Pod Insights Marketing School - Digital Marketing and Online Marketing Tips This Pool Builder Uses AI To Actually Close Deals (Whilst Sleeping) About this episode Eric and Neil break down a genius AI prospecting system a pool builder is using to target high-value homes, render custom backyard pools, and mail personalized postcards on autopilot. They also unpack Sequoia’s thesis that the next trillion-dollar AI company will sell work, not software, why AI works best when paired with human strategy, and how smart operators are using AI to create better content, better outbound, and better outcomes. Key takeaways ◾ AI can turn satellite imagery and rendering into hyper-personalized outbound. ◾ The next big AI opportunity may be selling outcomes, not software. ◾ Services businesses may benefit more from AI than most people realize. ◾ AI alone often produces mediocre work, but AI plus human judgment can outperform either one alone. ◾ Great prompts and real context lead to far better outputs than generic AI requests. ◾ The best creators are using AI to spot patterns, generate variations, and improve what already works. Chapters 00:00 How a pool builder uses AI to close bigger deals 02:17 Sequoia’s trillion-dollar AI thesis 06:39 Why AI alone still fails in business 07:58 ClickFlow for AI SEO content 08:32 Why AI + human beats AI alone 12:02 A smarter way to use AI for content creation 𝗔𝗕𝗢𝗨𝗧 𝗧𝗛𝗘 𝗖𝗛𝗔𝗡𝗡𝗘𝗟 Welcome to Marketing School, one of the top business podcasts with over 61 million downloads. Each episode delivers actionable marketing tips and strategies from two entrepreneurs who actually test what they teach. The show is hosted by Eric Siu, founder of Leveling Up and Single Grain, and Neil Patel, co-founder of NP Digital and one of the most recognized marketers in the world. 🎙️ Learn More About the Hosts Eric Siu – Leveling Up: https://www.youtube.com/@LevelingUpOfficial Neil Patel: https://www.youtube.com/@neilpatel 📩 Free Resources Ubersuggest: https://www.ubersuggest.com/ Answer The Public: https://www.answerthepublic.com/ ClickFlow: https://www.clickflow.com/ ✅ Subscribe for Daily Marketing Insights!
Transcript 0:00 Speaker 00 Finding customer information shouldn't mean digging through emails, call notes, and spreadsheets. HubSpot's Starter Plan brings all of those details together, so it's easier to track what's happening with every deal, and what to do next. It pulls information from calls and emails. Then it gets to work, logging and summarizing them. Right after your call ends, HubSpot pulls next steps from your call notes and drafts suggested follow-ups. And it stays up to date for you, so you can build demand, win more deals, and spend less time on repetitive work. Your records, insights, and next steps are ready for you to act on. And you don't have to miss a beat searching for any of it. Try the Starter Plan for $10 a month. Learn more at hubspot.com. Neil, did you see the, um, this, this guy, this guy that builds pools? Okay, so he basically closes these $50,000 pool deals. Like, here, I'm gonna show you over here. He uses OpenClaw for this.
0:44 Speaker 01 Like a swimming pool? Are you talking about?
0:45 Speaker 00 Yeah, swimming pool, swimming pool. Swimming pool, okay. Thank you for that. So, okay. Neil, this OpenClaw bot finds 500 grand to 1.2 million dollar homes without pools. It renders a pool in their backyard and mails the owner a postcard showing the before and after on autopilot. Here's how pool builders can close 50K deals with this system, okay? So it scans the satellite imagery, it filters by lot size, it does all this stuff over here. And then check this out. So this guy's marketing tactic, comment pool, and I'll show you the full breakdown. And so he gets 1.2 million views on this. I think this is genius, right? You can see the rendering. I'll make it a little bigger. Can you see that? So you can see lots scanned over here, lots scanned in Tampa, pool rendered. And literally, they get a postcard. So I think this is pretty cool. Because now you have an agent that can end-to-end handle this. So look at all the homes, and it'll create the postcard, it'll create the rendering.
1:30 Speaker 00 And this is a nice way to get people's attention when it comes to outbound. But what's funny to me, Neil, is when you look at what this guy has, uh, if I can come off of this real quick. He gets 1.2 million views on this. And then at the very bottom, he's like, DM me if you want a custom OpenClaw for your system. So, OpenClaw system for your business, okay? So, he's calling this out as a case study. That's cool. But you know what's funnier, Neil? Manus comes in. So this employee from Manus, you can see, uh, go to market at Manus. Oh, look, another homie, Neil. But he's like, hey, I saw this, and I just had to try it with Manus AI. Delivered all of these in one session, personalized to your name and need. This is hyper-personalized sales at its best. So it's like, marketing on marketing on marketing.
