1 00:00:02,720 --> 00:00:10,559 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,600 --> 00:00:14,560 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:14,600 --> 00:00:17,880 Speaker 1: Eastern on Apple Coarclay and Android Auto with the Bloomberg 4 00:00:17,920 --> 00:00:21,040 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,360 --> 00:00:23,600 Speaker 1: or watch us live on YouTube. 6 00:00:23,880 --> 00:00:26,720 Speaker 2: I'm gonna start with the Meta news because it looks 7 00:00:26,720 --> 00:00:31,000 Speaker 2: like mister Zuckerberg really is putting himself personally on the 8 00:00:31,080 --> 00:00:33,280 Speaker 2: line here for some of their AI businesses. Ed Lodo 9 00:00:33,360 --> 00:00:37,360 Speaker 2: joins us Bloomberg b Tech co host. He's out there 10 00:00:37,400 --> 00:00:39,720 Speaker 2: in San Francisco where I think they have some technology people. 11 00:00:40,360 --> 00:00:43,440 Speaker 2: And what's the news coming out of Meta today? Can 12 00:00:43,479 --> 00:00:44,800 Speaker 2: you tell us what that is and kind of if 13 00:00:44,800 --> 00:00:45,559 Speaker 2: it's important or not. 14 00:00:46,479 --> 00:00:50,479 Speaker 3: Yeah, our reporting is very detailed. Which site sources that 15 00:00:51,040 --> 00:00:54,320 Speaker 3: Mark Zuckerberg is getting much more hands on on the 16 00:00:54,320 --> 00:00:59,639 Speaker 3: minut sha of generations generation model releases, AI model releases. 17 00:01:00,240 --> 00:01:03,360 Speaker 3: But the bigger picture is that Meta, which has kind 18 00:01:03,400 --> 00:01:09,960 Speaker 3: of been the stulwork of open source AI models, is 19 00:01:10,040 --> 00:01:13,760 Speaker 3: realizing that it may not be the viable path. So 20 00:01:13,840 --> 00:01:16,200 Speaker 3: there is a specific model that they're due to release 21 00:01:16,240 --> 00:01:19,280 Speaker 3: called Avocado, and at one time that had been due 22 00:01:19,319 --> 00:01:22,240 Speaker 3: to be an open source model. What we're reporting citing sources, 23 00:01:22,319 --> 00:01:26,080 Speaker 3: it's now likely to be a closed source model. Alexander Wang, 24 00:01:26,120 --> 00:01:28,160 Speaker 3: who leads this kind of AI lab team that marks 25 00:01:28,200 --> 00:01:31,319 Speaker 3: Zakovolk's put together, is a great advocate for closed source. 26 00:01:31,640 --> 00:01:34,280 Speaker 3: And what you need to know is that in the 27 00:01:34,319 --> 00:01:37,200 Speaker 3: earlier days, when models were much smaller and Meta kind 28 00:01:37,240 --> 00:01:40,679 Speaker 3: of wanted workshopping among industry and academics. 29 00:01:40,240 --> 00:01:41,880 Speaker 4: Worldwide, it worked. 30 00:01:42,200 --> 00:01:44,480 Speaker 3: But the problem now is that these models are so 31 00:01:44,680 --> 00:01:48,280 Speaker 3: big the resources required to utilize them are so severe 32 00:01:48,760 --> 00:01:51,480 Speaker 3: that it's just not realistic to have an open source 33 00:01:51,520 --> 00:01:56,520 Speaker 3: policy universally. Because you need money and private industry has money. 34 00:01:56,600 --> 00:01:58,360 Speaker 3: You have to make it a kind of for profit 35 00:01:58,400 --> 00:02:01,240 Speaker 3: exercise in order for the economics of training and then 36 00:02:01,280 --> 00:02:04,440 Speaker 3: running the models to work. And that's what our story details. 37 00:02:04,280 --> 00:02:07,240 Speaker 3: It's really is a must read. What I would say 38 00:02:07,280 --> 00:02:09,000 Speaker 3: is that Meta in its earning school in July did 39 00:02:09,080 --> 00:02:11,000 Speaker 3: kind of tell us this was coming. They're committed to 40 00:02:11,000 --> 00:02:12,600 Speaker 3: open source, but they're going to have to start looking 41 00:02:12,639 --> 00:02:15,680 Speaker 3: at the reality of what it takes to build and 42 00:02:15,720 --> 00:02:17,440 Speaker 3: train a model and then put it out into the 43 00:02:17,440 --> 00:02:20,200 Speaker 3: real world in terms of who can use it all. 44 00:02:20,280 --> 00:02:21,440 Speaker 5: Right, ed, you've been very busy. 45 00:02:21,480 --> 00:02:23,680 Speaker 6: I know you've been writing about SpaceX as well, so 46 00:02:23,760 --> 00:02:25,000 Speaker 6: I'm going to ask you about that. 47 00:02:25,200 --> 00:02:27,120 Speaker 5: Tell us about this IPO. 48 00:02:27,440 --> 00:02:29,520 Speaker 6: I mean, it seems like it's going to be trying 49 00:02:29,560 --> 00:02:32,000 Speaker 6: to rival the Aramco IPO that we saw a few 50 00:02:32,080 --> 00:02:34,760 Speaker 6: years ago one point five trill and evaluation. What's the 51 00:02:34,800 --> 00:02:36,280 Speaker 6: single biggest justification for that? 52 00:02:37,040 --> 00:02:39,240 Speaker 4: Yeah, I mean, we're reporting that it's happening. 