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- [00:06]
A
Hello, hello, hello. Welcome to another episode of the Always Be Testing podcast. I'm your host, Ty degrange and I'm really excited to talk to Doug Bell today. Doug, how are you?
- [00:16]
B
I'm well, Ty. Sun is shining nice and warm and toasty here in Northern California today.
- [00:22]
A
My home away from home. I left my heart in the bay and found home in Texas.
- [00:27]
B
I tell people you guys have better tacos. We just talked about this time. Much better tacos. Totally worth the trade.
- [00:33]
A
It was all for the tacos. It was all for the tacos.
- [00:35]
B
All for the tacos.
- [00:36]
A
Amazing. Doug is a fractional CMO to the stars, aka SaaS Brands. He's an awesome guy. I've had the pleasure to collaborate and work with him in the past. He's co host of the Cannonball Go to Market weekly live stream, which we were just talking about. Highly recommend you check it out. Co author of a top 40 sub stack. No big deal. And I think you're in for a treat today, gang. Is that correct?
- [01:03]
B
You got it. All right. You forgot to mention Brad Pitt lookalike. Otherwise everything is just spot on. Ty, good job.
- [01:10]
A
That's impressive. That's really impressive. So what was it like collaborating with Lewis Hamilton on F1? Just jump into it.
- [01:19]
B
Yeah, it's funny. I'll tell a little story before we jump in, but this is like my old. It's my joke because I don't look anything like Brad Pitt and I try like it's an audience warmer and I tried that in Berlin in 2017 and my co host from Germany was like, don't do that. Nobody will understand the irony. So know your audience at the point. I know your audience. It went over like a lead balloon pretty fast.
- [01:41]
A
And I was like, the Germans didn't like the sarcasm.
- [01:45]
B
That was not funny. You do not look like Brad Pitt.
- [01:49]
A
This logically doesn't add up. Love it. This is very timely conversation, gang, because Doug is eating, sleeping, breathing AI as much as one can in this ecosystem, which is the topic of topics. LLM tooling, kind of variants of how to figure out this vibe coding thing. Ever since that has become a thing and ever since AI has dropped on us and the LLMs have dropped on us in late 2022, not only does he has he dove into the making and building aspects with with AI tooling, which is really fascinating, but from my perspective, he's a true B2B SaaS marketing leader. Fairly accurate.
- [02:34]
B
Yeah, sure, sure. Like everything. Keep it coming, Ty. This is good, Ty. You make me feel good. Go Ahead, come on.
- [02:40]
A
My part time job is hype man, so that's, I enjoy that part of my job. So the intersection of AI, intersection of SaaS, it's all coming. So fasten your safety belts, it's going to be good. Question one. So you've grown companies of varying shapes and sizes. Automation anywhere, Lean Data, Search metrics. When you kind of look back, what are some of the patterns that bubble up for you and what are some of the things that you have seen? Really kind of work to help create beneficial pipeline from that CMO's perspective?
- [03:19]
B
That's wow, really good question, Ty. And you mentioned three brands where the growth story was very different. But if I can oversimplify the world in each case, each was a really good growth story for its own reasons. Automation anywhere. For folks who don't know this company, I think it's got about a $7 billion valuation. They're the support infrastructure, autom and AI for what are now called managed services companies. They used to be called business process outsourcers. Right. Ty, you and I worked together at searchmetrics. You were one of my amazing agency support folks there. That was an SEO platform. It was bought up by Conductor some time ago, but sort of the SEO's SEO platform, if you will. And then Lean Data is this amazing lead orchestration engine, right? And in each case, Ty, the thing that sort of got us over the hump from a growth standpoint was when in some cases it was accidental. I'll be honest, this is going to sound really clever, but in each case we tapped into untapped or unaddressed problems that our customers were having and just sort of go back through the order at Automation anywhere. The idea of labor arbitrage, because if you think about it, all these white collar jobs, IT support, customer support, they all migrated over about a 15 year period offshore to say India or to the Philippines and what have you. And they were running out of countries to go offshore because you had all these huge companies competing for the lowest possible labor cost. And so that when I started There, we were 8 million in revenue by time I exited. Three years later, we were at 80 million in revenue. Right. And not because the marketing was amazing. It was, but it was because we tapped into these huge companies running out of Runway for labor Archerage. And so we were in there going, hey, we can actually make the people that you're using to deliver these services more efficient. And that worked wonderfully once we tapped into it, I think, Ty, we actually worked on this stuff together. Search metrics and that was people didn't know how to generate content that would rank right. And that was part of what we worked on together. And it was very much saying, oh gee, we have a way of dealing with content, like piece level content together. And not like we have the best SEO platform ever. We were just like, hey, we're addressing this problem. And then interestingly enough at Lean Data, it was just. What it got down to was bottom of funnel orchestration was falling apart because there was so much volume because of the old playbook. The old playbook was jam leads through. And then once we sort of recognized it wasn't just lead management, it was total bottom of funnel orchestration. You get growth and incredible marketing. Of course, Ty, always.
