· 43 min read

Scaling from $1M to $100M ARR: Lessons from a Tech Marketing VP

Scaling from $1M to $100M ARR: Lessons from a Tech Marketing VP

In this episode of Learnings at Scale, Max sits down with Charlie Liang, VP of Marketing at Kula and former Head of Demand Gen at Lattice. Charlie, a SaaS marketing expert with over a decade of experience, shares what he’s learned helping companies scale from 1 million dollars in annual recurring revenue to 100mm in ARR and beyond.

Max and Charlie talked about poker math and how to apply it in marketing, the best cold outreach charlie has ever received, the importance of process, and a whole lot more.

Featured Chapter: Poker Math & Probabilistic Thinking (00:02:20)

Charlie and Max talk about ‘poker math’, or making probabilistic decisions under uncertainty with limited information. They talk about how this applies to business, marketing and making high-stakes decisions with limited data, much like poker players assess probabilities and bet accordingly. He argues that focusing on the process – making the best possible decisions given available information – is more important than short-term results.

Click below to check out the featured chapter on YouTube!

Full Episode:

Charlie shares lessons from a decade of driving marketing at high growth SaaS companies. He stresses the importance of understanding customer motivations, leveraging data to inform decisions, and documenting processes for scalability. Charlie also shares his perspective on the role of AI in augmenting marketing efforts, while maintaining the human element for strategic thinking and personalized outreach.

Click below to check out the full episode on YouTube!

Actionable Lessons:

Episode Chapters:

Quotes and Insights

And if you keep doing that over and over again, you're going to make 4 percent of all the money that you put in. [...] the math is going to catch up.

And I've been on both sides of this, right? I've sold and also been sold to, and I think being sold to the biggest mistake I've seen people make is not asking enough discovery questions upfront.

And a lot of times, like people make the mistake of not doing a big enough test because if you're doing a half-assed test, you're not going to get the real results, right?

Full Transcript

[00:00:00] Charlie: Eventually we all reach diminishing returns. You got to zoom out a little bit and figure out, okay, I've built a good model here. Is it more worth it to invest more resources into ~this channel or ~this unknown that might yield this other outcome?

[00:00:13] Max: My guest today is Charlie Liang. Charlie is a SaaS marketer with more than a decade of experience accelerating growth at some of the world's top companies.

[00:00:23] Charlie was previously head of demand gen at Lattice. a company that he joined at Series A and left at a more than 3 billion valuation. Charlie helped build the team that more than 15x'd revenue during his time there, and he is currently VP of Marketing at Kula. Today, we're going to learn from his experience scaling companies From under a million dollars in annual recurring revenue to a hundred million in ARR and beyond.

[00:00:48] Stick around to learn about poker math and how to apply it in marketing. The best cold outreach Charlie has ever received and how AI is gonna make this kind of thing a whole lot easier. The importance of [00:01:00] process and documentation and a whole lot more.

[00:01:02] Charlie: You get the process the results will obviously the results are important, but the results will come, right? There's a reason why everyone says, trust the process. Because the process is, I think, arguably more important than what shows up on the scoreboard.

[00:01:14] Because ~there's, ~there's macro factors that impact the scoreboard, things outside of your control, but if you focus on what you can control and building, the chemistry and having the foundation in place, the rest will follow.

[00:01:25] Max: Yeah, and like we were talking about before ~we start, ~we hit record, ~like ~thinking about things through ~like ~poker math, right?

[00:01:30] My background where I started my career was equity derivatives trading and my first exposure ~really ~to poker was through that where it's not like this, seedy game you're playing and with a bunch of people, a couple of drinks in them and losing a bunch of money.

[00:01:44] It was my,

[00:01:45] Charlie: which does happen.

[00:01:46] Max: Yeah. But it was ~like ~my head of trading, using this to instill ~like ~fast math and probability and help me understand this. And it's, Interesting with poker because a lot of sort of blackjacks probably this way too, right? The outcome is [00:02:00] completely independent of the choice, right?

[00:02:01] Like you're trying to make the best probabilistic choice Which doesn't necessarily always mean you're gonna win, right? You can there can be a probably crazy outlier But you need to just be grounded in okay, do the math. Is it a or b do a and then Independent of the outcome you just have to continue doing that.

[00:02:17] Charlie: Yeah, exactly like in poker I played a lot of poker in college and you know recently I since the pandemic I've you know picked it up I think one of the biggest like One of the oddest things I always thought poker players did was that they would celebrate when, and when they say they, like myself included, we would celebrate if we got the money in good, right?

[00:02:41] Let's say you're Pocket 2s for example, right? And you're, you got it in versus Ace King. You have 52 percent chance to win, right? That's getting in good. Still pretty much a coin flip. But you got it in good because you got that 4 percent edge. You got value. If you keep, yeah, you got the equity value.

[00:02:57] And if you keep doing that over and over again, [00:03:00] you're going to make 4 percent of all the money that you put in. Cause it, the math is going to catch up. But even if they lose the pot, they're like, oh it's fine. I got my money in good. I played well. And so I always thought it was really odd, but other people might, people that are not as familiar might think you lost the pot.

[00:03:13] You just lost, A lot of money, right? But as long as you focus on getting in good, and I think it has applications to tech as well. If you do the right thing don't worry about the macros. Like it's all going to even out, right? You just got to focus on doing the right things.

[00:03:26] Max: Yeah. And you get into even just taking that all the way into something super specific, like running marketing experiments.

[00:03:32] If you're going to take the first experiment and then, oh, it didn't work. So let's move on. You're never going to iterate your way into anything successful. ~Like you have to be, ~you have to be at the outset, willing to do, ~there's no number to it, but several very many ~experiments

[00:03:42] and then that gets into things like that sizing too. Like, how do you think, okay, ~you got a, ~whether you got a hundred thousand dollar marketing budget or a million dollar marketing budget or a hundred million dollar marketing budget. Like you still have to figure out how do you size those bets and do those things.