53 00:02:39,400 --> 00:02:39,560 Speaker 7: You know. 54 00:02:39,639 --> 00:02:42,440 Speaker 3: My understanding from sources is the work as well underway. 55 00:02:42,560 --> 00:02:45,600 Speaker 3: They're speaking to the bankers, they've told the investors, they're 56 00:02:45,680 --> 00:02:48,080 Speaker 3: hiring for the internal roles that you need when you 57 00:02:48,160 --> 00:02:50,440 Speaker 3: do a big IPO, and the targets the middle of 58 00:02:50,520 --> 00:02:51,040 Speaker 3: next year. 59 00:02:51,440 --> 00:02:51,600 Speaker 4: You know. 60 00:02:51,680 --> 00:02:54,040 Speaker 3: The valuation is what everyone's talking about. One point five 61 00:02:54,080 --> 00:02:57,920 Speaker 3: trillion dollars. We confirmed that the company's latest valuation in 62 00:02:57,960 --> 00:03:01,000 Speaker 3: the private markets through a tender settled at more than 63 00:03:01,040 --> 00:03:05,120 Speaker 3: eight hundred billion, So that is kind of like a 64 00:03:05,160 --> 00:03:08,120 Speaker 3: stepping stone to an IPO. But what I understand is 65 00:03:08,160 --> 00:03:10,320 Speaker 3: they need some cash for a specific project. We can 66 00:03:10,320 --> 00:03:12,400 Speaker 3: get into it if you want. That cash is probably 67 00:03:12,440 --> 00:03:15,600 Speaker 3: well north of thirty billion dollars, maybe forty billion dollars, 68 00:03:16,680 --> 00:03:19,680 Speaker 3: and that would exceed what Aramco raised in twenty nineteen, 69 00:03:19,720 --> 00:03:22,160 Speaker 3: So from a dollar raised perspective, it would make it 70 00:03:22,160 --> 00:03:24,680 Speaker 3: the biggest IPO of all time, which is exciting. 71 00:03:24,639 --> 00:03:27,560 Speaker 2: It surely is. I mean, particularly for the bankers on that. 72 00:03:27,800 --> 00:03:30,480 Speaker 2: What's the total valuation? Do we know the total valuation 73 00:03:30,960 --> 00:03:34,040 Speaker 2: of SpaceX these days, because I've heard some just monster numbers. 74 00:03:34,639 --> 00:03:37,600 Speaker 3: So Elon Musk has been pushing back on X recently 75 00:03:37,640 --> 00:03:42,040 Speaker 3: about reports of SpaceX's valuation. What we have reported, and 76 00:03:42,080 --> 00:03:45,840 Speaker 3: this is we stand by that reporting, of course, is 77 00:03:45,960 --> 00:03:49,840 Speaker 3: SpaceX has gone through a tender, a secondary offering. That 78 00:03:49,960 --> 00:03:54,920 Speaker 3: is a mechanism where the company allows existing employees and 79 00:03:55,120 --> 00:03:58,520 Speaker 3: some insiders early investors to sell the shares they already have. 80 00:03:59,280 --> 00:04:02,120 Speaker 3: As part of that, SpaceX actually buys back some stock, 81 00:04:02,280 --> 00:04:05,120 Speaker 3: but they don't raise any new equity, They don't raise 82 00:04:05,200 --> 00:04:06,520 Speaker 3: any funds for. 83 00:04:06,680 --> 00:04:07,760 Speaker 4: The company's treasury. 84 00:04:08,080 --> 00:04:10,880 Speaker 3: But you still need a price for those shares, and 85 00:04:10,920 --> 00:04:14,280 Speaker 3: that determines the valuation. That price was settled at four 86 00:04:14,360 --> 00:04:16,719 Speaker 3: hundred and twenty one dollars a share, and that gives 87 00:04:16,720 --> 00:04:19,520 Speaker 3: evaluation north of eight hundred billion dollars. 88 00:04:20,240 --> 00:04:21,080 Speaker 4: And that's settled. 89 00:04:21,320 --> 00:04:26,560 Speaker 3: But again SpaceX does this twice a year typically, you know, tenders, buybacks, 90 00:04:26,560 --> 00:04:29,800 Speaker 3: et cetera. But in this case, this would be the 91 00:04:29,839 --> 00:04:32,239 Speaker 3: big one to kind of get fair market value ahead 92 00:04:32,240 --> 00:04:32,760 Speaker 3: of an IPO. 93 00:04:34,279 --> 00:04:37,400 Speaker 7: Stay with us. More from Bloomberg Intelligence coming up after this. 94 00:04:41,000 --> 00:04:44,719 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 95 00:04:44,800 --> 00:04:47,840 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 96 00:04:47,880 --> 00:04:51,200 Speaker 1: Auto with the Bloomberg Business app. Listen on demand wherever 97 00:04:51,240 --> 00:04:54,360 Speaker 1: you get your podcasts, or watch us live on YouTube. 