Is Encyclopedia Britannica planning an IPO?

0:00Did you see that Encyclopedia Britannica is planning an IPO? I did from your sheet over here well see Neil cheated so okay so this is interesting because you and I like growing up Encyclopedia Britannica I always wanted to buy the CDs for no reason just because they look cool it's like these encyclopedias but the cool thing is they were fading it's like oh Wikipedia is taking over blah blah blah but Encyclopedia Britannica they're licensing a lot of the data and basically I think they're doing they're generating 100 million in revenue and 45 million profits. So it looks like they're floating a$1 billion IPO.

0:37So it's 250 years after its founding and 23 years after getting trounced by Wikipedia. The company has found a niche in the AI licensing space, providing LLMs and chatbots reliable information and data. Good for them. I never would have seen this coming. I would have never seen that coming too. What they should just do is sell to one of the LLMs and don't go public. You can have this data just for yourself and no one else. I'm pretty sure Google or one of them would pay for it. How much do you think they pay? Do you think they pay over a billion? Well, they just said billion dollar IPO. Someone could pay a billion dollars for them.

1:07It's a drop in the bucket for this kind of stuff. And the interesting thing here, so this kind of goes back into politics, but people are calling Wikipedia, Wokipedia now. And if you look at, you would have thought that, did you see the, the, the, how much they're spending on server costs versus salaries? I know DEI makes up over 30%. Okay. So get this. I think they do what? Like 150, I don't know. 200 million? I don't know. Something like, okay. So anyway,$3 million is spent on server costs. You would have thought it would be a lot more. $3 million a year on server costs, right? Considering they probably get like billions of visits.

1:40$3 million a year to me is very affordable for their traffic level. It's nothing. They spent$104 million on salaries, I believe. And you mentioned 30 % of that. It's towards DEI initiatives. It's something ridiculous. Yeah. And so it's like, whoa. When they say like, when you go woke, you go broke. and I'm not saying I support that or anything. I'm just saying like, in this case, it's like, crap. The cost structure is out of whack, which is why Encyclopedia Britannica is coming out of nowhere. Here, Wikipedia's annual budget report from 2023 to 2024 reveals that they spent 50 million of their$177 million budget on diversity, equity, inclusion.

2:19Yeah. And it's pretty much breaking down. Wikipedia spends 29 % of its total budget on DEI. That's kind of crazy. Look, I'm all about hiring people. I don't really care. We're both for it. I don't care what race, gender, anything. I just want really amazing talent. We just want production. Yes. You can be an alien and you can be pink. If you're great at what you do, I'm rooting for you. It's really black and white for me. Yeah. And when I look at what's happening is if you're just spending money for the sake of spending money, you're not doing it justice to your customer base. Wikipedia's customer base would be for all those people who are reading it and consuming it online.

3:01They should be focusing on quality. And if they did that, maybe they would generate more revenue. Yep. Okay, so this is something I really love. You want to know Elon's secret to running Tesla, SpaceX, X, and Doge? No. Okay. You don't want to know? No, I want to know, but I don't know what it is. Okay, okay. So Elon's secret to running Tesla, SpaceX, X, and Doge is, this is called The Theory of Constraints. So there's a great book out there called The Goal. Amazon's Jeff Bezos used to make all his manager read it, right? It basically talks about how in every single company, you have one major bottleneck at a time.

3:38You can't solve, there's, sure, there might be hundreds of thousands of bottlenecks, but there's always one major bottleneck. What Elon does is he looks at all the companies every single week. He's like, Tesla, what's the biggest problem here? SpaceX, what's the biggest problem here? He goes, he flies, he takes his Gulfstream, he flies around and solves that problem. Sometimes he'll work with a frontline engineer or something like that to solve the biggest problem. But because he knows all the details for every company, he can go in, jump in, high level, he can go low level as well. But all he does is focus on that because he's already delegated running the day-to-day to his operators, right?

4:07He's got Gwyn, I think it's Gwyn. And then he's got Linda Iaccarino for X. And Doji's working with Vivek on that as well. but he's got a lot of people he can delegate to. But he just lasers in on the major problem for each one. So he's got at least four major problems a week and he just solves that. And when I heard Marc Andreessen talk about this, I was like, oh, this is actually the book, the goal. It's the theory of constraints. You're always gonna have more bottlenecks and just focus on the biggest one and don't try to do too many things at once. And that's how he's so productive. I get that.

4:44I run a similar playbook in my business because I never run the operations. I focus on the biggest problems, but I don't do a week by week. I just go, what are the two, three biggest problems I want to solve over the next quarter? And then I just focus on those and nothing else. And you just keep attacking those until they're done. Yes, every single day. And then what I do is once I get them done, I make sure that a systemized process, other people can rinse and repeat without me. And then I do try to check in at least a few times over the next few months to make sure no one's screwed it up. That's a key thing.

