Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGrowth Partners

Please welcome to the stage Guillaume Cabane, co founder and GP at Hypergrowth Partners. Hello. Thank you. Usually I would like run and jump over here, but I broke, I tore my acl so I'm gonna not gonna jump on the stage today. So I'm just gonna limp like around like this. Thank you for coming in this early in London. So happy to be here. My second time I was here last year, had a great, great event and it's looking to be the same today. So today we're gonna talk about how we get more customers. For any of you who are interested in making more business, that's what we're gonna talk about. So I'm Guillaume Caban, everybody calls me G, so feel free to call me G. And we changed a lot of the deck over the weekend. Jason wanted us to go from something more theoretical to something more practical. So we pulled up a lot of examples from the advisory clients that I have to show you how it's really done. Leveraging AI tools in today's marketing teams. There might be some holes, but point them out, we're not afraid. So yeah. I'm the co founder and JP at Hypergrowth Partners. We are a collective that does advisory for high growth companies. Previously I built the growth teams over at Drift Segment and Gorgias and I've advised Ramp, Reddit and many other companies. When I say an advisory collective, it means we are somewhat like a VC fund, but we don't give out capital. We, we invest our time in exchange for common stock equity. And we have about 30 senior leaders around the world working together. Now that, that said, today we're gonna talk about a couple of things, but mostly around how do we as marketing leaders take in the AI platforms, the AI tools we have today to be more efficient and a couple of wins that I've seen in a couple of channels. So I'm going to cover outbound SEO and paid. But first, I want to have a show of hands today to wake everyone up. Can you all tell me if your company has reduced headcount or decided not to hire because of or thanks to AI recently? Can we have a show of hands? Okay, so I'd say we have like 10% of the people. Okay, I'll ask the same question one year from now. My bet is that we're going to see at least 30% of the people. We can have a reduced headcount or less hires. I'm going to show you why today. Okay. So if you think about it, the real impact is that a year or two years Ago we were in, well, AI is good, but it's like less quality than humans. It's less. For less. Less cost. Right, Less quality for less cost. And nowadays what I'm going to show you is we have more, more quality, better quality and speed, but for less cost. Right. So what does it mean? Well, if you look into the, into the cost angle first, right. Typically what you see is you have different cost of acquisitions promotion, right? You have, you know, on the far right here you have like sales led, which we used to know, which is fairly efficient in terms of closing, but has a fairly high cost. Right. And on the left side you have PLG product LED growth. Right. Which is fairly cheap. Which is why when we were in the economic crisis of Quinu Post Covid, all the VCs were asking founders to do PLG because of like free acquisition. Sure, that sounds great, right? What they don't see or what they don't think is that PLG generally drives, sure, lower cac, but lower contract value, smaller customers. All right, and so you have kind of like this spectrum here from let's say low contract value, low ECV to high ecv, which is correlated with low CAC to high cac. All right? And that's a pretty typical distribution, you know, like a 10 to 1. And with, let's say those CACs, those ACVs, you have that typical like segmentation from micro to like enterprise. Okay? And with those, with that segmentation you have the channels. So on the, let's say cheap side, low CAC side, you can have like the SEO and the virality, all the PLG playbooks. In the middle you find like the outbound, right? And on the far end you can find the ABM and the partnerships, right? But that, that's yesterday. The point of that strategy is what we used to do for the past 10 years, right? Because if you follow like the logical conclusion of the AI shift, like what's, what's changing, right? The fact that we're now capable of doing faster and better quality. Example, we can scrape websites, we can scrape random content for extremely cheap and feed that back into AI prompts for outbound. For SEO drives an extremely low CAC on those channels. Which means what used to be mid market channels can now also be SMB channels because the CAC is dropping. You can have new audiences. If you look at this distribution, you can now do things like this, right? You can start saying, hey, I'm gonna acquire your startups through outbound. I can acquire mid market through SEO. How does that work? Well, it's easy. Like mid market prospects with SEO is possible because you have better quality, better diversity of content. You can create extremely high volume of high quality content. And on the outbound it's kind of the same thing. Right? Because you're no longer employing SDRs, which have a high cost. You can, at the same quality you can get lower contract value customers. So that's probably like the key learning we're gonna like hover around today is that the CAC to channel fit is changing and you gotta adapt to this new reality. Okay, so let's look at the first one, the first channel, like the biggie outbound. Okay. If you think back to like 2015, like what were the best SDRs doing? Like, I always learned from humans. You know, my, my wife is a sales, used to be a salesperson, so I learned a lot from her. Well, they do information gathering and research, email content composing and outreach on LinkedIn and whatnot and they're being persistent. Okay, this works. 