98 00:04:55,040 --> 00:04:55,919 Speaker 7: We had a client earlier. 99 00:04:56,040 --> 00:04:59,560 Speaker 2: Christine was referencing some funuciary trust is referenced on I'm 100 00:04:59,600 --> 00:05:02,640 Speaker 2: waiting for the BI survey on AI and like what 101 00:05:02,800 --> 00:05:05,640 Speaker 2: b I SERVI on AI? Matt Blocksham Joints is he's 102 00:05:05,640 --> 00:05:08,720 Speaker 2: a tech analyst for Bloomberg Intelligence. Hey, Matt, talk to 103 00:05:08,760 --> 00:05:11,279 Speaker 2: us about this BI survey on AI. What is it 104 00:05:11,320 --> 00:05:12,479 Speaker 2: and what's what's it telling you? 105 00:05:13,720 --> 00:05:13,960 Speaker 8: Yeah? 106 00:05:14,000 --> 00:05:14,200 Speaker 6: Sure. 107 00:05:14,279 --> 00:05:18,479 Speaker 8: So this was a big survey we did, polling the 108 00:05:18,640 --> 00:05:22,400 Speaker 8: views of six hundred and four C suite executives across 109 00:05:22,400 --> 00:05:25,440 Speaker 8: the range of industries across the world, really kind of 110 00:05:25,920 --> 00:05:27,960 Speaker 8: get trying to get a sense on how corporates are 111 00:05:27,960 --> 00:05:31,800 Speaker 8: assessing the current AI situation and what they think is 112 00:05:31,839 --> 00:05:34,600 Speaker 8: going to do to their businesses over the next kind 113 00:05:34,600 --> 00:05:36,440 Speaker 8: of two to three years. So we kind of looked 114 00:05:36,440 --> 00:05:40,000 Speaker 8: at the motivations for AI investment, what it could do 115 00:05:40,040 --> 00:05:43,400 Speaker 8: to headcount, what they're expecting in terms of revenue and 116 00:05:43,480 --> 00:05:45,599 Speaker 8: profit uptick, and you we had some kind of interesting 117 00:05:47,360 --> 00:05:51,640 Speaker 8: results out the survey. You know, not surprisingly, perhaps AI 118 00:05:51,839 --> 00:05:54,120 Speaker 8: is very much at the top of the c suite agenda. 119 00:05:55,240 --> 00:05:59,400 Speaker 8: Something like thirty six percent of those polls said it 120 00:05:59,440 --> 00:06:02,360 Speaker 8: was their top strategic priority. In another forty seven percent 121 00:06:02,520 --> 00:06:08,040 Speaker 8: said it was within the top three strategic objectives for them. 122 00:06:08,320 --> 00:06:12,400 Speaker 8: When we looked and asked about the main objectives behind 123 00:06:12,800 --> 00:06:18,880 Speaker 8: their AI strategies, what came out top was improving operational efficiency, 124 00:06:19,360 --> 00:06:23,160 Speaker 8: which was number one with forty seven percent of the respondents, 125 00:06:23,320 --> 00:06:26,839 Speaker 8: and in second place was boosting a revenue at twenty 126 00:06:26,880 --> 00:06:30,919 Speaker 8: one percent. Interestingly, headcount cuts were quite low down the 127 00:06:30,920 --> 00:06:34,800 Speaker 8: packing order. Only thirteen percent of respondents put that as 128 00:06:34,839 --> 00:06:38,720 Speaker 8: their top priority, and actually it was the highest ranked 129 00:06:38,720 --> 00:06:41,800 Speaker 8: in terms of the least priority. So I think it's 130 00:06:41,800 --> 00:06:46,680 Speaker 8: interesting that companies are looking to boost productivity, but they're 131 00:06:46,680 --> 00:06:51,000 Speaker 8: not afraid to make investments both in technology and headcount 132 00:06:51,360 --> 00:06:53,840 Speaker 8: in the near term to kind of release those opportunities. 133 00:06:53,839 --> 00:06:58,520 Speaker 8: And actually on a three year view, sixty two percent 134 00:06:58,640 --> 00:07:02,880 Speaker 8: of respondents they expect AI to lead to an increase 135 00:07:03,360 --> 00:07:06,080 Speaker 8: in headcount over the next three years, an increase, not 136 00:07:06,120 --> 00:07:08,680 Speaker 8: a decrease, and the average increase they're looking at is 137 00:07:08,720 --> 00:07:12,600 Speaker 8: about four percent. So that kind of flies in the 138 00:07:12,600 --> 00:07:13,760 Speaker 8: face of a little bit of you know, a lot of 139 00:07:13,800 --> 00:07:16,440 Speaker 8: the kind of headlines we see about job cuts. I 140 00:07:16,480 --> 00:07:21,840 Speaker 8: think overall, corporate see the need to invest more in staff, 141 00:07:21,880 --> 00:07:25,320 Speaker 8: you know, to roll out their AI strategies in the 142 00:07:25,360 --> 00:07:26,360 Speaker 8: coming years. Yeah. 143 00:07:26,480 --> 00:07:28,880 Speaker 6: Yeah, Well, Matt, you mentioned thirty six percent of c 144 00:07:28,960 --> 00:07:31,760 Speaker 6: suites now rank AA as their top priority. That number 145 00:07:31,760 --> 00:07:34,640 Speaker 6: actually strikes me as a little low. I would have 146 00:07:34,640 --> 00:07:37,080 Speaker 6: thought it would be at least half of the people's survey. 