[00:03:53] Charlie: The numbers matter. And you really have to, I think to be a good marketer, like it's important to ~know the matter, ~know the numbers. You can be the [00:04:00] best corporate marketer, brand marketer in the world. But at the end of the day, you won't be able to succeed if you can't articulate the value that it brings, right?

[00:04:10] And so ~that would, ~that's what separates ~like, ~World class. ~I think ~marketing leaders with folks that are really good at the craft is just explaining to your leadership team what that value translates into. And if you can't quantify it, I guarantee you they won't be able to understand it as well.

[00:04:25] So regardless of what you're doing, whether it's product marketing, brand marketing ~growth and demand gen is one of the. Easier things to be able to quantify because you're dealing with numbers, but ~you got to be able to articulate the value, like even if the value is things that you made up on a spreadsheet and the assumptions like are not, you're not basing it off of actuals.

[00:04:39] You can just start with assumptions and then get the measurement in place and then use that to quantify. But the numbers at the end of the day are what drives, the business and you need to be able to know your numbers in marketing.

[00:04:50] Max: Have you ever read the book? Superforecasters?

[00:04:52] Charlie: No. That seems interesting though.

[00:04:54] Max: I read it when I was in college when I was trying to interview for like investment banking jobs or, and ~that, ~that kind of thing. ~But it's, ~[00:05:00] it talks a lot about how, and I'm, I read this book now like 10, eight or 10 years ago, so I'm not going to remember all the specifics, but the TLDR as it remains in my brain is how How incredibly close you can often get to estimating things back of the napkin, just by thinking through a couple of inputs, right?

[00:05:18] Let's say you and I go grab lunch someplace here, and we can, okay, how much revenue does this place do? We can say, okay, we've been sitting here 30 minutes, It's 15 people have walked in, it's a Thursday afternoon, this is representative of probably a busy time, so maybe there are three hours a day that are this busy, and then maybe for the other half of the time it's this, and we spent 48 bucks and we didn't go that crazy, so maybe that's represent, blah, blah, blah, blah, blah.

[00:05:40] Then at the end of the, you walk this sort of thought process through, and then you start to back that out to, okay, so how much did they make in a day, how much did they make in a week, ~add a standard, some kind of error there, ~and then you go ahead and say, okay, what we think they did.

[00:05:50] 800 to 1. 2 million in revenue, let's say. And the book Superforecasters talks about this kind of stuff. And ~how incredibly, but the point is just like ~how incredibly close you need to get just by rough kind of back of the napkin stuff. ~And I don't mean to ask this as a leading question, but ~what I'm [00:06:00] getting at and what I'm curious about is when we talk about how important it is to know the numbers for marketing, do you think there's more value in, let's say someone that's like Financial background like really, a wizard with spreadsheets and models and can really prove it to the point that like a CFO would see it and they'd be like, okay, I get this.

[00:06:19] Or do you think there's more in that kind of being able to do that quick back the napkin and say okay, this marketing thing we're going to do it's going to cost 48 grand. Like here are the four to five ways we're going to profit off of. What, obviously one has a higher perceived confidence than the other, ~but as we were talking about before, that's often a thing with data, right?~

[00:06:34] ~Like the more inputs, the more sure or certain it seems, but often it can be the opposite. So ~I'm curious how you think about that between the like poker style, shooting from the hip math because you're sitting there and you're like doing this math at the table and then trying to make decisions versus all the numbers have been crunched and checked and double verified and all that.

[00:06:46] Charlie: Yeah, I think the larger, it's a great question. We're going through this ourselves as well, right? And I think there's different applications. I think that for larger decisions, ~you need to be able to, ~you need to have put in the work, right? [00:07:00] Explored all the different possibilities and be able to quickly ~be able to ~explain ~why you've, ~why you're proposing a certain thing, right?

[00:07:07] I'll give an example. Recently, we've shifted our go to market approach to focus on a smaller set of accounts with more narrow personas, right? And~ we explored, ~the reason we explored, doing this is because we have a high degree of confidence that our, based on close rate information and ACV information, that this this is going to pay off in the long run, right? We wouldn't have known that if we didn't go through and pull the historicals and like pretty detailed information by rep, et cetera, ~pull the historicals~ and then use that to build a model that that is easily understandable by the leadership team, right?

[00:07:47] And then we presented it to them and they're like, Oh yeah, that this makes a lot of sense, right? Using these ACVs, these win rates, we can back into, okay, how many do you need to hit our, how many do we need to get to hit our new business goal? [00:08:00] And then how much pipeline do we need? It's pretty simple math, but ~we, ~you gotta do the legwork there. So this is obviously a large decision involves multiple teams, sales, marketing, success, et cetera. And you have to do that if it's a large decision to get people bought in. Otherwise people are going to call bullshit on you or, ~they're going to think that even if you have, they're going to ~think that this is not a well thought out plan.

[00:08:19] So I think the shooting from the hip math is more relevant for kind of day to day decisions, right? Deciding on what types of ad campaigns to run where there's Sometimes not a lot of data, and you need to go out and get the data, right? ~And ~I think where the shooting from the hip is important is, How do you decide, how do you make decisions when the data is limited?

[00:08:44] ~So one of the you probably took this class as well, but ~One of my favorite classes ~that ~in college, I was an econ major was decisions under uncertainty, right? ~So the more uncertain the ~the more uncertain the decisions, the less information you have. And I think that's where you need to be an intuitive marketer to come up [00:09:00] with what experiments to run in the first place in the absence of data.

[00:09:02] And intuition is based on experience. So I think both are important, ~but the ~but there's like different applications to when you would use it. Is that kind of what you've seen running growth?

[00:09:12] Max: Yeah. ~Yeah. I think~ I think that's an interesting what, the way that made me think of it in the way that I would put it, I'm curious if you agree, is it's like the fast math, that's what you need on kind of the.