- [06:00]
A
Of course, Incredible. Always. Those are really, really succinctly phrased and some good, some good learnings in there. If I like mark the market, timing the shift and kind of thinking about it, those are, those are all really good things to keep in mind of. So spot on.
- [06:17]
B
Well, Ty, those were. When we worked together, we got lucky. I mean, let's say we're smart guys, we're capable people, but in each case we sort of got lucky. And I think that's if I have any takeaway from today's conversation with you and your audiences. How do we sort of change that luck paradigm? Right? So that's what I'm hoping to sort of pull out of this is like, well, those are three lucky situations. Hey, Doug, what about the other ones? Were you the bed? Well, let's just ignore those.
- [06:43]
A
I mean, not. And not to go too far down the rabbit hole, but it's really fascinating how often you could have, candidly, you could have world class talent, world class strategy, world class execution, and kind of get your teeth kicked in because of some of those tailwind, headwind timing competitor events that you referenced in that first piece. So I think it's a really good call out. And how do we reverse engineer a little bit together as a collective knowledge to set ourselves up to not be just beholden to luck or not. I like that. So second piece I'm thinking about is we've talked a little bit about. And you've talked a little bit about this middle section, this messy middle for the B2B lead management. Obviously it was sort of referenced in the first piece. How do you think about lead management and maybe flipping on its head a little bit, taking the inverse of what you shared of what wasn't working of like shoving them through the system. What's the 2026 version of lead management for people who are unaware.
- [07:45]
B
Yeah, yeah. Let me just say that the messy middle is very much about the transition that happens when you start thinking about getting to, how you're starting to get to buyers before they really need. They know that they need your brand. Right. And so when you're making that change, you're starting to go from the sort of classic waterfall approach. This is the classic funnel. And the messy middle I was writing about was how when you make the transition to activating interest as opposed to reacting to interest, how that requires very different seller follow up and very different seller tactics. And that's the messy middle piece. And so I feel like there's people that are better at explaining and really frankly have spent more time thinking about the other piece, which is the inbound. Like how am I more efficient with inbound? This is intense scoring, this is lead scoring, this is lead routing, this is lead orchestra. Like all those things. I'm going to let other people address that because I think there's people that are more expert. What I like to think about is what happens when you start a conversation with somebody who didn't know you existed and has a pain. That's a very different middle. And when you get there, Ty, there's so many vectors. There's a vector of who's taking the call, right. Who's making the call and then how are they approaching that engagement. And think about the difference between an inbound lead. I want a demo request and I'm willing to put up with an SDR as opposed to you reaching out going, I'm seeing this critical business problem that you're having. I think I can help you. Can we grab a little bit of time? One is SDR, by the way. Love SDRs. I've managed SDR teams. One is an SDR, the other is a business expert. And so what I'm talking about there is this transition from inbound order taking and really great sales process. By the way. That's really important stuff. I don't want to diminish it. Like doing that well is really important. It's really expensive to get an inbound lead. It's this transition over to a more expert led middle funnel. Because guess what, I started a conversation, I better be able to back it up when I get that person on the phone.
- [09:54]
A
Yeah, that's, that's phenomenal of like it's easy for I think others in the world or it's, I'm sure folks have fallen into that trap of sort of treating them very similarly or the same And I think that the difference is pretty massive when you think about the experience for the customer.