2015, 2018. It's slow and it's high cost. You look in the middle. What happened is that everybody started automating those sequences on like Apollo and Apple markets. We started having like huge volumes but low quality. And with that, well obviously the conversion rate dropped. What's happening since last year is that we're capable of doing, as I said, scale scraping, data acquisition and generating high value emails. And that is, and I'm seeing it, it's driving the conversion rate back up at a high volume, but the CAC is even lower. So we can have better performance than humans at a lower cost. This is the shift that we're seeing, right? And if you look at something like this, look all those data sources, there are a ton of sources we can get great data from. But let's, let's be honest here. Like which SDR is going to like do the job of going, going through at least one of the logos per data source to understand that, prospect that customer and compose a great sequence. Who's gonna do that? No one. They don't have the time. They've got minutes per email. A good AI can do that. All right. And I'm not here selling anyone AI. I'm just saying, like I'm gonna show you how it's done. So let's jump into an example that I worked on recently. And this is my latest advisory client, Reddit, fairly well known social platform. And they gave me a goal. Get 10% of the US advertisers advertise on Reddit by the end of the year starting from pretty much zero, which is a pretty big goal. Okay. The first idea I came up with is, well, let's scrape the Facebook and, you know, LinkedIn and Google Ad libraries, which are like public repos. You can find all of the ads, understand the ad, make sense of it, understand the company, understand aggregate third party data and inject that into an email. Well, for that example, we went with Clay just to prove out the feasibility of the concept. It's a good CDP and workflow platform to start. Not that I would recommend building something at scale there, but to explore, it's great. What you can see here is we have a prompt, we're trying to figure out the Facebook page so we can find the ads, and then we're querying an endpoint to find the ad data. What you're not seeing behind the scenes is that we're making sense of the ad and injecting that into an email. This is an example. All right. And so here it says like, hey, I saw your ad on Facebook. Here's a summary of the ad. We even inject the ad image that we saw. And then because we made sense of the ad and we made sense of the company, we who can start recommending the right subreddits where they should advertise. This email is super personalized. It makes a ton of sense. And we build that entirely automatically. And it works for all the US Advertisers, which is the entire market. Once it's done scaling, that is extremely cheap. It worked great. We have done this in less than two months. And as of yesterday, I looked up the numbers. We've beaten the SDR team that's been working on that for like a couple years, and there's 200 people. So, yeah, you can question the future of the SDR role when you see things like that. Right. And when I'm talking about the headcount I saw two days ago, three days ago, I saw this post from Maxime and he's saying, hey, we're having an Outbound AI growth lead. Somebody who does Outbound, who's good at growth, sales, ops, tech, marketing, copywriting. Now that's interesting. Means founders are reacting and are thinking, instead of having a sales team, SDR team, I'm just gonna have like one super skilled person who's gonna run the workflows. Okay, so what does it mean for like this like 10 year, 20 year, like sales marketing battle? It means marketing has won. That's what it means. Right. It means that Outbound is now owned by growth and Marketing teams, okay? Just embrace it like that. That war is over, okay? Because we can with those platforms. Scale scraping, tab building, intent signals. Like the key learning out of this is sequences are dead. If you think that the best way to engage customers is, is to have a series of pre written templated emails that are gonna fire until somebody responses like, you are in like the 2015, 2018 era. You're like two eras removed from reality. Okay? Every new email is built purposefully based on the situation, the data we aggregate and the existing conversation automatically. So that was for Outbound and now SEO. So because we have some of the best people at Hypergrowth, I've pulled actually advice from Kevin Indig who was the worldwide head of SEO at Shopify and Atlassian and Marcel, who was a CMO at Deepgram because they're better at me on SEO. And the summary is we're coming off of a world a place of pretty bad SEO, to be honest. All right, we all like, I am the main culprit here for sure. But like, we all like outsourced the creation of like a lot of SEO content to fairly, you know, low quality freelance writers to get, you know, on the search engine. And which was mostly like either like low cost generation, low value content or tokenized and spinning content, which all also produces low value content. Okay, so no one wants to read that. It kind of worked until it didn't. The playbooks that do work, the winning strategies in the previous era was like what we saw doing from like Zapier G2. If you think about it, like Notion and G2, they have this amazing, you know, product led growth and user generated content UGC in B2B, which is very rare. It's very hard to pull off. Like G2 has this treasure trove of like SAS reviews that no one else has. Okay. Or Zapier hired a team to build all of those like integration catalog. Okay, that's both of cases can be done, but like they're very expensive. They're very expensive. Okay, now we can use LLMs for programmatic page creation and we can get the data without the workload, uh, which in a summary can be like, not everybody can have a strong UGC motion, but everybody can be zapier nowadays. All right, so let's look at how it's possible in this case. This is for Deepgram. Um, and so what they did is that they did some very typical SEO keyword research. Like find the keywords that they think