AI-Powered Demand Gen with Guillaume Cabane, Co-Founder and GP @ HyperGrowth Partners

Thrilled with our guest for today and to see everyone. Welcome, welcome. As always, we are thrilled to have you here at Workshop Wednesday. Please make sure to drop where you're tuning in from so we can see where in the world you're from. Gee, I'm guessing you're joining us from the south of France.

That is right just above the city of Cannes where you have the film festival these days.

Wonderful. And we are going to see G next week when we are in London for Saster Europa. There are still tickets left, so if you are on that side of the world with us too. Please make sure to purchase your ticket so that you can see us in person. I'm going to drop our Workshop Wednesday code for you guys because there are still a few tickets left. But thank you so much for joining G. We are thrilled to have you.

Thank you.

Thank you. And yes, that's what you were, Nastra. I was there was the best event in Europe. So like such a great like, you know, minds meddling and like, you know, vibe. Just so good.

Amazing. Well, thanks. And we didn't pay G for that little plug either, so no, I don't.

Get paid for speaking.

Thank you guys so much for joining. And G, we are going to get things kicked off. As always, we're going to have plenty of time for your questions. G has an awesome slide deck for everyone to go through, but he's going to go through his slides pretty quickly and then we're going to plenty of time for Q and A. So please make sure to drop your questions in the chat throughout the session and I'll make sure to get you hopefully queued up to be able to ask G your question live. But we are really excited to have him back for another amazing session. G. Cabane of Hypergrowth Partners, he is a Saster fan favorite and today he's going to be talking about a topic that Jason actually spoke about on last week's Workshop Wednesday about incorporating AI into your demand gen into your marketing. So super timely, super talk topical right now and everyone's trying to make sense of what's going on in the ecosystem. So we're really thrilled to have G's presentation and help us sort through it all before we get kicked off on the slides. Would love for you all to get to know him a little bit better. So G, let's get kicked off and would love to hear a little brief intro of kind of what you're working on in your day to day right now and anything else you want to do to kind of set people up for your presentation today?

Sure, sure. So you know, everybody calls me G and that's, that's great. I love it. And I've been doing growth for the past, gosh, more than 15 years now. And these days I advise companies like post series A on how to grow faster. And as an example, I'm currently advising Reddit, which you'll see in the slides. I'm going to show examples of that. Previously I was advising Ramp, the fintech company out of New York. So some pretty like fantastic companies.

Amazing. And G, you're probably going to preview this a little bit, but we love to ask everyone what is the current SaaS tool or platform that's your favorite right now?

Yeah, so I mean obviously focused on like my topic of choice, which is like, you know, dimension, especially outbound. I think probably these days it's a battle between Clay, which is like everywhere, and probably Unifi, which is my former mentee from Ramp, that's building, that is doing also very well. So I'm not going to pick favorites. Just like between your kids, I'm not going to pick favorites. So those two are great.

Amazing. Amazing. Well, without further ado, I want to make sure we have plenty of time. G, I'll let you take it away and dive right in.