147 00:07:37,120 --> 00:07:39,080 Speaker 6: But what do you think, is that something that's just 148 00:07:39,400 --> 00:07:42,400 Speaker 6: set to grow in future surveys as really kind of 149 00:07:42,440 --> 00:07:46,320 Speaker 6: AI becomes central to a lot of companies workflows these days. 150 00:07:47,600 --> 00:07:49,440 Speaker 8: Yeah, I think so. I mean, like, you know, obviously, 151 00:07:49,720 --> 00:07:51,600 Speaker 8: if you add the forty seven percent that said it's 152 00:07:51,640 --> 00:07:53,800 Speaker 8: in the top three, I mean, you know, an overall 153 00:07:53,800 --> 00:07:57,720 Speaker 8: top three priority gives you the kind of vast majority 154 00:07:57,760 --> 00:08:01,200 Speaker 8: of the respondents. So obviously companies do have to wrestle 155 00:08:01,280 --> 00:08:03,640 Speaker 8: with lots of other issues too. You know that there 156 00:08:03,720 --> 00:08:06,840 Speaker 8: is going on in the world beyond AI, and obviously 157 00:08:07,000 --> 00:08:11,240 Speaker 8: trade policy is another big thing that's probably on the 158 00:08:11,600 --> 00:08:14,640 Speaker 8: radar for a lot of these companies too. So yeah, 159 00:08:14,720 --> 00:08:17,240 Speaker 8: you know, maybe it will kind of inch up, but 160 00:08:17,320 --> 00:08:20,000 Speaker 8: I think you've given that aggregate, you know, age percent 161 00:08:20,040 --> 00:08:24,480 Speaker 8: plus in the top three probably what you'd expect to see. 162 00:08:25,080 --> 00:08:27,160 Speaker 2: Matthew, how about return on investment here? That's kind of 163 00:08:27,160 --> 00:08:29,480 Speaker 2: what the streets starting to ask for now. We know 164 00:08:29,520 --> 00:08:33,040 Speaker 2: these companies can spend big money on AI, but what's 165 00:08:33,080 --> 00:08:34,559 Speaker 2: the return for shareholders? 166 00:08:35,960 --> 00:08:38,320 Speaker 8: Yeah, I think that's still very opaque. And actually, when 167 00:08:38,960 --> 00:08:44,360 Speaker 8: we asked the respondents to flag the biggest roadblocks they 168 00:08:44,360 --> 00:08:50,600 Speaker 8: could see to AI deployment, the investment needed in AI, 169 00:08:51,600 --> 00:08:54,880 Speaker 8: and the question marks around the return on investment, we're 170 00:08:54,920 --> 00:08:57,840 Speaker 8: definitely up there amongst some of the most important concerns 171 00:08:58,679 --> 00:09:03,360 Speaker 8: that respondents have, along side data security and clean data. 172 00:09:03,880 --> 00:09:07,480 Speaker 8: We didn't ask much of the most specific ROI expectations. 173 00:09:07,600 --> 00:09:09,240 Speaker 8: We just kind of get the sensor. It's a bit 174 00:09:09,280 --> 00:09:13,960 Speaker 8: too early to get an accurate read on that. I 175 00:09:14,000 --> 00:09:17,120 Speaker 8: think most companies are still kind of at a relatively 176 00:09:17,280 --> 00:09:19,760 Speaker 8: early stage of their AI trials, you know, lots of 177 00:09:19,760 --> 00:09:22,640 Speaker 8: them have moved out of the kind of testing lms. 178 00:09:22,679 --> 00:09:25,160 Speaker 8: They're into pilot phases, some of them are even moving 179 00:09:25,160 --> 00:09:27,720 Speaker 8: into scale deployment. I think it's fair to say a 180 00:09:27,720 --> 00:09:29,800 Speaker 8: lot of them are not really quite sure yet what 181 00:09:29,880 --> 00:09:32,199 Speaker 8: the return is going to be and how quick it's 182 00:09:32,240 --> 00:09:34,959 Speaker 8: going to come. And obviously it's kind of a bigger 183 00:09:35,400 --> 00:09:38,840 Speaker 8: issue for the wider tech sector. And you mentioned Oracle 184 00:09:38,920 --> 00:09:41,560 Speaker 8: as a kind of barometer for the kind of broader 185 00:09:42,000 --> 00:09:45,440 Speaker 8: pulse on AI, and I think the twenty twenty six 186 00:09:45,520 --> 00:09:47,280 Speaker 8: is going to be a really crucial year for kind 187 00:09:47,320 --> 00:09:50,920 Speaker 8: of what corporates make of the midterm ROI. And you know, 188 00:09:51,000 --> 00:09:53,480 Speaker 8: if they don't see a big ROI, then that's probably 189 