their audience is searching the one they want to rank for. Okay. Fairly easy Then they're using airtable to store that in an observable database, a command center, just like we were using Clay in the previous outbound example. And so now they have all these keywords, they have all of this data. Okay. And they're now using Air Ops, which is a LLM orchestration platform, which makes it possible to have different sub agents. Go look for what is the best title, what's the best page, where does the best screenshot, what are the examples? We have different. And then they bring it back together into one prompt with the data injection. That is a much better way to create content than have a huge prompt that tries to do everything because it tends to fail when you do that. And so we try to just break it down. We store the data in airtable and then we feed back the data from airtable into the final. Into the final agents. Okay. It's a fairly advanced workflow, but check out the results. The prior stage, like up to 2023, was like trying to do it manually with like, low budget. And this is when they're like, well, let's just like automate this. Okay, let's just automate this. They got 3.5 million clicks. Like, how insane is that? So what are we seeing here? We're seeing they have one person to build a workflow. And Marcel told me it took him like about 1000 hours. Sure. Okay. And then one human who's there ongoing for like control and validation. Okay. It replaces a team of 10 people. That's what it does. Okay. For now, it's possible to use LLMs to get organic traffic from SEO. Is it gonna last? I don't know. We'll find out. But there is a time window to exploit this right now. Scraping websites, building unique content, enriching it with third party sources, and doing the quality control. Okay, critically, last line here on the slide. The workflows with AIs currently produce better content than autonomous agents and better content than humans alone. Unless you're ready to pay like $10,000 per post. Okay, so better strategy. Let's go into paid. So paid, we got the. Oops, sorry, I skipped paid. We got the feedback from Rex. Rex is the world's best guy at paid. He handles all of PAID at HubSpot Worldwide. He is one of the very few people in the world that have spent over $100 million on, on Google search alone over the past five years. That's very, very rare expertise. And so before we used to have fairly, you know, fairly standard situation, you had either a paid team in house, or you had, you know, an agency or freelancers, okay? And the work that they would do is you would segment the ad campaigns by various customers, customer traits like genders and interest, geolocation and product, things like that. And then you break that down into, you know, the ad groups, the campaigns, the ad group, you know, the keyword targeting, the ad copy that goes with it, ads. And then you are fine tuning the bids all the time, okay? And Google tried to introduce AI support tools over the years, which didn't really work that much. The learning is. As of six months ago, that has changed. And it is working. Absolutely. It's making the job seamless. Like the LLMs now inside Google Ads are making targeting better, okay? They're better at showing the right creative. They're better at showing it to the right audience, at setting the bids, okay? They're gonna get you more conversions than you could manually if you try to override the AI. What's working the pro. The problems that are solved are audience targeting and bidding. What remains for us humans for now is the research part, as we saw, as well as the creative process. But wait, the creative process, the teams are also reduced. Like, we're seeing the first products where you can build ads, creative ads, and design ads just based on your website. It will create the ads and the video ads for you at $0 cost because they're happy for you to spend the money. Okay? So this is just the beginning. A practical example of this is, you know, the. The TLDR is if you're still trying to fight AI by segmenting campaigns into a ton of different budgets, like, you know, Netherlands, Luxembourg, and Belgium, and setting, like, different budgets here and there, you're fighting the wrong war. Just stop. Like, let the ad network figure it out for you. You know, let's. Let's say that you expand into. Into Benelux, right? And you have those. Those ad budgets, maybe Google's AI would have preferred to spend 7, 18, and 5 on a particular day or every day. And in the tests that we've done, the more you handcuff the system and restrict the AI, the fewer optimizations it can make on your behalf, and the worse off you will be. So what this means for paid teams, right, is, is that you have your job now kind of similar to what we saw in SEO. Smaller teams, more technical teams. Your job is to build the infrastructure to enable the AI platforms to learn, okay? The data quality is critical. It has to be able to learn the good and bad outcomes, okay? And you need enough budget to ensure the volume conversion again so it can learn. Okay. You gotta, you gotta create the conditions for that to work. And I'd say these days you're seeing different depending on the platforms, the conversions being like between like 25 to 50 a week so that this kicks in and you can start using things like performance max. Performance max. So a couple of takeaways that I want to share. I have a lot of takeaways. So across the board, generating leads comes with like less humans and more AI models. Okay. As we discussed, like, this is a final takeover of SDR into technical marketing roles. Okay. More than ever, this is a battle of cac. Okay? The AI change shift is shifting the CAC of many channels. It's opening channels to us marketers that we did not consider for those audiences. Okay. If you invest in technical people who can build the workflows that we saw, they can beat at least on SEO outbound channels, the pre existing teams at their game. Okay?

