---
title: "The RevOps Poker Game"
episode: 32
podcast: "The LeanScale Podcast"
publisher: "LeanScale"
guest: "Spencer Hodgson"
guest_title: "Revenue Operations Leader"
date_published: 2025-10-28
date_modified: 2026-07-22
duration: 00:35:05
word_count: 5955
topics: ["revenue-operations", "gtm-strategy", "forecasting", "sales-compensation"]
canonical_url: https://leanscale-knowledge-hub.netlify.app/podcast/spencer-hodgson-revops-poker-expected-value/
source: "LeanScale Podcast Knowledge Hub — https://leanscale-knowledge-hub.netlify.app"
license: "Free to quote and cite with attribution to The LeanScale Podcast."
---

# The RevOps Poker Game — Full Transcript

> Episode 32 of The LeanScale Podcast, with Spencer Hodgson.
> Published October 28, 2025 · 00:35:05 · 5,955 words.
> Machine-transcribed and **not diarized** — speaker attribution is inferred, so verify
> attribution against the audio before quoting a specific person.
> Structured breakdown: https://leanscale-knowledge-hub.netlify.app/podcast/spencer-hodgson-revops-poker-expected-value/

## 00:00 — Intro: Spencer Hodgson and Thinking in Bets

**[0:00]** (logo whooshes) - Today we have Spencer Hodgson, one of the smartest RevOps leaders I've come in contact with and really excited to go into what we're talking about today. So I think something that everybody in RevOps experiences, there is just an absolute inundation of data and so much to sift through and so many metrics to go through and so many decisions to make, which reps are performing well, which marketing channels are performing well, which customer success reps are doing well, and it's really tough to go through all of the data and know how to make sense of it. And I love how you've taken a play out of Annie Duke's book, "Thinking in Bets,"

## 00:45 — What is expected (estimated) value?

**[0:45]** and taking a professional poker player's mindset to RevOps. Can you explain to us how you're using the concept of estimated value, what it is in the first place, and how you apply it to the RevOps space? - Yeah, for sure, thanks. So I love this concept. I'm gonna call it estimated value. It's also expected value. It's known as a couple of different things, but basically applying game theory in a way to all of life, we can try to figure out what would I stand to gain from any one decision? And this, essentially, like in mathematics, they said that the probability, needed to be proportional to the value. So as the value goes up of what I'm expecting to get,

**[1:32]** if the probability is going up as well, that's gonna mean that I'm gonna have a higher result. But potentially, like for lower probabilities, it starts to get murky and you start to wonder, if my value is getting higher and higher, but my probability is going lower and lower, where does it break even? Like where am I making a good bet? And so this is what I've gotten really passionate about, trying to figure out how to optimize decision making in multiple spots in life to bring about that value. So I'd love to just dive into what expected value or estimated value is, if that's all right. - Yeah, that's perfect. I think it's been a little bit

## 02:09 — The math: probability x value (the lottery)

**[2:09]** since I've taken a math class. So if we can get a refresher, I'd appreciate it. - For sure, yeah. So this is estimated value here where you take the probability of the first result times the value of the first result, plus the probability of the second result times the value of the second result, and so on and so forth. So if you were to be, let's say we'll just stick with the lottery example, and you know that you're gonna be spending $2 on the lottery ticket, and your probability of success is extremely, extremely slim. So your chances of losing $2 is very high, but your chances of gaining however many million dollars,

**[2:49]** let's call that the first probability, the probability is very low, but the value is very high. So what you can do is you can look at all of the different probabilities, the probability of winning the first, you know, the jackpot, the probability of winning, you know, one of the other kind of side bets where you maybe don't get the special ball, but you get all of the others, and that's a different, you know, maybe just a single million dollars or something like that. You can add up all of the probabilities times the meta values, and then you'll get the estimated value of your bet, which most of the time for the lottery is gonna be less than $2.