Awesome. Thank you so much, Leila. So you know, as we're discussing, my name is Ji. I'm currently at Hypergrowth Partners where I'm the co founder and jp. I've actually previously launched the growth teams early on at Drift and Segment and Gorgeous and yeah, I work with great companies like Ramp, Reddit and Workstream and so many others. We have like, you know, we've worked with over 50 different companies at Hypergrowth. So you know, if you're in the series A stage or later, you want to grow faster like do reach out for advisory. With that said, for today, I want to cover the evolution of the B2B stack and where we're coming from, especially going back to 2015 and where we're now and how to pick the tools given on your stage and your scale and your needs. And then I'm going to go into what you all want, which is the practical example and workflows. So with that said, let's get started on the evolution where we're coming from. And the reason why I'm showing that is I've been here for a while. You know, I've been doing marketing for more than 20 years now and I've been doing outbound and demand gen for almost all that time. And so I have a pretty good perspective. But you know, what's going on with AI is like it's heavily taking over the sales role. And so this presentation, this deck is geared towards outbound and AI taking over sales. And how can we make the most of this switch? So you know, if we go back to something like it says 2018, but probably even before, like, probably even like 2015, it's a world where the outbound was run by the Reps, by the SDRs and reps were in charge of everything, you know, the contact list, like building list out of sales Navigator or Zoom info, maybe if they had a license. But also the email copy, the sequences and the mailboxes. And he had this one to one relationship between the humans and the mailbox, like one rep, one mailbox. So you know, as a consequence of this very manual process, the three output is a, is a low volume of email since low volume of engagement and a fairly high cost per contact engage or high cac. But you get a pretty good response rate. You know, 2015, 2016, 2017, we would get maybe like high single digit response rate, positive response rates which is why we had huge SDR teams back then. And so if you move forward to the end of 2019, towards 2023, I'd say that bottleneck of having those huge, and that cost, having those huge SDR teams started to be identified and solved really by those platforms like Apple Market and Apollo, but also by having more technical people handling the infrastructure being having the ownership of that infrastructure still within sales. But you had like more like sales ops and those platforms have both the audience product as well as the sequencing product. So in Apollo and Apple Market I'm sure, you know, you can go and like find the contacts and, and build the sequence, right? So I'd say much more efficient, but the reps are still in charge, right? More efficient, but let's say they are empowered, but they're in charge. Well, obviously you know what, you know, you know what happened, what we all know which is outbound volume exploded, right? And, and while the cost per contact engaged, the CAC decreased, but so did the conversion rate because everybody was spamming everybody. And so we got to a point where we were below 1% engagement rate at a fairly high volume. And you can see like all those curves are crossable there. And so we were at a turning point at the end of 2022, 2023, kind of like outbound was no longer working at that scale. But now what's happened, which we were all surprised by with, you know, coming of age of like real, like generative AI tools, it's that sure, like we're going to go into it. The workflows are all automated. The copy is fantastic. But what I want to talk about is that the process is entirely out of the SDR hands. Right? It is the out of the process. The modern stack covers everything they used to do. So like the audience building, sure. That's automated. It's based on signals nowadays. The copy generation automated, the outreach and the response handling automated. It's entirely within the scope of growth of marketing. Growth marketing with technical people. What's fascinating is that the conversion rate is back to single high digits. Now. Whether that remains the case or not, I'm not sure I can predict. Well, maybe I can. Like it seems unlikely it's going to stay high because it's high right now because most companies have not adopted the modern approach yet. And so there's like this few number of companies that have this great copy, great outreach, great sequencing, and the rest don't. Eventually everybody's going to catch up and. But what it means that there's a, there's a time window right now to act and reap the benefits. So how do we do that? Right. So, you know, where do the SDRs end up in the, in this AI world? I guess they don't. I guess they don't end up in this AI world. They become AES, closers in ops, or they, they are displaced entirely. All right. For now, the closing is still done by humans. Humans mostly want to talk to humans to buy something and sell something. Though there are industries I know of, companies, products that are being built for specific industry sets like dev platforms where engineers would prefer to buy from a bot than from an ae. So you're going to see some evolution on that in the next coming months. So something to look forward to. Okay, so we looked at history. Now, which tools should you pick? What's the right tool for you right now? What do I recommend? Well, first I want to say that there are, there are three focus areas you should look into. The first one, it's the tam. So the audience building, right, What TAM is for, total adjustable market audience and scoring the audience break it down into like multiple segments based on the forecasted value and forecasted cost to close them. The second is the intent, what we call signals, right, to, let's say laser focus. The efforts on a smaller subset of that audience to increase the conversion rate with better copy, what we call an excuse. And the last is, well, the Action. Right. How do we send an email or LinkedIn and whatnot? Once you've looked at those three buckets, those three pillars, you can decide, well, do I want a platform that does everything for me? Right. Like a done for you. Right. Or do you want to build, let's say, a composable stack? I do both, depending on the situation. Right. What's clear is that a lot of the early done for you platforms like, you know, the outreach, the sales loft and even the, maybe less, but even the Apollo, like those are becoming legacy, right? In Apollo you'll find a touch of AI. Those are becoming a legacy because that's very important. Their pricing is user based, so they're constrained. They are, they are incentivized to have more reps on the platform, which is not the world we live in today. Just keep that in mind. The platform you want to invest in is a platform where the pricing is