So.

Invest in those technologies in AI workflows and you will thank me later. Just two deep thoughts before I leave you and we can go into the Q and a seemingly unrelated one is the tech cycle is accelerating. I've been doing this for now 20 years. I've been buying, I bought millions of dollars of SaaS over the past 20 years. And I used to be able to make a good evaluation, a strong recommendation and say, hey, this recommendation that I've done based on all the software I've seen to do outbound or whatever is good for the next couple years, this is the winner. This is the best technology these days. I make a recommendation, three months later, it doesn't make sense anymore, right? Because there's this new company, this new model or usage of a model that completely changed the game. It is really hard for me and for all marketing leaders to build conviction on which technology to build. On top of probably this means you need a composable tech stack. You cannot invest all of your marbles in one big platform. You do want to be able to compose with different technologies, have an independent database, and so you can switch and replace parts of your workflow. Second thought, I've just given you like 20 minutes on how AI is better than humans at many things. I believe that's true. I believe also we're going to see something opposite. We're going to see like the certified real human, which can be the new like Parmigiano Reggiano of like sales or like, hey, like this is a stem. This is like actually a meat bag that's talking to you. And some people are gonna like that. Some people will pay more to be able to like engage with a real human. And that's a reality. And we probably want to think of how do we offer those two paths? Right. Maybe there's a VIP treatment for the enterprise prospects. Speaking of which, are we seeing the same shift in, in closing on the AE space? Not right now. For now, most people prefer humans. However, I'm seeing the first steps in AES becoming the puppets of AI models. If you think of Gong Gong records and understands the entire like deal situation and will recommend to the AE what to say, what not to say, which competitors to bring up, and how to price, that is the AE being the puppets of an AI model. Okay. I'm also seeing some industries where the, where there's some models being built, some chatbots to do the closing, built on the conviction that some buyers will prefer buying from an AI model. You think that's crazy. I think that's crazy. But there's a great example. Look at tech buyers, engineers. Do you think engineers prefer talking to a sales rep or to an AI model? You got the answer right. So that shift will, will happen and it's gonna be gradual, but we will see part of the market going to real humans, part of the market going to like entire, like AI models, like the entire cycle. And most of the market being like, the start is AI and the end is human closing. And that's it. Thank you very much. And I think we have ample time for questions. Thank you. Human taking the risk. Go for it.