- [10:11]
B
It is. And I have to say it's, it's incredibly manageable, if you will. And again, it's. I feel like we really have, we have become very efficient. We as marketers within bound, we're really good at that piece. It's the. I feel like we sort of said outbound is too hard and it was incredibly hard. And I don't want to be obtrusive and I don't want to cold call people and I don't want to people. But I think that world has gotten. It's more, it's easier to do and better to show up with value because of AI. And I think that's why that messy middle is important. We need to work through those systems and processes.
- [10:43]
A
Yeah, absolutely. And AI is sort of obviously a big theme for a million reasons. You've delved into it immensely. So there's all these. That becomes such a big consideration. We were just obviously talking about it, go figure for our team earlier today. In a similar fashion, if you, let's say you get dropped in to 10 to 50 million AR SaaS company tomorrow, pipeline isn't where they want it to be. You want it to be. What are some like diagnostic checklist type thinking things that you would do to assess to determine how to improve that?
- [11:23]
B
I love that question. I love that question. And I have to say, like, that's just called a Tuesday for me. Unfortunately, my entire client base.
- [11:31]
A
Right.
- [11:32]
B
Just a quick background. To me, I'm a fractional cmo and so venture capital or private equity funds will bring me in and be like, hey, how do we get the growth moving in the right direction? So like I said, that's a lot of, A lot of my time is sort of in there. And a lot of it's psychology, frankly, with executives who are incredibly talented. So as much as I could talk about that, I think that's another, that's another podcast. But a couple things to note. The first is we ultimately have to measure from the bottom of the funnel up to better understand dynamics of the total funnel. And so one of the measures I always recommend, and I always start with is this idea of sales velocity time. And so that's like, it's. I actually had to write it down like, because I, I have, I have it like, I have it in a place where I just use an agent to go measure sales velocity. But it effectively is a way of saying, am I producing enough pipeline to meet the quotas of the sellers or am I producing enough pipeline to be able to say that I'm going to make a number in a given quarter? Right. And so what you're talking about here is if you will, we're going back to middle school math. There's metrics across the top and then there's a denominator, right? And so the metrics across the top are deal size. It is how many opportunities do I have? Right. And what's my win rate? And then you're dividing that by the length of a sales cycle and what that'll spit out is the number. And so if you need to be producing or processing $20,000 a day in pipeline to hit your number and you're producing 15, that's where I always start. Like hey look, none of the bs, no MQL stuff, no sellers don't know what they're doing. Let's get away from all that stuff. We're one team. This is not Kumbaya. This is just measures that say, hey, are we performing or not? And if it's lower than what it needs to be, then we need to start talking about how we go and correct for that. And then what I'm doing is, I'm saying okay, good, look, here's the world we live in right now. I'm going to oversimplify. We have outbound. This is the tools, tactics and strategy to start a conversation in order to help a customer versus companies that have self identified and have decided that they need help. That's inbound, if you will. For inbound, it's dead simple. What is my meeting booked rate on unique users? And by the way, sometimes it's unique users, sometimes repeat. It depends on your business model. But there is a number of visitors to a website. How often am I booking a meeting on that? And I'm at a min, I've got to be 1%. 2% is sort of. You're doing great. I've seen some companies at 4% best in class. If you're product license PLG Motion, you can see even higher meeting booked rates. Right? Because you're basically giving them the product and then the other is outbound. And right now outbound is under a huge amount of stress. So I'm going to give you this incredibly low number and it's going to feel weird that it's so low. But I just would caution you and say this is where I think everyday AI can help us. And that is a meeting booked rate of 0.05%. That's sort of like Baseline, that means you're sort of contacting the right people, maybe not at the right time, but you've got pretty good SDRs and they're doing a decent job of sort of setting up a meeting, if you will, or setting up a conversation. I want that to be 1%, but I'm okay with 0.05. So it is sales velocity one that bleeds out old BS. Okay. Then it allows me to go, great, what else do I need to look at? Because I'm going to guarantee you one of those other two metrics has a problem. Right. By the way, the other piece is what if my win rate is really low or it's a poor win rate? Quite often I want to make sure they're getting the right meetings. And so both tell me whether they're getting the right meetings or not. And then I'm doing another diagnostic into what's a win versus what's a loss and why. That was a lot. Those are the three metrics I look at. And otherwise I'm going to give you my whole playbook, Ty, so I'll shut up.
- [15:27]
A
I mean, that's just amazing and a lot to digest in a great way. Yeah, that's really fascinating. I don't know. So that's 1 to 2% conversion on inbound to form, like form submission, not PLG. And PLG, you want to be higher.
