1 00:00:03,120 --> 00:00:07,480 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:10,480 --> 00:00:15,520 Speaker 2: I will say BUCkies is maybe the most confusingly amazing 3 00:00:15,560 --> 00:00:16,800 Speaker 2: place on the planet. 4 00:00:17,120 --> 00:00:20,720 Speaker 3: Right it is. It is a mind boggling experience. 5 00:00:21,400 --> 00:00:23,200 Speaker 4: Sam is telling us a story about BUCkies. 6 00:00:23,320 --> 00:00:23,760 Speaker 3: I heard. 7 00:00:23,920 --> 00:00:27,479 Speaker 1: Why was it? Hey, Sam? Why was it? Insane? I 8 00:00:27,520 --> 00:00:29,520 Speaker 1: gotta know? Wait are we recording? 9 00:00:30,120 --> 00:00:31,000 Speaker 4: We're recording right. 10 00:00:30,920 --> 00:00:34,479 Speaker 1: But wait, you guys started without me. Well yeah, okay, 11 00:00:34,680 --> 00:00:35,760 Speaker 1: so this is off the record. 12 00:00:38,880 --> 00:00:41,800 Speaker 4: I did a deadlift one, Jimmy. 13 00:00:41,880 --> 00:00:45,919 Speaker 1: Okay, uh barges. 14 00:00:46,080 --> 00:00:48,239 Speaker 4: This isn't After School Special, except. 15 00:00:47,840 --> 00:00:50,400 Speaker 1: I've decided I'm going to base my entire personality going 16 00:00:50,400 --> 00:00:53,640 Speaker 1: forward on campaigning for a strategic pork reserve in the US. 17 00:00:53,760 --> 00:00:55,480 Speaker 4: Where's the best with imposta? 18 00:00:55,640 --> 00:00:58,240 Speaker 1: These are the important question? Is it robots taking over 19 00:00:58,240 --> 00:00:58,840 Speaker 1: the world? No. 20 00:00:58,920 --> 00:01:01,800 Speaker 4: I think that like in a couple of years, the 21 00:01:01,880 --> 00:01:04,080 Speaker 4: AI will do a really good job of making the 22 00:01:04,080 --> 00:01:07,320 Speaker 4: Odd Lots podcast and people to say, I don't really 23 00:01:07,400 --> 00:01:09,240 Speaker 4: need to listen to Joe and Tracy anymore. 24 00:01:09,440 --> 00:01:10,360 Speaker 3: We do have. 25 00:01:11,760 --> 00:01:15,640 Speaker 4: The perfect welcome to lots More where we catch up 26 00:01:15,680 --> 00:01:17,960 Speaker 4: with friends about what's going on right now. 27 00:01:18,120 --> 00:01:22,520 Speaker 1: Because even when Odd Lots is over, there's always lots More, And. 28 00:01:22,440 --> 00:01:24,679 Speaker 4: We really do have the perfect guest. 29 00:01:26,920 --> 00:01:30,120 Speaker 1: Oh, Joe, did you see did you see PEPSI results 30 00:01:30,120 --> 00:01:30,839 Speaker 1: from last week? 31 00:01:31,160 --> 00:01:33,759 Speaker 4: You know what, Okay, I'm gonna admit something. I haven't 32 00:01:33,800 --> 00:01:35,880 Speaker 4: been paying that close attention to earnings. 33 00:01:35,520 --> 00:01:39,119 Speaker 1: This season, which I actually had that feeling that you weren't. 34 00:01:39,200 --> 00:01:39,920 Speaker 1: But why is that? 35 00:01:40,520 --> 00:01:40,679 Speaker 3: Uh? 36 00:01:42,600 --> 00:01:45,440 Speaker 4: I don't know, like I think I'm like like paying attention. 37 00:01:45,560 --> 00:01:48,640 Speaker 4: I don't know, like looking I have no justification. Maybe 38 00:01:48,680 --> 00:01:50,720 Speaker 4: I just think you like too much about the FED 39 00:01:51,000 --> 00:01:54,680 Speaker 4: and trying to read monetary policy stuff. And you're right, 40 00:01:54,720 --> 00:01:57,880 Speaker 4: I have no I have no defense. You know, wait, 41 00:01:58,000 --> 00:01:59,800 Speaker 4: how did you know I had a How did you 42 00:01:59,840 --> 00:02:02,000 Speaker 4: have this feeling that I've been slacking at the job? 43 00:02:02,120 --> 00:02:07,360 Speaker 1: Because I was about to say something sarcastic. No, because 44 00:02:07,440 --> 00:02:10,120 Speaker 1: I can, I can tell I think. You know, it's 45 00:02:10,160 --> 00:02:13,320 Speaker 1: funny after we've done the Odd Lots podcast for I mean, 46 00:02:13,440 --> 00:02:16,679 Speaker 1: it's actually coming up for ten years in twenty twenty five. Yeah, 47 00:02:16,760 --> 00:02:19,640 Speaker 1: it is actually disturbing that we tend to think of 48 00:02:19,680 --> 00:02:23,200 Speaker 1: the same questions. We tend to be on the same page. 49 00:02:23,280 --> 00:02:26,280 Speaker 1: We tend to not actually have to like tell each 50 00:02:26,280 --> 00:02:28,880 Speaker 1: other that many things. That's right, Like we can just 51 00:02:28,919 --> 00:02:32,280 Speaker 1: say one sentence and we both immediately know like what 52 00:02:32,320 --> 00:02:32,800 Speaker 1: we want to do. 53 00:02:32,960 --> 00:02:33,880 Speaker 4: Yeah, jeez, but. 54 00:02:33,960 --> 00:02:35,880 Speaker 1: Yes, I could tell you weren't paying attention to earnings. 55 00:02:35,919 --> 00:02:38,919 Speaker 1: I kind of feel like earnings are there. I've said 56 00:02:38,919 --> 00:02:41,040 Speaker 1: this before, but I swear to god they come up 57 00:02:41,200 --> 00:02:43,079 Speaker 1: more often than four times a year. 58 00:02:43,280 --> 00:02:46,040 Speaker 4: We were recording this, by the way, on February fourteenth, 59 00:02:46,040 --> 00:02:48,680 Speaker 4: twenty twenty four, four h six pm, and I'm looking 60 00:02:48,760 --> 00:02:51,679 Speaker 4: at a TV right behind you, Tracy, and there is 61 00:02:51,720 --> 00:02:54,600 Speaker 4: a headline Cisco to cut five percent of its global 62 00:02:54,600 --> 00:02:55,560 Speaker 4: work force. Yeah. 63 00:02:55,639 --> 00:02:58,120 Speaker 1: So this is a big theme of earnings right now, 64 00:02:58,639 --> 00:03:02,480 Speaker 1: which is Layoffs was aware of. Yes, in part because 65 00:03:02,480 --> 00:03:06,000 Speaker 1: they're also hitting our own industry media, but predominantly they've 66 00:03:06,000 --> 00:03:08,240 Speaker 1: been in tech so far. And it kind of raises 67 00:03:08,240 --> 00:03:12,560 Speaker 1: the question about what levers companies actually have to pull 68 00:03:12,800 --> 00:03:16,079 Speaker 1: to boost earnings and profit margins right now? Do you 69 00:03:16,120 --> 00:03:19,600 Speaker 1: remember we spoke to Samuel Ryans absolutely last year. So 70 00:03:19,680 --> 00:03:24,720 Speaker 1: Sam nailed the earnings trade last year and he kind 71 00:03:24,720 --> 00:03:26,840 Speaker 1: of has like a new thesis now. Sam. It's good 72 00:03:26,840 --> 00:03:27,959 Speaker 1: to talk to you on lots more. 73 00:03:28,400 --> 00:03:30,880 Speaker 2: Oh, it's fantastic to be here. And at least Joe 74 00:03:30,919 --> 00:03:34,320 Speaker 2: didn't make up an excuse to not be paying attention. 