incentivized to have less humans, not more. Okay. The second thing is there is a volume where it makes sense, maybe a percentage of your pipe to invest a lot more than just a platform and control the different components, which I call a composable stack. So let's look at that. So first you have the, let's say making the reps more efficient. So we have the outreach, the Apollo, the Emperor market. Those are for reps, so there's no code really. And they work well up to like maybe like a hundred thousand emails, maybe a bit less, maybe like 50,000 emails, I'd say a month, which is high, but you'll see we can go much, much higher. There's little customization possible in there, little, let's say, of the AI craziness we can put in there if you want to have a bit more control. The newer platforms would be something like a clay, which I use a lot. We've talked in the very, at the, at the very beginning, Unifi and Common Room for the signals, those are very different. Like clay is like a spreadsheet and I'll show you some examples. Spreadsheet, like for outbound, great. To test and discover your audience, your signals. Common Room is a marketplace for signals and Unifi is an all in one modern AI platform. But if you want even more control and more volume, the things that I would use at the large companies like the Ramps and the Reddits would be cargo plus waterfall which is, you know, something which is much closer to a zap or a make.com for outbound purposes. And you can just stitch all of the ei components that you want. So let's look at a couple of the examples. Speaking of Clay, here's a great example on like just in minutes, how do you estimate the audience size, number of accounts based on a set of criteria. So in this case, you know, I'm looking for companies that work in SaaS with specific company sizes, maybe specific keywords, right? So here we're doing enterprise B2B SaaS, smart organizations and kaboom. For that set of filters, we find 4,000. Not only you get the TAM size, you get the list of companies. You can quickly validate that it's the right kind of companies. It's really hard to go anywhere else and like do that inspect, move it to a table and play around with the table. So this is like the best tool for that, right? And obviously you can build a scoring system and in there, so you can say hey, like you know, based on those companies, based on the fields that they have, have a point based system to like sort through the companies. Now if you want to laser focus the a large list and you want to have a good excuse to put in your, in your email. You know, whereas in the past I had to build signals one by one like pull like clearbit and G2 and do all the API integration, now there's marketplaces where you can do that, one of which is common room here. And so in common room you can just like in a few clicks like activate the integration from like, you know, a Reddit, a LinkedIn, a snack, Twitter, like G2. It's just all there and just it will aggregate and find all the companies that are showing intent based on your filters. You can see the example of the intent here. You can actually aggregate the intent data per account and get an intent score, which is something I struggled to do even like three years ago. Right now you can have a bell curve of intent with maybe a decay model and push those accounts, those contacts to whichever engagement platforms you want, which is fascinating. It means that those tools are displacing most of the value part of outreach out of outreach. Outreach is used only to send email, but all of the intelligence is out of it lives elsewhere. Now if you're in the composable stack camp, then a great signal I'm always using is job changes, right? Whether it's a champion moving campaign, so somebody who's moving from a current customer company to a prospect non customer company, right? And you want to reach out, or whether you have a gate blocker, which is the opposite, somebody said no to buying your product. And eventually they move out and you want to reach back to the same company. That means you're scraping monitoring LinkedIn changes all the time. You don't want to do that yourself. Well then you can use a platform like loanscale here to track a set of accounts, a set of users, or maybe even target accounts that are opening roles for a possible champion based on the job description. As you can see the bottom right that's like just so great. You can't imagine the amount of work I've had to do to make this happen just a few years ago. Speaking of the composable stack, the best so high volume approach which I covered in the 2x2 earlier in the axis is something like a cargo. So as I said, it's very similar to Zapier make or N8N. It's entirely dedicated to B2B dimension automation. So as an example here it has direct integrations with waterfall, which is probably the best, well actually the only contact data aggregator. What that means is that it enables you to have multiple vendors, data vendors into one API and just pay the bare minimum price and just have one endpoint. And you can have like the zoom info and the Apollo, the Clear bit, the Lusha PDL all like one API point. Right. So just going back here, you know, you can have a workflow where you're going to get the signal from, you know, a loan scale, hit waterfall, have the best data coverage and push it back to whichever outbound system you want. And this is where the intelligence lives. This is what a platform, a company, sorry, like Reddit or Reample. All the high volume senders sending more than 100,000 emails a month are using. This is what gorgeous users to send like 300,000 emails a month because you have a lot more control and you're not dependent on any part of the stack. So let's jump into some examples that I worked on recently here. So as I said, I recently became the advisor for demand gen to the Reddit advertising business, the SMB advertising business, great company. And they came with the goal. We they said want to get to 10% of US advertisers on Reddit by the end of the year. And that's a tall order. Like sure it's Reddit, but like we're talking of 10% of the entire US market. Okay, so how do we do that? Well, one of the first ideas is to scrape the Facebook ads library, Google LinkedIn ad library to find who's advertising right now. That would be a good fit for Reddit based on Reddit's ICP. So you know, gaming companies, SaaS companies and reach out with a good excuse about, hey, we saw your advertising on, on Facebook or on LinkedIn. What about, you know, replicating the same ad? Well, that's exactly what we did. As you can see here, this is screenshots from clay and we use clay to prove the feasibility of the concept before we invest too much. We just wanted to go there and you can see here there's a GPT prompt to find the Facebook page, which is harder than one would think accurately at scale. And then get the Facebook ads library match, pull all the data from the Facebook ads library and inject it in an email. And that's just fantastic.