**[3:22]** You expect to lose your $2 most of the time. You expect to win some large number, very small percentage of the time. And that means that, you know, like let's say your estimated value on the lottery would be most of the time negative 150, something like that, is for a $2 ticket. But when that lottery gets to a certain amount, once you're into that, I think the math ends up being in the 750 millions or so, the probability starts to outweigh the fact that you're gonna lose. So, although you expect to lose your $2, eventually it starts to make money as a bet, where the estimated value becomes, let's say $2.20 or something like that,

## 04:00 — Good bet vs. good outcome, and Kaizen

**[4:00]** because now you're in the positives, and that is a good bet. So, where I think this gets really interesting is, you can think of it as, everything can be thought of as a good bet or a bad bet. Not, did I succeed or did I fail? Because not winning the lottery or not winning a certain game of poker or something like that, doesn't mean that you made the wrong decisions. And so this is where I think it gets really important and interesting as well is, how do you focus on your own decision making and your assessment of the probabilities and your chances of, you know, maximizing XYZ value? And then how do you turn that into,

## 04:44 — Pot odds: a poker example

**[4:44]** you know, positive estimated values as much as possible? So, and then this gets to a principle that my company is one of our core values. It's something we're really passionate about called Kaizen, where you're constantly trying to hone in on self-improvement. So, just because you failed, we should be asking ourselves, am I still, was I making the right decision based on the estimated value? So, let's go into one more example with poker, where I think it can get pretty concrete. So, if I am in a pot that is for $200 and it's just me and one other player and that player bets $100, now the pot's up to 300 and I have a decision. Do I call? Do I fold? Do I raise?

**[5:33]** And if I am trying to think in bets, right? I'm trying to maximize my value here. I, what I need to ask myself is, if I make this $100 bet, what do I stand to gain and what's my probability that I gain it, right? So, this pot, once I call, if I were to call, would be worth 400, the 200 initial, the 100 from the opponent and then the 100 from me. And then that 100 is what I'm calling. So, my $100 is at stake in order to make $400 total. And I then can use that to say, I've basically got a 25% pot odds here. Like, I need to think that I'm going to win this hand more than 25% of the time in order to have a good bet.

**[6:25]** So, if I believe that my hand wins 26% of the time, I should call. And that's where it can get really interesting with like I'm saying these decisions. You can expect to lose. Like, you expect your opponent to have a better hand than you, 76 or not 76 actually, than you wouldn't call. You expect them to have the better hand, 74% of the time or less, and you would still call. And so, this is where I think it can tease out some of the gray areas. As long as your hand is better than winning 25% of the time, which it can get into a lot more math there, but as long as you suspect that your hand is better winning more than 25% of the time, it makes sense to call.

## 07:08 — Starting a business as an EV bet

**[7:08]** - I think that makes a lot of sense. And also just in terms of decision making is the most important part. I think of another example too of maybe starting a business. So, the majority of businesses go out of business. So, I think only 10% make it past the first five years of being in business. So, the odds from a percentage basis are against you. However, the potential financial outcome is definitely worth it if you make it past that, and then you could have some potential exit or create something that can create some scale and continued on wealth beyond that. So, I think rather than just thinking of it as,

**[7:50]** oh, well, 90% chance of failure, it means I shouldn't do it. It's, you have to put the value in it to say, okay, well, if that 10% chance hits though, it's well worth the investment. And if you do it enough times in the long run, then you'll be successful. So-- - Absolutely. - So, I think bringing that layer in in decision making is really important. And being okay with I lost, but I made the right call. Extreme example, if you knew you had a 50% chance to win the billion dollar lottery, you should go buy a $2 ticket. Even if you lose, it was a good decision to do it. - Yep, absolutely, yeah. And I think with your example of starting a company,

**[8:34]** it's a really good one as well for estimated value because you can also think, what do I stand to lose if this company doesn't work out? Like I've wasted, I don't know, let's say five years of my life. I've spent things like I have opportunity costs I could have been spending elsewhere. I've spent some number of dollars of my own money, some amount of relationships trying to fundraise XYZ. But what's the real cost? Because certain things too are, they could be very positive estimated value if you're, you don't stand to lose very much by making this bet, right? Like, and with some businesses, you can start up a side hustle at very little cost to yourself.

## 09:09 — Applying EV to go-to-market and RevOps

**[9:09]** And it could be an absolutely good bet because it's almost impossible to go to negative estimated value. It might just not pay off as much as you desire and you decide to go with something different for your time later on. - Right, right. And managing the upside and downside risks is just a really different perspective and way of thinking when you're approaching decision-making in business and in life in general. So taking this and tying it to a go-to-market context, bringing it back to RevOps, how do you use estimated value to make decisions in a go-to-market context? - Yeah, great question. So I think in some ways we have it really good in RevOps

**[9:50]** because we have the data, like you said, everybody's talking about data, it's out there. It's not quite the same as like when you're deciding to start a business or not. Like you kind of have to jump, you have to leap. - Yeah, you have to make assumptions on those percentages, right, you have to, it's not given. It's not like a school math problem where you say, hey, you have a 50% chance of this business being successful. You have to use some judgment in it. But you're right, in RevOps, you have the actual conversion rates. - Yeah, this is what I love about it and why I love applying it here. So I'm gonna walk through a little bit

**[10:22]** of how I would go about thinking about a specific example.

## 10:29 — ICP example: enterprise vs. mid-market vs. SMB

**[10:29]** So if we think about something like an ICP, I'm gonna use circles to represent probability and I'll use squares to represent value.