75 00:03:34,600 --> 00:03:37,120 Speaker 1: I just admitted it, just admitted Joe is very good 76 00:03:37,160 --> 00:03:42,120 Speaker 1: at taking ownership for his faults. Is faltisfying, Yeah, faults? 77 00:03:42,760 --> 00:03:45,200 Speaker 3: I mean I was just riffing off excuse flation. 78 00:03:45,520 --> 00:03:48,000 Speaker 4: Oh yeah, oh thanks, I got I picked that up. 79 00:03:48,000 --> 00:03:49,160 Speaker 4: I picked that up, Thank you. 80 00:03:49,200 --> 00:03:51,720 Speaker 1: So this is one reason I wanted to talk to you, Sam. 81 00:03:51,760 --> 00:03:54,640 Speaker 1: So last year we had this episode where we talked 82 00:03:54,640 --> 00:03:58,640 Speaker 1: about how companies were basically pushing price, so raising their 83 00:03:58,680 --> 00:04:02,920 Speaker 1: prices to offset lower volumes, and arguably they've been doing 84 00:04:02,920 --> 00:04:05,600 Speaker 1: that in the post pandemic environment for a while now, 85 00:04:05,960 --> 00:04:09,360 Speaker 1: and I think like it kind of went viral after that. 86 00:04:09,440 --> 00:04:11,960 Speaker 1: I don't know if that was your experience, it was. 87 00:04:11,880 --> 00:04:12,960 Speaker 3: Certainly my experience. 88 00:04:13,040 --> 00:04:15,560 Speaker 2: If I'd known that it was going to go quite 89 00:04:15,600 --> 00:04:20,320 Speaker 2: that viral, I probably would have discontinued my Twitter account 90 00:04:21,080 --> 00:04:23,320 Speaker 2: for a week or two. 91 00:04:23,360 --> 00:04:25,320 Speaker 3: But yeah, no, that definitely went viral. 92 00:04:25,839 --> 00:04:28,159 Speaker 4: Yeah, we should talk to Sam more often, because I 93 00:04:28,200 --> 00:04:31,679 Speaker 4: do know and I do read some of your notes. 94 00:04:31,720 --> 00:04:34,320 Speaker 4: I don't read everyone because leave is short, but I 95 00:04:34,400 --> 00:04:36,400 Speaker 4: like click on them. And during earning season, you do 96 00:04:36,720 --> 00:04:41,919 Speaker 4: track earnings and you derive the macro signals from what 97 00:04:42,000 --> 00:04:43,880 Speaker 4: companies are setting out their conference calls you to a 98 00:04:43,880 --> 00:04:46,800 Speaker 4: close reading. So talk to us about layoffs because they're 99 00:04:46,839 --> 00:04:49,680 Speaker 4: not really showing up in the macro data yet. Like, 100 00:04:50,400 --> 00:04:53,120 Speaker 4: by and large, the labor market data is good, but 101 00:04:53,160 --> 00:04:55,800 Speaker 4: we do have a lot of earnings headlined, So what 102 00:04:55,920 --> 00:04:56,640 Speaker 4: is going on there? 103 00:04:57,520 --> 00:04:59,840 Speaker 3: Yeah, so let's start with the layoffs. 104 00:05:00,000 --> 00:05:02,120 Speaker 2: It's a strange world, right, because the layoffs get a 105 00:05:02,120 --> 00:05:04,680 Speaker 2: lot of attention, they get a lot of the headlines. 106 00:05:05,360 --> 00:05:07,839 Speaker 2: But at the same time, if you look back at 107 00:05:07,920 --> 00:05:12,719 Speaker 2: what was happening January, February March of last year, it 108 00:05:12,839 --> 00:05:15,359 Speaker 2: was far worse. It was far more of a massacre 109 00:05:15,680 --> 00:05:16,520 Speaker 2: on the text lage. 110 00:05:16,600 --> 00:05:19,679 Speaker 1: Yeah, if you look at the Challenger layoffs, you can see, 111 00:05:19,720 --> 00:05:22,080 Speaker 1: like the spike last year was a lot more than 112 00:05:22,080 --> 00:05:24,800 Speaker 1: it is currently, even though it feels like these announcements 113 00:05:24,839 --> 00:05:26,159 Speaker 1: are in the headlines constantly. 114 00:05:27,000 --> 00:05:31,080 Speaker 2: Yeah, And when you look at what you call it, 115 00:05:31,360 --> 00:05:34,279 Speaker 2: a company like Meta, what they did last year in 116 00:05:34,360 --> 00:05:38,680 Speaker 2: terms of headcount reduction, like Cisco, it was five times 117 00:05:38,880 --> 00:05:40,480 Speaker 2: what Cisco did today. 118 00:05:40,839 --> 00:05:42,039 Speaker 3: Right, So Cisco. 119 00:05:41,800 --> 00:05:45,560 Speaker 2: Lays off five thousand people. Meta did twenty five in 120 00:05:45,600 --> 00:05:47,000 Speaker 2: a single month last year. 121 00:05:47,160 --> 00:05:49,000 Speaker 3: So to me, there's a. 122 00:05:49,000 --> 00:05:52,560 Speaker 2: Lot of headlines about the layoffs, but it's not necessarily 123 00:05:52,600 --> 00:05:56,600 Speaker 2: going to translate into the overall jobs pictures simply because 124 00:05:56,640 --> 00:06:01,560 Speaker 2: you have a pretty tight labor market and it's not 125 00:06:01,839 --> 00:06:05,719 Speaker 2: really as bad as the headlines which would suggest. 126 00:06:05,760 --> 00:06:09,520 Speaker 4: So we did an episode recently with Jason Cummins at Brevin. 127 00:06:09,720 --> 00:06:13,760 Speaker 4: He's negative on the economy, but one of the things 128 00:06:13,800 --> 00:06:16,919 Speaker 4: that he says is that, Okay, his basic thesis is 129 00:06:16,960 --> 00:06:21,000 Speaker 4: that pricing power growth is not like it used to be. 130 00:06:21,040 --> 00:06:23,440 Speaker 4: Companies can't push price like they could a year ago 131 00:06:23,600 --> 00:06:26,680 Speaker 4: or two years ago. So in order to flatter margins, 132 00:06:27,040 --> 00:06:29,120 Speaker 4: they're going to be cutting jobs because at least of 133 00:06:29,160 --> 00:06:31,279 Speaker 4: the short term, you can get a profit margin boost 134 00:06:31,279 --> 00:06:33,880 Speaker 4: by having few workers. How does that square with what 135 00:06:33,920 --> 00:06:35,080 Speaker 4: you're actually seeing right now? 136 00:06:35,440 --> 00:06:39,160 Speaker 2: I would say Tech really did take their medicine last year. 137 00:06:40,040 --> 00:06:43,200 Speaker 2: You can look at Alphabet, you can look at Meta, 138 00:06:43,400 --> 00:06:46,279 Speaker 2: you can look at Amazon. Right the head counts are 139 00:06:46,320 --> 00:06:49,920 Speaker 2: all down pretty significantly on a year a year basis. 