It worked.

This was a couple days of work and with a couple days of work to get it fine tuned and nice, it's just running, it's humming. I can do like a couple thousand. It's a highly targeted, highly like customized personalized emails per week. It's not super high volume, it breaks. Once I went over like 50k rows on clay. But this is just magnificent. Like this is just so good. Like I saw your ad on Facebook, YouTube, whatnot, boom. Summary of the ad which is AI generated. All the AC was AI generated and there's a screenshot of the actual ad on the side. And then we're even injecting the relevant subreddits that are fit based on the industry and the company data that we get. With this we are getting pretty good. Obviously this is like I can't show the actual data. Like we're getting really good reply rates. Really, really good reply rates. It's amazing. For a stack that costs us close to nothing, we're talking like a couple thousand dollars of entire stack that's almost a hundred times less than it used to be before. So fantastic. Similarly similar end to end but with a platform now you can do the same thing all in one, right? Within Unify. So you can see here within Unify, so the opposite end of the spectrum, no code. In a couple of minutes you can get all the list of companies visiting your website. Built an intent level over the past 30 days. Get this bell curve, as I said of intent all the people, the prospects and create an engagement, right? And say hey, based on the company's accounts that have seen my pricing page with a champion that changed job and on G2, saw my competitor and are not on Salesforce then move them to Salesforce and Engage. That's just like wow, that's just so good. Those accounts Here are just so, so qualified. Right. And, and so you know, you can build and stack playbooks one after the other. You can see here like it's doing a couple thousand companies at once. And you can have Playbooks at the account level but also at the personal level you can have playbooks based on seniority based on role based on. So that's like the all in one approach. And if you look here at an example from Unifi, you can see here that the prospects have fantastic reactions. Right. Why? Because we're doing this like typical, this reveal loop approach for which I personally am famous, which I kick started in 2017. This is becoming a standard approach, but still getting that contextually within minutes. High quality. It's hard to pull off, to be honest, without such a platform. Okay, so with that said, I shared a couple a bunch of examples. I do want to give a couple of takeaways and then some thoughts and then we can move into the Q and A. So takeaways should be obvious like outbound lives within know growth marketing ops like live with it, embrace it. It's the way it is. It's not going back. Okay. It's all about moving the human, prior human workflows of audience, finding the TAM, the signal discovery which used to be like on LinkedIn and the outreach which used to be in while in outreach to an entirely automated workflow which can be built for you platform or let's say low code or some code based on the volume and the personalization that you want. And yeah, I'd say that's where we are right now. A couple of links here which I'll leave open for a second of the tools that I've shared, Unify and Clay and Waterfall and loan scale on cargo and Apple market great platforms. Before we move to Q and A, one last thing, some closing thoughts. I was with a CMO yesterday and we shared a couple of thoughts I want to share here. One, the tech cycle is accelerating. It's obvious. Looking after the cycles I presented earlier, the first cycle was seven years, the second is like four years. And now two years into this AI cycle and the products change what, every quarter? Maybe. So how do we as marketers, as technologists cope with that? How do we make a tech investment a bet knowing that that decision, that product we're buying, maybe on a yearly contract, can be superseded next month by something way better. It's very difficult. Second and last thought, as we discussed, we're now in an era of very high quality automated outreach. Soon, if not already indistinguishable from the best human sdr. I can see it in the conversion rates. It's like pretty much the same thing. How will buyers react? It's not just outbound that's at stake. It's the core concept of reciprocity and how people perceive the entire email channel as a communication channel. People respond to people. What happens when buyers lose trust in email as a communication channel because they think it's all just like AI bots and how will we handle that? That's it. With that said, thank you so much. I'll go back here and we'll go into Q and A right on time.

Great presentation, G. Thank you so much. We have a lot of questions as well. I'm going to start off first with some of the more tactical questions that we're getting just like on the actual workflow examples you gave. And then there are some more like bigger picture practical questions, especially for some folks that are a little bit earlier stage. But we'll start with just some, some folks again that had some specific questions about your workflows. Mike, I'm going to p pull you up. You had a question about phone calls. Mike, are you there to jump in and we can bring you up?

Yeah. Thank you, Taylor. Thanks G. That was, that was pretty awesome. My question is for, you know, you, you brought up like sales loft and stuff like that back in 2018 and you know, grab your 50 leads every morning and, and all, and all that kind of stuff. A lot of those cadences involved, you know, phone calls and different voicemails that you would leave and stuff like that. And certainly so one just in general, what about that part of like an SDR's tasks and then, and then another like question has to do with it is there's probably some correlation between like deal size and current effectiveness of like what you're talking about. And so that, that if you could kind of include that.

Sure, 100%. So it's funny because like I, I, I kept this for like more the early stage audience but they're great questions. So on phone calls, you're absolutely right. There's a comeback of phone calls because of what I just said on closing thoughts on email. 100% it is industry dependent. There's some industries where phone calls just work better, especially more like traditional industries. There's tools, for example like Orem, are you R O R U M sorry? That makes phone calling at scale a lot more efficient still using humans to do the actual conversation. I've tried the AI platforms to place and have the call, the voice. For now, they don't work. We've placed 427 calls in the most recent example last month and we had a zero success rate. Not zero percent. We had. Not a single call went well. Okay. There's just too much delay. The AI just doesn't pick up the, you know what the person is saying. It's just, it's just weird. Okay. It's going to get there though. Like don't get. It's. Eventually it's going to get there. It's a question of like, when does it get there? We're not there just yet. For now, people. What's very obvious is the audience people, us consumers will get used to AI voices on inbound calls. When you're calling United or Comcast, you're going to get that instead of a phone tree. Just better experience. And after some quarters of that, they will be used to like the outbound phone calls. Yes, we did. To your second question, which is the deal size, 100% at Reddit, at ramp and almost everywhere. The examples that I shared are for SMB and mid market, above mid markets. So the enterprise territory, we don't use it because the risks involve of like wrong copy, wrong person, yada yada, outweigh the cost savings. There's just, there's not enough enterprise companies for that to be worth it. Like in most companies I work, there's like a couple of thousand real like enterprise account, full stop. And just with like a couple of reps, you can just cover that neatly and just too much history. You can't right now load all of the context of like, you know, 20 different, you know, business units. So if you're selling to Delta Airlines, this is not going to work. So yeah.

