#113 How to Earn Your CFO’s Trust – with Stephen Diorio, Author of "Revenue Operations"

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So go to get weflow.com to start you free trial today. Hello and welcome to another episode of the Reffup's Lab podcast. I'm here with Philip. And our guest today is Stephen Dioreal. Do you like the cookie? Deoreal. Okay, awesome. Yeah, I butcher every name, so sorry about that. Stephen, great to meet you. Welcome to the pot. How are you doing today? Great. Super excited to discuss revenue operations. Yeah. I think, you know, we actually wanted to have you on the podcast for a long time. You actually wrote a book about revenue operations called Revenue Operations and published that in 2022. You know, we had Sean Lane on the podcast. We had Yaku on the podcast. Harry Harris who all wrote books about revenue operations. I think you were the first one to release it. So curious, why did you write the book? I've been doing code and market strategy for decades. I was one of the co-founders of the first code and market strategy firm. In 1993, I've basically been trying to convince senior leaders and boards to reallocate resources to grow faster, more efficiently, more reliably. Over the years, I became a gardener analyst. I saw the rise of tens of thousands of technologies that could help us grow. But fundamentally, organizations don't understand the math. There are accountants can't describe the value of growth investments. And mostly, they can't work together to grow. So I've written several books about how technology transforms a go-to-market. But if we're going to get dogs and cats to live together, sales, marketing, success, IT, and finance to work as a team, we need some type of a unifying principle or system. And so I wrote the book, primarily, to convince people to work together and understand the math and the finance that really describes how growth assets and investments work together to drive revenue and cash flow. So the books primarily to throw it boards to get them to become smarter. Yeah, I love that. I mean, I think what you just said has a big cultural component, because obviously, when you work better together, it's a lot more fun. But today, we're going to talk about the math of growth and really focus in on how to become more efficient, predictable, repeatable across that entire revenue life cycle. So I mean, today's topic right is the math of growth. You see it as one big equation. Can you share, Brad, what do you mean with that? Sure, well, let's start the fundamentals. Again, I've been around the block. I'm an engineer. And so I think systemically, in the 1980s, if you looked at the investment or spend associated with growth, it would look like a lot of paid media, a lot of promotion, a lot of salespeople in cars, very, very little technology, some in the call center. And there were almost no digital channels, the internet didn't exist fast forward 10, 20, 30, 40 years. If you look at what people will call the golden market mix, which is not a spend, but the growth investment mix, it is mostly capital expenditure and in support of growth assets. So what I mean by that, growth asset is the database or knowledge base. A growth asset is the digital channel systems, which is roads and bridges to our customers. It is content, it is technology, it is brands. The brand is an asset. In fact, it's the biggest asset in many or most companies. It's at least 20% of a B2B firm. So we don't understand how to measure and manage those assets. If we were managing a building, a truck or factory, as our jobs, we would understand the capital investment, the maintenance involved, the value of that building. Everybody takes care of their house because it's an asset. And if you let it, you don't take care of it, it'll grow in value. That's not the case with marketing sales. At all, we don't think about the value of our customer relationships, the value of the data in our business and knowledge in our businesses, the value of our brands, which really drive a lot of the conversion that we try to measure in pipelines. So starting with the basis that people don't even understand, accountants who do the math, can I even describe the value of the assets and investments we are making? They describe everything as expense. We're starting in a whole. So the whole notion that the equation to growth requires a different math starts with the foundation of we don't even know what we're measuring. Does that make sense at all or does that make sense? It makes a lot of sense. I mean, I think when you think about the term of sales and marketing expenses, and that typically in software companies being 56% of the total capital investors, it says it right there. It's an expense, but you don't think of it as an ROI calculation or something that you invest in that essentially carries dividends over time. So it resonates really, really well with me to be honest. Well, I'll pack that a little bit. Let's just go through the income statement you have. SG&A, which is a sales general, all of what is called go-to-market, and that's a word. My friend Larry Friedman wrote the first book on that. That's a misused word. But all sales, marketing, advertising, customer success, service and support. Most of it falls under SG&A, which is 20, 30% of the company. The CPA is the financial accounting standards board here in the United States. Iso, globally, does not require you or provide you any guidance on what cost to sell us. It's just all a bunch of costs, and it's all lumped together. I can't tell how much of that cost was associated with the customer, how expensive a treatment model is, what a different customer experience costs. Certainly not fully loaded. If I have a digital channel, I'll usually just measure the variable advertising costs or content