Meet back here. So you mentioned that you want to now have a composable tech stack in SaaS. And like SaaS obviously always tries to sell annual contracts or multi year contract, which is the opposite of what you recommend. How do you think the accelerating change in velocity is impacting customer lifetime value for SaaS? Yeah, so basically, especially in sales and martech.

Okay, so if I got this right, you're asking like if the tech cycle is accelerating and G is recommending a composable stack, are we gonna see more churn? And if I'm a SaaS vendor, like how do I react to that? Great question, great question. Well, I mean, on the product side, seems obvious that you want to be able to try and be the best all the time. Obviously. Sure. Okay. I think what I haven't covered today is there's a huge value on proposing something unique, different. If you saw the Reddit example. The Reddit example was about scraping the Facebook ads library with tools here and There. Why do I do that? Because no one's selling that data. No one is selling like a structured database of all the Facebook ads in the US which sounds crazy because the data is public and there's an API, but no one's doing it. If you're capable of offering something that is unique and that produces unique outcomes through the LLMs, then that is truly valuable. You have this niche market all for yourself. So I think we're gonna see instead of having like huge platforms that try to do everything, for example, like all the YC companies that are doing like AI agents that does the entire SDR for you, like the output of that is like, eh, it's not great. It's okay, but it's not great. Okay. What we are seeing working, however, is like very specialized LLMs at like a small thing with unique data that produces great output. So I don't know, if I had to put my money somewhere, I'd put it like specialized LLMs for now.

Hey, I have a question about. I think what we're talking about, artificial intelligence, particularly for marketing and sales, is companies becoming much more capital efficient.

Yes.

You're also an investor.

Yes, I am. For better or worse.

Yeah. Are you reducing the check sizes? Are you telling companies like, I won't give you more than a million bucks because you should be able to go all the way to Series A with that.

Yeah. So Christophe Jansis is somewhere around here. So like, that's a better question for him. But yes, like the huge rounds we were seeing, which were driven by huge, you know, capital expenditures for headcount, especially in California. Do they make sense? I guess it depends what you're building. If you're investing on engineers building, sure. If you're investing on like sales people, marketing people, like maybe not. It also means that the moat is becoming harder to build in marketing. And so yes, like, I've reduced the two things. One, I've reduced the number of checks because I have a hard time building conviction on what is going to be the successful technology platform two years from now. It's becoming extremely hard to read. It's always been a difficult job. It's harder. And second, yes, we're looking at burn rates and we are questioning like, why are you burning so much money? Why are you not building the outbound automation infrastructure, the SEO infrastructure at a fraction of the cost that what is. Yes, that pressure will start to disseminate and go around all the boards around the world for sure, 100%. So I agree with that.

Absolute, absolutely amazing talk thank you. The one thing that you need is data and you said you were scraping. So in the terms of service, for instance of LinkedIn, it says you're not allowed and if you try, your account gets banned within a day. And many other websites, how you're circumventing this.

Yeah. So there was, I believe in 2019, 2020, there was like the 9th Circuit Court of California, there was a case that happened against LinkedIn. And I remember, if I try to remember where the case settled, is that whatever LinkedIn lets Google scrape for search purposes, it has to allow anyone else to scrape. Okay. Otherwise that is anti competitive and that's illegal. Okay. You can't just decide that you will get let Google do something and then you're not gonna let somebody else do it. Okay. So whatever is public, you can scrape. Okay. So that covers a lot of the signals we want because a lot of the content of LinkedIn is public. That's one second. The risky part of that is if you're just tokenizing and just like printing back the LinkedIn content you saw. Now if you're using LLMs to make sense of what you saw, summarizing and making content that's interesting with information you have. Well, first it's really hard to prove where you got that from. Right. And even if that's the case, just think about it. If you had a Salesperson Go on LinkedIn, look at somebody's profile and write an email, is that illegal? No. Why would that be legal if a large number model does the same thing? And so that is going to be a legal question that I think is going to be fascinating is like if we have AI impersonate human beings do the exact same job at a fraction of the cost, why is the outcome different? And my bet is it's not going to be different. And also you can't say like who did it and for what purpose. So.