[00:09:20] Intra budget decisions, let's say like we're ready We're gonna spend a hundred grand on paid this month and now we're gonna deploy that and then okay Should we see an opportunity to spend five or ten grand do this thing and we think it's gonna happen and then it's Like, okay. Well, if you went through the trouble of modeling that out Maybe the opportunity is gone

[00:09:35] but yeah, you're totally right. That ~it's I think ~it's, I think in many ways there's even like what we were talking about with the podcast, right? Like we're setting up all this equipment and it's yeah, part of that is, to ~do ~hopefully record high quality audio and stuff, hopefully this guy came out well, but the other side of it is you went through the trouble to come out here.

[00:09:50] Like I want you to see that we actually care enough about this podcast to set up the camera, set up the audio. ~Amazing setup, by the way. Thank you. And ~and it's the same ~when you're doing, ~when you're doing things internally and not obviously like people don't love like corporate [00:10:00] politics and stuff like that, you got a CFO who's got a million things on their plate or CEO who's got a million things on their plate.

[00:10:05] And sometimes just bringing that polished report or presentation. It's not about the presentation It's about then the CEO can just tell because the PowerPoint slides are laid out and like the numbers have been you did the sensitivity analysis and you know You did ran the P&L numbers and you gave them a worst case mid case best case the US you know you wrote up your explanations on assumptions and then it might not even be that they go and dig through all that.

[00:10:30] They might look at it for two minutes and be like, Okay, makes sense, looks like you did the work, right? And it's often as much about that as it is about the work, is the thing.

[00:10:37] Charlie: That's a really good point too, because you brought up the, essentially, personas, right? When you're making decisions, you either are the sign off person, or you need to sell the decision that you're making to whoever is signing off.

[00:10:51] I think if you're making the decisions yourself, and you can do that quick mental math, and you trust it. Then you're good. Yeah. To your point on ~the intra, ~the intra budget [00:11:00] decisions, right? If it's within your control and you feel like there's, especially when there's, time sensitivity, you feel like it's important to make a decision quickly, then, just go do it.

[00:11:09] ~And just do that calculation, whatever you need to do in your head. ~And then there's if you're selling the decision, you have to think about what you would need to see if you were in the group that you're selling to, right? And it's a little bit easier if it's one person and you've worked with that person and what they want to see, right?

[00:11:23] So ~you just give, ~you need to convince yourself first and then put enough information to be able to sell the decision. ~A little, ~it's even harder when it's a larger group because then you're dealing with three or four decision makers, right? And you need to Cover all the bases and sometimes it's hard to think about all the bases.

[00:11:38] Max: And put yourself in all the different people's shoes in there.

[00:11:40] Charlie: Exactly. Yeah. While also make it simple enough to understand by that entire group. So yeah, I think ~large selling, ~selling big decisions to large groups is probably one of the hardest things to do. ~I think, as a marketer or frankly, any other kind of business group ~

[00:11:50] Max: ~as well.~

[00:11:50] But, it's interesting talking about buying groups that it brings up this thing that Alex and I talk about Alex, my co founder which is that when you're selling [00:12:00] internally, people will often talk about the buying groups and all these different, the decision criteria and all this.

[00:12:04] The one thing that I never hear anyone talk about, I'm curious how you think about this, ~because I think it comes back to. This is an application of maybe not the shooting from the hip math, but being able to articulate value in that sort of intuitive ~ oftentimes inside of companies for better or for worse, there's a lot of politics.

[00:12:12] And so any internal person, for anything that someone's going to, change from A to B. It's okay, I still have a job with option A. So then if I switched to option B, whether it's an agency or different software or whatever, that internal person.

[00:12:27] They might not be compensated based on the impact of that thing, right? Like a lot of very, many companies aren't like bonusing their employees on profitability, let's say, right? ~So of course, like we're all saying yeah, everyone, everyone owns the revenue number and everyone's pushing forward and all this stuff.~

[00:12:37] Push comes to shove. Like people have to think about their paycheck and not getting fired and being able to provide for their family and all that stuff. So ~then that, ~then comes the decision that's like you could have the best pitch in the world and ~we could, ~you could ~show to ~show someone like, okay we're definitely going to ~make ~improve this thing for you.

[00:12:53] But then you're on the other side, you have someone who has a completely different decision set where they might be thinking like, okay, yeah, if I [00:13:00] improve profitability, Sure, like when I get to my performance review and if I'm able to demonstrate that ~was by this which is a question mark ~Then maybe I'll have this positive impact However, if anything goes wrong here if this blows up then I'm the person that brought in this thing And so their risk reward, yeah, completely opposite your risk reward and a big thing I think with like selling or anything is like how do you try to Align that risk reward.

[00:13:23] Charlie: Yeah, I mean, I think it's a really good point. I think that there's a couple of things. One is we have a really good product marketer on our team that just went through this for the specific target audience that we're going after, right? You need a good personas deck,

[00:13:39] Max: right

[00:13:40] Charlie: and I'm not talking about just one slide with a couple of different, bullet points, like a half assed one, right?

[00:13:46] Like really good one. That's well informed. ~You got to talk with. ~You gotta get a good sample size, customers, prospects, third party research, listening to, gong calls, things like that. Looking at, things like Attention, right? [00:14:00] Just get all the information available to you and create a very specific, the more specific the better, right?

[00:14:06] We created ones for this industry that we're targeting and this is not a big surprise, but the same people within this industry care about different things than other industries, same titles, right? So get very specific with the persona slides. I think it's one of the highest leverage things that a marketing, usually it sits in product marketing, but like a product marketing person can do that enables both the rest of the marketing team, but also the entire GTM function.

[00:14:33] Cause now they're, it brings clarity to who you're talking to. The other piece of it is. And I've been on both sides of this, right? I've sold and also been sold to, and I think being sold to the biggest mistake I've seen people make is not asking enough discovery questions upfront, right?

[00:14:55] And building that understanding before jumping into a one size fits [00:15:00] all presentation, because you can probably save a lot of time and you're going to build more respect that way. If the prospect feels that you understand them and then you can also build your talk track because now you know what they care about and what their motivations are, right?