costs going into it. I don't matter value of the infrastructure like I wouldn't have factory. The whole notion that we don't even understand cost and shows of costs to sell, and financial systems don't give us the granularity to break those costs out, load them up, or even provide us standards for when we amortize our computers. There are rules. There are no rules or math that finance us to adhere to to measure costs to sell. If cost to sell is a term that everyone throws around, you show me a hundred companies. I'll show you a hundred definitions of it and none of them are right. Sorry to go on that tag, but we're starting from a really, really crappy foundation here. I think what you often see is basically in the first years of a company, right? You just scramble. You try to find some kind of sales motion that somehow works in all revenue motion. That works and just is repeatable. You try to scale it up. If you do a serious A or B, then you get more bigger checks written for your company, and then typically investors will start to require you to do proper reporting. I think nowadays it probably even starts a bit early on. I'm sorry. Even in public companies like IBM, I was on a global ISO task force to convince organizations to put brands. If you drink beer, Miller Course is a big beer company. The brand is worth 40% of their business. We tried to get finance to even recognize when you buy a company, they bought a company. They paid 40 cents out of the dollar for that brand that they don't record it anywhere. It's like if you bought a car and you didn't park it anywhere. You're not even saying I got a car, got stolen, worked this much money. I would argue, yes, a series ABC have varying degrees of sophistication, but IBM are or shot or electric, they don't do it well either. So there's no gold standard here. (laughs) - Okay, so obviously, I assume that you have a view on how to break it down, right? Because I think it's like, let's say, obviously there's the counting world, but then there's also the reality of if you don't start, I'd say most companies start to put KPIs in place across the different funnel stages, right? So, I mean, just give us some guidance. Like, when you think of the entire revenue lifecycle, where does it start, where does it end? And then also, what are typical things or typical challenges you see across that lifecycle? - Oh, that's great. Let's get into more comfortable territory. No, I got a little bit of a sort of territory there. But I didn't want to, I didn't want anyone to walk away from this conversation thinking that there was a right way to do it. I'm sorry. So, let's think about the revenue cycle. First, you know, serious decisions created the sales funnel. And then me or a bunch of other people bolted on the bow tie because we have to execute transactions, build loyalty and expand relationships. So I think everyone's familiar with the bow tie and the wing by design skies made it popular. What's missing there is what's called a closed loop process of continuous improvement. And what that means is all the bow tie does describe is how good or bad you did. Here's our conversion rates. Here's our customer health score. Here's our NRR and recurring revenues. But no one's asking the question, is that good or bad or how can I make that better? And so one of the points I would want to make is, yes, marketing at the front of the funnel does some basic metrics top of the funnel awareness, consideration preference. Those are good things driven by market research, driven by advertising metrics. They give you a general sense as to whether, whether marketing is getting through. As you go deeper into the funnel, you're gonna see things like engagements and visits and response rates. These are important, but we also, and I think you know, measure what we can measure versus what's important. But that's fine. And at the end of that process, we have this notion of leads, marketing qualified leads that get improved to sales qualified leads, sales assigned leads. And there's math and algorithms. And that's really where people spend a lot of their energy and that handoff is certainly a point of friction. But I think people overplay that because a third of the opportunities that are really gonna close in a given quarter, drop out of the sky based on some action that happened 12 or 18 months ago, or in our LLM search. So I think we overestimate that our entire go to market is encompassed in 30 to 90 days. And virtually every piece of business we have was generated by a quality website visit. And I literally have the head of a very large company who thinks that's his entire business. When the reality is it's an 18 month sales cycle, half their leads come from what is called LLM search, which is invisible, half of them are coming from content syndication, which came from all sorts of different places. But they don't measure it 'cause it takes 18 months to see it come up the other backend. So I think we overplay the corrosion rates, they're easy and they buy us towards productivity. I'm not saying they're bad, it is an important point of fixture, but there's a lot more associated with that. And that then goes down the logical funnel where everybody's KPIs are, advances, opportunities, sizes, stage, proposals. And that's fine, but that's just a revenue forecast. What's really interesting is the other side of the boat tie. And this is where cheap financial officers are starting to get scared. Because when I sold you a paper clip or a car or a can of soda a few years ago, if I did all of those things for $10, that $10 is pretty stable. I can put it at the books, I can record that revenue, the cash is gonna come in and I can tell Wall Street, I sold that in a SaaS world, in a complex world with cross sell and all sorts of consumption metrics as