5:15One, it's checking in during. it's checking in on the metrics and then it's checking in after too. And I will say for me, I don't do enough of a good job there, but it seems like you're pretty on top of that. So that's good. Well, I get bored because this is all I do. All I do is just focus on what are the few problems that we need to solve, solve them, and that's it. I don't actually have to go in every single day being like, all right, guys, let's look at some spreadsheets or accounting or let's solve this problem that's related to this one account. I just look at what's causing the business not to grow as fast and I go in and I work on fixing those.

5:47And the ones I can't fix, I assign it to my co-founder because he's usually better at the opposite. On me, he's better at recruiting, operations, and sales. And I focus on marketing and M &A. Relentless focus, guys. If you think you're focusing pretty good right now, I would encourage you to think about how you can focus even better. I think you've been really good. I've gotten better at it. I think 2025, I'll be even better at it. You can pick one here. We have a couple more we need to do. Sure. So the next one I want to talk about is, we already talked about marketing tactics for 2025. Let's talk about the different agents that you'll need.

6:26And I don't know if you saw Mark Benioff's event for the agents, the agent force. I don't know what it was called, but I was watching it on CNBC and I was reading tons of articles on it. Yeah. What was happening. So, okay. This is actually, I mean, do you want to talk about that first before I go into this article? No, you can just go into it. It was just a event talking about how AI agents is the future. And he was just talking about Salesforce all the time and resources people can save, efficiency. He even gave an example during that conference on here's how many support tickets that Salesforce was answering through humans and how it's drastically reduced I think it was by something like by half.

7:08I'm making up a percentage, but it was something large like that. You know, someone posted something to X yesterday. I guess I spent a lot of time reading X. So they talked about a complex problem, a customer service problem that they were having. And they thought they were talking to a customer service rep, right? It wasn't until like nine minutes later when the problem was solved. And it was a complex problem that it said at the very bottom, powered by Intercom. So Intercom is a chat. It's a chat tool, right? chat. It's a little chat you can add to your site. And it's just like, man, who cares who solves it?

7:41As long as it gets solved, that's what matters at the end of the day, right? So this article is written by Anthropic. So they created Claude. It's a really good article. It's building effective agents. So if you Google building effective agents Anthropic, I would encourage everyone to read it because this is the world that we're moving into. So the one thing I want to call out, these are the different AI agents that you're going to need. an orchestrator worker. So you're going to need an agent that's almost like an overseer, like a manager, telling all the other agents what to do. That's one that you're going to need, right?

8:13And then another one that you're going to need is an evaluator optimizer. So you're going to need someone that's checking the work, which is what we just talked about. So you have an orchestrator worker, an evaluator optimizer, right? Which when you think about these things... Well, let's go back. So you've got the orchestrator, you've got the evaluator. Are they trained using different LLMs? Because if they're trained by the same ones, ones of the people doing the work are also the ones checking it and they're trained on the same model so they make the same issue. They can be trained on the same data, but you would just say, hey, your role is this.

8:46And then for the other one, it's like, your role is this. And they should be passing data to each other so they have more context sharing. But you get what I mean, right? Because if someone's doing the work and is trained by the same model and it's off, there's a value at our node that is actually inaccurate. Well, I mean, I would imagine we go into a world, again, where they can share the data. For example, there's certain things you know that I don't know when it comes to SEO, for example. There's certain things I know that you don't know. But imagine if we can pull that data. This is like a separate thing, but people talk about the importance of data lakes.

9:16You know what data lakes are? Data links? Lakes, like a lake. Okay, like Lake Erie. So right now, the problem with a lot of data is you have data silos, right? Yes. And if we continue to move into a world where SaaS is usage-based pricing, you want all the data to be combined into a data lake. So instead of silos, it's all just combined into a lake. And I would imagine that's kind of a similar scenario here where you're combining all of the data coming into these orchestrators and these evaluators into a data lake. So I'm not technical. I could be talking out of my ass right now, but it sounds logical to me.

9:52Sounds logical to me too, but I'm assuming instead of a lake, eventually it'll be a data ocean or something. Yeah, something really big. Yeah, because there's too much data. Yeah. So I think this is, I would just encourage everyone to read it. And it actually has these nice little illustrations on how this all works. But at least this starts to put it, it starts to make agents a little more tangible for people instead of just talking about it. Okay, so what are the other agents that you need? Is those the main ones? Those are kind of the main ones. So you have the workers, the orchestrators, the evaluators.

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12:39I'm sure other ones will pop up, but they didn't talk about it. so i want to discuss two more things before we wrap up the first one i want to talk about this one's a short one do you actually have blog comments on your blog anymore or no uh no we don't dude we've noted you know we turned off blog comments in 2024 we've we i should post a stat on this we've we've scraped the web and we just noticed that generally blogs get way less comments than they used to be people more so comment on social media um and then you have deal with a lot of junk comments and stuff like that. So it's just easier to disable them all.