Thank you. That totally answered my question. That that's similar to what I thought you were going to say. So that means you did a good job in, in your speech and your talk. Given that people could kind of guess at what the answers would be for their own questions. Good job and thanks a lot.

Thank you, Mike.

Thanks, Mike.

We are going to move on to a question from Ash. He has some questions about how you include what details to include in the email. So Ash, I'm going to bring you up now to ask your question to.

G.

Hey, thanks Gene. We do a lot of outbound ourselves for clients. Appreciate this talk a lot. I'm curious, you know, nowadays you don't really have the chance to include a lot of links and things like that in emails to have, you know, because they're filtered out from it. Spam filters. The example that you used, you actually, you know, scraped things like ad library and things like that, and then you included an image in your, in your outbound email to that, that audience. Curious, how does that impact your deliverability? Is that, you know, things like that working? And then a corresponding question to that is like, you know what, what is your answer to how we bring audiences into sort of, if you will, a digital sales room or some sort of piece of collateral or content beforehand before they even engage with, with you afterwards?

Okay, okay, great questions. So traditionally I agree with you. I avoid links. Every time I see, you know, a company I'm helping where they have a direct calendly link, I ask them to remove it and go for a response instead to make it more human. Right. I never in my, as a human, which I'm supposed to be most of the time, I never send an email to somebody else that I don't know with like, hey, how about you book a calendly link because there's no connection. I never do that. Right. That's what you see is their appetite on the other side. So it's just not human esque. So we try to avoid that. That said, it depends on TAM size. So can you, can you, do you have a benefit of like a lower response rate, more efficiency? Right? It depends on domain authority, especially for including images. Now Reddit has one of the best domain authorities in the world and they send gazillion of legitimate emails to legitimate users per month. Like, I don't know the number, but like it's just called, it's like enormous. Okay. And so it's so big that me sending 10,000, 50,000, 100,000 emails of outbound to businesses per month doesn't even register on the spam filters because the domain is whitelisted. It's Reddit. And so my strategy changes and every time I can hide my emails behind the forest of legitimate emails. It also works for Gramp, which sends a gazillion, maybe less than Reddit, but a lot of add your receipt and here's a transaction per day to legitimate users. And so in all those cases I'm like, hey, I can take more risks, I can do things differently. Because if it does get through, obviously it looks more human because nobody thinks these days that this is automated, especially for Reddit's audience, which is SMBs. So it's like we're talking small SaaS, game developers, indie hackers, all the people who good advertise for ready communities like it looks very human. So I can do the screenshot. This is, hey, what about this community? Have you thought about it? This ad would play very well. So it looks human, which is what I want.

Yeah, yeah, that's perfect. That's really good. Yeah, that's a really good clarification because I think, you know, from, from Reddit to ramp that those things might work, but they might not always necessarily work for, you know, small to medium sized enterprises which are still getting their emails warmed up and not necessarily hitting the inbox.

Yeah. And volume wise, if you're a small business and you don't, you can't hide behind that forest of legitimate, you know, emails, then you are going to have to build a quite a large number of like new domains, warm them up. And I would say these days probably stay below 60 emails per day per domain, which feels sounds low but that's where we are. So I have people who are building a hundred domains with like one to two mailboxes per domain to get that. You know, that's where we're at right. These days.

And for what it's worth, social is working out really, really well for us.

Yep. And for your second question on like digital sales room, I don't do much of that, that's more on the enterprise territory. But I have found which brings kind of close to that, which is there are some audiences which are not warm enough, we don't have enough signals and so we do want to nurture them, send them content. And so we do things like for example building free tools and do the outbound on the free tool to create the engagement and the brand awareness and see if there's engagement there and then bring them closer to the main paid platform that, that works. And so trying to like find tangential opportunities, signal opportunities, companies launching hey, like this free tool helps you like do this thing. So that's, that's the closest I've done which, which kind of works.

Thank you so much. Appreciate it.

Thank you. Ash, we have another question, very related. So Ash, this was a good segue. So we have a related question from Tito. I'm going to bring you up right now to ask your question live Ng it's probably going to be a few more about the domains and creation and how to kind of scale up. So Tito, I'll let you dive in.

Thank you. G. First of all, I appreciate you doing this. I've been following you for a long time and I've been in the sales development space also for 12 years. It's good to Have a sounding board today. I actually want to pick your brain a little bit and see if you're seeing what I'm seeing. So if I understood here correctly, you're working with companies whose average deal size might be very small. And some of your capacities and tools that you're talking about are based off of, you know, the 50,000 emails.

Right.