140 00:06:50,720 --> 00:06:57,640 Speaker 2: The really interesting thing with the consumer products group companies, 141 00:06:58,080 --> 00:07:00,320 Speaker 2: you know, you're Procter and Gambles, your Unilely. 142 00:07:00,800 --> 00:07:04,040 Speaker 3: Your Coca Colas, they really. 143 00:07:03,680 --> 00:07:07,719 Speaker 2: Haven't had the hiring binge over the past two or 144 00:07:07,760 --> 00:07:11,800 Speaker 2: three years that would allow for a lever on that front, 145 00:07:11,920 --> 00:07:15,200 Speaker 2: particularly when they're running out of pricing power. So if 146 00:07:15,200 --> 00:07:18,160 Speaker 2: you're running out of pricing power and your primary way 147 00:07:18,280 --> 00:07:23,720 Speaker 2: of getting additional revenue in the door is volume, you're 148 00:07:23,880 --> 00:07:28,080 Speaker 2: probably going to find it pretty difficult to lay a 149 00:07:28,120 --> 00:07:32,160 Speaker 2: significant number of people off right. You're looking for that 150 00:07:32,400 --> 00:07:38,920 Speaker 2: incremental freedom lay being sold. That takes a manufacturing facility, 151 00:07:38,920 --> 00:07:41,679 Speaker 2: that takes somebody to make it right. It's a much 152 00:07:42,440 --> 00:07:47,160 Speaker 2: it's a much less interesting way of making margin. But 153 00:07:47,200 --> 00:07:51,160 Speaker 2: it's really important from the perspective of can they really 154 00:07:51,240 --> 00:07:53,280 Speaker 2: lay a lot of people off And I really don't 155 00:07:53,320 --> 00:07:56,400 Speaker 2: know that they can, particularly if they don't want to 156 00:07:56,400 --> 00:07:59,880 Speaker 2: get dragged in front of Congress and be a qu 157 00:08:00,080 --> 00:08:02,440 Speaker 2: used to price gouging and then laying people off right. 158 00:08:02,440 --> 00:08:04,480 Speaker 3: That is a really bad political look. 159 00:08:05,160 --> 00:08:09,920 Speaker 2: And so I mean, if I were Mark Zuckerberger Jeff Bezos, 160 00:08:10,120 --> 00:08:15,200 Speaker 2: I would really root for a significant layoff on the 161 00:08:15,200 --> 00:08:18,119 Speaker 2: CpG side, simply because you're going to have them dragged 162 00:08:18,120 --> 00:08:21,520 Speaker 2: in front of Congress instead of zucking Bezos. 163 00:08:21,880 --> 00:08:23,720 Speaker 1: I wanted to ask you about this actually because we're 164 00:08:23,760 --> 00:08:27,600 Speaker 1: recording this, like Joe said on Valentine's Day, and we 165 00:08:27,680 --> 00:08:29,760 Speaker 1: just saw the Super Bowl and one of the ads 166 00:08:29,760 --> 00:08:32,280 Speaker 1: that ran during the Super Bowl was from the Biden 167 00:08:32,320 --> 00:08:36,240 Speaker 1: administration about shrink flation, and they have also made noises 168 00:08:36,280 --> 00:08:40,680 Speaker 1: about price gouging and basically been saying that companies need 169 00:08:40,720 --> 00:08:45,040 Speaker 1: to start bringing down their prices as overall inflation and 170 00:08:45,200 --> 00:08:49,199 Speaker 1: supply chain pressures start to dissipate. And I always wonder 171 00:08:49,800 --> 00:08:53,280 Speaker 1: how scary is that type of jaw owning actually for 172 00:08:53,400 --> 00:08:56,600 Speaker 1: companies and CEOs, because it feels like, Okay, you know, 173 00:08:56,880 --> 00:09:00,400 Speaker 1: the President can say stuff about prices, but ultimately it's 174 00:09:00,400 --> 00:09:04,760 Speaker 1: a free market economy and unless you're engaging in monopolistic 175 00:09:04,920 --> 00:09:09,400 Speaker 1: practices or doing something illegal, you're allowed to raise your 176 00:09:09,440 --> 00:09:12,440 Speaker 1: prices again, as long as you're not colluding or something 177 00:09:12,480 --> 00:09:12,800 Speaker 1: like that. 178 00:09:14,240 --> 00:09:15,040 Speaker 3: It's really not. 179 00:09:14,960 --> 00:09:20,000 Speaker 2: That scary until the you know, the FTC gets involved. 180 00:09:20,280 --> 00:09:20,439 Speaker 3: Right. 181 00:09:20,480 --> 00:09:23,920 Speaker 2: It's something where you're like, eh, we have to tread lightly, 182 00:09:24,280 --> 00:09:28,959 Speaker 2: but you're not going to lower prices because you get 183 00:09:29,040 --> 00:09:32,720 Speaker 2: yelled at from Washington, right, You're going You're only going 184 00:09:32,720 --> 00:09:36,120 Speaker 2: to lower prices if it's advantageous for you in some way, 185 00:09:36,360 --> 00:09:40,960 Speaker 2: and that is just the way it works. It's a 186 00:09:41,120 --> 00:09:45,360 Speaker 2: very I would say it was politically advantageous from the 187 00:09:45,360 --> 00:09:49,040 Speaker 2: Biden administration, but it's not all that nerve wracking, you know, 188 00:09:49,080 --> 00:09:52,800 Speaker 2: if you're a corporate CEO that has raised prices over 189 00:09:52,800 --> 00:09:56,240 Speaker 2: the last few years, because frankly, you're really not raising 190 00:09:56,280 --> 00:10:01,280 Speaker 2: prices that much going forward, and you basically told everybody 191 00:10:01,400 --> 00:10:02,160 Speaker 2: you're not going to. 192 00:10:02,520 --> 00:10:04,800 Speaker 4: So just sorry to be clear on the staying on 193 00:10:04,840 --> 00:10:08,079 Speaker 4: the layoffs real quickly. A tech company, I mean, one 194 00:10:08,120 --> 00:10:11,760 Speaker 4: of the amazing things about software