a service usage. If I book a revenue for $100, that can go up to $200, it could drop to 50, and there's 25 post booking variables that came from the go to market, poorly written proposal, poorly written specifications, poor rollout plan that can either double or cut in half the lifetime value of that customer. No one's looking at those things, governance, over terms, setting the right expectations, being realistic about onboarding. So even if the funnel was really, really predictive, we now have all this variability on the backend based on, well, they didn't certify, we didn't roll it out. Consumption didn't hit our targets. Usage and an adoption didn't hit. We got the terms wrong, and all of a sudden we think we're sending out $100 in voice, and it turns out to be a $70 or a $60 in voice. And everyone's looking for somebody to blame. And the culprits are typically product marketing. They didn't provide the right specifications, somebody in sales deviated from pricing norms, client expectations by customer success weren't create. So we've got all these variables that aren't caught in the typical sales funnel that are really driving the profitability and scale of accounts. In terms of cash collected, if I had to give you one metric that you're driving towards, it's reliable and predictable growth in future cash flow. Because once you get to that, that means the growth is profitable, that means you collected the money on time and it's growing and it's a metric that Wall Street cares about. So if you're tied to firm value, your metrics are going to be more sound. If you're tied to conversion rates, when loss rates, you're going to have all sorts of variables that you're not factoring in that are really a cause that we're not. So I talked a lot there, but I walked you through the funnel. One last aspect of that, most businesses today are basically saying, we have such upside in our accounts in terms of usage, cross sell, that all we got to do was grow within our accounts. The average complex software company has probably 10 or 20, 30 products to sell. Their penetration is maybe 5 or 10%. Yet they have no meaningful way to measure share of wallets or even total opportunity. How many people with faces, eyes and lips exist in that account who could buy our product? How many of them have I talked to? How many of them are predisposed to buy me? And what is the likelihood that they will adopt or expand our solution? That's a relatively straightforward picture. It's just that we don't even know who those people are. And they're talking to 10 or 20 different people in our organization and nobody can create that picture. So those types of things, we're telling Wall Street, we have so much upside in our accounts that we're going to drive the account penetration. Yet most organizations can't show me a credible picture of exactly who and where that's going to happen. This whole notion of account-based marketing, account-based selling, or the commercialization of customer success, those are nascent concepts. There's really cool math that you could do to create holy cow. Can you introduce me to five people in account to sell these four products? That's pretty coherent. I rarely, rarely see metrics that reflect that. So on the back end of the bow tie, there's all sorts of messiness. And no one ever looks at, we will always look at the, whether we book the deal, but it's a completely different person who actually collects that money and it's shocking how different those numbers are. And there's no one to blame because the guide to blame was 18 months ago when he wrote the post. So it's very, very messy. And then finally, the closed loop. What did all that cost me? Who was adding it up to say, what was my win rate? What was my profitability? Were my plan assumptions right? I'm a huge believer in the scientific method. That whole funnel, the budget's associated with it. The staffing, the treatment model. I think everyone knows what a treatment model is. Call them five times, send them flowers on the anniversary date. Make sure you meet them face to face once a year, cost a lot of money. That's a treatment model. These come out of sales law often, things like that. Every treatment model has a cost. I treat my wife very nicely. That's very expensive treatment model. My accountant, I send him a card at Christmas or a digital email saying thank you. So all these customer satisfaction, customer experiences, Everyone talks about a great customer. experience, but no one says what it costs. And no one says, is it worth it? It's really worth it with my wife sort of worth it with my account. But you got to put a number on it. You know, who you're going to buy the flowers for? Who's budget that's coming out of? And at the end of the day, if you buy the flowers, is there going to be an outcome, you know, happy wife, happy life? So none of those things are ancient. We use the word customer experience all the time. And I rarely find a finance person who can say, it's a hundred dollar customer experience. There you say a good customer experience. So honestly, think about the budgets associated with personalization. Who in the world isn't personalizing the customer experience? That is a huge capital investment that falls in a bunch of budgets and is anybody adding that up going, oh, cow, you know, that's a lot of money to make somebody marginally more happy when they're proud of what a boss from us anyhow. And so this is where I kind of go nuts and they all get back to, you know, we don't even have the math to describe these things. So I talked a lot there, but I did hopefully walk you through the bow tie. Hey, Philip here. Are you enjoying this episode? Well, good news because you can find more free red ops and go to market resources on get me flow.com/rethops access over 20 cheat