Great, great answer. Just some of the stuff you can only see once you're logged in.

Yes.

And then your account and the IP will be logged and so on.

Yeah. But for example, I'm allowed to download my data. And so if I download my data and I pass it to the LLM, then I'm allowed to do that. And so I think it's going to be really hard eventually to prove, you know, whether. But I don't disagree with you. I think like LinkedIn, the bigger question is like, why is LinkedIn doing nothing? Like why is LinkedIn not selling the data or building LLM tools for salespeople? Because they are the ultimate source. You got to wonder what they're doing, especially because they removed their intent data product three weeks ago. So you got to wonder, is it because they don't care or is it because they're going to announce something big? I think the latter.

You can pay for the API in order to scrape. So that's the model. Thanks so much.

Hey, so yeah. I have a question, I guess about roles and skills, which I think is interesting. I think there's like a key red thread through what you said of sort of like, keep a paid person, but they need to become more technical. Technical. Keep an SEO person, but they need to become more technical. I'm interested in thinking how you think about first, what skills you should be looking for in terms of hiring and training. But also what roles in a traditional marketing org do you see as like, very defensible in this moment and which do you see as kind of cool?

Okay, thank you. So there's a couple of questions linked to that one, which is like, I heard a lot with it. What, what are SDRs going to do? What are salespeople going to do? Right. And well, a lot of the SDRs are gonna end up being AES. Like SDR was always a training ground for AES. And so the SDR world is going away. The people will become closers or will evolve into something else. What's that something else? Probably sales ops. They will handle the orchestration, the workflows. What we're doing right now, whether it's in sales, in marketing, for SEO purposes, for algon purposes, is what for now we're learning from the 10% best people and impersonating their behavior. We still need that 10%. If I don't know what makes a buyer tick, I can't write the prompt. So I need somebody that's creative, that understands reciprocity and all of the sale, the, all the sales things to help me build those workflows. The same is true on content. Like if I can't say, if I can't do the keyword research, then I can't do half of the work. So we still need the expertise. We just don't need the execution anymore. That's the thing. The expertise is super important, which is hard because the expertise comes from having executed and failed. So eventually the people here who have the expertise, you're going to be uniquely valuable because no one else is coming after you. It's fascinating when you think about it. No one else will be trained and into spending money on Google Ads because no one's going to have to do that anymore. And so you're like the last dinosaurs who have been able to spend money freely like crazy. Just think about, like the people who come in five years and they're going to ask you what you spent, like $30,000 to figure out if it worked. Like, how crazy is that? Yeah, you were mad men, right? That's going to be true across the board. Like, you, you hired random freelancers to write content on a keyword and figure out if it works. That sounds like archaic. And so we're gonna move to more technical people that are creative, have deep expertise in the channel for sure, and can build the workflows to replicate what they wish the freelancers of that team would do. So that's what I think is gonna happen. Absolutely.

Super interesting. Thank you.

Hi, great talk. Thank you so much for outbound. Like your main channels these days are, you got email, you've got LinkedIn and you've got phone. What do you think the future is of these kind of channels? How long will they remain viable channels? And do you see other channels that are emerging that people should be looking at as well from an outbound point of view?