modern tech companies. But 195 00:10:11,800 --> 00:10:14,319 Speaker 4: why software is this amazing business model that people love 196 00:10:14,400 --> 00:10:17,720 Speaker 4: is you build it and then it just in theory, 197 00:10:17,880 --> 00:10:20,600 Speaker 4: is a money making machine forever, and then the code 198 00:10:20,679 --> 00:10:23,800 Speaker 4: lives on when and so at least in the short term, 199 00:10:23,840 --> 00:10:25,400 Speaker 4: if you're not too worried about R and D or 200 00:10:25,440 --> 00:10:29,199 Speaker 4: product development, you could cut workers expand margin very clearly 201 00:10:29,240 --> 00:10:32,240 Speaker 4: without necessarily take your revenue hit in areas like tech 202 00:10:32,280 --> 00:10:36,360 Speaker 4: and software. But basically your contention is that in areas 203 00:10:36,400 --> 00:10:40,360 Speaker 4: like consumer package goods, et cetera, there is just not 204 00:10:40,640 --> 00:10:43,920 Speaker 4: much levers you could pull to cut workers without also 205 00:10:44,000 --> 00:10:45,320 Speaker 4: affecting your ability. 206 00:10:45,000 --> 00:10:47,360 Speaker 3: To do business exactly. 207 00:10:47,720 --> 00:10:53,520 Speaker 2: I really do think it's somewhat problematic when you look 208 00:10:53,600 --> 00:10:58,280 Speaker 2: back over the past oh decade or so, you know 209 00:10:58,320 --> 00:11:05,400 Speaker 2: a lot of these CpG companies really haven't added employees 210 00:11:05,559 --> 00:11:09,920 Speaker 2: on net in any meaningful way, so it's it's not 211 00:11:10,040 --> 00:11:13,600 Speaker 2: as though the employee leverage is really where they want 212 00:11:13,640 --> 00:11:17,680 Speaker 2: to reach. What I would say is that, you know, 213 00:11:18,040 --> 00:11:20,960 Speaker 2: we called it price over volume when I was on 214 00:11:21,040 --> 00:11:23,960 Speaker 2: about a year ago. What I would say now is 215 00:11:24,200 --> 00:11:29,920 Speaker 2: you're beginning to see that price that companies put in 216 00:11:30,720 --> 00:11:34,120 Speaker 2: begin to show up in margin in a very meaningful way, 217 00:11:34,320 --> 00:11:38,640 Speaker 2: particularly gross margin, and those gross margin dollars are flowing 218 00:11:38,679 --> 00:11:43,840 Speaker 2: into the quote unquote brand building that they need to 219 00:11:43,880 --> 00:11:46,640 Speaker 2: do in order to try to get volumes back. And 220 00:11:46,880 --> 00:11:49,840 Speaker 2: you look at the you know, the metas and the 221 00:11:49,840 --> 00:11:54,000 Speaker 2: alphabets of the world, they're kind of telling you that 222 00:11:54,000 --> 00:11:58,120 Speaker 2: that's exactly what's happening. These companies are taking the incremental 223 00:11:58,120 --> 00:12:00,640 Speaker 2: dollars that they're making on the gross margin line and 224 00:12:00,679 --> 00:12:04,280 Speaker 2: they're putting them into advertising and marketing in a meaningful 225 00:12:04,320 --> 00:12:06,920 Speaker 2: and significant way to compete for those volumes. 226 00:12:07,440 --> 00:12:09,880 Speaker 1: I was going to ask you exactly about this, like 227 00:12:10,040 --> 00:12:15,640 Speaker 1: how companies actually push through volume increase in the current environment, 228 00:12:15,720 --> 00:12:20,040 Speaker 1: and so you think that it's ad spending and basically, 229 00:12:20,120 --> 00:12:23,560 Speaker 1: you know, increasing brand awareness. One of the reasons I 230 00:12:23,640 --> 00:12:25,800 Speaker 1: really like talking to you sam is because you do, 231 00:12:25,880 --> 00:12:29,840 Speaker 1: unlike Joe, you do look at the earnings and like 232 00:12:29,880 --> 00:12:33,520 Speaker 1: specifically what companies are saying on their calls with analysts, 233 00:12:33,880 --> 00:12:37,280 Speaker 1: what CEOs are saying, Like what are some interesting things 234 00:12:37,320 --> 00:12:40,600 Speaker 1: that you've picked out from the current quarter. And you know, 235 00:12:40,640 --> 00:12:44,240 Speaker 1: for instance, I mentioned pepsi earlier, but like, are they 236 00:12:44,320 --> 00:12:50,160 Speaker 1: saying things specifically about either pricing, power diminishing or volumes increasing. 237 00:12:51,520 --> 00:12:52,960 Speaker 3: So one of the. 238 00:12:52,679 --> 00:12:56,760 Speaker 2: Most interesting companies this past quarter was Unilever, and they 239 00:12:56,800 --> 00:13:02,480 Speaker 2: do everything from skincare to ice cream, and they when 240 00:13:02,520 --> 00:13:05,000 Speaker 2: they put out their earnings in their presentation, they have 241 00:13:05,120 --> 00:13:09,120 Speaker 2: this great chart and it's thirteen point three percent pricing 242 00:13:09,160 --> 00:13:12,920 Speaker 2: in Q four of twenty twenty two and a decline 243 00:13:12,920 --> 00:13:16,640 Speaker 2: of I believe it was three point eight percent in 244 00:13:16,960 --> 00:13:22,360 Speaker 2: volume in Q four twenty twenty two. That evolved into 245 00:13:22,400 --> 00:13:27,079 Speaker 2: two point eight percent pricing in Q four of twenty 246 00:13:27,080 --> 00:13:32,720 Speaker 2: twenty three with slightly positive volume about one point eight 247 00:13:33,280 --> 00:13:40,439 Speaker 2: percent volume. That is a really interesting kind of mentality. 248 00:13:39,920 --> 00:13:42,280 Speaker 3: To take forward that if you're a. 249 00:13:42,240 --> 00:13:46,240 Speaker 2: Successful CpG company that raised prices, and you raised them 250 00:13:46,440 --> 00:13:49,120 Speaker 2: at the right time, and you began the process of 251 00:13:49,280 --> 00:13:52,760 Speaker 2: slowly allowing that price to flow through the system. You 252 00:13:52,800 --> 00:13:56,120 Speaker 2: didn't get too greedy. You simply allowed it to work 253 00:13:56,120 --> 00:13:59,439 Speaker 2: through the system. You're beginning to have those volumes come back, 254 00:14:00,640 --> 00:14:03,840 Speaker 2: and then you go, I think it's five or six 255 00:14:03,880 --> 00:14:06,360 Speaker 2: slides later, and you look at what happened with their 256 00:14:06,360 --> 00:14:09,840 Speaker 2: gross margin. Gross margins were up two hundred basis points. 