00:09:53,520 --> 00:09:56,760 Speaker 8: going to slow the pace of revenue growth and that's 190 00:09:56,800 --> 00:09:58,439 Speaker 8: going to have a knock on effect to the levels 191 00:09:58,440 --> 00:10:01,520 Speaker 8: of investment we're seeing. But I likes of Oracle and 192 00:10:01,679 --> 00:10:03,439 Speaker 8: open eye on the revenues that bringing in. 193 00:10:04,480 --> 00:10:07,560 Speaker 7: Stay with us more from Bloomberg Intelligence coming up after this. 194 00:10:11,520 --> 00:10:15,200 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 195 00:10:15,280 --> 00:10:18,679 Speaker 1: weekdays at ten am Eastern on Applecarplay and Android Auto 196 00:10:18,760 --> 00:10:21,840 Speaker 1: with the Bloomberg Business app. Listen on demand wherever you 197 00:10:21,880 --> 00:10:24,880 Speaker 1: get your podcasts or watch us live on YouTube. 198 00:10:25,600 --> 00:10:26,360 Speaker 7: Let's switch gears. 199 00:10:26,360 --> 00:10:29,160 Speaker 2: Going back to earnings here, earnings continue to kind of 200 00:10:29,160 --> 00:10:31,800 Speaker 2: trickle out a little bit, particularly from the retail oriented 201 00:10:31,960 --> 00:10:34,520 Speaker 2: companies that packet foods companies. One of them is Chewy. 202 00:10:34,679 --> 00:10:37,880 Speaker 2: Let's break that down with Diana sat Open. Yes, she 203 00:10:37,920 --> 00:10:40,640 Speaker 2: is an analyst covering the retail space consumer product space 204 00:10:40,679 --> 00:10:42,160 Speaker 2: for Bloomberg Intelligence. 205 00:10:42,760 --> 00:10:44,440 Speaker 7: What are good friends at Chewy dot com doing? 206 00:10:45,120 --> 00:10:46,720 Speaker 5: They're doing fairly well. 207 00:10:47,640 --> 00:10:52,640 Speaker 9: You know, they actually reported sales and profitability that beat 208 00:10:52,720 --> 00:10:57,959 Speaker 9: analysts expectations, you know, for their outlook, it seems that 209 00:10:58,000 --> 00:11:01,959 Speaker 9: they're a little bit conservative that actually, you know, level 210 00:11:02,040 --> 00:11:04,880 Speaker 9: up some of the gains earlier this morning for the stock. 211 00:11:05,440 --> 00:11:08,480 Speaker 9: But again it seems that there's a lot of tailwinds 212 00:11:08,520 --> 00:11:09,160 Speaker 9: going forward. 213 00:11:09,640 --> 00:11:14,160 Speaker 6: Yeah, what's reaving that more conservative outlook that you mentioned, Diana, 214 00:11:14,280 --> 00:11:17,640 Speaker 6: Is it something related to you concerns about consumer demand 215 00:11:17,679 --> 00:11:18,280 Speaker 6: moving forward? 216 00:11:18,559 --> 00:11:20,120 Speaker 5: That is absolutely the case. 217 00:11:20,120 --> 00:11:27,640 Speaker 9: They're seeing household formation, which is adoption versus surrendering a 218 00:11:27,640 --> 00:11:31,200 Speaker 9: little bit subdued compared to historical averages, and they think 219 00:11:31,240 --> 00:11:34,720 Speaker 9: that that's going to overflow into twenty twenty six. 220 00:11:35,040 --> 00:11:37,080 Speaker 5: We're not necessarily agreeing with that. 221 00:11:37,240 --> 00:11:39,680 Speaker 9: We think at we're a little bit more optimistic in 222 00:11:39,760 --> 00:11:43,680 Speaker 9: terms of, you know, the pace of adoptions going forward. 223 00:11:43,800 --> 00:11:45,960 Speaker 9: So this is going to make the industry a little 224 00:11:46,000 --> 00:11:46,760 Speaker 9: bit more interesting. 225 00:11:48,520 --> 00:11:50,960 Speaker 2: This is it people recall definitely one of the pandemic 226 00:11:51,040 --> 00:11:53,880 Speaker 2: stocks that just surged to a high of at one 227 00:11:53,920 --> 00:11:57,320 Speaker 2: hundred and eighteen hundred nineteen dollars a share back in 228 00:11:57,520 --> 00:11:59,560 Speaker 2: early twenty twenty one and then came down to a 229 00:11:59,559 --> 00:12:02,679 Speaker 2: more normal level here. So going forward, what's the growth 230 00:12:02,800 --> 00:12:05,960 Speaker 2: drivers for Chewy? Is it taking share from the mom 231 00:12:06,000 --> 00:12:10,079 Speaker 2: and pop pet stores, is it we're just macro. 