- [15:42]
B
Obviously I want PLG to be higher because I'm putting people in the product and it's not a meeting booked rate. And I would almost say there's sales LED and there's PLG metrics and I'm not a PLG person, so I'd say probably talk to somebody who's got a better idea there.
- [15:56]
A
And then on Outbound, you're basically saying your rate to book meeting is quite low. 0.05, which is not even. Not even half a percent. Half a percent. But you want it to get to 1%? Ideally, yeah.
- [16:14]
B
0.05 says that I have a competent SDR team that is pointed at an icp. One percent says that I have a competent SDR team that's pointed at prospects who need your product but don't realize it yet. Sort of called the hidden. They have a hidden. There's a hidden problem, there's hidden pipeline, if you will. And 1%'s just sort of. I'm identifying the right customers. I don't have the right message, like I'm not crushing it, but by the way, that's a 20x return, Ty. That's 20x from 0.05 to 1 and like just stop there and you're doing great. Hey CROs and cmos, you're crushing it at that point point. Everything else is great.
- [16:51]
A
Yeah, it's really fascinating. My brain's racing. There's a lot to go go on there. I'm going to let, let people digest that. Getting into your playbook, you've got some, some heavy hitting things to share. We talked about the zombie CMO piece of like okay, he come in the irrelevant CMO versus one that's very much alive and, and, and viable and, and making significant leadership contributions to growth. How do you kind of see that voiding the negative outcome and optimizing for the very much alive version of the cmo?
- [17:29]
B
Yeah, and Ty, the piece that you're referring to, it's on my substack and I have to admit like I have been that zombie CMO at times in my career. So it sounds like a bit of a scold or a judgment. It's not meant to be, it's more of a clarion call.
- [17:44]
A
So makes you a great judge of writing about it and sharing those names of course.
- [17:50]
B
Hey, I poop that bed personally. So yes, I can tell you when not to do that.
- [17:55]
A
You've seen all ends of the spectrum which I think is exciting.
- [17:59]
B
So the contention tie in that piece was just this. We have understandably we are all relying on a playbook that when everyday AI was rolled out, so this is ChatGPT, Claude, Gemini, et cetera. When it was rolled out, that playbook became less and less and less and less and less relevant. Right. And so it became less relevant because what we were all doing, especially in SaaS and especially as CMOs, we were all fighting over the 5% of a CAM that is looking for a solution to their problem at any given point in time. And so we were just really, really, really, really good at fighting for that 5%. My contention is this, that the game has changed enough and if we're using and I'm going to answer the question of how do I go from zombie to non zombie? And the answer is going to be data. And I'll get really specific here in a moment but really what we're talking about is how do we find the hidden problem? In other words, the 15% of the market that has a problem you can solve for but isn't yet looking that 15%. By the way, I'm quoting Gartner. These are Gartner's numbers. 5% looking at any time 15% has a problem that you can solve that isn't looking okay. So the zombie CMO piece basically said, how do we get to that 15%? If you're not trying to get to that 15%, you know, the point diminishing returns has been reached. And there's a whole other thing about how AI is so deeply impacting search. Right. Like there's this whole, like we could have a whole podcast just on that piece alone. But suffice it to say, it's putting huge pressure on SEO and paid because paid is getting more expensive and we're getting less organic traffic. And if you're not grabbing the large language model traffic, you've got a bit of a problem. That's another sort of hallmark of the zombie cmo. They're following the old content playbook. How do I create content that fills the top of the funnel with people that are never going to convert? Okay, so all right, back to how do I unzombify, if you will. Right. Well, it's actually incredibly, incredibly straightforward. Stop thinking about your first party data as being so first party data just means data I can get right from Google or from Facebook. And the data I'm getting from how people reacting to me, my website, all that stuff, how do you go and take that and actually in many ways go great. That's about the 5%. That's useful data, but it is not the data that helps me get to the 15%. And so what a non zombie CMO will do is to say, how do I use publicly available data? This is, I don't know if I'm in construction. This is permitting data, right? Here's the wonderful thing about regulated industries. They have to share data with governments, federal, state, local governments on what they're doing. And so if I'm marketing into construction industry, I have huge amounts of publicly available data that will tell me who's working on what project when. Think about that. If I'm marketing general contractors, I know what they're working on, right? And if a project's going sideways, I don't have exactly. I know two pain segments. I have projects that are going well, projects that are going poorly. So it is to say that the non zombie CMOs, and we call these revenue growth engineers are beginning to understand that data is how they get to the customers that need them before everybody fights over the 5%. And that's what the whole substack is about. Cannonball, go to market substack. That's entire like over 100 posts that go through and show people how to do this. But I would just say, like, the reason that I'm talking about zombie cmos is because I was one up until a year and a half ago. And I want the rest of my incredibly bright, talented peers to get out there and actually adopt AI so they can get to the 15%.