257 00:14:11,160 --> 00:14:14,520 Speaker 1: Two hundred basis points or twenty basis points. 258 00:14:15,160 --> 00:14:20,320 Speaker 2: I was on lift, Yeah, two hundred basis points, So 259 00:14:20,400 --> 00:14:22,520 Speaker 2: gross margin was up tow hundred basis points. One hundred 260 00:14:22,520 --> 00:14:26,400 Speaker 2: and thirty basis points were spent on BMI brand market 261 00:14:26,760 --> 00:14:31,240 Speaker 2: brand marketing investment. So what they're doing is they're pouring 262 00:14:31,480 --> 00:14:35,400 Speaker 2: these gross margin dollars back into marketing in order to 263 00:14:35,440 --> 00:14:39,960 Speaker 2: get the volumes that they want. And that is indicative 264 00:14:39,960 --> 00:14:44,040 Speaker 2: of what's happening across the space. You can look at Kimberly. 265 00:14:44,080 --> 00:14:50,880 Speaker 2: Clark had a very similar type of not necessarily you 266 00:14:50,920 --> 00:14:53,560 Speaker 2: know numbers, but they had a very similar type of 267 00:14:53,600 --> 00:14:57,280 Speaker 2: message in that we are going to spend on brand marketing, 268 00:14:57,720 --> 00:14:59,720 Speaker 2: and we're going to do it in a very significant 269 00:14:59,720 --> 00:15:03,240 Speaker 2: way because we want those volumes back. Right, we push 270 00:15:03,320 --> 00:15:05,760 Speaker 2: price to the extent that we think we can. Now 271 00:15:05,760 --> 00:15:08,640 Speaker 2: it's all about getting those volumes back. And those AD 272 00:15:08,680 --> 00:15:12,760 Speaker 2: dollars are beginning to flow back into Meta and Alphabet 273 00:15:12,800 --> 00:15:16,800 Speaker 2: and you saw it in you know, in Meta's numbers. 274 00:15:17,280 --> 00:15:21,080 Speaker 2: I would suggest this is not a short term trend right. 275 00:15:21,160 --> 00:15:25,360 Speaker 2: It is very much something where they do not want 276 00:15:25,360 --> 00:15:27,440 Speaker 2: to be in the headlines for laying people off after 277 00:15:27,520 --> 00:15:29,720 Speaker 2: raising prices so much. What they want to do is 278 00:15:29,720 --> 00:15:32,880 Speaker 2: they want to get volumes back while spending on ad dollars, 279 00:15:32,960 --> 00:15:38,120 Speaker 2: and AD dollars don't get you in the headlines. One 280 00:15:38,320 --> 00:15:43,360 Speaker 2: really interesting point on that is when mulsen Core's it 281 00:15:43,400 --> 00:15:46,080 Speaker 2: was earlier this week came out with earnings, they spent 282 00:15:46,160 --> 00:15:51,560 Speaker 2: more money on advertising to kick their competition while they 283 00:15:51,560 --> 00:15:56,760 Speaker 2: were down. It was an amazing, amazing conference call that 284 00:15:56,800 --> 00:16:00,720 Speaker 2: everyone should listen to. That when your competition's down, you 285 00:16:00,720 --> 00:16:03,600 Speaker 2: you don't just sit back and take the volume that 286 00:16:03,640 --> 00:16:09,000 Speaker 2: you're getting. You spend more. You really cement those gains 287 00:16:09,000 --> 00:16:13,080 Speaker 2: that you're getting. And it was it was amazing. 288 00:16:14,800 --> 00:16:31,560 Speaker 4: I have to read that. So the basic mechanism is 289 00:16:32,320 --> 00:16:36,280 Speaker 4: for twenty twenty, to tolerate some market share loss in 290 00:16:36,400 --> 00:16:42,760 Speaker 4: exchange for increased significantly increased prices. Then over time those 291 00:16:42,840 --> 00:16:45,680 Speaker 4: increased prices you don't have to keep increasing them. Over time, 292 00:16:45,760 --> 00:16:48,440 Speaker 4: they become a little more competitive as the inflation process 293 00:16:48,480 --> 00:16:51,120 Speaker 4: generally rolls on, and so now it's about getting that 294 00:16:51,200 --> 00:16:53,600 Speaker 4: market share back and sort of a little more stability 295 00:16:53,600 --> 00:16:56,600 Speaker 4: on price. When you sit there increasing AD spending, I 296 00:16:56,680 --> 00:16:58,440 Speaker 4: was like, oh, good, this will be the this will 297 00:16:58,440 --> 00:17:00,520 Speaker 4: be the savior of media. But then you said, no, 298 00:17:00,560 --> 00:17:02,440 Speaker 4: it's all going to Meta anyway, So I guess not. 299 00:17:04,320 --> 00:17:06,840 Speaker 3: I mean, yes, that is the exact flow. 300 00:17:07,000 --> 00:17:11,240 Speaker 2: And it's really intriguing when you think of it as 301 00:17:11,640 --> 00:17:14,840 Speaker 2: price all volume shifted to what I call PAM, which 302 00:17:14,920 --> 00:17:19,919 Speaker 2: is price and margin but also price and marketing dollars 303 00:17:19,960 --> 00:17:24,680 Speaker 2: shifted to that that really benefits the major platforms. 304 00:17:24,960 --> 00:17:25,680 Speaker 3: Right, it is. 305 00:17:27,080 --> 00:17:33,120 Speaker 2: Meta in Amazon's boondoggle. However, if you think about what 306 00:17:33,520 --> 00:17:36,840 Speaker 2: the boom really means for Meta and Amazon, it means 307 00:17:36,920 --> 00:17:40,200 Speaker 2: they basically get a free right or a free option 308 00:17:40,800 --> 00:17:45,640 Speaker 2: on investing in AI because their revenues are ripping as 309 00:17:45,760 --> 00:17:49,000 Speaker 2: everybody really wants to compete for those volumes. So you're 310 00:17:49,040 --> 00:17:53,240 Speaker 2: getting a tremendous uptick in AD dollars. You're getting everyone 311 00:17:53,800 --> 00:18:01,040 Speaker 2: throwing money at the incremental dollar of coming in the 312 00:18:01,040 --> 00:18:05,400 Speaker 2: door for revenue, and that is a really interesting kind 313 00:18:05,400 --> 00:18:10,560 Speaker 2: of dynamic that POV basically built the AI world. Huh. 314 00:18:10,640 --> 00:18:13,040 Speaker 1: I want to ask you more about AI, But just 315 00:18:13,119 --> 00:18:18,119 Speaker 1: before that, what would be the proximate trigger for consumer 316 00:18:18,160 --> 00:18:22,560 Speaker 1: package good companies specifically, I guess, to bring prices down. 317 00:18:22,720 --> 00:18:25,600 Speaker 1: Would it be if like the ad spending doesn't pay 318 00:18:25,600 --> 00:18:28,359 Speaker 1: off and translate into higher volumes than they have to 319 00:18:28,400 --> 00:18:32,320 Speaker 1: start discounting. It just seems like there's a general reluctance 320 00:18:32,400 --> 00:18:34,960 Speaker 1: to go down that route at the moment. So, yes, 321 00:18:35,040 --> 00:18:38,520 Speaker 1: they're not raising prices as much, but most of them 322 00:18:38,640 --> 00:18:40,800 Speaker 1: definitely aren't actually cutting them either. 