I’m Dominating SEO. If You’re Struggling To Get Impressions, Watch This

0:00Eric Siu:Using only 20 % of your business data is like dating someone who only texts emojis. First of all, that's annoying. And second, you're missing a lot of context. But that's how most businesses operate today, using only 20 % of their data. Unless you have HubSpot, where all the emails, call logs, and chat messages turn into insights to grow your business. Because all that data makes all the difference. I would know because I use HubSpot at my company. Learn more at HubSpot.com. The new way to do AEO and SEO is via API. And you know, it's interesting. We had a call recently with a company that is literally they do documentation for dev companies.

0:37Eric Siu:Okay. So let's say they're doing just call it$10 million a year. Okay. They raise a lot of money. Let's just say$24 million to do this documentation. Okay. And the interesting thing is they've gotten to that, that level by having like a powered by button at the very bottom of the documentation they do for everyone. Okay. So anyway, my point of saying this is that I think they use an API. So ClickFlow, we have an API as well that people use to generate content with. But I think the way you're going to do it is like people just go log into Cloud Code, command line interface and just say, hey, can you just do this for me?

1:05Eric Siu:Can you build this for me? They can plug it into their agents. The agents do the work. The agents could go out there and buy stuff. There's a ramp CLI now. So the agents marketing agents type of thing. So I think most SEO companies now or AEO companies, whatever you want to call them, the way to do it is via API. And we have the documentation for ClickFlow. And we actually use that documentation company for it. but I think it is using API because you need it to plug into your agents to get the work done faster. And if you aren't doing it that way, I feel like, you know, it's not required right now, but I do think it's, it gets work done quicker for you.

1:36Neil Patel:Did you see that LinkedIn thread on how they know and how they mark that their content and the stuff that AI is creating, they know that it's AI generated? You mean like Google?

1:45Eric Siu:Yeah.

1:46Neil Patel:And I'm a big believer that they genuinely do know, you know, I was a believer even before I saw that. I was a believer that they do know that when content is AI generated, because if you look at all the stats and the data, even though both Eric and I have our own AI content writing tools, it does not rank well. And you could get short-term traffic, but over time we see AI content just not do as well. And it doesn't mean you shouldn't use AI to write content. It means you should use it in different parts of the content writing process. It's great for ideation. It's great for structure. It's great for research.

2:19Neil Patel:a lot of the writing I highly recommend doing it manual and I believe it's gonna keep going that way because if AI doesn't care if the contents written by AI and then they crawl it and then use it to create more content and keep learning it becomes a self-fulfilling prophecy and then

2:36Eric Siu:it starts hallucinating and they don't want that so what we do for a click flow so so what I've heard the customer save so what I've heard from our people working with the customers is that the content that they generate, sometimes they're just YOLO and let it publish. But similar to how like, like a fin does it with customer service, right? For like, sometimes I have a hard time believing this. And I've seen the content quality myself. I'm like, this is really good, right? But they say this is better than any other content generation tool that they've used. And that we have a human in the loop, right?

3:03Eric Siu:So that's what helps. So when they say like the content helps them get more citations and it ranks better, it does. But there's a lot of caveats. There's one, we have a human in the loop. Second, we spend a lot of time on iterating on it. And so that goes back to what you're just saying about Harvey, you can't just let it YOLO on its own. But I do think if we can get to a point where we have a lot of data around it, and we can just release our own LLM down the road, like a vertical one, that's like down the road. But that's at least what we're seeing on the ClickFlow side.

3:28Neil Patel:We've been seeing something interesting with content. So you know this, a lot of companies are publishing listicles on their own website. If you look at like chat GPT, and when they're doing the searches, I was with Sam from WriteSonic, a lot of the prompts now have site colon commands. So like chat GPT will run a site colon command on your own website to see the articles you have to see if it's relevant to what people are asking. And a lot of companies are creating articles like the 10 best web design shops, the 10 best really well, like a year and a half, project management shops and whatever, CRMs.

3:57Neil Patel:And they're creating their own pages for the services or products they offer. And what we're seeing is even though it can help you with GEO and helping you do better on chat GPT within six or so months of creating a lot of those listicles, assuming you do it in quantity, we see it hurt your organic search traffic.

