones. And 634 00:33:57,920 --> 00:34:00,920 Speaker 1: after lot also following a lot, the we have seen 635 00:34:00,920 --> 00:34:05,200 Speaker 1: no trash piling up in dormitories nearly campused. And also 636 00:34:05,280 --> 00:34:08,960 Speaker 1: that the people who got into a quarantine sometimes are 637 00:34:09,040 --> 00:34:13,040 Speaker 1: not getting uh meals meals in time, and then uh 638 00:34:13,280 --> 00:34:16,000 Speaker 1: sometimes they are just uh sort of getting only a 639 00:34:16,080 --> 00:34:20,719 Speaker 1: bread for meals. So because of all these issues, uh, 640 00:34:20,800 --> 00:34:23,640 Speaker 1: some workers have decided that they just want to quit 641 00:34:23,800 --> 00:34:26,160 Speaker 1: and go home. And because of a lack of our 642 00:34:26,200 --> 00:34:31,680 Speaker 1: transportation and also strict COVID controls, let's still uh in 643 00:34:31,760 --> 00:34:35,960 Speaker 1: place in the places at home. So what workers have 644 00:34:36,040 --> 00:34:38,799 Speaker 1: to walk back to where they come from. So in 645 00:34:38,840 --> 00:34:43,400 Speaker 1: the story that we reported, uh list twenty year old 646 00:34:43,400 --> 00:34:46,920 Speaker 1: have to walk about nine hours to get home. You know, 647 00:34:47,080 --> 00:34:50,880 Speaker 1: the rigid you know, sometimes brutal hours at a fox 648 00:34:50,920 --> 00:34:54,799 Speaker 1: can plant has been well documented documented. What is Fox 649 00:34:54,880 --> 00:34:57,960 Speaker 1: can't doing to get around this and is it impacting 650 00:34:58,360 --> 00:35:02,480 Speaker 1: supply at all because this slowd own iPhone production, So 651 00:35:02,960 --> 00:35:05,680 Speaker 1: what is happening in South fox Song is raising wages 652 00:35:05,800 --> 00:35:08,800 Speaker 1: by almost a third, and then it is also trying 653 00:35:08,840 --> 00:35:12,799 Speaker 1: to get the backup capacity elsewhere online to make sure 654 00:35:12,880 --> 00:35:17,200 Speaker 1: that the supply impact of supply will be minimized. And 655 00:35:17,320 --> 00:35:20,719 Speaker 1: at the same time, UH we have reported previously that 656 00:35:20,840 --> 00:35:26,080 Speaker 1: the UH, due to weakeningment, Apple is actually canceling the 657 00:35:26,560 --> 00:35:30,040 Speaker 1: UH ideas for any more orders for our new iPhones 658 00:35:30,160 --> 00:35:34,600 Speaker 1: this year. So this is like a given economic headwinds 659 00:35:35,760 --> 00:35:40,160 Speaker 1: on the one hand, and also giving UH the number 660 00:35:40,200 --> 00:35:43,879 Speaker 1: of workers require, it's probably not as many I think 661 00:35:43,960 --> 00:35:46,840 Speaker 1: it is. We still need weight kind more time to 662 00:35:47,160 --> 00:35:50,120 Speaker 1: figure out what exactly the impact is coming out of 663 00:35:50,120 --> 00:35:53,960 Speaker 1: this COVID UH incident in Central China and talk to 664 00:35:54,040 --> 00:35:56,520 Speaker 1: us a little bit about how this fits into how 665 00:35:56,719 --> 00:36:00,960 Speaker 1: President she has been handling COVID more recently against the 666 00:36:01,000 --> 00:36:04,479 Speaker 1: backdrop of what's happening with the Chinese Communist Party. So 667 00:36:05,320 --> 00:36:10,080 Speaker 1: after the party congress originally previously, people may be expecting 668 00:36:10,120 --> 00:36:12,839 Speaker 1: that there may be indication that China can come out 669 00:36:12,880 --> 00:36:16,520 Speaker 1: of UH. THEREI COVID and then no focus more on 670 00:36:16,880 --> 00:36:21,719 Speaker 1: economic growth, but clearly it's not happening. So for instance, 671 00:36:22,120 --> 00:36:26,399 Speaker 1: in uh Hanan or in a Zeno where are foxhansa 672 00:36:26,600 --> 00:36:31,239 Speaker 1: iPhone campus is located in the local leaders there are 673 00:36:31,280 --> 00:36:35,120 Speaker 1: still uh saying that they need to a prioritize zero 674 00:36:35,239 --> 00:36:40,399 Speaker 1: COVID and then not to implement COVID combating measures. So 675 00:36:40,480 --> 00:36:42,920 Speaker 1: I think it is going to be a bit difficult 676 00:36:42,960 --> 00:36:45,360 Speaker 1: and challenging for what China ready to come out of 677 00:36:45,640 --> 00:36:48,200 Speaker 1: zero COVID, And then I think it's hard to predict 678 00:36:48,480 --> 00:36:53,680 Speaker 1: when list might be a completely uh go away. All right, 679 00:36:53,960 --> 00:36:57,720 Speaker 1: Uh well, your story definitely worth a read, reading about 680 00:36:58,040 --> 00:37:00,560 Speaker 1: Don Juan Wan and many more that we will for 681 00:37:00,600 --> 00:37:03,319 Speaker 1: Bloomberg News. Thank you, and that does it for this 682 00:37:03,480 --> 00:37:06,360 Speaker 1: edition of Bloomberg Technology. Make sure you tune in Tuesday 683 00:37:06,400 --> 00:37:09,799 Speaker 1: our conversation which uber CEO Dara CAUs Rashah after the 684 00:37:09,800 --> 00:37:12,640 Speaker 1: company reports results. You don't want to miss that. And 685 00:37:12,760 --> 00:37:15,759 Speaker 1: of course check out our podcast wherever you get your podcasts. 686 00:37:15,760 --> 00:37:18,840 Speaker 1: I'm Emily Changing, San Francisco. This is Bloomberg