323 00:18:41,240 --> 00:18:44,600 Speaker 3: Oooh, what would be the impetus for a price cut? 324 00:18:45,520 --> 00:18:48,600 Speaker 3: I don't know that there is one that is. 325 00:18:49,920 --> 00:18:52,560 Speaker 2: I would say that's kind of the conundrum of anyone 326 00:18:52,840 --> 00:18:55,320 Speaker 2: who's looking at it and saying, I really want to 327 00:18:55,359 --> 00:18:59,480 Speaker 2: see prices at the grocery store go back to twenty twenty. 328 00:19:00,320 --> 00:19:07,120 Speaker 2: That's simply going to not happen. That's that's really that's 329 00:19:07,119 --> 00:19:11,760 Speaker 2: a really tough one. You know, you could maybe see 330 00:19:11,800 --> 00:19:16,439 Speaker 2: some price competition, but at the same time, you know, 331 00:19:16,440 --> 00:19:20,120 Speaker 2: there's a pretty high industry concentration on the shelves. And 332 00:19:20,160 --> 00:19:26,199 Speaker 2: if one person begins to hold price and do it 333 00:19:26,240 --> 00:19:30,280 Speaker 2: successfully and have volumes begin to pick up slightly, it's 334 00:19:30,400 --> 00:19:34,439 Speaker 2: unlikely that you get price cuts. The one way I 335 00:19:34,480 --> 00:19:39,000 Speaker 2: think you could see significant price cuts would be if 336 00:19:39,000 --> 00:19:46,720 Speaker 2: you have the gpl ones or something really actually reduce 337 00:19:46,880 --> 00:19:52,560 Speaker 2: the overall consumption of food, that that could have an 338 00:19:52,600 --> 00:19:56,320 Speaker 2: overall effect on price. But we haven't seen that yet, 339 00:19:56,640 --> 00:19:59,080 Speaker 2: and I'm highly. 340 00:19:58,720 --> 00:19:59,520 Speaker 3: Skeptical of it. 341 00:20:00,080 --> 00:20:03,080 Speaker 1: I've I told Joe this. I've stopped eating lunch, not 342 00:20:03,119 --> 00:20:06,479 Speaker 1: because I'm on ozempic, but because I just don't want 343 00:20:06,520 --> 00:20:09,639 Speaker 1: to pay twenty dollars for a sad salad anymore. It 344 00:20:09,720 --> 00:20:14,920 Speaker 1: is funny listening to this conversation how little competition comes up. 345 00:20:15,000 --> 00:20:16,919 Speaker 1: And I think this is something we talked to you 346 00:20:16,960 --> 00:20:19,840 Speaker 1: before about, Sam, and I think we definitely mentioned it 347 00:20:19,920 --> 00:20:22,600 Speaker 1: in that excuselation article we did. But just the idea 348 00:20:22,680 --> 00:20:26,440 Speaker 1: that no one's incentivized really to do price wars because 349 00:20:26,440 --> 00:20:28,640 Speaker 1: it's just a race to the bottom, and why even 350 00:20:28,640 --> 00:20:31,080 Speaker 1: try to compete on price when you could just hold 351 00:20:31,080 --> 00:20:34,720 Speaker 1: the line and boost margins that way. 352 00:20:34,760 --> 00:20:39,720 Speaker 4: Sam, you mentioned AI, and I have this theory that, Okay, like, 353 00:20:39,760 --> 00:20:43,200 Speaker 4: if Nvidia is talking about AI, I believe it. If 354 00:20:43,520 --> 00:20:45,680 Speaker 4: Meta is talking about AI, believe it. If Google is 355 00:20:45,680 --> 00:20:49,120 Speaker 4: talk about AI. I believe it. If some random other 356 00:20:49,160 --> 00:20:52,000 Speaker 4: companies talking about AI, my assumption is, Oh, this company 357 00:20:52,040 --> 00:20:54,480 Speaker 4: is doing badly and they're just trying to drop in 358 00:20:54,520 --> 00:20:57,359 Speaker 4: some buzzwords on the conference call to get analysts and 359 00:20:57,480 --> 00:21:02,159 Speaker 4: investors excited. I have no evidence for this theory, but 360 00:21:02,280 --> 00:21:04,320 Speaker 4: what is what is your What are the patterns of 361 00:21:04,359 --> 00:21:05,760 Speaker 4: who's talking about AI and what? 362 00:21:07,280 --> 00:21:07,359 Speaker 3: Like? 363 00:21:07,440 --> 00:21:10,400 Speaker 4: Actually I do more levitted, Like UPS cut a bunch 364 00:21:10,400 --> 00:21:12,639 Speaker 4: of workers recently and then their CEO came out and 365 00:21:12,680 --> 00:21:14,680 Speaker 4: said like, oh, we're not you know, these are jobs 366 00:21:14,680 --> 00:21:17,440 Speaker 4: that could be done by AI, and like, I'm like skeptical, 367 00:21:17,480 --> 00:21:19,800 Speaker 4: but you know whatever. So but it sort of feeds 368 00:21:19,840 --> 00:21:22,120 Speaker 4: into this thing that AI is what people talk about 369 00:21:22,160 --> 00:21:23,080 Speaker 4: when they're having trouble. 370 00:21:24,160 --> 00:21:24,680 Speaker 3: Yeah. 371 00:21:24,960 --> 00:21:28,440 Speaker 2: So on the UPS front, one, they're getting absolutely destroyed 372 00:21:28,440 --> 00:21:34,600 Speaker 2: by Amazon. Right instead of Amazon shipping through UPS and FedEx, 373 00:21:34,720 --> 00:21:39,160 Speaker 2: what are they doing? They're shipping through themselves. So UPS 374 00:21:39,280 --> 00:21:43,320 Speaker 2: is using AI and blah blah blah to mass the 375 00:21:43,400 --> 00:21:47,760 Speaker 2: fact that they got their lunch eaten by Amazon and 376 00:21:48,600 --> 00:21:51,480 Speaker 2: never saw it coming. I mean, Amazon went from basically 377 00:21:51,520 --> 00:21:55,399 Speaker 2: having no market share a decade ago to being the 378 00:21:55,440 --> 00:21:59,960 Speaker 2: size of UPS. On the shipping front, it's an under report, 379 00:22:00,440 --> 00:22:05,159 Speaker 2: under talked about the story that they just destroyed. 