The Lean Revenue Factory: Leveraging AI for GTM Success

Yeah, we're going to be talking about efficiency and a lean revenue factory and, and how to set up for, to get AI working for you rather than the other way around.

So let me just get to.

There we go. Okay, let's get to it. Thank you, Stephanie. Thank you Gerhardt. Thank you for the shout out for the book. I really do think we can do this deliberately. I'm going to walk through a story that's kind of sad and then, and then it kind of, we get some lessons from the past and then we get to the hope part of the story. That's kind of the arc of the presentation today. But you know, we're going to start with.

What we're all trying to do. A startup. A lot of us are at startups. Startup is an asset class that's capable of transforming million dollar asset into a billion dollar one. That's not true about commodities, not true about gold, not true about stocks, not true about bonds. But we can turn because of the people that we are, we spot things that other people haven't seen. And those opportunities we're able to exploit, we're able to build them out, we're able to turn them into take a million dollar asset and turn it into a billion dollar one. And the way we do that is through phases. In the beginning it's all about product. We spotted an opportunity, we built something that was amazing, that can add value to people, that can create impact.

Over time. With that amazing product, we got to get it to market. That's what we're talking about today. You know, go to market becomes disproportionately more important. During the scale up phase we have a great product. Now we got to get it into people's hands and create ongoing recurring impact which generates recurring revenue. And then when we get to kind of that grown up phase or it's more about strategy, it's still all go to market and product. But now we can do some big strategic moves like M and A or entering new markets or doing product extensions, et cetera. That's how we turn million dollar assets into billion dollar assets. And some of the kind of underlying pieces of that equation, you know, we, we talked is gtm and we got to do that efficiently. We're going to talk about GTM efficiency. Some of it is, then we're going to talk about lessons that we can learn from what happens in efficiency in a factory. And then we can talk about some of those core principles of revenue architecture Gerhardt that you referred to. They're in that coffee table book.

That we standardize around as we're turning million dollar assets into billion dollar assets. So let's talk about GTM efficiency. This is a very very simple metric. Comes right off the income statement. Anybody can measure it. Literally just look at your income statement trailing 12 months sales and marketing spend. We're ignoring stock based compensation. So it's just the stuff in your income statement sales and marketing spend over by how much did your annual recurring revenue go up in the same period trailing months? So that's revenue from new customers, revenue that we renewed into revenue that we expanded with our existing customers and then it's taking a hit for non renewals or attrition. Just the net change in ARR on the denominator and everything we spent to get it in the numerator times 100%. So if you spend $1 to get $1 of net new ARR, this metric would be 100%. If you spent $2 to get $1 of net new ARR, this metric would be 200%. Let's look at how that plays out. So you know, If I'm spending.

$2 to get a dollar of net new ARR, I'm in that blue range, $2 or less. If I'm spending between 2 and $4, I'm in that yellow range. If I'm spending over $4 to get $1 in net new ARR, I'm IN that red range where I may want to be thinking about what I'm doing. And the more I spend for the same amount of growth, the less efficient I get. Conversely, the less I spend for the same amount of growth, the more efficient I get. So down is good, up is bad on this GTM efficiency metric. So let's look at some trends over the last five years. This represents quarterly numbers for the last five years. We have gotten worse at this in the go go days of high growth, you could see 2019 through 2022, we spent less per new dollar of ARR than we're spending today. Growth is harder to come by.

And we're spending more money to try to get it. When you look at actual companies, these are actual company as of the end of Q1, 2023.

Sorry, 2024.

Some of these companies are chasing that growth pretty hard. You look at model N, you look at Zora spending more, spending more, spending more per incremental dollar of ARR Dropbox and and cresting over 400%. I'm going to spend $4 for every $1 of net new ARR.

The good news is on the other end of the spectrum, there are companies who are doing well. Now this. Now these companies tend to be the ones that are chasing growth the hardest. On the other end of the spectrum, there are companies that are spending less than $1 for $1 VAR or less than $2. And many of these companies are actually getting more efficient. You see AppFolio spending less overtime to get a net new dollar of error at last year and less overtime. Datadog, less overtime. Palantir, less overtime. So we've got kind of a tale of two cities here. We're chasing growth. We're trying to do it the way we've always done it. Some of it's working, some of it's not. GTM efficiency is indeed the important thing about the scale up phase of any startup's journey. Startup, it's all about the product and product market fit. Scale up. It's all about GTM efficiency. So let's look at what happens in a factory and see if we can take some lessons. Manufacturing factory cares about three things. High volume.