Being sent and all that. It's, it's very high volume. You talked a little bit about the enterprise being different and it being much more high volume, but I've actually started talking about this with other people. Oh, I was trying to share screen. I wanted to share some of the emails that I've been getting. Is that, is that possible?

Can I do that, Taylor?

Let's see if we can show you.

If not, no big deal. But here's what I'm seeing. I'm getting a lot of emails and now they look personalized, but I can smell the AI so quickly. Like it says, hi T. I'm excited to see how your leadership has influenced the innovation of B2B. Go to marketing.

Yeah, they're not great, you know, and.

And I can, I can smell that. So I think similar to in the early days, the first time I got the high Tito in 2004, I was like, somebody's emailing me. Now I'm just. You send me, I don't care. So I agree. Right, good. But what's next? Because there's no wait.

There's two things. One, you're not. You're not, you're different. You're not the usual buyer. In most cases, you work in sales and marketing. And so you get a lot of those emails. You learn how to identify them and you know how they're built. There's many, many industries where that's not the case. That's one second. All of those emails either lack somebody who's really creative, like a crazy creative like me. I can give some examples of that. Or a more modern AI platform, which is happening. So, for example, like we at Ramp did a sequence for CFOs of SaaS companies which they should be able to smell BS like from pretty far. Right? And we had no signal. So it's cold, cold email, which is the worst situation. And the email we built is we scraped very typically the LinkedIn page. Nothing surprising there. We found the college. Nothing surprising that we did not want to say, hey, you went to this college? Because that's not great. Okay. What we did is that we paid a freelancer to identify what is the most. Sorry, what are the college sports team of every US College. Right. Then we pull the data on the upcoming sports games and we send an email to the cfo and we said, hey, Tito, I see you're from this college. The basketball team is going to go play against this other team, and I'm betting you 50 bucks that they're going to lose. It's 50 bucks on me or you do a call right now. Nobody believes that this comes from a human. And I see Rob says that he got this email. Yeah. So nobody. Why? Because it's so out there. It's just so different. It's like me mailing you, especially in the US where all CFOs went to college and all people who went to college, especially at that level, keep very strong ties with the college sports team. Nobody believes it's from an AI, but it is.

But what happens when, you know, that's the High Tito of 2004 now in 2024 is all these other things. What happens when this merges? Like, well, I. What I've been doing is I know.

Exactly what's at the end. You will either there's going to be two kind of people. There's people who are going to say, hey, I don't care if this comes for a human or not. I no longer care. The only thing that matters is whether the email is valuable and I get value from this. And B, this can be a second part of people who say, hey, I no longer trust this form of communication because I don't know if it's from a human or not. And so I will retract into my bubble of like, hey, this is not trustworthy. But that's going to happen to email, it's going to happen to phone calls, going to happen to all other things. And so what we express as reciprocity, which means when you are convinced it's from a human, you will do some efforts that will happen less and less often. That's the concern.

I'll share one last thing here. I want to see if you're seeing the same thing. But I'm desensitized, for example, to direct mail. When I get a piece of paper in the mail, says, tito, offer for you. I'm like, you know, throw it in the trash. So I think email is going the same way. But what I think will happen is, for example, we do a lot of outbound in the enterprise space. And what's working is we go to an AI tool and we build, let's say, a song for the company and it's How GMTO should be friends. And then I send you an email that says, gee, I made you made a song for you. Check it out. And it's on YouTube. We upload it, you know, like long term.

Long, long term. All of this, you'll be convinced it's from. It's from Robot. I'm going to share two things to close this out. One, you're pulling my leg on the snail metal example, on the physical metal example. So I got, I got the shared list. Like everyone in the room here, think about this. The 100 people here. Think about this thought experiment. You're Tito. You have this great office or home office. And you have a mailbox. And you get junk mail in the mailbox on a daily basis. Okay? You take the junk mail, put it in the trash. You don't have any remorse, no second feelings. It goes in the trash and you move on with your day. Okay? Now, as you pick the next day, the pile of junk mail. On the top of that pile of junk mail, there's an envelope that is obviously human, written with, scribbled with an old handwriting, and there's a stamp that's licked and put on the envelope. And there's your name on the back of it. And it's obvious it's from a human and from an old grandma. Now, how likely are you, Tito, how lucky are the other people in this room to take this envelope and put it in the trash? Because you don't know who it comes from and you don't care. Zero. There's no way. There's no way you can open it. Why? But why? Why?

I see the ink.

This is pattern interrupting. Because now AI is the pattern. And only a human can break the pattern by being.

Yeah. There's two things. One, you have reciprocity. You feel for the person that went through the effort of writing to you, to this curiosity. Okay, so those two things are happening. That is what we try to replicate with the AI tools. We're trying to trigger your reciprocity sensor and your curiosity sensor.

But If I get 20 of those exact envelopes, exactly one doesn't work anymore.