- [21:49]
A
That's amazing. That. And it kind of dovetails perfectly into AI eating a website. What does that do for B2B marketing? How do you. How does a SaaS CMO in 2026 actually adopt AI at the core of the strategy? It's just love to hear your perspective on that. You've already talked a little bit about building agents and that's a huge focus of the substack and all the content you're putting out. We'd love to get a peek behind the curtain and what that means for people.
- [22:20]
B
Oh, gosh, I'm falling into this role of being a scold and scaring people. It's not what I want to do. But let me just say this. What Ty is referring to is this article I wrote, gosh, almost probably three years ago now that effectively said for inbound, the average website is going to start to shrink. And the reason it's going to shrink is because it will become the number one customer for websites are going to be the large language models. The reason that's going to happen is user experience. I think we all had that tipping point where we were using one of the chats, one of the large language models, whatever you want to call them, and you were like, this experience is so much better than going and googling and looking for links. Always think in terms of what's the superior user experience. And so that's happening. And there was a point in, I think it was September of last year where the average B2B website achieved inversion. And inversion just simply means that the number of direct searches surpass the number of organic searches hitting the website, which is mind blowing to talk about. But what it says is, first of all, if you're not at that point and you're listening to this or you're watching this, you should be worried. Because what that means is that you're behind from a brand standpoint. The other thing is to say it just recognizes what's happening because guess what, everybody's going with a better user experience, which is, if I have a problem, I'm going to choose to use chat or Claude or Gemini to research my problem. Which takes us all the way back to this idea of AI eating your website. Well, guess what? AI doesn't need to Consume all the stuff that real people need to consume on your website. So what's happening is sort of, and you've heard this described as Listicles. How do I make it easier for AI to read? You know what, don't worry about Listicles. Think about how you can structure your website. And this is AI schemas, if you will. How do you structure your website so that the chatbot gets what it needs? And what that ends up doing is this. You're going to see these websites get smaller and smaller and smaller and the cms, in other words, what's being exposed to the large language. And the models are going to get sort of bigger and bigger and bigger and they're going to be more accustomed for the large language models. And then who wants to go visit a B2B website? Nobody. Right. Like they know, especially if you're marketing to marketers or sellers, they know they're getting tracked. Right. They don't want to be on there. So they're, they're as anonymous as they can be. But what ends up happening is again, user experience. The experience they have on your site is terrible. It's terrible. I don't care how good your website is because they know you're being tracked. So what's going to happen is they're going to spend more and more time with the large language models. And I would tell you there is a point where your website is down to a page or two. Most of the content is, if you will, in the back end. It's indexed, it's searchable, but you're not navigating to it on the website. It's orphaned. That's for the large language models to go figure out whether or not they should facilitate a conversation between them and the B2B websites. Chatbot. And so I think that's what's, that's what I, that was my whole thing. It's like it's going to be chatbot to chatbot.
- [25:29]
A
Yeah. Who was it? Aaron Levy or Jason at Saster? Somebody came out in the last two days and dropped a really great one liner which was essentially that. Exactly. It's going to be agent salespeople talking to agent marketers and agent agent brands talking to. It's. It's going to be agent to agent communication.
- [25:49]
B
But Ty, hold on. I wrote my piece three years ago. Well, but Ty Holder, can I tell you something? I got totally wrong just so because I just, I think I just to
- [26:00]
A
steal from Brad Pitted again.
- [26:05]
B
Well, I'm going to steal from South Park. I just sniffed My own fart. So let me stop doing that. Let me just say this. I predicted that would happen. This environment that I think they're rightfully speaking about. I said that was going to happen in 18 months and that was three years ago. So the speed of check. I misunderstood the speed of change dramatically.