Cost efficiency and product quality. If you're building a factory and you can get high volume at an efficient cost and high quality, you're doing it exactly right. If we take that factory and we say, well, what if that were a revenue factory? Let's look at that as a lean revenue factory. How do those translate? High volume translates into scalable growth, meaning I can get more, I can get more, I can get more. It's a repeatable scalable action that gets me more over time and I can get the volume that I want. Quality in manufacturing translates into quality revenue in recurring revenue. And quality revenue is the type that renews. So the type that renews and expands, that is durable growth. That is the type of thing that, you know, I'm creating recurring impact with the right customers and they're renewing year after year and they're expanding their use. That's quality revenue and cost is just what we talked about. GTM efficiency. I'm doing this in a way that I'd like to do on Monday and on Tuesday and on Wednesday. And the more I do it, the more I like it because every unit of growth is efficient and economic to me. So I want scalable growth, sustainable growth, durable growth. If I'm building the GTM version of that factory. Now in a factory also we've got production lines. So I've got a, you know, if you think about craft manufacturing where an individual craftsperson is building an individual product, that's a no volume operation, high touch High customization. The industrial revolution innovated on that and put things on assembly lines and standardized things so that we could do slightly higher volume. We labeled this low volume and low touch. But assisted production and then further innovations added machinery and automation. This is what we're talking about today. How do we get machines to work for us and how do we do high volume, lower touch or even no touch gtm? Each of those corresponds to the way we might serve a customer in. In a GTM organization, an enterprise sales pursuit might be highly customized and high touch. An SMB pursuit might be lower touch and a PLG product led growth pursuit would be zero touch, all handled by the product itself.

So factories going after growth, efficiency and quality, dividing up their work into production line depending on the product and the market that we're serving. If we're going to do this in gtm, we've got to understand also that every one of those production lines has an input, some throughput and an output. In gtm, the input or prospects, the output are what we just talked about growth, quality and efficiency. And in GTM our throughput is how quickly we can move prospects from awareness, interest and consideration through to initial commit and then adoption, renewal and expansion. How quickly can we do that? What's the velocity and at what rate can we do that? What are the conversion rates? And when things are working we want to do more of it and when things are not working, we want to do less of it. Well, how do we know if it's working or not? We pay attention. Like we measure it, we want to measure each of those of those conversion rates and then through what we call a closed loop, that data is going to come back in and help us adjust what we're doing in inside the box. What's inside the box? It's process inside the box. Depending on the GTM that we're pursuing, we've got both, we've got process that's being executed by a combination of systems and people.

If we know what that process is.

And then we can compare the output that's happening to and then we can measure the output that's happening. We can make adjustments. If we don't like the output, we can come make adjustments. If we do like the output, we can do more of what works. But if we don't have that process well defined in that box, then we will not be able to make adjustments when we don't like the output. The output happens because of random process. How do you change a random process? The output happens because of a specified Process. Great, then let me go. Either do more if I like it or less if I don't like it. That's how a factory is built. That's how we want to build the operational backbone of a gtm, a lean GTM factory as well. You can imagine if you wanted to employ a robot to do a job for you, you would need to be able to instruct that robot what to do. And that is what the promise of AI is in a GTM factory. But we need to be able to instruct the robot what to do, what is the process that we're running and what are the expected outcomes.

So let's talk about.

Quality management. In.

In manufacturing we've got six sigma to measure quality that measures the level of defects. In software development we have agile that defines all the processes that we want to follow to ship software.

In factories we have lean management as a set of methodology that we follow. In product we have fine thinking, that's a process to follow to to get close to the customer, develop empathy, prototype and iterate. And in NETWORKING we have ISO 9000. These are all processes and standards that we follow in various aspects of the economy that would be in that box that we the results of which we would measure and we would make adjustments to it. What is that in gtm?

That is the question. Like speaking to a founder who recently 2024 had a 6, 2023, sorry, had a $6 billion exit. He said, look, the state of expertise in my GTM teams is woeful. Not enough executives put in the hard work to learn the trade.

But revenue generation is the result of repeatable processes. This founder is bemoaning the fact that his executives, he has to look hard to find executives who've actually put in the work to learn the trade and run repeatable processes for repeatable results.

What really needs to happen in if we're going to build lean revenue factories is we need to establish standards, need to certify on those standards and then we need to continually improve based on those standards so that we can build a reliable machine. We believe, I believe in 2026, just two years from now, everybody will require that all hypergrowth companies, all PE backed companies, all companies that are serious about that second phase of scale up.