2:11 Speaker 01 Did I tell you I got hit up by Manus? Have they hit you up for social bills?
2:16 Speaker 00 Videos? Yeah.
2:17 Speaker 01 They hit you up? The Manus team?
2:19 Speaker 00 Uh huh.
2:20 Speaker 01 Okay. If you ever need to be connected to more people there on that team, let me know.
2:25 Speaker 00 Well, how come you didn't do a deal? Hey, how come they don't sponsor this podcast? This would be the perfect podcast for them to sponsor. We love Manus.
2:33 Speaker 01 Manus.
2:35 Speaker 00 Okay, Neil's doing it right now. I can see Neil's in the middle of it. Neil's like, oh, good idea. Okay, thank you, Neil. But I made a video for them, by the way, when they first came out. That video got like 200,000 views on it, a long form. So they got some conversions out of that. Okay, and, and I called it out as a big winner last year, even though the AI said I was sensationalist. Okay, so I'm gonna move over as Neil pulls that up. Neil, I want to talk about Sequoia's $1 trillion thesis. Okay, have you heard of this?
3:04 Speaker 01 Uh uh.
3:05 Speaker 00 Okay, so Silicon Valley is finally waking up to this $1 trillion thesis by Sequoia. So Sequoia Capital, they are a popular venture firm. They funded some of the most iconic companies. I think they funded Apple back in the day. So Sequoia's thesis that the next $1 trillion company will sell work, not software, is the most important reframe in AI right now. So the argument is if you sell a co-pilot, you're competing with every new model release. But if you sell the outcomes, so books closed, contracts claimed, customers driven, for example, claims handled. Every AI improvement makes your margins better, not your product obsolete. So the key insight most people are missing, for every dollar spent on software, $6 is spent on services. Thank God, Neil, that we have a services business for both of us, right?
3:48 Speaker 00 So don't think about AI for accountants. You want to think about the AI accounting firm, not AI for lawyers, but the AI law firm, okay? So you look at, you look at this over here, what they're basically saying is that this team, we just published a paper on how to measure these economic outcomes. We call them outcome primitives. We tracked 1,300 agents over 21 days, creating $32 million of economic value, so securing jobs, winning 200K grants, and shipping e-commerce shops. If your AI product is a co-pilot, you're competing on software margins, losing the big AI labs. If you're an AI product that delivers the primitive, you're competing On services margins, transforming outdated, inefficient industries. So choose your battles wisely. I don't even know how to read this this this chart over here.
4:32 Speaker 00 All I'll just say is that services as a software, it's become the sexy thing. And thank God we stuck around, Neil. You could you could have sold out, but you didn't.
4:41 Speaker 01 That's right. On a side note, I just did an introduction to the Manus team and told them how your past videos drove a lot of views and they should work with you. Good luck.
4:49 Speaker 00 Us, work with us for this podcast.
4:51 Speaker 01 I just said to you.
4:52 Speaker 00 No, I don't want I don't want to do a one off video. That's annoying. I just just sponsor this podcast. Like we have HubSpot, they're a great sponsor. We're taking one more.
5:01 Speaker 01 So cool.
5:02 Speaker 00 Yeah. Here, try, try, try reading this real quick, Neil.
5:05 Speaker 01 I can't see it. The text color and writing is too hard.
5:08 Speaker 00 Okay, so I I'm going to try to understand this real quick. So outcome magnitude, human effort equivalent. Okay, so so for AP asset product, uh, asset production. Okay, uh, decision support, interpersonal navigation, health optimization. Okay, let's look at this.
5:25 Speaker 00 I don't understand this. All we need to know, Neil, is there's a $1 trillion thesis by Sequoia. And that's why you have Y C, you have companies like Sequoia talking about backing more services companies.
5:34 Speaker 01 But this, this, this is outcome based. So you're selling outcomes. They say it's a trillion dollar.
5:39 Speaker 00 Which is what we've been doing anyway. You're selling outcomes where you're going to do it and do it more efficiently.
5:44 Speaker 01 But this is the same thing as service as a software as a service, is it? I don't know, it doesn't sound like it.
5:48 Speaker 00 I I think, I mean, this Sequoia one over here where you see this this picture, I don't know who this is, but services as a software, Y C was talking about. I think Sequoia is also talking about it too. So the next trillion dollar company will sell work, not software, is the most important reframe in AI right now. And I tend to believe that, which is why we're not trying to. Yeah.