232 00:12:09,920 --> 00:12:12,240 Speaker 7: Stuff, household formation and things like that. 233 00:12:12,440 --> 00:12:15,439 Speaker 9: Well, there's gonna be a couple of things. They're focusing 234 00:12:15,559 --> 00:12:20,080 Speaker 9: on verticals besides merchandise, which is you know, they're doing 235 00:12:20,120 --> 00:12:23,760 Speaker 9: a lot of bad care. They're expanding into that. They 236 00:12:23,800 --> 00:12:28,960 Speaker 9: are currently have fourteen buildings on that they're expanding into 237 00:12:29,040 --> 00:12:32,440 Speaker 9: eighteen by the end of the year. So you know, 238 00:12:32,559 --> 00:12:37,360 Speaker 9: you have healthcare, you have sponsor ads in the website, 239 00:12:37,520 --> 00:12:41,280 Speaker 9: you have you know, the membership program, you have a 240 00:12:41,440 --> 00:12:45,120 Speaker 9: Chewy Plus. So all of those things were probably going 241 00:12:45,160 --> 00:12:50,240 Speaker 9: to be teilwinds for the company going forward. They're focusing 242 00:12:50,320 --> 00:12:54,840 Speaker 9: on like gaining mid to high single digit sales growth 243 00:12:54,920 --> 00:12:57,960 Speaker 9: over the next few years, which is I think it's 244 00:12:58,040 --> 00:13:01,960 Speaker 9: a normal forecast, but right now they're you know, growing 245 00:13:02,000 --> 00:13:03,920 Speaker 9: two times the size of the industry. 246 00:13:04,000 --> 00:13:06,040 Speaker 5: So yeah, it's interesting. 247 00:13:06,280 --> 00:13:08,520 Speaker 6: Is this a trend that you're seeing moving forward for 248 00:13:08,720 --> 00:13:11,840 Speaker 6: a lot of these kind of consumer based companies shifting 249 00:13:12,120 --> 00:13:14,880 Speaker 6: back a little bit to that in store sort of 250 00:13:14,920 --> 00:13:17,200 Speaker 6: experience because that seems to be a strategy that's worked 251 00:13:17,240 --> 00:13:19,960 Speaker 6: for other retailers outside of the space as well. 252 00:13:20,240 --> 00:13:20,480 Speaker 3: Yes. 253 00:13:20,760 --> 00:13:25,520 Speaker 9: So, you know, the pet industry, it's very sticky in 254 00:13:25,600 --> 00:13:31,319 Speaker 9: terms of demand. So once these companies get the pet 255 00:13:31,400 --> 00:13:34,920 Speaker 9: parent at the start of the you know, pet ownership, 256 00:13:34,920 --> 00:13:36,520 Speaker 9: they are going to have them for the rest of 257 00:13:36,559 --> 00:13:39,160 Speaker 9: the life of the pet. So you know, that is 258 00:13:39,200 --> 00:13:44,840 Speaker 9: obviously a very interesting dynamic compared to other retailers. But 259 00:13:44,880 --> 00:13:47,600 Speaker 9: in terms of, you know, the in store experience, this 260 00:13:47,720 --> 00:13:50,360 Speaker 9: is something that pet Co is also doing. They're leveraging 261 00:13:50,400 --> 00:13:56,040 Speaker 9: their fourteen hundred stores to also increase that traffic and penetration. 262 00:13:56,160 --> 00:13:58,040 Speaker 9: So definitely interesting times. 263 00:13:58,160 --> 00:14:04,080 Speaker 2: So Walmart, Amazon, how does Chewi compete against those players 264 00:14:04,080 --> 00:14:07,000 Speaker 2: that have big, big e commerce platforms. 265 00:14:06,640 --> 00:14:09,800 Speaker 5: So based off of them, they compete on price. 266 00:14:10,320 --> 00:14:12,120 Speaker 9: We a couple of years ago, we did a price 267 00:14:12,120 --> 00:14:15,880 Speaker 9: and study with Amazon, but Walmart and Chewy and other 268 00:14:15,960 --> 00:14:20,520 Speaker 9: retailers and Chewy and Amazon, we're pretty close in terms 269 00:14:20,560 --> 00:14:26,000 Speaker 9: of pricing where Amazon. Where Chewy beats Walmart and Amazon 270 00:14:26,120 --> 00:14:29,080 Speaker 9: is that their customer service. They you know, if you 271 00:14:29,160 --> 00:14:32,760 Speaker 9: call them and you have any questions about the food 272 00:14:32,880 --> 00:14:35,840 Speaker 9: that you're going to feed your dog, they're very knowledgeable 273 00:14:35,880 --> 00:14:38,160 Speaker 9: compared to you know, Amazon customer service. 274 00:14:38,200 --> 00:14:39,840 Speaker 5: So that is like the edge that they have. 275 00:14:40,920 --> 00:14:41,880 Speaker 6: Oh, very interesting. 276 00:14:42,000 --> 00:14:42,160 Speaker 10: Now. 277 00:14:42,240 --> 00:14:45,320 Speaker 6: Another bright spot, of course is autoship, right, which is basically, 278 00:14:45,320 --> 00:14:47,480 Speaker 6: if you're a pet owner, this is the thing that 279 00:14:47,560 --> 00:14:51,000 Speaker 6: you sign up for like my cat's food each month, 280 00:14:51,080 --> 00:14:53,080 Speaker 6: and then it just keeps charging me every month and 281 00:14:53,120 --> 00:14:56,200 Speaker 6: then I get surprice delivery of cat food that I 282 00:14:56,240 --> 00:14:59,760 Speaker 6: was not maybe expecting. But so obviously that's a bright 283 00:14:59,800 --> 00:15:04,520 Speaker 6: spot for Chewy. What's the outlook for that part of 284 00:15:04,560 --> 00:15:06,600 Speaker 6: the business. Is that something that could be sustainable? 