**[10:41]** Let's just say that I have a decision to make, right? Is my company gonna go and kind of strategically place themselves and invest more time, energy, marketing dollars, hire new reps in the enterprise market? Let's just, we'll do this one. This top will be enterprise.

**[11:05]** Am I gonna invest more time in the mid-market or SMB?

**[11:16]** And it's a tough, scary thing for a company to decide, everybody wants to move up market. We're all thinking, I mean, actually many companies. - Usually, I'd say many times out of 10. Companies we work with want to move up market. - Exactly, oftentimes the goal is to move up market, but we need to know and understand what do we expect to gain before we invest all of this time and energy. And so this can help make that decision. So for what you would do is you would take your existing win rate or your conversion rate or whatever you're measuring. Like if you're doing, let's say cold calling, you could say, what's my chances of them?

**[11:57]** Once I dial, how often do they pick up? Once they pick up, how often do they book a meeting with me? Once they book a meeting, how often do they become a deal? Once they become a deal, how often do they win and so forth? So you could look, all of those are probabilities that we could kind of factor in here, but I'm gonna just take the kind of the closing motion of, once we've created a deal, how often do we win that deal, right? And so like, let's say that my enterprise win rate is, I don't know, 20%, my mid market win rate is 30%

**[12:35]** and my SMB market win rate is 40%, right? So it's easier to win the smaller deals potentially in this example, but I stand to gain more from my, the ACV of those deals. So the amount of this ACV is where it all comes down, right? Because what I've said right now isn't enough to decide, does it make sense for me to move up market or not? Because it depends on how good the ACV is for the enterprise company and how much worse it is for SMB. And it could be that actually mid market is my best way to go. And it all will depend on my, the ACVs. So in this fictional example, if I were to make this a, let me just think of easy math.

**[13:31]** Let's do this at 10K, is the ACV. And we'll do this one as 5K.

**[13:44]** And we'll do this one at halfway 7,500.

**[13:51]** So right now, what I can do is I would do 0.2 times 10 to figure out what my expected first value is. We're kind of back in this probabilities here, right? So we've got the probability of success times for the first result, times the value. And so I can do that and I can figure out what my probability is for, or my estimated value is for probability one enterprise and same and so on and so forth. But what I attempted to do here is these values should be equal, right? Because my ACV of 10K times 0.2 is gonna get me the same as my ACV of mid market.

**[14:40]** So this is 2000, I'm gonna just use this.

## 14:47 — Layering in pipeline volume

**[14:47]** And then this is 2000. - When the ACV and conversion rates are the same, and so you're coming up with a similar expected value, would you layer in something like volume of pipeline you think you can produce in either one of these channels? - Yeah, so that is a super important thing to factor in here, which would be how do I, kind of like a scientist, right? How as I influence my like subject material whatever it is that I'm studying, if my being there is somehow manipulating the behavior of the experiment, then it gets very messy. So, but I would think you would, we would try to make an educated guess here. And the good news is we still have a better,

**[15:31]** it's, in my opinion, a little bit easier than you're in the company example where you're just like, what would it be like, is this industry something that they need a new upstart like me to start in? Because we might have some better indications of when we had two enterprise reps instead of one, how did that affect our win rates and ACVs? When we put in some new marketing collateral and did that change anything? So you do have to kind of guess at what me spending and deciding between these two, if the estimated values are the same, you have to try to figure out is investing more in one or the other valuable at all, or do I keep it the same?