Asset creation. First phase is all around product, as you remember. Second phase is all around gtm. Third phase is all around strategy or strategy comes into play. But companies in this hyper growth phase are going to require leadership to be certified in an operating model for recurring revenue business. And that is why this is the book that Gerhard that you were referring to. That is why we've published a set of standards and operating principles that can help you get serious about turning a million dollar asset into a billion dollar asset. So I'm going to. We've now looked at GTM efficiency, what it looks like, what it looks like in manufacturing, what efficiency looks like in manufacturing, and lessons that we can take from that. And now I'm just going to click into three of the six models that constitute revenue architecture and help us do more of what works and stop doing what doesn't work. So the first model is the data model. Second model is the GTM model. Third model is the growth model. I'm just showing you a little bit if you want to continue learning about this. Happy to do that. I'll show you how at the end of this. So what is a data model? Data model.

Starts with the principle of recurring revenue. A first principle of recurring revenue, which is recurring revenue starts where the traditional sales and marketing funnel starts, stops. That's a big statement. I mean, you think about the traditional sales and marketing funnel. We go through awareness, we go through education, we go through selection, and then we get to the point where both parties make a commitment, we sign a contract, we enter a commercial arrangement. That's the end of the sales and marketing process. But it's the beginning of the customer relationship and the paid revenue relationship, which means I'm just beginning, I got to activate, I got to retain, I got to expand. And the only way that that retention and expansion is going to is if we're delivering recurring impact because recurring revenue is a result of recurring impact, not the other way around. So everything's got to focus on not on getting that sale, of course we got to get the sale, but on getting that impact to happen. If that impact happens, then everything else flows from there. I get renewals, I get expansion, I get compound growth. Well, if impact is the thing that I've got optimized for, why don't we make impact the objective of every single phase? Why don't we go look for customers that are a good fit for getting recurring impact? Why don't we help them self educate and we educate them so they can qualify in to an impact equation. Why don't we help them make selections, help them activate, help them retain all based on recurring impact and then we'll measure that. We talked about this earlier in the throughput conversion rates and volume metrics are all measurable. So as I bring people into that funnel, how do they convert from awareness to education, to selection and in what volume and do I like that? And is that intolerance or out of tolerance with my expectations? If I can measure those things and put that data model in place, those are indeed the signals that feed back into to say whether my processes are working or not. If I don't like my CR6, in other words, I don't have enough, a high enough percentage of customers who committed, actually activating on the product. Let me go look at the processes that I'm using and let me make adjustments. Let me get that CR6 up. So that's the data model. Very high level look at the data model. Let's take a look at the GTM model.

If we're choosing a GTM motion and we talked about those production lines earlier, we want to choose a GTM motion that, that corresponds to the amount of recurring revenue that we're going to acquire, retain or expand. And we'll talk about that in terms of annual contract value or acv. On the x axis of this graph you see that annual contract value. And as an example, let's say we're going after annual contract value of $10,000. Okay, so I'm looking for $10,000 contracts. That means I'm going to pursue a certain lead generation approach, a certain sales approach, and a certain customer success approach that makes sense economically for landing $10,000 contracts and then for delivering recurring impact to those customers on the back of that $10,000 commit. That would be a medium touch motion. And the way we think about it, that the appropriate sales demand generation motion is outbound. The appropriate sales motion is a two stage sales motion, meaning I have a sale, an SDR qualifying and then an AE closing and then I'm running my customer success by volume. Like each, each of my customer success managers has a certain amount of volume that she can cover and we've architected our processes that way. Now it's very different if I have a $1000 ACV or a $100 ACV all the way on the $100 side, there's no way I can do a two stage outbound by volume strategy. I got to do a self service inbound community strategy. If I'm selling $100 deals and conversely on the other side if I'm selling million dollar deals, I can afford to put way much into that. I can do a dedicated sales approach by account, a dedicated CS approach by account, and a dedicated and then a network based demand generation strategy. We want to pick the GTM motion that matches the, the ACV that we expect to get. And we want to architect each of those specifically as if it were a production line. If we manage it as a production line, then we'll know that the outputs of that are related to a specific set of processes and we can do more of what works and less of what doesn't. In that production line. If we're just looking at it by averages, we actually don't know where things are broken. So that's the GTM model. And then in that data model and GTM model, specifically the GTM model ladders all the way up into a growth model. As we mentioned before, we're all trying to turn million dollar assets into billion dollar assets. We're doing that in phases. We've got a startup phase, a scale up phase, a grown up phase. And over time, if we're lucky enough, the only thing that's going to limit us is the total addressable mark. Our growth will follow an S curve and if we're doing things right, we'll be in a steep part of the curve until we start to attenuate because we're reaching the limits of the market now. These retention over time is a bigger and bigger piece of our revenue stack.