So there's a. And I had a talk a couple weeks ago. There was a question at the end on will people still believe what's in the email? Is email a viable channel? And I think that's a tough one. I'm not too sure because right now, if you think of, like, why email works, it's because in some cases, you know the person. In other cases, you see value in the email or it elicits, you know, trust, reciprocity. Like there's a reason there's a forcing function forcing you to respond. Okay. When you truly believe it's a human that has gone great lengths to engage with you, you feel compelled to respond. Okay? And I always give up. Like my snail male example about the grandma writing you a letter and you being cursed and opening the handwritten letter. Now the question is, when that is truly done by an AI and you no longer can tell the difference, will you a distrust all form of email communication because this could be a bot, or will you be look at the face value of the content and say, hey, this is actually helpful. And I think we're see divide a polarization where we see some people going one way, some people going the other way. Overall, email is at risk because we saw the charts with like the cost going down. All right, that only means one thing. Everyone here in this room and elsewhere is going after, like outbound AI based email volumes are going to go up, people will be desensitized for sure. There's a time window right now to exploit it. Right now it works 12 months from now here, next year, I'm not so sure. Right. And so you got to explore this time window, but eventually you got to think, how do I stand out? Is that by doing phone calls? Is that by doing LinkedIn? Is that by doing, like in person things? Email is at risk for sure. There's one company that's doing something interesting that I saw. They're using your actual LinkedIn connections. When you go on a website, it says like, hey, you know Matt that uses this product? Do you want to ask him? So leveraging trust and networks so that you say, hey, like, I know Matt, I had coffee with Matt. Matt is a real human and I will trust his advice. Going back to the certified human Parmigiano example I had, do you see any.

New channels emerging or things that we should be looking at from an outbound point of view or is that.

Not really yet. Not really yet, like video didn't really pick up. Phone call is coming back because of technologies like om. Phone calls is definitely coming back, but nothing new.

Yeah, I run SDR agencies and phone is where we drive pipeline, not email or LinkedIn.

Cool. Thank you.

Yes, I had a question about the AE meat bags.

Yes.

At the enterprise level, if we're getting rid of SDRs because we're automating them largely out of existence, where do the AES gain their skills? Where do they learn their craft? Where do we stand in 10, 15 years time?

Yes, yes, absolutely. I hope my wife won't listen to this recording when she hears the AI meatbag reference. Yeah, that's. That's a tough one. That's true. As I said in, you know, marketing, as it is in sales, the people who. Like SDR is a great job out of college. For people who want to go in sales, that job is going away and you can't just go out of college and start building like AI workflows. You just don't have the experience, you don't know how to write.

Right.

And so either we're going to have more training in one form or another that brings them up to speed to what is required. I think what we're gonna see is gonna be an expert's role to build and maintain those workflows with the sales tactics that we know for such a small fraction of the workforce that those people can be trained. We're talking like in the U.S. if I recall correctly, I think there's 700,000 salespeople like SDRs and AE combined. Okay. How many of those are SDRs? I don't know, a third? You know that's a good like 150, 200,000 people. Like that's, that's a big workforce that and a job function that lasts only like 18, 24 months. So yes, that is a real challenge of how do CROs train their future closers without having them, you know, being SDRs initially. I don't have the perfect answer though. Yes.

Hi. Based on your background with Drift and all the other companies you've had exposure to, are you seeing AI take on discovery in a very advisory role? Not just if then and some recommendations, but real advisory.

And when you mean discovery, you mean end of sales process?

Part of the sales process process, yes.

Yeah. So GONG is kind of doing that and, and all the AI recorders you think of discovery, there's like, there's multiple parts of discovery. There's the sdr, BDR part of the discovery, trying to understand the business and you know, doing the information gathering like Bant style gathering. And then there's the on call discovery where they're trying to like create some rapport with the, with the person and then try to, you know, get the information they want to help them close. Yeah, no, I'm not seeing anyone do that for now. There's no system that is trying to make it click with the buyer to understand. For example, a good way to look at that is are we seeing AI be efficient in enterprise deals? And the answer is not yet. Okay. Enterprise deals are complex that are long. There's lots of potential buyers, lots of information and AI just isn't efficient there for now. There's just too much context, too much risk. If you have any involved, this is still left to humans and it will be left to humans for a while. To be honest, what we are seeing, however, it's tools that help teams summarize data when they hand over. That is pretty close. So we're seeing fantastic tools that help sales team AES understand all the marketing context of the acquisition and the SR context and tools for CSMs to understand. Hey, this company that was just closed, what did we promise? What did we agree to? Who's this customer who's going to be the user? And summarizing that so the onboarding goes a lot better. That I think is fantastic. But the, what you said about. No, I don't, I have not seen anyone do that. Let me know if you do. You're working on it. Cool. Awesome. I think we had time. Thank you very much for coming. Have a good day.