[00:15:16] And you can tailor it to everybody that's in the room with you that you're selling to, whether it's one person or a mixed group.

[00:15:22] Max: If you wanted to build that personas deck and you're just you have nothing.

[00:15:26] Where do you start? ~What do you do? ~What are you doing first?

[00:15:28] Charlie: I would do three things. I would go and Listen to gong calls or like whatever recording software you have with this specific prospect, right? So let's say you're targeting product managers in the 401k space, go find a record of that in your, your software, your gong, and go listen to those, all those calls and listen to like as many as you can.

[00:15:54] And then go talk to your customer success team and say, Hey do we have any [00:16:00] upcoming calls with specific audience? And then either, prepare a list of questions that they can ask or ask to join the call or do it over email, right? Just get that information somehow.

[00:16:11] And that information should match like, what you're like, you need to, start ~like ~with a set of questions, right? That you're trying to find out. And then the third thing would be to ~like ~do third party research, ~right? ~But the third party research, depending on how specific your audience is probably going to be generalized and honestly the least useful.

[00:16:26] Yeah. I would start with the, just talking to people.

[00:16:28] Max: You've been in a lot of, like building the marketing function in the early days in a lot of companies. How do you approach that differently in the absence of a lot of that? If there are no gong, I'm sure you've been in that situation probably where there's, you got to figure it out and maybe it wasn't a persona deck, right?

[00:16:41] That was a specific question. But when there are no gong calls to refer to, there is no, TalkTrack to speak of, and you're really starting out like a blank piece of paper.

[00:16:50] What what are those, first two or one or two or three things that you're gonna go try and knock out to then get to that point?

[00:16:57] Charlie: I'll tell you a~ I ~Not a dirty secret, but like it's [00:17:00] something that I've learned to, that I've made a big adjustment to in my career.

[00:17:03] So earlier on in my career I'll apologize in advance, but I fucking hated tools like Notion.

[00:17:09] Max: Okay.

[00:17:10] Charlie: Because in my mind, ~I ~every minute spent on documentation was a minute that you, did not spend on execution, right? And when you have a small team, ~when it's one or two people, ~you just want to execute, you just want to execute, right?

[00:17:21] Because you're like, ~I got, ~I know what I need to do. Why do I have to write it down on paper? And that's not going to help you ~scale this podcast called learning as learnings at ~scale. Even if you don't think you're going to have ~a ~more hires on your team. If your team is like one or two people and ~you're, ~that's going to be the team for the next year.

[00:17:36] And who knows what happens after that? It is still good to document things because ~a, ~it forces you to think about like when you're writing it down, it helps your thought process. ~For me, it does at least.~ And it helps you think about, okay, why am I doing this thing? Is this thing really the most important thing? The second thing is it helps communicate to the rest of the company, Like it helps them understand your thought process, right? ~And that's a big piece of it is ~if people [00:18:00] don't understand why you're doing the things you could be the world's best executor. But if people don't understand it or, and they're not bought in then, and they don't have a chance to read and weigh in, then you're probably not going to be successful.

[00:18:11] Max: And also then anyone can tell the story of what it is, right? If it's not written down to a degree and ~not that ~not to imply that there's like this militant thing, right? But if it's not written down. There's nothing for people to refer to so they're just gonna say what they think which ~is ~might be completely wrong Especially if you're talking about like cross departmental stuff and that kind of thing

[00:18:27] Charlie: building the narrative to your point is very important And it's better that you build your own narrative, right?

[00:18:31] Yeah.

[00:18:31] Max: Yeah

[00:18:32] Charlie: So yeah, ~is that I mean ~you've talked to a lot of marketers and GTM leaders like ~is that ~how have you seen that approach happen

[00:18:38] Max: this is something that I'm trying to figure out honestly, in our business and with the documentation stuff, right? Cause where we are, we're not a software company, right?

[00:18:45] Like we're a professional services business, so everything has to be processed and documentation. But then at the same time, The thing that we have to balance that with is you go on our website and it says we don't sell a package or a process. We sell a solution, which is true, right?

[00:18:59] The way that I [00:19:00] always think about doing it is probably the lightest way to start. It's just Go through the thing and write down each discrete step that you did and even that action often when you look at it on paper You'd be like, oh, whoa I could consolidate steps two and three like four becomes redundant because of step seven

[00:19:16] Charlie: Yep,

[00:19:17] Max: and That's how we're trying to figure this out

[00:19:19] ~i'm very much learning as I go and just trying to figure it out. Yep So I ~do you have any tips?

[00:19:21] Charlie: I don't have tips but I was gonna say ~as you're saying ~as you're saying that one of the biggest things that I think that ~You ~Separates a good agency with a mediocre one is that's what we're like.

[00:19:31] Agencies make a lot of money. And that's what we're paying the agencies to do is to get that like cross pollination. You've seen more setups and growth patterns than we have because you work with a lot more clients. How can you use that without kind of, ruining ~confidential, ~confidentiality agreements and all that.

[00:19:52] How do you use that to help improve? Our setup, right? And we're not ~paying for we don't want to be ~paying for just tactical execution, which a lot of ~like ~agencies make the [00:20:00] mistake of falling into the trap of is just listening too much to the client. We want to hear what the strategy should be and then go in and test those assumptions.

[00:20:08] Max: Yeah. And ~it's a tough~ it's a very tough~ like ~tight rope ~often ~to navigate as the agency. ~Cause some, you want to be, especially, ~When you're working in the startup world because everyone's so busy, you have these teams where it's like probably there should be Two times as many people on the team as there are at any given moment because the goal is like we're trying to Triple this year and triple again, right?

[00:20:23] ~So then it's like you just do the math on that and then it's okay obviously at any given point the team's probably understaffed and so you there's special~

[00:20:23] Charlie: in this environment

[00:20:24] Max: Yeah, especially in this environment where you're not just ~you know, ~dripping in venture capital ~and yeah ~And so it can be~ it's definitely ~a tight rope to figure that out.