4:14Eric Siu:So

4:15Neil Patel:it's just like, we think that's the wrong approach because you're trying to do better in one place at the cost of another channel. And we don't think in the long run, at least at my company NPD, that you should be publishing this content on your own website or even publishing the content, because this kind of content is something where it'll help you with the algorithms now, but we don't think it'll help you with the algorithms in the long run because it's just easy to manipulate. Yeah.

4:42Eric Siu:Real quick, if acquiring customers has been a struggle for you and you are trying to figure out how AEO works, answer engine optimization, or the new version of SEO, how paid works, how all this AI stuff is going to play into your customer acquisition strategy, then check out my ad agency, Single Grain. It's singlegrain.com. And if it looks like it's a good fit, we'll help you with a free marketing plan. So again, go to singlegrain.com and we'll see you on the other side. So businesses can sell directly via meta and chat GPT ads. I think we're going to see a lot more of this. That's we're not saying by the way, get rid of your website.

5:09Eric Siu:I think the website is still important because the more information you could give agents to crawl the better. So documentation around your software, very important in my mind, whatever other information you have, get it all out there, do more podcast interviews, get your YouTube channel out there, you know, keep doing what you're doing because that stuff, they need stuff to ground on. It's not going away.

5:26Neil Patel:This is a random note. This is a marketing related, but you want to know what my wife does to try to make us all healthy every single week. What? Make you wipe your butt with clean toilet paper and organic?

5:36Eric Siu:No, but I don't know. I just bought a bunch of organic toilet paper.

5:39Neil Patel:I don't know what my toilet paper is.

5:40Eric Siu:Let me tell you what I bought. Go ahead.

5:41Neil Patel:Okay, so what she does is she chops up different vegetables like in different colors because, you know, like radish is a different color than cabbage and all this kind of stuff. And she tries to get all the major vegetables in her body every single week. Not every day because it's too hard to get all of them in. And then that way we have all the different colors and vegetables because she saw some report on how different vegetables have different things for you and the colors are all natural. And she just chops it up so tiny in food like lasagna that you can't see and you just eat it.

6:12Eric Siu:That's good. That's smart. That's a lot of work. What did she use to chop it all?

6:15Neil Patel:Her hand.

6:16Eric Siu:So let me tell you this.

6:17Neil Patel:So by the way, we'll move on. Don't worry, guys. We'll bring this back to marketing in a second. So I bought this, okay, real three-ply soft and strong bamboo toilet paper.

6:26Eric Siu:and I just started using it yesterday, like 4.6 stars, 4 ,000 reviews. I saw this on Instagram and I bought it because someone was writing something about the toilet paper you use. There's PFAS and all that because I was using like the Amazon one, the Charmin one. It's like, no, you got to get this if you don't want PFAS in your butt. What's PFAS? Forever Chemicals. I didn't know that. Yeah, so now you know. See? Better for your butt. Well, typically when we're home, we don't have toilet paper.

6:50Neil Patel:What? Do you use your hand? No. Our toilets are bidets. Dude, that's not enough. And then we have wet wipes.

6:56Eric Siu:Okay, yes, but I don't know what the wet wipes are in it's toilet paper But what wipes are made from like bamboo too or something like that. So it's like it might plant-based the dude wipes They're expensive. We don't use dude life.

7:06Neil Patel:So we use another organic brand. I think it's organic for the wet wipes I'm pretty sure everything in our house is organic even though it doesn't mean much for food Yeah, but we have bidets that clean you and then you have the wet wipes on top of that there's sometimes though the bidets

7:20Eric Siu:We'll just leave it at that. I'm just gonna send you this so you can buy okay guys let's bring this back to why a b testing is dyke so back to marketing guys yeah we're getting close to the end so yeah we are we still have 14 minutes left so a b testing was the gold standard for product decisions for 15 years the best ai companies abandoned it so this is from akash gupta for a generation of pms experimentation meant designing a controlled test allocating traffic waiting two weeks for statistical significance and hoping you had enough sample size to learn something that loop trained an entire discipline to think in cycles of weeks evals compressed the loop to minutes.

7:52Eric Siu:Three components, a set of inputs your product needs to handle. Number two, a task that generates outputs. Three, and a scoring function that produces a number between zero and one. You run on your laptop, no production traffic, no two-week wait, no data engineering pipeline. The math on what this changes is staggering. Teams running evals are doing 12.8 experiments per day. That's roughly 384 per month. A traditional A-B testing team runs maybe three. Over a quarter, One team has explored 1 ,150 variations. The other has explored nine. That learning gap compounds every single week. So the point of saying this, so he mentioned Ankur Goyal build the eval platform behind Vercel, Replit, Ramp, and Notion, $800 million valuation.