- [26:22]
A
I think that.
- [26:23]
B
Right. I think it's going to be bot to bot.
- [26:24]
A
Honestly, just to pause to give you a little bit of props here, like that, that that data came out of the broader usage of AI recently where it's that giant square and it's like 0.3% of the population. Obviously there's a MA. 8 billion people for goodness sake. We're very fortunate to live in this little realm of digital marketing, I guess right now. And I genuinely believe we are. And even in that subset, like you are well ahead of the game, like actual usage of agents, in my opinion and correct me if I'm wrong, a year ago was being like heavily talked about, oh, this is the future. But you were almost two years in the past. So props to you on the predictive powers and keep it coming. I think the audience needs to realize like you deserve those props because that is not a joke. That is some serious, serious head start.
- [27:21]
B
But be careful. Ty, you nailed it, buddy. You nailed it. Right. Be careful because we live in these little bubbles and we do. And so you and I and the rest of our community, we're way out in that sort of innovators part of the adoption curve. Like we're not even like the rest of the market. We're like right there and the rest of the market's sort of behind us. And that's not to scold that part of the marketplace.
- [27:43]
A
Yeah. Don't have an interest.
- [27:44]
B
Let's recognize we're in a bit of a bubble. And I have to say for my part, I think I have to do a better job of helping people along because this stuff I think is going to help marketers for years to come.
- [27:55]
A
I agree. And I think you're putting out a lot of the educational pieces to really help enable that, which is super exciting to me. Is there something interesting around going deeper down the AI path? I know we talked a little bit about fractional CMO versus full time. What do you think is more exciting for you to talk about because you have such a recent knowledge of stuff you're putting out there that's AI specific.
- [28:21]
B
I just say. I think what you're referring to is when do you need a fractional versus when you don't. In my answer to that. Really? Because we talked in prep a little bit ty about it. I just say you always need a full time cmo. Always, please. And I will actually explain why here in a minute because I think the next question is, yeah, I know. Because this is what I do for a living to be sure.
- [28:44]
A
That's like your job is fractional CMO and you're saying we, you need to be all full time.
- [28:51]
B
Yeah, yeah, it is. And I get it. My managing partner is probably going to see this podcast and like give me a call like, dude, you're fired. But let me explain, let me explain part of why I think this is so important. And guess what? There is a place where you can bring somebody in like me who would be incredibly helpful when you're between CMOs. So I'm not saying don't bring us in, but I think that there's something in the ether that says no, you should use fractional CMOs or fractional executive teams instead of full time. And I don't like that and I don't agree with it for a lot of reasons. So what I'd rather do, let's just start. It's just really here is if I have option A, talk about my business of fractional, I'm going to go with option B, which is let's talk about AI a little bit more and where we can be most helpful.
- [29:36]
A
Yeah, I think, I think that's the, the catch. I wanted to like divert us back because so much of your writing or recent conversation, what's really top of mind for everybody, I get, I get your take there to be like it's better to have a full time long term commitment to an extent. But the AI, the AI pieces, the agent, the agentic stuff, what's. What would you, how do you kind of counsel people to make sense of that? If, let's say they're in technology, in B2B SaaS, they're progressed in testing some of the tooling they've operated. They're putting some operational pieces in place with AI. What might they be missing? What would you ask them to kind of get them jump started around AI?
- [30:24]
B
Well, the first thing I'd say is congratulations. It's amazing that you're starting, that you're taking the plunge and I also know how incredibly overwhelming that can be. And I would also say I'm an advisor and I sit on occasionally sit on some boards as an advisor in the SaaS world. And there's incredible pressure coming from your investors right now. Incredible pressure because they don't understand how these AI playbooks are being deployed, but they want you to do the same. They want to see the results. Lower cac, higher CAC to LTV ratios, all the things they want from you. The first thing I want to say is, good job starting. Okay. The thing that if you could just do any one thing, the thing I would ask you to do is this. Two things, actually. The first is don't deploy AI. I'm going to give you a negative. I'm going to give you a positive. Don't deploy AI to amplify your existing playbooks. Please, please. And that's what a lot of folks are. Of course. I can create more content. I can be more personalized and better targeted. Da, da, da, da. You're just chasing the bottom of the funnel and everybody else is doing the same thing. So please don't do that. By the way, I think I just blew up about a billion dollars worth of market cap when it comes to all the SAI sass.