6:05 Speaker 01 I I think they say service as a software is like a $15 trillion industry.
6:09 Speaker 00 It is because way more people spend money on services than software, like six to one. Every dollar spent on software, six, six dollars is spent on services.
6:19 Speaker 01 Global software as a service market with estimated value of $10 billion exceeded.
6:24 Speaker 00 I mean, you're you're going to go to town with um, with MP Excel. That's what I'll say. Yeah.
6:30 Speaker 01 Time will end up telling, but yeah, we'll try. Uh, I can't find where the rank is. All right, let me just actually use AI.
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7:12 Speaker 01 Let's see what it says. Industry size.
7:15 Speaker 00 What are you looking for? Can you share your screen?
7:16 Speaker 01 Sure.
7:17 Speaker 00 Uh, okay. So what have we got here?
7:20 Speaker 01 So service as a software. It focuses on software as a service.
7:25 Speaker 00 Oh, it failed. Yeah.
7:27 Speaker 01 I tried it with chat GPT the other day too, and it failed as well.
7:32 Speaker 00 It feels, you know, these things fail quite often. Now that I speak to the agents all day, it fails a lot. Like, but it's still worth the trade-off because the, the gains you get from it are still worth it. So I'll, I'll take, like, you and I are not perfect. We fail a lot every single day.
7:46 Speaker 01 Yeah.
7:46 Speaker 00 So I'll leave it at that.
7:48 Speaker 01 Did I tell you I have a friend who works at a public traded company? And they did an experiment with different divisions and canning employees for AI, small divisions, okay?
7:57 Speaker 00 No.
7:57 Speaker 01 So like, uh, they ended up canning quite a bit of people on marketing and they wanted to see what could be done automatically in a few other divisions. So they tried marketing, sales, you get the point, right? And they didn't pick the big divisions that are making billions of dollars. They picked the smaller ones where they could afford to lose some money. And what they found was the ones where they cut people and they couldn't cut everyone, but they cut a lot of people. Or percentage-wise, it wasn't a big headcount number, so it wasn't big announcements. The results weren't great. And what they found was the biggest issue AI had was with strategy, especially in marketing. And it was doing a lot of subpar mediocre work. But here was a bigger thing.
8:39 Speaker 01 Some of the divisions they have are regulated and one of them made a mistake that cost them $6 million. So so at that point, there's like this AI stuff is cool. We want to pair it with humans. This is costing us too much money, both on the revenue front and on the penalty front.
8:59 Speaker 00 Quick break for SaaS founders listening. You know how content marketing works. You know how AI SEO works and you've been seeing competitors ranking for your keywords all day long, but you don't have the time to write and hiring a content team feels premature or just out of the budget. That's exactly why we built ClickFlow. It helps create AI SEO content that actually sounds like your brand. We're talking thought leadership, we're talking product content, comparison pages, without having to add more headcount. It also helps you do things such as building FAQs, internal linking, and telling you which old posts are hurting your domain. One user reported saving 90 hours per month and that was a part-time employee. You can get a 14-day free trial at clickflow.com. Scale your content without scaling your team. Back to the show. You know what I think?
9:41 Speaker 00 I mean, so I'll tell you what, the good news is our marketing school YouTube is growing faster now. And so I want to give Yon credit. But also at the same time, I was speaking to him. So he helps us with the YouTube strategy. And so, you know, he made a statement. I was just talking to him about it yesterday and I'll just make it public. It's like, he's like, yeah, you know, I don't, I, you know, I don't tend to trust AI when it comes to, you know, titles and strategy and all that. It's like, no, it's not AI or human. It's AI and human. When you do AI and human and you use something like YouTube API, you're going to get better results ultimately because it's going to spot patterns that you wouldn't have spotted on your own. Right? And so I think that's what people need to need to get right. It's, it's, it's, it's not or, it's and.
10:22 Speaker 01 Yeah, watch this, everyone. And Eric, be honest, do you think I'm a, if you had to rate my skills for writing copy, what would you rate me on a one to 10? Be honest. At least the marketing copy, like for stuff.
10:34 Speaker 00 Probably, probably 8.5 to 9.
10:37 Speaker 01 What, what, what would you rate me if I had to write marketing copy for a marketing company? Like marketing software, marketing agency?
10:45 Speaker 00 Probably like a four or five.
10:48 Speaker 01 Out of 10?
10:49 Speaker 00 Yeah.
10:50 Speaker 01 Like writing copy for my own website.