I agree, but that's the point. You've got to be the person who's on the edge, who's always doing the thing that the others aren't doing. You got to be in advance. And so that's why you've got to be the. On the leading edge of looking like a human and delivering more value in your communication, where all the others are part of the folks who are like Training behind and saying you like postcards which are, like, printed.

But you're either the leading edge of AI doing the things that nobody else is doing with AI or you're going to be the human that's doing the human things that AI can't do. And I think on the AI, being on the leading edge is excellent for SMB, and I agree with you. And I love your presentation, by the way. It's excellent. I got to think about more of that. But I also think that the human side, Humans need to keep evolving into what can the AI not do yet? If I do that, I open accounts. And that's what you do in the enterprise. That's what I believe.

Yes, we agree.

Okay, I got to buy you a beer.

Coffee today.

I want to.

I want to go chat.

You're.

You're incredibly fun.

You have to come to London, and G will be there to dive in more.

Let's grab a beer, slash coffee, whatever your drink of choice is.

Yeah, I'm flying tomorrow, actually, so I. I'll buy my tickets. I'll go see you there.

Yeah.

Awesome.

Thank you so much, Tito. Tripp, I'm gonna pull you up, G. We're getting a lot of questions of just people talking about testing, so, like, how do you kind of get it launched and going? So, Tripp, I'm gonna pull you up now to ask your questions, and I think it covers a lot of other folks, too, so let you dive in.

Sounds good.

AG thanks very much for the presentation. Really good. Inspiring. So you hear me? Okay, cool. Yeah. So we've got, you know, existing investments in existing tools, the zoom info and, you know, gong and kind of all the rest of it for outbound and so and an existing motion that's, you know, based on intent and all this kind of stuff. So my question is, like, kind of thinking about how to kind of find a test case or kind of a very, you know, what. What would you recommend to kind of the minimal viable product version of, you know, this kind of approach. I also, by the way, really appreciate all the nuance you provided because we. We're in a market where it is a kind of constraint, Tam. We're going after a niche, and so it's a tight community, and we don't want to, you know, kind of, you know, kill the golden goose here in terms of creating a bad impression or kind of burning our brand authority in the space we're in. So we're. We want to kind of go about it with a lot of empathy towards the buyers in this kind of community.

Yeah, that's fair. Yeah. So for, for all those cases, I think that something like if it's to test and you don't know whether it's going to work, you don't know what the audience angle fit is. You don't know what the exact message for the right audience. You don't know how to break it down. You don't know what signals work. You want to test a lot. That's when I use clay and that's. Clay is honestly, I love this. One of the few companies where I don't even own equity, which is rare in this space because I should own equity everywhere. I don't here. And I love them because I use it a lot with my portfolio companies because it's great to test. Downside, it doesn't, it doesn't scale super well. Like you want to go past, you know, the 50,000 moles and the enrichments and all the columns, it tends to break. But that's okay because by that time I've figured out and, and you know, they have a credit based system. You can use all the vendors based on credits. So you don't need to go through like all the, you know, the SaaS purchasing cycle for that, which is a pain. So you just put like a couple thousand thousand bucks to work on clay and you're going to test the vendors, the audiences, the playbooks. Send a couple hundred emails here and there and you'll know. Right. And at the point where clay breaks, if you have a good response rate, you're able to get to parity with the human s, then it's probably worth it to invest into a composable stack. Absolutely right. But you got to find those Playbooks before.

Awesome.

Thanks.

Thanks, Trip. We have another question from Garage, a little bit more about enterprise. So garage, I'm going to bring you up as well.

Perfect. Hey, great session. Love it.

Thank you.

I have two part question. The first one should be easy for you. So let's say I'm targeting chief information security officers or Chief Data Officers Global 2000 leaders.

Right.

So and the question is really related to intent signal and the real time data from those signals because everyone is invested. And I won't list the name of the tools, lots of ABM tools or platforms and things like that. Right. How what you proposed is phenomenal.

Right.

I love it. And how do you see the real timeliness or lack of it from the signals to address that audience?

Now that's a great point. And I'm just going to add on Top of that, before I answer, the real timeliness freshness of the information is a valid point for the signal, but also for the contact data. People in tech jobs change jobs, you know, every 18, 24 months, which means 1 24th you know, of your database changes per month, you know, at best, okay? And so if your data vendor scrapes LinkedIn, you know, every. The entire LinkedIn every six months, then you got 624 of the database, which is out of whack at any point in time, which is terrible, which is why you have bounce rates. Now, given the bounce rate should be in the low 2 to 3%, you can see how 624 is a problem. All right, and so what I recommend is that your investment on the stack, especially on the data part, scales with the ACV of the contract.

Right?