- [31:35]
A
Okay.
- [31:37]
B
Yeah, yeah. And if I really wanted to freak people out, I'd talk about Codex and Claude code. But I think that's the topic for later. Okay, so here, this is, all I'm asking is this. And we sort of ty you and I started the conversation today based on this concept and I said 5 versus 15%. Finding the hidden problem. This is where I want you to start. And look, this isn't magic. This isn't. You have to know AI really well. What I want you to do is to take your ICP ideal customer profile, and I want you to maybe print it out and I want you to take it. I want you to burn that thing and then I want you to take the ashes and bury them. And I never want you to touch that again. And here's why. An ideal customer profile is about what's good for your brand. Because you're going to go find customers that are like the customers you have today. What I want you to do is this. I want you to first subscribe to the substack because all these playbooks are there. So you guys can do this without having to listen to me. But what I want you to do is to think about how do I identify what are the signals that my future customers are sending about their business problems. And I'm going to give two quick examples. How do I use publicly facing data to go and say, oh, I recognize when someone's having a problem. Okay, I'll give you two quick examples of, of what those differences are and how to get to the Data. Okay. So the first is one of the. One of my clients. I did pro bono work, by the way. I said, this is also really stupid. But I shattered a go to market engineer just to see what they were doing. Because this is so much of how I do my work these days is I use go to market engineers. And they were working for an architectural. Sorry, a company that provides project software for architectural firms. Right. And what this brilliant person did is they figured out that buying behavior tends to be driven by the number of architects in a firm. And especially when there's a surge, when there's multiple architects hired in a short period of time, they need this project management software because guess what, Monday.com and Asana stop working in that situation. In other words, you've got a scale problem. And simply by saying, okay, that's a pain segment. And then identifying for every state pulling licensing. Because as an architect you have to be licensed and you have to associate that license with an organization by just simply going and pulling public databases using CLAUDE code. Right? And this is if you've used cloud code, you're just talking to AI and going, I have no idea what I'm doing. Will you help me go acquire this data? And it patiently goes and does this for you. Now this person's a go to market engineer. They didn't do that se, but they sort of started with CLAUDE to understand, how do I go acquire this data? Then they, they automated it into clay. But that was just a matter of going, hey, go scrape all these different licensing boards and then tell me when you're seeing a particular company that had an increase in architects. That's it. That was it. They went from a.0024% meeting booked rate to a 1.2% meeting book rate. They were or sorry, 0.05 to 1.2.24x. And then they were like, fantastic, you guys are heroes. See you later. Because that's all they needed.
- [34:51]
A
Wow.
- [34:52]
B
So that's why, that's why I'm saying like start, start with just getting to people have a problem. The second example I'll give you is a company called Texada. We actually did this in the live stream. All that. All Texada does, it's a leasing management software platform for companies that provide a construction equipment for construction firms. That's all they do. Right. And what we figured out in the can ball go to market live stream was that we could figure out with public data, Department of Transportation data. By the way, it's all public, just got to go to their sites. We Figured out that because each construction company had to bond, had to insure, they had to talk about what equipment was or wasn't on site and what equipment they planned on using. And so in this case, we said, wait, hey, your segment are companies that actually don't have enough equipment in the field. That's your segment. We express that as a utilization rate. If you have less than 60% of that fleet that isn't in the field, then that's who you want to target. That's it.
- [35:53]
A
Right.
- [35:54]
B
If you want to understand more, there's a whole case study, there's a whole thing. But in both cases, this was using cloud code and Python code that, by the way, we don't know how to create, Ty, unless you know how to create it. That went in and acquired the data and said, okay, here's how we know which equipment is in the field, which isn't. But the key thing was companies with utilization below 60% pick up the phone and call those folks, because guess what? They're bleeding cash. And that's. To me, that's the number one step. All CMOs can take now to not be zombies is to go and use public data to go, oof. These are customers that need me and need me now.
- [36:27]
A
That's amazing. Are you on the Clogbot bandwagon? Claude.
- [36:36]
B
Claude, whatever.
- [36:38]
A
Whatever it is. I'm getting the names mixed up, but the Claude code.