8:32Eric Siu:He ran an eval from scratch on this episode. Went from a score of 0 to 0.75 in under 20 minutes. That's a PM shipping a measurable quality bar before writing a single line of product code. So let me unpack this for people. So Andre Karpathy, super AI researcher, did he released auto research. I think these two kind of go hand in hand because auto research allows you to run computer experiments very quickly, right? AI experimentations. We're talking like every five minutes is running one and he's just leaving his computer on and doing, and he's found things that he couldn't, he's like, dude, over like 20 years of doing this, like he found a bunch of things that he didn't even know were possible.

9:04Eric Siu:Okay. I think when it comes to evals, evals are just, it's just a simple way of saying, Hey, what is defined as a successful test versus a non-successful test? That's all it is. Okay. Yes. And then you're just running it over and over, but we're going to see a lot more of this. And depending on what you're doing, if you're sending cold emails or if you're running paid traffic or whatever, you do need a good enough sample size when it comes to marketing. And you can't just say you're going to do 384. So I think it depends on your data sample size. But now when you set these agentic platforms up or your agents up, you're just going to say, Hey, I want you to run these tests.

9:38Eric Siu:And I want you to every week, I want you to run evals and just so it can recursively improve over time. That's where is all going and that's where a lot of this stuff has already gone with ai but not it's kind of starting to encroach on marketing so this way he's talking about we've seen this happen for years

9:52Neil Patel:this is it's new to a lot of people but it's not new in the bay area or the startup world there's one issue with this model it only works if you have high volume if you don't have high volume you can't do it i think for most companies who aren't heavily venture funded startups or large enterprises, they can't leverage this because they don't have volume. And a prime example of this is if you're a new entrepreneur, you set up a D2C e-com site, you're doing drop shipping, you're not even creating your own product, you're running Facebook ads, and you're getting five sales a day. And that's it. So 150 a month, you don't have enough conversion volume to run this playbook.

10:36Eric Siu:I think what's going to happen. So exactly what we're saying. But I think we're going to be using a lot more synthetic data in the future.

10:43Neil Patel:Well, if you think about, you know, MMM, MMM has been out for ages and it's what people have. What's MMM? Media mix modeling.

10:54Eric Siu:Okay. Yeah. Right. I thought you were talking about M &Ms.

10:56Neil Patel:No. When you think about, and some of the solutions that Google offers and a few of the others, right? Median and the list goes on and on. When you think about it, you're taking data from what happened in the past to figure out what's most likely going to happen in the future. And it's saving a lot of time and money. And companies are also starting to look at not just, hey, where are we spending our money and where should we? They're also looking at incrementality in which, was this person actually buying because of the ad or were they already on the checkout and gonna buy anyways and the ad just took credit?

11:32Neil Patel:And that's another big problem in marketing as well because we spend a lot of money on advertising, but yet was the sale actually caused by, you know, marketing or was it not? And dude, we see this all the time. And the way you see this is not what I'm talking about incrementality or, you know, causality. It's when you have the executive team just being like, what would happen if we turn off all our ads? Let's try that for a week, right? That's their way of saying, did the ad actually cause or does marketing actually cause more sales for us or is it just taking credit for sales that we would have already gone and it isn't that simple because if you just turn off your advertising and your marketing for a week a lot of what you're closing in that current week came from people who saw your brand and from advertising and marketing that happened you know months ago or a year ago so it of course isn't that simple but you know when you think about incrementality testing and you think about MMM, because of AI, it's more easier for companies of all sizes to use this stuff while it wasn't possible for smaller organizations in the past.

12:43Eric Siu:Yeah, I think what people can learn from this. So what Neil is saying is true. This is not necessarily new on the marketing side, but I think on the PRD side, so a product requirements document, this guy is basically saying that evals are the new PRD. And so when you have a very specific spec-driven document, and it shows like, it defines what a win and what a loss is. I think this is going to be built in a lot more to whatever agents I'm building, for example, whatever workflows that I'm building. So it's just on top, like, hey, I want you to have an eval here, right? That's just going to be built into whatever scaffolding that you have in the future.