If you got a bigger install base and you're retaining most of it, that becomes the largest part of your revenue stack. That's the white line. And so the importance of retention, the magenta line, gets higher and higher over time. As we grow, it is really important that we retain that we renew and expand our existing and acquisition, where it's the only thing that matters in the beginning, becomes relatively less important than retention and expansion over time. So startup phase, find out what works. Scale up phase, figure out how to do that efficiently, do more of what works and less of what doesn't. GTM efficiency, grown up phase operationalized for long term sustainability and enterprise. This is where we get into some strategic moves around consolidation, expanding the market and increasing the profitability and managing for public shareholder returns. Different things at different stages. As I'm building that because I have different objectives in different phases, I'm also going to be working on different things in different phases. So during the startup phase, I care a lot about pricing and packaging. I'm doing founder based selling, I'm establishing my data model so I'll be able to measure what works and what doesn't. And I'm making choices around a GTM model. Those are the things that matter. I'm less worried about long term Profitability, Durability, Interoperability, 12, 11 and 10 respectively on this graph, those aren't going to be worried about. But if I'm putting in big heavy iron systems around those things and I still don't have product market fit, I got out of order. Conversely, if I skip some of those things in the early stages that I have to do, founder based selling to get product pricing and packaging right, to get product market fit right, establishing my initial data model and choosing my GTM model, getting repeatable price. If I skip any of that, it's going to come back to haunt me later on. So I want to deliberately pursue growth in phases, focusing on the things at the right time. That is, that's how we think about a growth model. Those three things.

Are three of six models in that we call revenue architecture.

And all of that together is creates something that is deceptively simple. Like it sounds complex, it's like, oh my gosh, that's a lot of stuff to work on. Yeah, but I'm going to work on it sequentially. I'm going to put it together, I'm going to architect it the way that a clock maker makes a clock. And all, all of that is going to be hidden behind the simplicity of a well running GTM factory. When you, you know, manufacturers know that when a factory is running well, the only time they have to really pay attention to the underlying mechanics is by exception when something gets out of tolerance. And that's the same thing for those of you who've run a well oiled, well architected, well run GTM operation. You know that the machine works for you rather than the other way around. And the only things you have to manage are the things by exception. We want to architect that so that we can achieve the simplicity on the far side of complexity. We want to put in the work like that founder said for that $6 billion exit, put in the work to learn.

To architect our GTM so that we can accomplish what we want. Now here's the thing. If I want robots working for me in that system and we saw low touch, no touch and low touch motions in that GTM model, I can get robots to work for me. I just have to be able to instruct them correctly. If I want robots to be assisting my salespeople, I need to have a defined process. I need to be able to instruct them how to assist my salespeople. If I want robots to assist my CS people during the onboarding or ongoing impact realization phases, I need to be able to instruct robots on how to assist my CS people. If I want robots to do it all on their own. I need to be able to instruct them on how to do that. And all of that ladders up to a very simple process. So as Gerhard said in the beginning, we'd love to. We'd love every. Go to market professional in the market to be a certified revenue architect to really do the work, to roll up their sleeves and learn.

How to build out a lean revenue factory. And we can do that through certification. We can do that through a book. And I know, Stephanie, we were going to potentially take any questions that we have. I'd love to answer questions about that approach to thinking about building a lean revenue factory.

Well, thank you. You know, we didn't get the questions. Oh, wait, we do have a question. No, what we have is comments about comments. This is absolute gold. This is so great. Oh, wait, there's someone who has a question that they're waiting to type it.

Comments are good. Questions are good. Whatever conversation.

Yes, yes. I mean, this is incredible. Oh my gosh. If every organization had someone who could do this, this is, it's, it's so, it's so important. And just like the comment said, it's gold. It really is. How long did it take you to get from this complex idea and really simplify that?

You know, I want to give full credit, as Gerhardt did, to Jocko von Derkoy. This is, you know, he's a systems thinker and an engineer by training.

My contributions to this are small compared to his. And he's been working on this for 10 years. He's been working on this for 10 years, you know, as a chip engineer and somebody who thinks about the different layers of, of a chip system. Yeah, there you go. You know, you, you've got the physical layer, you've got the lot. The lot. The data layer, you've got the logical layer. There you go. Blueprints for a set that's probably 10 years old, right? Yeah.