- [36:43]
B
Yeah, cloud code. Yes, Ty, and let me just say this, the entire cannibal go to market substack, we got to top 40 because we leaned into what I'll call prompt engineering and progressive prompting. And then building agents around that. We're now doing a complete pivot. We're saying, how do we use Claude code to create applications that can do that work? So I just talked about segmentation, like, oh, God, Doug, I think I followed you. How do I do that? Well, gee, what if you could code an app to do that for you? So it was always on. We've pivoted really hard because the power of code now exists with dummies like me who can now code this stuff. So we're going that way just simply because all the promises of AI doing the thing I talked about before, segmentation. Imagine if you could just go and tell Claude, hey, this is what I need to do. Will you produce an application that measures who's in pain in Texas because their equipment utilization rate dropped below 60%? By the way, every time an account does that, will you send a text? Sorry, will you send a message to an SDR to call them.
- [37:47]
A
Yeah, it's insane. Okay, we need to drop where people need to go to subscribe immediately. This is too good. Cannonball GTM give us the yeah.
- [37:58]
B
So just hey, easiest thing to do is to Google. Although I just talked about how Google's going away. But just Google Cannonball go to market substack. It's cannonball gtm.com substack. You'll find us there. And I will say that when you get there, there's a piece of content that says start here because there's a lot to unpack. We're trying to teach go to market engineers and growth leaders at the same time how to do this stuff. So start with that article and then everything will miss all the mystery will go away for you.
- [38:31]
A
Amazing. Amazing. This could be three and a half hours but you've already dropped tons of value. I'm so grateful. Obviously you have a stellar book collection in behind you. I am a fan myself. Any suggested go to book can't misses that you want to throw out to the audience?
- [38:51]
B
Yeah. Gosh, great question. I think my current favorite that I'm obsessing about is and there's Now I think three books in the series which is 10x is easier than 2x. And if you haven't read it, it is just this. It's by a PhD in human behavior. And so it's not that like I've made a lot of money and I'm going to write a book about it type of guy. He's done the research and it effectively says how do I narrow my focus down to things that are actually going to drive a lot of growth and how do I get rid of all the stuff that's slowing me down? And it's a dead simple playbook and it gives you effective tools. So it's not just some guy like me going, you know what, focus on the things that are going to create growth. 10x versus 2x. You're like, how do I start? Highly recommend the book. I think it's 12.99 on Amazon. Check it out.
- [39:39]
A
Awesome. It's already in my shopping cart. Doug, anything that folks may not know about you that you haven't shared or that's interesting that we want to share with the audience?
- [39:51]
B
Sure. You can figure out what. Congratulations. But I was for nine months the lowest paid professional athlete in the history of sports. So if you guys can sort of look at me, I'm five nine. So it's probably not NBA. It's probably not football. I was not a kicker but if you Google me, you'll figure out what it was. I do pop up on occasion, but, yeah, that's probably the thing people don't know about.
- [40:13]
A
I have to know what sport that's amazing.
- [40:15]
B
White. So rodeo kayaking.
- [40:18]
A
Rodeo kayaking.
- [40:20]
B
There you go. Yeah, it's not a lucrative sport, but it was good. I couch surf for nine months in my. Before I left corporate M and A to go live on people's couches and eat peanut butter sandwiches and ramen. Amazing experience.
- [40:35]
A
What's the difference between rodeo, kayaking, and kayaking?
- [40:37]
B
It's. Think about it as. There's the different aspects to it, but the thing people probably will recognize the best is the playboat competition where there's a standing wave and you're in these tiny little boats and you're just. You're in there playing the wave and you're doing acrobatics and all that stuff. And then sort of like there are other events. I know it's completely crazy, but there are sort of other events associated with it, like creek competitions where you're going through. And people probably think of, like, getting through all these slots or all these gates on a. But it's the playboat thing that's called kayaking. Yeah.
- [41:09]
A
This has been an amazing episode for many reasons, but the answer to that question is. Is one of my favorites of all time. And you never cease to amaze. Doug, it's great to see you again. It's always a pleasure. You did not disappoint. I'm grateful for you coming on the show, man.
- [41:23]
B
Thanks for having me on time.
- [41:24]
A
Take care. Thanks, everybody.
- [41:26]
B
Cheers. Thanks. Thanks, everybody. Bye.