sheets, reports and guides that will help you become a better revenue operator or join over 2000 subscribers who already get the latest resources right into the inboxes without a free newsletter. Just go to get me flow.com/rethops. Yeah, no, no, I think totally understood. I just want to point like to a few things that resonate with me and also triggered me in some sense. So I think one thing that is like super important, like one thing that you said there is like, I think the the overall goal of every sales organization is to create repeatable revenue. I think that's just like a fundamental principle that everybody needs to understand. Do you want to modify that to say reliable revenue, fuel and acquisition? Or liable? I get the spirit of what you're saying. Yeah, okay, reliable. Reliable revenue generation, right? So basically in a sense where you can say, okay, you know, basically in Q1, we can make plans for Q2 or even Q3, Q4, right? And you can basically prepare for that. You understand sort of like what are the input metrics, what are the, what are going to, if you know the input metrics, you understand what the output metrics will be and so on. So I think that's like the in general, like I think is a good framework to put into consideration here. But then, right, so I think like, and then if you go like further down and you look for example like into a CSM organization or an SDR organization or whatever, right, these are managed by by by different people who don't necessarily need to look at the overall equation of the entire business. They need to look and understand sort of like, okay, what can I do, what is my, and that's a brilliant port. If you have great net promoter scores, that is highly correlated to a very profitable, repeatable account, but it's not on their score card. And it's not being rolled up into a dashboard that I think that's a great, I think that's one point you're making this incredibly good point. Yeah, yeah, I mean like basically what I'm trying to get at is basically, you have you have different kinds of metrics, but I think you have like, they are metrics that are relevant for like the leadership team, they are metrics that are relevant for the, you know, like extended leadership team, let's put it like this. And then they are metrics that are like very different that are relevant for like the frontline manager at the direct level, where they are more like on a tactical level, they're operating more on a tactical level. So like that, where they are looking at mostly is sort of like the signals that let them make like the next decision, but it's very hard for them to kind of like zoom out and look at the overall equation of the entire business because you're just like a small, you know, a cog and they just cannot really like influence the entire equation. I think I think you said four or five smart things and I'd look to reiterate how smart you are. The smartest thing you said is the thing you didn't say accurate and accurate sales forecasts is not an objective because if you want accurate sales forecast, I'm going to sandbag and give you a very low one because I know I can hit that number. So I like the fact that you focused on reliability and repeatability. I also like the fact that you said I'm doing calls and effects actions at the beginning of the revenue cycle lead to outcomes at the end of the revenue cycle, which shouldn't form how well I'm doing or what I could do better. A caveat there is it is not one leads or website visits, but it's many people showing up on time for QBRs, people doing training on time, net promoter scores, fixing problems quickly. And so what I really like about what you said is if I'm going to have a happy customer, it's a lot of people in a lot of different cogs and places, doing the right thing and aggregating those things, you know, it is really good. A couple of caveats there. One, one of the things we never explore is what our assumption was. You know, if I wash the dishes and made the bed and brought flowers home, you know, I'm assuming that my wife will be happy and tell her friends she's happy. Is that a good assumption or a bad assumption? So a lot of times we don't say like we have to have an NPS score of nine in order to retain the account because if it goes to eight, our retention rate will go down 50 fold. Good assumption, bad assumption, but no one ever documents the assumption. And I think we all know the scientific method, establish it, make a guess, try something, see if it worked and adjust. So no one's ever questioning our lead scoring criteria or, you know, different treatments or how many times you should send a gift or how many salespeople in a given market or how many times somebody's got to see an ad. There's this whole response function, which is poke them five times they buy, poke them four times they don't, you know, so maybe 4.5. And so one of the things it's related to what you said, but it's good to measure the inputs. It's good to measure the outputs, but it's also good to write down the darn assumption of what the inputs were supposed to be, you know, what's a good input and what's a good output because if I don't write that down and I can't, that's what budget so she said, oh, that's what training is based on. That is what and that's where the resources are applied. So I'm just observing, you should people should write those things down or at least write their guess down. You know, we need five people in any market in order to cover the market effectively. Good assumption, bad assumption, but you could test it if you write it down. So I sorry if you're going down that road, but I really build something. I think it's a great point. I think like one problem that I just see often is like, okay, you need to do something for like a couple of cycles until you actually