And so you think about those different layers and you know, you can think about. I mean, every, every aspect of science has this. When you think about how to describe the human body, we have a skeletal system, we have a muscular system, we have a cardiovascular system, we have a nervous system. Each of those is accurate descriptor of what's going on in the body. But they operate in layers. And this is the same way. We've got a mathematical model, a data model, a GTM model, a growth model. Each of those describes what's happening in this factory. But they, but we need to understand each of them and put them together. Jocko spent about 10 years working on that. We've worked with.

Dozens of unicorns, maybe hundreds of unicorns, and thousands of companies. And so, you know, and, and the real, and the real time when you need to be thinking about that is during that middle phase. I've got product market fit and I now need to figure out how to go repeatably build a GTM motion that's going to create scalable growth.

And let's say someone wants to go in and get certified, how long would that typically take them?

So the certificate, the base level certification, it's an eight hour course over the, over the course of four weeks. Um, quite easy to do. It's not, it's not an easy course, but it's not a heavy lift in terms of hours. It's eight hours. There's an exam at the end. I've done it three times. We've got level two certifications that go beyond that. Those actually, I would say are quite difficult. But this revenue architecture certification that takes those three models that I just showed you, blow them out in detail and adds the other three is an eight hour commitment.

Okay. Yeah. I mean, that's totally doable. Wow.

Totally doable.

And now the questions are flowing in.

There you go.

Oh, my goodness. All right, so we have a question. How do you know when it's safe to table certain strategic conversations and move to the next phase, I. E. What would you say are the core essentials to safely end the product market fit stage and then move over to scaling?

Oh, so good. We need confidence. Like, we need confidence and.

We don't always gain enough confidence early enough in our career to be able to answer that exact thing like, how do I know when it's safe? I want to learn from people that have gone before me. I want to learn from systems that have been proven out. I want confidence to be able to say, now is the time to focus on this and then is the time to focus on that. And so it's a great question. I mean, speaking specifically.

Go to market fit or, sorry, product. Market fit is measured in terms of retention. Like if I am creating recurring impact for my customers, they will be revoting and revoting again on every birthday. So when I have good retention, I have product market fit, but I don't always, I can't always wait a year or two years to see if retention is going to happen. So I can actually go into the product and see what usage patterns are. I can see if I'm retaining their usage, if I'm retaining their usage then I've actually won their hearts and minds and they're actually using the product. I can predict that they're going to retain and I can declare victory on product market fit. So I actually want to pull that decision in.

As soon as possible, but I want it to be based on real data, use data, impact data so that I can then go figure out how to scale it.

Yes, yes, yes and yes and thank you. Okay, more questions. How much of the thinking assumes an SDR model or is it assuming an AI based SDR model?

Great question. I think we are still learning what an AI SDR can do and can't do and I think we're going to learn that AI and automation can do more than we think, but we're not going to get it right. All out of the gates. I showed you that medium touch model that assumes that there is something a human or a robot doing the qualification and then an AE stepping in to do the rest. If you click one up in that GTM model that's slightly lower touch. The education might be all self education, like not an sdr, but I might have a self guided demo or a self guided education path that can actually be handled maybe even with a bot answering questions. We have a lot of innovation to do there, Stephanie. And we're working. Winning by design. I personally am working with a lot of customers who are looking to take as much manual work out as possible, either replacing the human work or augmenting the human work and helping them get more done with less time. But it all depends on having a well defined process. So if I say hey, I want an sdr I got to be that AI SDR says okay, cool, what do you want me to do?

Right.

Yeah. If we can't answer that question then great. We have great technology. They're sitting there waiting for instructions.

Exactly. Or you know, bad instructions come in and we don't, we don't want that. Oh my gosh, so many great comments here. Someone even says that they think that they should now pay you a retainer for a week of business coaching because that's how much they got in this 30 minute session with you. And, and you know, just a lot of gratitude. I know we're two minutes over so we should probably head out here. But yes, please make sure you all connect with Dave and learn, learn more about this all.

Do people get in touch with Dave? Really appreciate it. Follow me on LinkedIn. But also winning by design.com you can find that certification right on winningbydesign.com I know, we're going to send the slides over and I'll make sure that we have a link right on that final slide with call to action. And we'd love to be in touch. Whatever stage you're in. Startup Sc up, grown up would love to be in touch.