13:15Yep. I think they used to be cool, but now it's like, because it's so filled with junk, you might as well just get rid of it. Yes. And people are like, oh, you want blog comments because it keeps updating your page. No Google. I'm like, it used to be effective. Not anymore. Not anymore. So my recommendation to most people, if you don't have tons of comments per post that are high quality, just turn them off. Like TechCrunch used to get tons of comments per post. Not anymore. No one cares. And it's not because of traffic. TechCrunch is still extremely popular. People don't care to leave comments as much.

13:47I think one of the last topics, and I know we can go on this one for quite a bit, is the future of marketing agencies. Because we both have one. Yeah. So, I mean, this is just a conversation for us to have. I think we're going to... Actually, you go first. I think we're going to go into a world where agencies will still be needed, but if they're not leveraging AI, they're going to be dead. And I'm not talking about from the aspect of, hey, are you embracing Google's Pmax? I'm talking about more of if you aren't leveraging AI within your workflows, your systems, or having AI agents to make things more efficient, you're going to end up being dead or being replaced by someone else.

14:32so far from what we're seeing, we're not seeing agencies get hit because of AI. We're seeing companies requesting more because of AI. So to keep the math simple, if a company was spending$100 ,000 and they were getting, you know, call it 500 outputs, they're like, cool, we're still spending$100 ,000. But because of AI, we don't want 500 outputs. we want 600 we want 700 now for all tasks and outputs you may not be able to increase it because technology may not be there where it can help you with some of those things but for some things you can like for example we have a creative uh we do creative work and we do commercials uh we won an award recently for an ai created commercial we literally created the commercial fully from ai we won awards for it it was great performed extremely well it was for a true company.

15:23Bless you. Thank you. And if we weren't able to, if we didn't leverage AI, could we have still created that commercial? Yes. Would it have cost us way more? Yes. Would that mean that the client would have pay way more? Yes. And for us, we were able to give a client a great output at a very reasonable price within their budget. And we were able to give them what they were expecting, which was more than normal because of AI. And it didn't really change our economics negatively or positively. It just meant that we were able to produce a better quality product at the end because of the technology.

16:00And it created better performance from an ROI perspective for the client running ads. And it created recognition for us and it made win-win for the customer and us. Yeah. I think that the thing I'll say to close this out is AI is going to augment your agency and it's going to quickly show who is not using it. And so the things we were talking about earlier during this recording was, oh, I can use it to self-diagnose myself. I'm not a doctor, but at least it tells me kind of where I'm doing with like, oh, certain health things or like where I'm trending with my health scores, VO2 max or whatever, or I can do like a financial model and things like that, right?

16:35I'm just augmenting now. And I would say I'm not necessarily smarter, but the AI has made me smarter because I have more output coming out. I'm more efficient. The thing that I remember that applies to the future marketing agency is what Satya Nadella said. And this is when Brad Gerstner and Bill Gurley asked me this question. What are you guys going to do about headcount with Microsoft and what they're a$3 trillion company? And so Satya's like, less headcount, more cost per headcount, more GPUs per researcher. And so it's more AI power and people are going to be paid more because they're augmented by AI.

17:11So the people that are augmented, they deserve to get paid more because they're augmented, right? But less headcount because he doesn't seem to believe that everyone's going to be augmented by this stuff. Or some are going to be more augmented than others, and those people will get the job. It's a competitive market, right? And the reason it's a competitive market is because, well, great talent's hard to come by. And the great talent's going to get even stronger. And because of the savings due to AI, you can pay the great talent even more money. Yeah. And it's worth it. Instead of saying, hey, I need to hire five people for, I don't know, let's just easy round them to$100 ,000.

17:43So that's$500 ,000. Why don't you just hire like two people and then pay them like maybe$150 each or$175 each. Or$200. That's still less. $400, right? $400. And then you give 20 % cost saving. Uh-huh. Yeah. And in that$200, you've allocated, you know, a thousand bucks a month for each person for AI software to help them become more efficient. Dude, when I talk to our engineers now, it's like, oh, this would have taken us at least three months to build. How long did it take you? Oh, it took like three days. and it's like, oh, this feature would have taken an entire two days to build. It's like, oh, yeah, it took me like an hour.

18:20Okay, so you either embrace it or you don't. That's where the future of not just marketing agency are growing, just the future of companies. I totally agree with you. So that's it for today, guys. Please don't forget to rate, view, subscribe and don't forget to check out marketingschool.io slash agency if you want to grow your agency faster and we'll see you tomorrow.

18:44Thank you.