380 00:22:05,080 --> 00:22:07,640 Speaker 3: Everyone in their path. I mean, that's what Amazon does. 381 00:22:09,000 --> 00:22:12,760 Speaker 2: When it comes to companies talking about AI, there are 382 00:22:12,800 --> 00:22:14,240 Speaker 2: some ones that I think. 383 00:22:15,600 --> 00:22:17,400 Speaker 3: Do it to cover up it, but there's also some. 384 00:22:17,440 --> 00:22:23,440 Speaker 2: That do it because they actually have something and it's 385 00:22:23,520 --> 00:22:26,959 Speaker 2: probably underrated. So one of the examples that I'd use 386 00:22:27,080 --> 00:22:32,280 Speaker 2: is Kroger, So they talk about AI in their earnings 387 00:22:32,600 --> 00:22:36,040 Speaker 2: and on their conference call. If you think about how 388 00:22:36,200 --> 00:22:41,000 Speaker 2: much they have in terms of data on consumers, that 389 00:22:41,200 --> 00:22:45,520 Speaker 2: is a pretty big database with which you toss in 390 00:22:45,800 --> 00:22:47,560 Speaker 2: AI on top of it, and all of a sudden 391 00:22:47,600 --> 00:22:52,880 Speaker 2: they actually have something suit the right the large language 392 00:22:52,880 --> 00:22:55,879 Speaker 2: models that everybody likes to talk about. There are companies 393 00:22:55,880 --> 00:22:57,840 Speaker 2: who have been collecting data for a long time that 394 00:22:58,080 --> 00:23:00,479 Speaker 2: didn't really know what to do with it, that all 395 00:23:00,520 --> 00:23:03,879 Speaker 2: of a sudden are probably sitting on gold mines in 396 00:23:03,960 --> 00:23:07,440 Speaker 2: terms of how to run their business, how to let 397 00:23:07,440 --> 00:23:10,159 Speaker 2: me have a coupon at the right time, how to 398 00:23:11,240 --> 00:23:13,720 Speaker 2: not have me have a coupon at the right time, 399 00:23:14,200 --> 00:23:17,760 Speaker 2: incentivize me to go buy XYZ product. 400 00:23:17,359 --> 00:23:17,960 Speaker 3: Off the shelf. 401 00:23:18,400 --> 00:23:23,160 Speaker 2: Those are very very interesting data sets, and I think 402 00:23:23,200 --> 00:23:27,600 Speaker 2: it's anyone and their brother, you know, has AI. It's 403 00:23:27,760 --> 00:23:30,480 Speaker 2: really the data to train the model that I think 404 00:23:30,560 --> 00:23:34,879 Speaker 2: is going to become increasingly important over time, and companies 405 00:23:34,960 --> 00:23:39,000 Speaker 2: that have been collecting that data are going to surprise 406 00:23:39,000 --> 00:23:39,639 Speaker 2: a lot of people. 407 00:23:40,240 --> 00:23:44,240 Speaker 1: This is my well, if I was going to come 408 00:23:44,280 --> 00:23:47,080 Speaker 1: up with investment thesis, which it's a good thing, I'm 409 00:23:47,080 --> 00:23:49,880 Speaker 1: not paid to actually do this, But I think insurers 410 00:23:50,040 --> 00:23:52,520 Speaker 1: are really interesting right now if you think about it 411 00:23:52,520 --> 00:23:55,879 Speaker 1: from like a sort of data AI perspective. And I 412 00:23:55,920 --> 00:23:59,240 Speaker 1: remember someone made this argument a long time ago. I 413 00:23:59,240 --> 00:24:00,840 Speaker 1: think it was in a book, and for the life 414 00:24:00,880 --> 00:24:03,159 Speaker 1: of me, I cannot remember what book it was, but 415 00:24:03,200 --> 00:24:06,440 Speaker 1: someone made the argument that like in an environment where 416 00:24:06,480 --> 00:24:10,919 Speaker 1: the government is like reluctant to be assertive or active, 417 00:24:10,960 --> 00:24:16,000 Speaker 1: then insurers become the de facto arbiters of acceptable behavior 418 00:24:16,200 --> 00:24:18,480 Speaker 1: and business because not only do they have all the 419 00:24:18,560 --> 00:24:22,000 Speaker 1: data about what people actually do, but they're also able 420 00:24:22,359 --> 00:24:25,120 Speaker 1: to price it. And I think a lot about that 421 00:24:25,200 --> 00:24:27,639 Speaker 1: in the current context of like not just AI, but 422 00:24:27,680 --> 00:24:31,320 Speaker 1: also wildfires and floods and other things that we've talked 423 00:24:31,320 --> 00:24:33,480 Speaker 1: about before. Joe, I buy it. 424 00:24:33,680 --> 00:24:36,720 Speaker 4: I I I one hundred percent by it that they 425 00:24:36,720 --> 00:24:43,760 Speaker 4: insurance insures are new overlords. Wait, Actually, Tracy and Sam, 426 00:24:44,440 --> 00:24:46,919 Speaker 4: what is the deal with Coca Cola margins? And I 427 00:24:46,960 --> 00:24:48,600 Speaker 4: ask you this in part because like, didn't you get 428 00:24:48,800 --> 00:24:51,240 Speaker 4: some sort of like little like debate with Jube Channo's. 429 00:24:51,200 --> 00:24:53,440 Speaker 1: I wasn't even I wasn't even trying to debate him. 430 00:24:53,680 --> 00:24:55,360 Speaker 4: I know what happened. So what is the story here? 431 00:24:55,359 --> 00:24:55,919 Speaker 1: This was? 432 00:24:56,040 --> 00:24:58,119 Speaker 4: I still totally get it. Actually, what was what was 433 00:24:58,119 --> 00:24:59,200 Speaker 4: this conversation about? 434 00:24:59,280 --> 00:25:01,960 Speaker 1: I don't understand. So he was saying that like Coca 435 00:25:01,960 --> 00:25:05,240 Speaker 1: Cola's raising prices and they're going to keep raising prices 436 00:25:05,320 --> 00:25:07,240 Speaker 1: or so I don't have the tweet in front of me. 437 00:25:07,320 --> 00:25:09,959 Speaker 1: And all I said was it was kind of a 438 00:25:10,000 --> 00:25:13,720 Speaker 1: messy quarter in terms of pricing. Because Coca Cola specifically 439 00:25:13,760 --> 00:25:18,440 Speaker 1: calls out a few hyper inflationary markets in their earning statement. 