[00:20:29] Cause you want to push the ball, you want to be proactive and you want to push the client to the thing. But then you also want to be respectful of them and recognize that like they hired us so that they don't have to worry about this thing. Like the CEO doesn't want us bringing every little thing to them.

[00:20:41] And then you just got to, read the room, figure it out and~ calls every now and then make sure it's all good and stuff. But ~it's definitely, something that I think is Where you're always trying to figure out in this business, and I think it just comes down to a lot of ~like ~communication a lot of framing, like really pushing on ~like ~how do you want this to work and getting into that nitty gritty?

[00:20:58] but But yeah, [00:21:00] process. So much of it just like processes, like the security blanket around all this other like everything's so variable and everything's so in flux and like the way that you've got to start talking about something super specific, like how to do, how to execute like an outbound campaign or whatever, right?

[00:21:16] Like that the way you might do that today 12 months ago. It changes so

[00:21:21] Charlie: quickly,

[00:21:22] Max: right? Yeah. And so you need to have these You need to build systems, but they also need to be flexible so that they're supporting that kind of like agility and ability to test out the new thing and making it easier. And the million dollar question.

[00:21:35] Charlie: Yeah. What have speaking of kind of the variability, obviously the macros have changed a lot in the last two years, right? They flip flopped with the funding environment, being completely different, interest rates, all that, jazz, and at the same time, Obviously seen a huge influx of AI, right?

[00:21:51] That's what all the buzz is about. There's probably going to be ~a new wave of, there already is ~a new wave of companies leveraging ~all the ~all the goodness that AI has come to develop. What are you seeing [00:22:00] that GTM leaders like what's top of mind for you or ~for, ~for GTM leaders that you've talked to recently in what is it, March, 2024?

[00:22:09] Max: Yeah. March, 2024 was top of mind. I don't know if if this has been directly said to me by a GTM leader, but connecting the dots of a lot of different conversations on what I'm seeing some companies that are just having crazy performance in this environment doing is, I think it's a lot of in B2B at least.

[00:22:24] And I think this is also, ~I think this is true for consumer. This is ~true for any business that's trying to transact on the internet, but really getting good at maximizing the value of people on your website. Which sounds simple, but

[00:22:36] Using tools like warmly Let's say or you can do it with other tools But warmly I like because they like they'll send you visitors on site like into slack and so then You can have this set up where obviously it's not going to identify 100 percent of visitors.

[00:22:50] That's what everyone will say. Oh, it's not right all the time. It doesn't need to be right all the time. It can be right one 10th of the time and have a ton of value. And so doing things like that where it's okay, now everyone that comes to the [00:23:00] website, this is referenced against our account list.

[00:23:01] And then if it's someone that's in our account list, sales gets notified. We can talk until we're blue in the face about optimizing a landing page. You get it from 2. 5 to three. Like awesome. We got a 20 percent improvement on a landing page. That's awesome. Not to say we shouldn't also be doing that, right?

[00:23:14] It's you got to do all these things well But let's not also sleep on the opportunity to have the SDR go and just message that person and totally take the conversion rate To 10 percent or whatever, you know create just different like it can be a magnitude different.

[00:23:28] Charlie: ~Yeah. Yeah I think that's it's a really good point.~

[00:23:28] One of my Mentors always, always, you know, this is one of my favorite phrases that he would say is reach the people that count, don't count the people that reach, right? ~And ~which brings me to the point I'm a big fan of AI, ~right? ~I think it's the future. But the question I have to ask myself, or, our GTM function is, do we trust AI?

[00:23:50] AI to be able to formulate a an email or outreach, sequence that, with our highest value prospects, like we have a target [00:24:00] account list. ~Yeah, sure. ~AI can help, but are we automating the whole thing? ~No way. ~No way. We don't trust that, right? That's how you walk into a chainsaw. That's how you walk into a chainsaw, right?

[00:24:07] And we only have like 5, 000 accounts that you're targeting. Let's make sure we put our best foot forward. So I think AI is come a long way in terms of augmenting and streamlining that process. But at the end of the day, we still need a human to click send.

[00:24:19] Max: Yeah. And I think that is, I think what you just said I'm no like AI expert. I just work in marketing and obviously we're all trying to figure out how to use it. ~And me neither.~

[00:24:25] Charlie: Yeah.

[00:24:26] Max: . And we have a couple of clients that are like, You're doing some really cool stuff in like generative AI space and so on.

[00:24:30] So I just hear those guys talk and I just shut up and listen. Cause they blow my mind anytime they start showing me stuff. But I feel like that there, there's just how would I put it? It's Almost like a philosophical kind of misunderstanding that I feel sometimes with AI where it's like, people are, obviously some people are afraid of it.

[00:24:46] Cause they're like, okay, I'm gonna get my job displaced. But with something like what you're talking about would we trust it to send an email to our top prospect? No way. But why bother? Like, why, cause ~I think, I I did the sort of, ~I think a lot about sales cause like ~when I start, ~when we started Opuscope I was the SDR.

[00:24:59] That's all I [00:25:00] did. I just spent the first nine months of my job, all I did was email people. And that's how I met you, right? And I tried all kinds of different things all the way from, super personalized, that's how I met you, calling out poker and using that in a cold email, all the way to the other end of the spectrum to sending super automated emails.

[00:25:14] And what. What you find is that if AI can make the email writing even just a little bit easier, the amount of output that you can get from an SDR. is so much higher. And it's not even about output. Like output's a thing, but of course, like it's also about the outcome you drive, but it's that it can make the job so much more pleasant because when you're doing that SDR work and you ~sat, ~sit down at your computer at eight in the morning and you pull up outreach and you have 74 emails to write and then you finish the first one and you wrote a great email and you're like, okay, 73 more of those to go.

[00:25:48] ~Yeah. Yeah. ~So just the fact that AI can ~like. ~help get an email started.