285 00:15:06,920 --> 00:15:08,120 Speaker 5: Yes, absolutely so. 286 00:15:08,360 --> 00:15:12,080 Speaker 9: Right now, eighty four percent of their revenue comes from authorship, 287 00:15:12,400 --> 00:15:15,680 Speaker 9: which allows them to have a lot of scale and 288 00:15:15,760 --> 00:15:19,440 Speaker 9: allows them to be very profitable. So that is obviously 289 00:15:19,520 --> 00:15:22,280 Speaker 9: they have been growing since I started covering this company. 290 00:15:22,280 --> 00:15:24,320 Speaker 9: It was like in the seventies and now it's eighty four, 291 00:15:24,400 --> 00:15:26,600 Speaker 9: so it's probably going to get to the nineties soon. 292 00:15:26,840 --> 00:15:28,600 Speaker 6: It's very convenient because you sign up for it and 293 00:15:28,600 --> 00:15:29,600 Speaker 6: then you forget about it. 294 00:15:30,360 --> 00:15:33,480 Speaker 7: Stay with us. More from Bloomberg Intelligence coming up after this. 295 00:15:37,400 --> 00:15:41,120 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 296 00:15:41,200 --> 00:15:44,280 Speaker 1: weekdays at ten am easterne on Apple, Corplay and Android 297 00:15:44,280 --> 00:15:47,600 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 298 00:15:47,640 --> 00:15:50,760 Speaker 1: you get your podcasts, or watch us live on YouTube. 299 00:15:51,600 --> 00:15:56,360 Speaker 2: Krakerbo reported some numbers today, some disappointing guidance stufs kind 300 00:15:56,360 --> 00:15:57,800 Speaker 2: of flat on the day, but the stock has been 301 00:15:57,840 --> 00:15:59,920 Speaker 2: down pretty significantly this year. They had that whole low 302 00:16:00,120 --> 00:16:02,040 Speaker 2: go change that was a real problem for them, and 303 00:16:02,040 --> 00:16:03,600 Speaker 2: they're starting to see in their traffic. 304 00:16:03,280 --> 00:16:06,280 Speaker 7: Pretty big time. Stocks down about fifty percent year to date. 305 00:16:06,320 --> 00:16:09,080 Speaker 2: Michael Halen joints his senior restaurant and food service analyst 306 00:16:09,080 --> 00:16:13,200 Speaker 2: for Bloomberg Intelligence. Michael, what did the company report today 307 00:16:13,240 --> 00:16:16,640 Speaker 2: and what's management saying about kind of the future plans here? 308 00:16:18,360 --> 00:16:23,360 Speaker 10: Yeah, so, you know, guidance was cut and this was 309 00:16:23,400 --> 00:16:26,840 Speaker 10: their fiscal first quarter, so it's it's always tough to 310 00:16:27,280 --> 00:16:32,920 Speaker 10: have a guidance, revenue and ebitdoc cut after your first report, 311 00:16:33,000 --> 00:16:37,120 Speaker 10: but they hadn't seen a bounce yet in their traffic 312 00:16:37,200 --> 00:16:41,480 Speaker 10: post logo change controversy and everything that that went along 313 00:16:41,520 --> 00:16:45,360 Speaker 10: with it, you know. On the positive side, they said, 314 00:16:45,440 --> 00:16:48,480 Speaker 10: you know, traffic has now steadied at this down ten 315 00:16:48,560 --> 00:16:52,120 Speaker 10: to eleven percent level, which is translating into a you know, 316 00:16:52,160 --> 00:16:53,760 Speaker 10: a down a mid single digit. 317 00:16:54,160 --> 00:16:55,360 Speaker 7: Same store sales. 318 00:16:55,920 --> 00:16:59,560 Speaker 10: You know, So if you're if you're a glass half 319 00:16:59,600 --> 00:17:03,600 Speaker 10: full investor, you're saying that, you know, after the stabilization 320 00:17:03,800 --> 00:17:08,320 Speaker 10: comes in improvement. You know, their new guidance has a 321 00:17:08,320 --> 00:17:10,560 Speaker 10: pretty wide range. So the low end of the range 322 00:17:10,640 --> 00:17:13,520 Speaker 10: is assuming no improvement through year end, which we think 323 00:17:13,560 --> 00:17:16,359 Speaker 10: could be sounds pretty conservative to us, you know, and 324 00:17:16,400 --> 00:17:19,240 Speaker 10: then on the higher end they would see a gradual 325 00:17:19,400 --> 00:17:24,199 Speaker 10: slow improvement in traffic going forward. So what are they 326 00:17:24,240 --> 00:17:26,520 Speaker 10: going to do? You know, it's going to be a 327 00:17:26,720 --> 00:17:30,720 Speaker 10: continue to be about improving the operations, right that's been 328 00:17:32,600 --> 00:17:36,160 Speaker 10: you know, a key tenant under under CEO Julie Messino. 