10:52 Speaker 00 For, okay, writing copy for your own stuff, like when I think about like quick sprout, for example, like I think eight point five nine out of ten. I think if you're writing for an agency, actually, no, you have written for your agency. I think, no, I think you do do a good job with, yeah, so I would say probably around the same range. Uh, but I I don't know why I think you, what area do you suck in? I I clearly think you suck in one area. What what is it? What area would you suck in? Yeah, what area do you suck? I I think you suck at something, but I don't know what it is.
11:17 Speaker 01 No, in copywriting or something specific in marketing?
11:20 Speaker 00 So, no, in copywriting.
11:22 Speaker 01 No, overall in copy, I'm really good.
11:24 Speaker 00 Yeah, but so I my point is, I think you're good overall, but I clearly, I think you suck at something. I don't know what it is, but continue.
11:29 Speaker 01 Okay, so let let's say he's eight point five. I I I agree, I'm not the best marketer at everything. I probably would give myself a nine out of ten. So similar, I think Eric was around eight point five.
11:39 Speaker 00 Eight point five nine, yeah.
11:40 Speaker 01 Yeah, so similar, I would give myself a nine out of ten. I never give tens, I always think you can get better. But how often do you think I use AI or now let's rate chat GPT or Claude or any of these for copywriting compared to me?
11:52 Speaker 00 Two or three.
11:53 Speaker 01 Okay, so people would assume, and Eric already knows the answer to this. Um, he doesn't know where I was going with this, but he knows the answer. Even though I'm a much better copywriter than AI itself, I'll come up with copy variations. And once I have the versions I really like and want, not always, but maybe like fifteen percent of the time, twenty percent of the time max. I'll put it into AI and ask them for more variations, because you know what? If you give them a good input.
12:22 Speaker 00 Yep.
12:23 Speaker 01 Sometimes, very rarely, but sometimes it does come out with even better variations than what I came up with. So even though AI is not as good a copywriter as me, if you take someone who's really good at what they do. And then they input that into AI, it can give you really good outputs.
12:39 Speaker 00 Yep, and to Neil's point, this is all garbage in, garbage out again. So if Neil has already written it already, and then he just runs it through a prompt, it's gonna be much better than saying, write me a good marketing article. That's not gonna work well, right? And you know why my X articles do well? It's because I work with it all the time. I'm like, hey, what's all the cool stuff we worked on recently? And then I might dictate out something I want to talk about on top of that. So you have two layers. Then you get something really good, right? But you're not gonna get it if you don't give it good context. Because like, again, like, how is somebody supposed to just read your mind and just create something that's gonna work? Like, it's never worked like that, so.
13:11 Speaker 01 I know we're running out of time, but I'll give you a pro tip. You probably may already be doing this. I was talking with Sam from Right Sonic. He's doing something that's really interesting. He takes all the news within a category. So you could be AI, marketing, you pick whatever industry you're in. Then he looks at that news that's coming out, he looks at backlinks, social shares, comments, engagement, shares, whatever metrics he can get, because some platforms are closed, some you can easily crawl and scrape. And he's looking at that in real time. So like an hourly basis, right, as close to as real time as possible. And then, of course, he's still looking back a day, two days a week, etc. That tells him what's really hot in his industry.
13:53 Speaker 01 And then they looks at everything that he's created in the past that's resonated with his audience and what hasn't. So cross references that eliminates all the stuff that it thinks would not do well based on his audience type. And then he has AI create variations of the stuff that did well with his own taste and flavor and adding his own thoughts. So he's not just ripping or copying. He's just using that topic. Like if there's something new in the news that Claude is releasing a new model and everyone's sharing it and it's going viral, call it um nine point eight out of ten times. He'd be like, if I create something on this tied to marketing, it'll do well. And the AI creates something related to that based on what I can see around the web. He goes in there, fine tunes it, publishes it.
14:37 Speaker 01 Uh, his engagement numbers from the stats that he was showing, he was screen sharing. So it wasn't actual like a dashboard comparing posts, but we went through like ten posts. Um, no joke, it was more than double the engagement for all the posts that he was using the AI versus the ones that he was doing by hand. So the AI ones performed by double compared to the ones he was doing by hand. Sure, he had input on the AI ones, but it just goes to the show the power if you combine humans with AI.
15:05 Speaker 00 Yep. Yeah, I mean, guys, it's just, it's just technology. It's no different. Like all technology exists to help make human life better. That's what I believe. So anyway, that's a good place to end it. We will see you all tomorrow. Don't forget to rate, review, subscribe.
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