A Product Market Fit Show | Startup Podcast for Founders
00:15:12 · Alex Halliday
[00:15:12] S0: Yeah, I mean, I think it's interesting that we created this separate category of AEO for a long time and now I think there is this conflation again into one system. Which I think is actually a better model. You know, Google is going AI first with AI Overviews and AI Mode, ChatGPT, and now Claude. Very important for businesses to understand. I think much of the practices that worked very well in SEO continue to work, but the contrast is turned up on some of the sub-bullets. In particular, the importance of information gain, so adding materially like net new information to the market through the content that you write. So Zola is a customer of ours. They have all this pricing data on how much things cost in weddings. So they create these pages which talk about how much wedding florists cost and wedding buffets and all the different variants of weddings. Because they have all this really interesting data inside the business and so their play is really providing, the models and human users with just this amazing set of content. That talks about all of those interesting pricing and vendor questions that come up. Maybe Klaviyo is another example of ours where they have all this data on email open rates and the behavior of email for marketers, and they can use that to combine with their internal experts, and internal expert interviews to create rich content about all the practices that email marketers do. Because that's the audience they're really trying to talk to. So I think information gain is one big theme of how can you take unique information from inside the business and put it outside the business.
00:16:43 · Pablo Srugo
[00:16:43] S1: Let me ask you this, maybe because I'm selfish and maybe we can make it tangible. We go through some of the ideas through this. Let's say I was actually a customer, for the Product Market Fit show and I'm like, I want to get more views. I want to get more traffic. I want to rank on all the chat apps and on Google and all this stuff. And money is no object. I'm not going to, I don't want to do paid stuff, fully organic, but money is not the issue, right? What would be some of the things that would make the most sense to do?
00:17:05 · Alex Halliday
[00:17:05] S0: Yeah, so one thing we would do is we would figure out the intents that people are expressing that the Product Market Fit show probably isn't a good place to answer. So we would have a couple of agents that would spend their time looking at startup conversations, Hacker News, Reddit. Really understanding what the evergreen questions are that people are asking and the discussions people are having. And then what new questions are emerging, because Claude Code is on the rise or the QBs might be removed from New York State, right? So you really want to think about evergreen questions and then frontier questions. So that's the intent cloud that you have a right to speak to, and then it's the content creation to speak to that. And so, you would put all of the transcripts that you've ever had on the show with a definite bias to the most recent ones into AirOps or into a system like Google Drive or wherever they live and you connect them to us. And then, we would have a process which would on a regular cadence, identify the highest priority questions to answer. Would ping you to then go and approve those along with a ton of research from your shows. Probably some questions for you to answer as well to really make sure that that article had your perspective, your overarching narrative and then we would publish that content rich with references to your shows. Like links to where people could go get them on Apple Podcasts or YouTube, and treat that as an ongoing content production drumbeat. So that you can start to get all of the great value out into the world in an organized way, and then on the pages of content themselves. We don't have to go into all, but there's best practices around structuring that content to make sure you're basically spoon feeding those answers to the models and preparing them for citation. Because ultimately you want to be quoted a nice big paragraph in a ChatGPT response saying on the Product Market Fit show, Alex Halliday said, XYZ, and that's a really useful chunk that matches the user intent that you've identified as one. So that would be one loop that would be really valuable to you. You'd be totally within your rights to create that and it's a durable strategy for you. It's not something like gaming the system and consumers would love it. You're adding to the conversation.
00:19:14 · Pablo Srugo, Alex Halliday
[00:19:14] S1: That's the classic blogging approach, just using AI to make sure that you're always touching the latest frontier questions and leveraging as much of the work you've already done in the past. [00:19:25] S0: Yeah, and I think if you were a brand in that same situation. You would really think about what are the offsite, like not on your own domain. What are all the pages that influence the ChatGPT for those priority questions as well. So we do a full audit of that. You've got, a heat map of influence. So maybe Reddit or a Substack, or a YouTube channel driving most of the sentiment and opinion for the things you care about. And so, the play for those would be different. Obviously, it wouldn't look like publishing. It would look more like outreach or conversation participation. [00:19:56] S1: Let me ask a little bit about competition. Competition has really risen to the top, at least for me as a VC. It used to be a bit more of a secondary thing. I think any investment, obviously, you ask about competition but it was not the most important thing. Lately, it just tends to be number one. Because there's so many ways to deliver insane value. Really, the big question is, why isn't everybody else going to do it? With the example you gave, my question would be something like, why couldn't I, or what's the difference between what you're offering and let's say putting all my transcripts into Claude Code. And then, having a scheduled task that runs every week and checks the latest questions, and writes a block for me.
00:20:31 · Alex Halliday
[00:20:31] S0: Yeah, it's a great question. I mean, you certainly could do that. It actually might work quite well, to be honest, given that use case. But if you think about content in the current market, competition exists on the startup side but it also really exists on the content side as well. So each piece of content is in composition with a sea of other pieces of content and so to get the most from an AI model. It's much less so the capability of the model, it's much more so the context that you can have available for the model, right? When doing any sort of content task inside of AirOps, we have a huge data engineering team whose sole job is to make sure that we can give that model an unfair advantage when it's tackling your problem. So if it's, for example, a page you want to have ranking in Google search or it's a particular question for ChatGPT. Before you even start writing we understand every single page that is in competition with it, we understand all of your pages that could be in competition with that, you don't want to cannibalize your own content. We understand which questions you should even be going after in the first place. We collect almost one point two billion answers every sixty days from these answer engines and we analyze them. And then once you create your content, we also have a full picture of your tone and voice, your do's and don'ts in your language, your sitemap for internal linking. So you can think of this as like if Claude is the model at the beginning in the center of the picture, can you give it these concentric circles of knowledge that are actually quite hard to compile, but give it that unfair advantage so the content you create is more likely to win, and then the nice thing also about doing things through us is we also track the impact. So you know, hey, in January we published twenty eight pieces of content. We know that ten of them are absolutely crushing it and we should go do more of those. And that knowledge feeds back in to our agent on a go forward basis. So I think in the case of like working with your transcripts, you would have a really good result just doing that with Claude Code and that works well. I think when you're dealing with tens of hundreds of thousands of pages or millions of pages.
00:22:33 · Alex Halliday, Pablo Srugo
Prioritization is the most important thing, followed by the context you can provide on competition and those are two things we nail for our customers to make sure they continue winning. [00:22:44] S1: I'm really worried because listen, you've been listening for what? Ten, twenty, thirty minutes now? Clearly you like it and the thing is, the next episode is way better and you're going to miss it. You're going to miss it, because you're not following the show. So take your phone out and hit that follow button. And do you see any reasons for what works broadly? Because again, we think about this strategy, it's the same strategy just done with AI. But is there any reason that this changes? This is something you hear a lot. It's like, well, there's going to be so much AI written stuff, slop. Whatever you want to call it, whether it's good or not. It almost, when you just think about that at a high level, you're like, there's no way this is still the future. There's no way five years from now, it's still all about blogging. There's going to be so many blogs, but is that real? Or is this just going to be, this is still the strategy and there's a reason for it?