329 00:17:36,760 --> 00:17:38,919 Speaker 10: It's also going to be food innovation. It's going to 330 00:17:38,960 --> 00:17:42,760 Speaker 10: be Southern favorites, it's going to be twists on old classics. 331 00:17:42,800 --> 00:17:46,800 Speaker 10: It's going to be bringing back items that people love 332 00:17:46,880 --> 00:17:49,240 Speaker 10: they want to see return to the menu. But I 333 00:17:49,280 --> 00:17:54,679 Speaker 10: think what really stood out is their willingness to listen 334 00:17:54,800 --> 00:17:59,400 Speaker 10: more closely to their customers. I think that's a big 335 00:17:59,520 --> 00:18:03,080 Speaker 10: key point of focus for them moving forward after the 336 00:18:03,119 --> 00:18:04,560 Speaker 10: controversy that they suffered. 337 00:18:05,080 --> 00:18:07,159 Speaker 6: Well, Michael, So in terms of what are they going 338 00:18:07,200 --> 00:18:10,000 Speaker 6: to do right, it seems as a cutting capex is 339 00:18:10,160 --> 00:18:11,960 Speaker 6: a part of the plan. Is that something that you 340 00:18:12,040 --> 00:18:15,720 Speaker 6: think wood single discipline or does it actually risk slowing 341 00:18:15,720 --> 00:18:17,000 Speaker 6: to turn around even more? 342 00:18:19,119 --> 00:18:22,520 Speaker 10: Well, they're going to still refresh the stores. What they're 343 00:18:22,640 --> 00:18:27,320 Speaker 10: cutting back on is a more extensive remodel, which was 344 00:18:29,240 --> 00:18:32,680 Speaker 10: in tandem with the logo change, which was something that 345 00:18:32,800 --> 00:18:34,200 Speaker 10: was angering customers. 346 00:18:34,520 --> 00:18:34,720 Speaker 4: Right. 347 00:18:34,840 --> 00:18:40,480 Speaker 10: So I think the capex change is probably you know, 348 00:18:40,560 --> 00:18:43,960 Speaker 10: the lowered capex is probably smart. But they're going to 349 00:18:44,000 --> 00:18:46,840 Speaker 10: continue to refresh their stores. They're going to continue to 350 00:18:46,880 --> 00:18:49,160 Speaker 10: give them a fresh coat of pain, improve floors where 351 00:18:49,200 --> 00:18:51,359 Speaker 10: they need to clean up the bathrooms, things of that 352 00:18:51,480 --> 00:18:55,720 Speaker 10: nature that nobody's going to get up in arms over. 353 00:18:56,520 --> 00:18:59,160 Speaker 2: I'm actually surprised in hindsight that maybe this manager team 354 00:18:59,480 --> 00:19:02,679 Speaker 2: kept theirs there. I mean, this was a real self 355 00:19:02,680 --> 00:19:06,960 Speaker 2: inflicted wound there. What's the shareholder's been saying. Has it 356 00:19:06,960 --> 00:19:08,879 Speaker 2: been any pushback other than selling the shares? 357 00:19:09,600 --> 00:19:12,679 Speaker 10: Yeah, So listen, Julie Messino the you know that you 358 00:19:12,760 --> 00:19:16,160 Speaker 10: make a great point, Paul and Julie Messino. The reason 359 00:19:16,160 --> 00:19:18,480 Speaker 10: why I believe she's still there is that she was 360 00:19:18,480 --> 00:19:22,119 Speaker 10: doing a great job until until this controversy hit. You know, 361 00:19:22,200 --> 00:19:27,240 Speaker 10: this is a chain that had been bleeding traffic for years, right, 362 00:19:27,320 --> 00:19:30,160 Speaker 10: They've been really struggling for a long time to bring 363 00:19:30,200 --> 00:19:35,200 Speaker 10: in younger consumers, right, and she had shown pretty good 364 00:19:35,280 --> 00:19:41,000 Speaker 10: success over the twelve months leading into the logo change. 365 00:19:41,280 --> 00:19:44,200 Speaker 10: Same Star sales at the restaurants were up five percent 366 00:19:45,320 --> 00:19:48,879 Speaker 10: in the August quarter. So I think that's why, you know, 367 00:19:48,960 --> 00:19:53,600 Speaker 10: the proxy fight kind of failed, the attempt to remove 368 00:19:53,600 --> 00:19:56,120 Speaker 10: her from the board failed, And why she still has 369 00:19:56,160 --> 00:19:59,199 Speaker 10: her job right now is that they this chain was 370 00:19:59,240 --> 00:20:01,879 Speaker 10: a mess prior to her arrival, and she was showing 371 00:20:01,920 --> 00:20:04,560 Speaker 10: some pretty good progress up until August. 372 00:20:05,280 --> 00:20:09,960 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 373 00:20:10,160 --> 00:20:13,640 Speaker 1: and anywhere else you get your podcasts. 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