440 00:25:18,520 --> 00:25:21,720 Speaker 1: The only one they named specifically is Argentina. They've never 441 00:25:21,800 --> 00:25:26,240 Speaker 1: mentioned hyperinflationary markets before, I think, or at least not 442 00:25:26,720 --> 00:25:29,000 Speaker 1: in Q four last year. I went back and checked, 443 00:25:29,480 --> 00:25:33,399 Speaker 1: and then they specifically say in the earnings call that 444 00:25:33,640 --> 00:25:37,240 Speaker 1: they don't think pricing is going to be as strong 445 00:25:37,400 --> 00:25:39,199 Speaker 1: this year. So that's all I said, Like, Oh, it 446 00:25:39,240 --> 00:25:41,600 Speaker 1: was a slightly messy quarter in terms of pricing. So 447 00:25:41,640 --> 00:25:43,600 Speaker 1: I'm not sure how much you can take away from 448 00:25:43,680 --> 00:25:46,720 Speaker 1: it that they're absolutely going to continue, you know, the 449 00:25:46,720 --> 00:25:50,320 Speaker 1: POV strategy and also they're guiding for lower pricing power 450 00:25:50,400 --> 00:25:53,840 Speaker 1: in twenty twenty four and Jim wasn't having it, and 451 00:25:54,200 --> 00:25:56,320 Speaker 1: Sam you backed me up, So I appreciate it. 452 00:25:57,520 --> 00:26:00,000 Speaker 2: Yeah, I mean it was it was pretty straightforward. Right, 453 00:26:00,240 --> 00:26:03,240 Speaker 2: They got two points give or take for the year 454 00:26:03,400 --> 00:26:08,439 Speaker 2: out of hyperinflationary markets. They guided to seven to eight percent. 455 00:26:08,480 --> 00:26:09,400 Speaker 3: They landed at ten. 456 00:26:10,000 --> 00:26:12,440 Speaker 2: So guess what that gets you to eight and not 457 00:26:12,600 --> 00:26:16,760 Speaker 2: to mention they had guided the year for seven to 458 00:26:16,800 --> 00:26:20,600 Speaker 2: eight percent, dominated by price and so I mean you 459 00:26:20,640 --> 00:26:23,440 Speaker 2: look at what they did. They kind of nailed exactly 460 00:26:23,520 --> 00:26:26,439 Speaker 2: what they said they were going to do. They you know, 461 00:26:26,440 --> 00:26:29,920 Speaker 2: Coca Cola was pretty straightforward, as as was Pepsi, as 462 00:26:30,040 --> 00:26:33,320 Speaker 2: was Unilever, Parked and Gamble. You can go down through 463 00:26:33,320 --> 00:26:37,719 Speaker 2: the list that twenty twenty four is not going to 464 00:26:37,720 --> 00:26:40,359 Speaker 2: be the year of price increases. It's going to be 465 00:26:40,640 --> 00:26:45,359 Speaker 2: back to the algo and that algorithm is you know, 466 00:26:45,480 --> 00:26:48,440 Speaker 2: call it two to three percent on pricing and two 467 00:26:48,440 --> 00:26:52,679 Speaker 2: to three percent on volumes. And they're all competing on 468 00:26:52,720 --> 00:26:55,680 Speaker 2: that volume front and really trying to get that number up. 469 00:26:56,240 --> 00:26:58,240 Speaker 2: So to me, I was I was looking at the 470 00:26:58,320 --> 00:26:59,880 Speaker 2: chainos tweeting like. 471 00:27:00,000 --> 00:27:02,639 Speaker 4: Well, it sounds like it's normalized. It sounds like if 472 00:27:02,680 --> 00:27:04,399 Speaker 4: you're the fan, if you're anyone, like you're. 473 00:27:04,280 --> 00:27:07,400 Speaker 1: Basically not normalizing though. It's like two percent price increases 474 00:27:07,440 --> 00:27:11,920 Speaker 1: instead of like five or seven percent. Okay, all right 475 00:27:11,960 --> 00:27:12,840 Speaker 1: from like a CPO. 476 00:27:13,200 --> 00:27:16,919 Speaker 4: Yeah, like okay, right, I mean it sounds like like 477 00:27:17,040 --> 00:27:19,120 Speaker 4: if you're just the back road thing is like we're 478 00:27:19,119 --> 00:27:20,000 Speaker 4: back to sort of normal. 479 00:27:20,080 --> 00:27:22,919 Speaker 2: Huh yeah, And you've got to step function up in 480 00:27:23,040 --> 00:27:26,320 Speaker 2: terms of revenue, and then you know, you get to 481 00:27:26,400 --> 00:27:30,240 Speaker 2: drop those down to shareholders. And I don't actually think 482 00:27:30,280 --> 00:27:34,320 Speaker 2: that shareholders have realized that. You know that that step 483 00:27:34,359 --> 00:27:37,960 Speaker 2: function higher is a step function. It's you know, you're 484 00:27:38,000 --> 00:27:40,920 Speaker 2: not getting you're not going to have that step down 485 00:27:40,920 --> 00:27:41,760 Speaker 2: in a meaningful way. 486 00:27:42,160 --> 00:27:45,399 Speaker 1: I do actually want lower prices on coke, though I 487 00:27:45,480 --> 00:27:49,080 Speaker 1: drink a lot of diet coke. I guess I've played 488 00:27:49,080 --> 00:27:52,080 Speaker 1: a stereotype there, but I would appreciate if that could 489 00:27:52,119 --> 00:27:52,760 Speaker 1: go on sale. 490 00:27:53,119 --> 00:27:56,000 Speaker 2: They'll they'll probably do some sort of promo at some 491 00:27:56,119 --> 00:27:59,160 Speaker 2: point stock maybe maybe they'll have a bud light moment. 492 00:28:00,160 --> 00:28:04,280 Speaker 1: Oh dear, I personally can't do volume. If I was 493 00:28:04,320 --> 00:28:06,440 Speaker 1: a company right now, I'd be doomed. I just can't. 494 00:28:06,480 --> 00:28:14,720 Speaker 1: I buy like one bottle per Dredge and take it home. Yeah. 495 00:28:15,320 --> 00:28:18,400 Speaker 4: Lots More is produced by Carmen Rodriguez and dash El Bennett, 496 00:28:18,440 --> 00:28:20,600 Speaker 4: with help from Moses Onam and Keil Brooks. 497 00:28:21,000 --> 00:28:24,159 Speaker 1: Our sound engineer is Blake Maples. Sage Bauman is the 498 00:28:24,200 --> 00:28:25,800 Speaker 1: head of Bloomberg Podcasts. 499 00:28:26,280 --> 00:28:29,639 Speaker 4: Please rate, review, and subscribe to Odd, Lots and lots 500 00:28:29,640 --> 00:28:32,560 Speaker 4: More on your favorite podcast platforms. 501 00:28:32,600 --> 00:28:35,360 Speaker 1: And remember that Bloomberg subscribers can listen to all our 502 00:28:35,440 --> 00:28:40,040 Speaker 1: podcasts ad free by connecting through Apple Podcasts. Thanks for listening.