[00:25:51] Charlie: Yeah.

[00:25:52] Max: Identify a couple of persona specific pain points. Do a little bit of research like that can be the difference between SDR, ~like a, ~doing a good job and a bad job, but [00:26:00] also enjoying that work and being able to focus on ~the like ~the business thing that they're trying to do and not just write the email

[00:26:05] Charlie: Exactly.

[00:26:06] Yeah. ~I think the ~I think AI is gonna eventually might replace all of our jobs, right? I don't think it's anywhere near that. I think that it is a Multiplier. Yeah, it's gonna make the best even better and it's going to make ~the risk reward, or sorry, ~the reward for being the best even higher. Because now instead of the best being three to four X, they could be 30 to 40 X because ~all their, ~a lot of their tasks can be streamlined through AI, right?

[00:26:32] It just makes them ~like ~faster. And if you're good at making decisions, then that's just going to be a multiplier. ~There's a, here's a shameless plug for my LinkedIn profile. This is probably ~Eight years ago now, ~right? ~I was working at Engageo and Engageo at the time was ~a ~very hot, right?

[00:26:43] ABM software got acquired by Demandbase, that's it's moot. I think someone wrote me an email and I wrote a LinkedIn article about it because it was such a great email. The email was titled, the best prospecting email I ever received, right? And it got like a stupid amount of likes ~on, on, ~[00:27:00] on LinkedIn.

[00:27:00] I think it was like half a million views. But essentially I'm not going to ruin it, you should go take a look at it, but essentially we'll link it

[00:27:06] Max: in the show notes,

[00:27:07] Charlie: right? Yeah. We'll link in the show notes, but essentially that email could have probably took that person like an hour to write, right?

[00:27:13] And it worked because it got through. But today, it could probably be done in 30 seconds, right? If you had the right, algos plugged into the AI. Yeah, I think it's going to make our jobs a lot easier.

[00:27:24] Max: One thing I'm curious your thoughts on as a, someone that's leading a team and I'm sure you have a lot of, experience.

[00:27:29] People who, people who are reporting to you who might be their first job, right? And I'm curious ~ I'm gonna I'll lead the question a little bit, but I'm curious ~how you think about how AI impacts early career development. Because I've been thinking about this a lot, because we were talking about, my background earlier, and so I, I didn't have a technical background.

[00:27:42] Background in college or anything like I you know, I didn't study computer science I studied economics at a liberal arts school in Colorado ~in my ~I was optimizing for like maximum time riding my bike and getting out of school in three and a half years, ~you know ~So that was like I was not trying to take all the advanced classes Maybe I would do that differently now, but so I spent a lot more time like self teaching myself stuff [00:28:00] I started working and then I was like, okay, ~like ~I really have to learn this Python thing because it seems like it's gonna be pretty important and I ~you know ~Started slowly.

[00:28:06] I read the like what is it's like there's this one Python book that gets you started That's really well known that I'm losing the name of and I you know I read this book and I'm watching YouTube videos and then I'm like my brother is pretty savvy with coding and stuff And so I would ask him questions He told me that you know find a project that you can do Simple project that you can do.

[00:28:22] And then that was the big unlock for me. Cause then it was like, okay, I'm now actually, I'm not just writing like a hello world, Python script. I'm like doing a thing and then it leads you to start Googling and then, you're spending all this time on stack overflow, which got killed by chatGPT and and that was, a very useful exercise.

[00:28:38] And now I still use Python every now and then I don't, I'm not writing code all the time, but like our director of analytics and I were working on something the other day and it was super helpful that I was able to just like, in this case, I use chatGPT to write the code, but I was able to vet it and stuff.

[00:28:48] But what I'm getting at is that what I think is fascinating is generative AI in a way it makes the actual the trade, like the skill itself, way less valuable, and the [00:29:00] intuitive understanding much more valuable. Because now if I wanted to go and learn, back then, I was trying to take, okay let's say, data source A and output it in spreadsheet format B for some file upload or whatever.

[00:29:11] And now, I could just upload those two files to chatGPT for all intents and purposes and say, make A look like B, and then get code. ~And ~I'm curious how you think about that with early career development because it's amazing that you can do that. And it sets this level playing field where you don't have to be this expert in Python or in coding to be able to have the same outcome.

[00:29:31] It's more about how you think about it. But there's still certainly a positive impact that comes from having that learning of figuring it out for the first time. ~Yeah. I'm curious how you think what would you, as we're like in this early we're really just in the early days, ~what would your recommendation be to your, someone that reports to you or someone junior in their career that's trying to like upskill and like how that might affect the way they go about that.

[00:29:48] I think there's two things. ~I think that ~if you think about the work that AI is displacing, it's mostly grunt work, right? It's mostly [00:30:00] manual. tedious task or things that take time that it automates. Great. What it is not ~currently, I don't think it's ~currently capable of doing is replacing the strategy. So I think ~that which means ~that the value that you provide is going to be even more heavily weighted, even earlier on in your career on the strategy ~and this ~and the decision making. ~So ~I would spend a ton of time just getting good at strategy, talking with marketing leaders, thinking about how they think, talking with industry experts reading up on marketing tactics, right?

[00:30:36] Charlie: Just being really good at the things that I can't do. And the second thing I would probably recommend is, and this helped me like earlier on in my career, but it wasn't AI, it was like, just being good at the systems, right? I was a marketing ops guy to start. I was a Marketo certified expert Marketo champion, whatever, right?

[00:30:53] Like really good Marketo user. I was a really good Salesforce user because I realized that there were shortcomings, ~and there still is ~ [00:31:00] in marketing automation that. You could only leverage Salesforce to accomplish such as workflows, such as formulas, things like that, right? Like just like things that were tactical, but made a huge difference in how good your marketing automation and operations could be.

[00:31:15] So I don't think that changes. I think you still need to be like really good at You still have to stand out like your resume still has to stand out from all the others, right? Because now arguably it's gonna be even more competitive less jobs So you have to do you know, like one or two things really well, what are those one or two things for you?