know what is good or what is bad. So you kind of like forest into heuristics quite often because those assumptions also change. If I look at the last 12, 24 months of the SaaS industry, the amount of times things have changed. New things being introduced massively changing the environment, changing guidance and so on. It's very hard to basically make an assumption in the beginning of the year and then kind of like to go back to it at the end if like you're such a dynamic environment, but I can't get it out of sorry. Yeah. So one question I have here is so obviously just playing this back to you, right? So the top of funnel is fuzzy, right? There's the dark funnel where it's actually really hard to measure. Like I think the understanding of brand, the understanding of touch points, the understanding of, you know, what happens the, you know, six to 18 months before somebody actually comes into your funnel is often unmeasurable, right? So it's actually really hard to calculate. So I think that's like, it's just a thing that I think, you know, the worth thinking about because it actually is something that every company has and we see it a lot at WeFlow actually, like we have people that we interacted 18 months ago and then suddenly they come into the, into Book of Demo and then they buy you know two months later, but it was actually a very long journey, but if the touch points we can measure are extremely short. And so it actually the, like the conclusion you can draw from that is entirely wrong, right? So I think that's like one observation. And then the other observation is the way I hear it's like that the whole servicing, onboarding, expansion, renewal, cycle and the measurement around that is still very nascent. What would you say? Like those are the areas where most teams struggle or is it like mid funnel when you go from like new logo into conversion, is that the the more challenging piece, but because I feel like that's actually a lot more controllable and measurable versus the top of funnel being very fussy and often And it's kind of the science and art of marketing where, you know, and then the success model is actually very measurable, but maybe uninvested and only had like a real, maybe like awareness in the last two or three years where in an NRA and GRR have basically become more important in the investor mind. I'm curious how you see those. I love that. And I want to break that down because you looked at three vectors. One was time, backwards looking, forward looking, behaviors and customer success that would predict the renewal will not happen, backwards looking, top of funnel. Two, you said dark funnel versus, I'd say, different places. Some things we just don't know. Some things we just got to look in a different place. And so let's look at time. Yes. There's a lot of dark funnel there. For example, what is the number now? 90% of the purchase process happens before they even engage you. So our top of funnel is even blind, right? 90% has happened before. Now, a couple of things. One easy thing to do is people tend to lock it on quarterly or monthly measures. Go back and look 18 months in advance. You might find that a third of your opportunities came from something you did a long time ago. Those are findable. Another cool thing, you can use all sorts of signals now. And last 18 months to say, what are people prompting on? Where are they? Did they go to a competitive website? So I would say absolutely dark funnel exists. But ask yourself different timeframe, different places. What if I was using something like demand science to monitor keywords across all sorts of places off my website? Those are different places that may give me a little bit of a signal. But I also love what you're saying, which is, it's backward looking is fine. It's history, it's data. But forward looking is also important. If you talk to someone in customer success, they'll tell you, I can almost guarantee based on the behavior and signals I'm getting from this client that they're not going to, they don't show up to meetings, adoption is behind. They're not using all the product capabilities. So forward looking signals that say, well, half the people haven't been trained. And they're barely even using all the good stuff in our product that we sold them. So I love, look, try to push forward and get forward looking signals. And another thing, it's imperfect. Try to go back and in different places to try to get signals and combine them. And even guests, I guess that people are going to our competition. Guests are good as long as you write them down and look for sources. I mean, so much that we do is gut feel. And I'm totally acknowledging that a lot of stuff is really hard to find or expensive to find. And you have to do that. But you made some really, really good points. And I think forward looking signals are available now in different departments from different signals, including to think about product telemetry data. Our products could tell you whether someone's going to stick around. And again, this isn't rocket science. It's just being diligent about, it's just being diligent. So I think that's good. There's another thing. I used to run the Forbes Marketing Caliburary Practice, CMO's, Cry or Wine, depending on your preference, that nobody respects them and that no one appreciates their value. But the reality is it's really difficult to measure. There's a brilliant man named Frank Finley, who runs the Marketing Accountancy Standards Board, which is a bunch of academics and scientists. So looking at that, you know, you talk about the funnel and you have to live in the funnel of the bow tie. But if you really think about it a little different way, everything we do, whether it's drive a car, go on a sales call, do an ad campaign, build a channel, write a white paper, run