Which most people don't do. So for example, example for, not for Reddit, ACV is too low. But for ramp selling to CFOs where in ACVs in the 5, 6 figures range easily, right? Spending $0.10 doesn't make sense. We should spend multiple dollars to get the proper data, which we do. We absolutely do. Which means we pay data vendors at reamp to scrape LinkedIn real time. @ the moment we are about to send the email, not two months before, not two weeks before in the workflow trigger. Once we have all the signals, we recheck LinkedIn to make sure real time this person is still in this job at this company. Okay? And the signals, the higher the value, the more we invest on getting our own source of signal so that we can pay to run faster on a smaller subset or to create custom signals that's even more valuable. As platforms like Common Room start to become commonplace, everyone's going to use those signals and people will be desensitized. Like Tito was saying earlier, you have an incentive to build custom signals. Example of which, for example, when I was at Gorgias in the CS E Comm E Commerce space, we built signals to monitor weather disruptions to USPS and FedEx warehouses so we could reach out to E Commerce stores and say, hey, your packages to your customers are going to be delayed. Are you ready to handle the influx of CS tickets? And often we'd be able to send that email and get in the inbox of the CS leader before they knew that they would be disrupted. So we would inform them and that email is valuable. They said, thank you. And then the storm disrupts the logistical chain and we're like, great, we got to talk. Custom signal. So invest more to get Higher quality data alongside your acp.

Cool.

Thank you.

Sure.

Thank you so much.

Koresh.

We're going to close out G with one final question. Going back to your first point in your presentation about the future of SDRs. So I'm going to bring up Tashin to ask your question.

I was afraid you were bringing up my wife, who's a salesperson, started as an sdr.

Tashan, are you there?

I'm here, I'm here. One second.

How's it going?

I'll bring the wrath of your wife. So I started as an SDR and it's where, you know, we gain a lot of skills to essentially close sales. So my question is more of like a two prong approach. One thing I'm kind of recognizing with AI and adoption at these larger companies is that they're just not doing it like, or they're very slow to it, which is why I still think the role will exist or at least evolve. So it leads into the next question of what are your thoughts about how the AE role is going to look at these larger companies?

Okay. Love it. I agree. They still exist 100%. I mean, I'm working with companies. Name them. What? There's like hundreds of SDRs. What's happening, it's why I think we're on the verge of a cataclysmic event is that I'm starting to see a CAC inversion. Where it used to be that SDRS were more efficient than automated outbound automation for most cases, and you would stack both for different use cases. Okay, what's happening now is that the CAC of the channel is low with automation, and so the companies that rely on humans are going to be spending more, have less return on investment. That switch is happening right now. It's happening very fast. And that's going to create a lot of pressure to make the outbound channel just forget like how it's done, the outbound channel more efficient. And so that's gonna be cataclysmic because, like, there's no way humans can compete with those fully automated platforms. 3 months, 4, 4 months, 5 months from now in the U.S. at least you could outsource it. That's a different story. Let's say, like US based SDRs. There's no way. There's no way. Except for like, there's a couple of industries and like, sure, like, generally speaking, like, you're selling to like SaaS and whatnot.

Like.

There'S no way on the SMB mid market sector that you compete with those AI platforms. I just don't see it. All right, which creates a good question of how do you train AES? Getting to your second point, because generally the way to go into the AE role was to start as an SDR and get trained there out of college. But there's no SDR world anymore. All right, so that's going to be an interesting challenge that's happening. How does the AE role evolve? I think it's a good change for now, which is they're going to be focused more on the closing part of the process, not on all the chasing, getting people to join calls and be on calls. Like this is going to be back to back on calls, just the closing. They're going to have an AI summary of all the contexts where the space processing contact company came from. What's the need? What's the signal ready for them with? If you think of like how Gong does it, like there's a, there's a prompt for the human. So the AI is prompting the human like hey, like say this on the call and it's going to work. This is our forecast of the best things to say. Right, so that's what's happening right now. Yeah, thanks. Thanks.

Good thoughts. Appreciate it.

Thank you. Sure thing.

Follow up question to that, G, like, what is your best advice for someone who's an SDR right now?

Get into an AE role, get into ops, get out of the SDR role. It's never, it's never been a career to be honest. SDRs, it's not, it's not a long term career. No one's like long tenured SDR and a good sdr, those two things don't exist. But what's going to remain for a long time is people who are creative build those workflows, build those playbooks. And so you can either become really creative, really good at creating all those workflows on the OPS growth side of the world, or you can go and become really good at the closing. And like working with humans, just don't stay in the middle. Just don't try to like, you know, bang your keyboard like a monkey as fast as you can because you're not going to win that battle.

Amazing G. You have so many amazing comments and feedback in the, in the chat of people. Just really loving this presentation. Super insightful. Again, very timely. So thank you so much for spending some time with us in advance of Europa. Again, G is going to be with us next week in London, so please make sure to join us. Also some folks that he dropped of just talking about as well. We have the CEO of Gong to will be on stage with us. So really great. And G will see you next week in London and everyone else next week for workshop Wednesday. But you can watch all the sessions at Europa live on our YouTube. So please make sure that you're subscribed. And then we'll see you back the week after Europa. So thanks everyone and we'll see you soon.

Thank you so much.