[00:31:35] AI is such a hot thing right now. Why not be really good at AI, right? Get credentials, get a deep understanding of how to use AI and when, and I guarantee, get really good at writing prompts. So just be the world's best at one or two things. It can be AI, it can be something else, but I think that's how you stand out in this market, right?

[00:31:55] Similar to what you're doing here, right? With you didn't have to have, a whole [00:32:00] setup on the road, three cameras, like the best of, the best equipment and you brought that all in, a lot of suitcases.

[00:32:06] Max: Those three came with the studio. So fortunately I only brought two bags.

[00:32:09] ~Exactly. ~

[00:32:09] Charlie: I think, and we were chatting before the show about this is that's what makes you stand out, right? Cause. ~Even in the content space, ~there's a lot of folks doing podcasts. There's a lot of folks doing, all different sorts of content, but you recognize that like ~in order to be, ~in order to stand out, you have to be just better than the others.

[00:32:23] Max: Yeah. And I, yeah, I appreciate the compliment. Thank you. I think ~it's ~it's a lot about, control all the variables you can control, right? ~If they're, ~if you're starting your career out, ~like you~ you're often ~like ~grasping at areas where you can create value and you don't know enough about the business to really do it, so then it's just what can you control? Spend more time reading and ~trying to do ~focus on self improvement and whether it's learning how to write prompts or whatever. ~I'm, ~talking about early career, one thing I was curious about is that I saw that your first, Job was at Google, right?

[00:32:51] Like a contract job at Google? . And I don't know exactly what you were doing. I'd love to hear about it, but ~what I, ~one thing I was wondering is. Did just being on the ground that [00:33:00] early at Google ~wall, all, thing like ~back then that was really early days of Google ads and stuff like that.

[00:33:04] Did you see something there that made you think, Oh okay, marketing is a place to a direction I want to go. Or was it more like ~a, just a, ~you just happened your way into marketing ~and, or just curious about that. Cause I, ~I saw that and I was like~ that's, ~it must've been a pretty interesting time just to be in that room.

[00:33:15] ~I guess.~

[00:33:15] Charlie: Okay, so ~very I'll ~I'll give you, it's not as interesting or it's a weird, ~I, it's a, ~I stumbled upon Google, right? To understand why I took that job versus, or I took that job, you have to understand ~my, ~What happened during college? We were talking about this before, right?

[00:33:30] So during college, I was not the best student, got terrible grades, and spent more, probably 2x or 3x more time on poker than I did at coursework, right? ~And that, ~so what that meant was I didn't have a lot of experience. Like I didn't spend summers interning like I should have. I spent summers just grinding at online poker, right?

[00:33:54] It was a short term beneficial for me, but long term it probably set me [00:34:00] back. My partner did completely the opposite, right? She was like a model student, did interns at Cisco and was able to land a job even in 2010, immediately, right? And that was a couple years removed from the crash in 2008, and I think the environment ~is, ~was probably similar or even worse than it is today, right?

[00:34:18] So what that all meant was like, Are you going to hire someone that just graduated college with no, no experience? You can imagine how well the interviews went. So I got I got calls, but I probably went on 50 or so interviews ~until, and ~I was just getting really like frustrated because, ~I just couldn't, ~I was living at home, move back home after college and I couldn't find a job.

[00:34:40] And poker was like, it went downhill after the, online poker got shut down. I woke up one morning and I got a call from an unknown number. I picked it up and it was a a recruiter from a temp agency. And they're like, Hey we saw your resume and would like to interview you for a job at, I blacked out after that.

[00:34:58] So I'm like, yeah, Google, right? ~I'm like job. Yes. ~Sign me up. ~I didn't care. ~[00:35:00] I didn't care what kind of job it was. ~And some way, somehow I, ~even though it was ~like, ~a contract, job. ~And ~the job was basically looking at pictures of products and confirming whether it was that product or not.

[00:35:11] ~So like I would work on like image recognition. ~It was image recognition. It was for Google shopping. And it would be like, Hey, help train the algorithm for coffee makers. So ~like ~my job was literally eight hours a day. Is this a coffee maker? Yes. Or no. So some

[00:35:21] Max: amount of the Google shopping algo is. All of it.

[00:35:24] No, I'm just kidding. So if you see

[00:35:26] Charlie: a coffee maker out in the wild and it's not, it's probably, it was probably a mistake on my part. But that wasn't really marketing, but I think what happened there was that because people saw Google on my resume, they were much more that was my differentiator, right?

[00:35:40] They were willing to talk to you. They're like, oh This person's working at Google. They must, be able to do something. I was able to have a lot more conversations. And that's how I landed in into my first job at in marketing was that, there was a little company called Adaptive Planning.

[00:35:53] Later Adaptive Insights at the time. And it was like a 60 person company and ~they were like, I was marketer, I was going to be marketer number five. ~They were willing to take a chance [00:36:00] and it was like super entry level marketing, but that's how I ended up in marketing.

[00:36:03] Max: Okay, nice. And then what was your path from there?

[00:36:05] ~What's like the, I'm like, that's like the biggest can of worms to open. Obviously. ~

[00:36:05] Charlie: ~Path from there to to sum it up is like ~I was doing marketing ops before it was called marketing ops. ~So basically like you mentioned Excel. ~We did a lot of it was an enterprise sales motion. So a lot of it was just email spray and pray. And. acquiring lists, cleaning up those lists. I got pretty good at Excel from doing that. And then loading it into Eloqua at the time, which is a marketing, early marketing automation platform. And just We would do these monthly webinars and I was responsible for running ~that, ~that webinar program.

[00:36:32] So just like emailing people, on about webinars about happy hours that we were doing in random cities, cause we're still in the CFO. So we did things like, I got really good at knowing where all the smaller cities are in the US, that kind of work, right? And then building lead scoring before it was called lead scoring.