a cadence. Any action we take to grow or investment drives only nine outcomes. So you talked a lot about outcomes, MQLs, conversion rates, sales. But all we're really trying to do is change customer behavior in nine specific ways. Will they buy more? Will they buy faster? Will they eat more? Will they pay more? Will they stay longer? Will they say nice things about us? So it's really funny. No one ever looks at that as an outcome, but price sensitivity. If I do a lot of stuff like hire, you know, a fancy model or spend a lot of money on my advertising, if people are willing to pay twice as much, that paid off. Are we asking, are we, if we're likable, will they refer us? Are we looking at share of wallet, dying faster, you know, winning more, buying bigger things? So it's funny. If you just think about it as a human customer and you're poking and prodding them and throwing money at them resources, are they paying more? Are they staying lower? And so a lot of times people don't look at those outcomes, price sensitivity. People think that's a great sales job. I'd be on basically says if it's a risky deal and it's a tie, we win. And or, you know, a luxury brand. If it's within 20%, they're going to, they'll pay 20, 30% more for me for the same thing, not 40%. What makes that happen? Price sensitivity is fantastic. So I love that because every one of those actions does has a business outcome. Whether it's volume, share, lift, velocity, margins, cost of sell or even future option value, which is wow. Every time this guy brings me a really cool product, I knew idea. It's great. So if you brought me another idea, I'm going to buy it. I mean, quite frankly, you know, there are certain companies like Apple or even Miller Chorus who can say, I know I sold you dog food last month, but now I'm in the car business or now I'm in the tractor business. And they're like, oh, okay, I'll give it a shot. I mean, apparently Miller Chorus has such future option value that if they rolled out a line extension for, you know, anything you name it, you know, Latvian gluten free beer, they're like, sounds cool to me. I'll give it a shot. And so if you're rolling out a line extension into cybersecurity or content management, it's adjacent to your space or it's an extension of your product, their receptivity to it is huge. You know, like, I'm not buying dog food from Oracle and I'm not buying a car from Miller Chorus, you know, they'll buy anything from Apple. So I think it's actually really interesting what you say because like, so we are like a real example of this where we see touch points met a lot on top of funnel. Right? We see as like, you know, like after 12 to 18 touch points, people start to know us. They're actually aware of what we do and they start to actually have an interest. And I think it's very much like you center basically a brand round driving, creating value to your core bios in different ways that are totally, you know, unrelated from your product. So that at some point they are, they drive awareness. And I think this is such a big topic that like is often kind of right like the CMO's cry because well, that is that is kind of the reality that nobody on the stand is very hard to measure. But you look at, you know, for example, a revolution, one of the most successful new banks in the world, they invested heavily into brand. Now they have tons of product and they're rolling them out. And I think, you know, the the best companies in the world, they get that right at some point of time. Apple is an example. I'm coming example. And I think it's actually the reality in science as well, right? We look at, you know, some players in our world that have done some similar things. But look, I think we could, you know, continue this for a long time. We're actually, you know, I need to, I need to leave because I have another meeting coming up here. A quick question before you, before you let you go. I mean, obviously you wrote a book on the ref sharps, right? You've been in that space for a long time. Is there any other book you would recommend outside of your book, which we'll obviously link to in the show notes? Absolutely. If you haven't figured it out, I'm a big believer in the scientific method. And if we have assumptions that define the vote tie, we have to evaluate and adjust every quarter, every day, every week, every call. That's called a scientific method. Document your assumptions. Look at the causal drivers and adjust. And the number one word I have is even if you're measuring the right things, who is discussing and adjusting. The book I would recommend is my favorite business book called The Gold by a physicist named Eli Gouldret. And it's actually a book about a factory. But I think it's the best business book ever written. And it's really just a business book about the scientific method, which is I assume in the book, he assumes automation is going to work. But he realizes that actually it's a number of other problems that have to be solved and they adjust it and they learn as they go. So The Gold by Eli Gouldret, I think it's the best book, business book ever written. Awesome. I think this is the first I think we've never had. had this really, really appreciated. Stephen, thank you so much for coming on and everything you've done in this space. So really appreciate it. Greg and I'll send you a couple of articles with some of this math and so that it's not as of terror and I really enjoyed hanging out with you guys. Same here. Thank you so much. Thank you for listening to the Revots Lab podcast. If you enjoyed this episode and would like to support us, share it with a Revots friend or trepos of five-star rating right now. And if you have feedback, questions or guest ideas, just send a message to Janice or me on LinkedIn. Thank you and see you next time.