[00:36:49] So that kind of work. And then eventually that translated to a career in demand gen, which I was doing already, but it was, demand gen was like, I think really started to take off in the early 2000s. [00:37:00] 2010s. And then just getting good at that, learning all there is to learn about, demand gen picked up how to do some ads to compliment emails and then events.

[00:37:09] And then eventually that ~learned, that, you know, ~got me more exposure into content and product marketing just working with some really good people there. And then that took me to where I am today is running the a small, but mighty, marketing org.

[00:37:20] Max: . One thing I'm curious about with that, and ~I think I heard this, ~I think I heard you talking about this in another interview and you touched on it there, but it sounded like ~earlier, ~early in your career, you and I have this shared, it sounds like a similar shared experience in a way, albeit in very different industries that early in our careers, we had to do a lot of like automation, like process automation.

[00:37:37] How does that sort of systems thinking lens, how has that influenced, the way that you approach marketing overall, like later in your, later in your career now leading teams and that kind of thing.

[00:37:47] Charlie: I think systems think I like the word systems thinking because

[00:37:50] ~there's a it's like a system, right? ~Basically you're trying to build a machine. What is marketing? If it's working correctly, it's supposed to be a revenue generating machine. So I think that line of [00:38:00] thinking. helps you focus on the why. A lot of people, a lot of times people get bogged down into the how ~and the, ~and then the process, but like it forces, which is important, right?

[00:38:10] But it forces you to think about why you're doing things right. And marketing and GTM for that matter, and businesses, it's just a giant problem set, right? So if you can articulate the why, which, can be a, either revenue or derivative of revenue. So a derivative of revenue would be like pipe gen.

[00:38:30] ~So by~

[00:38:30] Max: why you mean your, ~the thing you're trying to impact,~

[00:38:31] Charlie: the thing you're trying to impact, then you can reverse engineer and build a system to drive that outcome. And I think that's really important to think about because that's how you ladder up and impact business goals But if you can't I think the system is important But the why is the most important right and then just working backwards to solve the why

[00:38:50] Max: ~yeah That makes sense.~

[00:38:50] And probably, like we were talking about earlier ~with doc, ~with something like documentation, if you're building these systems, ~like ~you have to be able to stack the growth, you have to be able to move from, okay we figured out [00:39:00] motion a, whatever it might be, we're doing cold outbound ~or we have some, whatever, ~we do a webinar and it drives X pipeline ~or whatever, ~but you have to be able to think through that systematically and then build, stack, move on to the next one, pass it off to someone else, move on to the next one and try and build these programs to keep that like curve up into the right.

[00:39:14] Charlie: ~Yeah. ~Yeah. And also I think the systems is important, right? You want to, if you're focused on, let's use the outbound example, you're trying to build the world's best outbound engine for your specific vertical and your, ICP, but once you've reached diminishing returns, eventually we all reach diminishing returns.

[00:39:32] Then you got to Zoom out a little bit and figure out, okay, I've built a good model here. Is it more worth it to invest more resources into this channel or is it more worth it? It goes into the decisions under uncertainty coursework that we're talking about. Is it more worth it to invest it into this or this unknown that might yield this other outcome?

[00:39:53] And then it becomes a I don't know, what's the allocation, right? ~So it's, ~so in that sense, it's a little bit of intuition. ~You, ~we talked about shooting [00:40:00] from the hip earlier. You have to shoot from the hip cause you don't know this, like this brand new thing, how it's going to work.

[00:40:05] And then you have to shoot from the hip on, okay, how much of a test do we want to do? How big do we want to go? And a lot of times, like people make the mistake of not doing a big enough test because if you're doing a half ass test, you're not going to get the real results, right?

[00:40:19] ~So you have to. ~Push a good chunk of your chips into this new test. And there's going to be a time where everyone has to do the new test and you have to invest in it properly to get the proper signal on whether it's going to be worth it or not.

[00:40:31] Max: Yeah. ~That's, ~that's a great point that you caught.

[00:40:33] And I think that's a really good application for having that, ~like that sort of ~mental math background, like the poker math. ~ Like to your point of And this is not to say that people, obviously this could sound super biased coming from like someone that runs an ad agency,~ like there is a motion to test at every level, like if you have 200 bucks, if you have 200, 000 bucks, ~like ~there is something that you can do with that budget, but an important part is figuring out ~like ~what table am I actually playing at, right?

[00:40:48] If you have a hundred dollars and you go sit down at a hundred dollar a hand blackjack table, you're not going to be there very long. It doesn't matter if you're the best blackjack player in the world, but Marketing, companies will often do that with marketing, ~but they'll talk about ~you'll see this often in like high [00:41:00] ACV SaaS, right?

[00:41:00] Where someone will say, okay, we have a 5, 000 budget and we want to run this experiment. And then you'll say, okay What is an acceptable CAC for you? And they'll say it's, okay, 15, 000. And then so you'll say, okay, so what you want us to do is you want us to go run it. Let's just walk through the math.

[00:41:16] You want us to run an experiment where the metric of if this succeeds is like often did we get a customer or did we get a demo booked or something? And you're telling me that the CAC that is acceptable is 15, 000 and the amount of money that you're willing to allocate to the experiment is a smaller fraction of that.

[00:41:32] Like you don't have to be a math genius to say that~ okay. ~You're most likely no matter how the best team in the world could deploy this experiment for you, right? But it you probably won't have any signal value out of it because there's just not enough budget like if you have a cac of this like Obviously your experiment budget probably has to be bigger than the cac of one customer,

[00:41:51] Charlie: Yeah,

[00:41:52] Max: and it's interesting to see how like Budgets can just get burned by ~sizing it too small, ~sizing it too small, sizing it too small.

[00:41:58] And then the objective was to save some [00:42:00] money, but you ended up spending a lot more money along the way. Yeah.

[00:42:03] Charlie: It becomes a distraction if you're not like the whole company has to be committed to to these experiments, right? ~Otherwise it's not going to make sense.