## 16:13 — Factoring in rep costs

**[16:13]** And you're gonna, you will have to make some educated guesses to figure out what, where to proceed. But I think what's interesting about this example is it's told us that the mid market is the route to go. And this just happens to do with what I, the numbers that I decided on. The enterprise and SMB expected values are the same, and then the mid market is higher. Now, the other thing that we haven't mentioned yet is the costs like an enterprise rep probably costs more than an SMB rep. And a mid market rep might be in between those. So you can also factor that in because you're not just gaining a $10,000 ACV. You are technically like with this value,

**[17:00]** it should factor in the total value that you make doing it. So it's not as simple as either we get nothing, we spend nothing on the 80% of time we lose with the enterprise. And we spend nothing on the 60% of the time that we lose with mid market, I mean, sorry, SMB. We could look at the costs too. And it could be that the marketing collateral is a lot more expensive to put together. And that could mean, you know, that it's more helpful to stay with SMB. - Maybe we put some numbers to this example. So let's say, let's just use the rep cost. There's other costs that probably come in. But let's say the rep cost, the SMB rep is gonna be like 100K.

## 17:40 — Deal counts, profit, and the full EV

**[17:40]** And then the enterprise rep is gonna be 250K. So would you take that 0.6% loss rate applied to the salary of the rep? So like, okay, we expect to lose 60K. And then would you take the 20 or the 80% loss rate expected in enterprise and apply it to the 250K to see, okay, now take the positives and the minuses and let's see which one is a better decision to make. - Yes, yeah, exactly. And I would also wanna layer in here like the count of deals expected, right? So that's another thing that we haven't accounted for yet. But if we can put in like the count of deals, right now I gave this example so that a single deal

**[18:39]** at the current rates makes the same kind of expected amount. And this does help me understand like how the bets are. Should I be betting more on one or another? But where I can get interesting in what you had mentioned is it could be that at the volume that we're doing, we can't make the profit to pay for that salary. You know what I mean? - Right, right. So if this is like currently we're doing 50 deals at SMB and we're doing like 10 or something like that here, then on average we're making 2K 10 times for enterprise and we're making 2K 50 times. This is all close one times here that I'm thinking at least for mid market.

**[19:33]** And that can kind of tell us profit wise, do we have enough money to make the reps kind of paying for themselves to make it a bet that we can continue to make? Even though these two bets are estimated value, expected value wise, they're the same bet. Does that kind of make sense? - Yeah, yeah, but if you carry it through, so if you say 2K times 50, that's gonna be 100K.

## 20:00 — SMB +$40K vs. enterprise -$180K

**[20:00]** - Exactly, yep. - And then you expect to lose 40K. So your like final expected value if you bring this all in would be plus 40K. And then on the top, it's 20K

**[20:16]** and then let's get 0.2 times or 0.8 times 250.

**[20:25]** You'd expect to lose 200, so you're negative 180. So in this example with all these variables, you have positive 40 and then you have negative 180 on the enterprise if you're comparing SMB and enterprise. So taking that like line of mathematical thinking to this, SMB market might actually be a better bet for you to invest in. - Exactly, yep, exactly. Like the bet itself again is the same, but in order to figure out that the other costs associated like you said, like these salaries, if the market has to pay an enterprise rep 250K, then our company going up market might not be worth it because we can't really afford to have an enterprise rep

**[21:14]** unless they're also able to be increasing that something like this. If I'm a company trying to decide between these three options, it could be that I've never really hired a true enterprise rep before. So I'm trying to compare data for what it looked like when a mid market or an SMB rep was trying to win an enterprise deal at what I considered an enterprise deals ACV. So it could be that they could command 250K, that's why we pay them more, but it could also be that for my company, this isn't a good bet. - Well, and I think this is where poker and other games, they're solved and meaning you have all of the data on the table.

## 22:01 — Business as an unsolved game: intuition and judgment

**[22:01]** This is where business gets a little bit more in the gray area. And I think this is where really good leaders will have to make some judgments on what they expect. So, okay, the mid market rep, maybe it was producing that. I think if I pay someone 250 or I get that level of talent, this is what I think it'll affect on conversion rates and potential ACVs. So you're gonna have to put in some placeholders for that data in order to run this calculation and then make a decision. - Absolutely, yeah. And just one quick thing too is even in poker and most games, you still have to do that because your opponent's hand is not visible to you.

**[22:41]** They are betting in such a way or they're acting in such a way that they're representing a certain hand. But no matter what, you have to use your intuition for games like poker. For certain games like chess, there's no point discussing this because there is just a best move that a computer can figure out. But like you said, in business, like we have to, the people who make the better intuitions about this stuff are going to succeed more and their companies are going to do better. - But I don't think a lot of people are even framing their thinking this way. And I think this really helps. Like when you break it down data point by data point,

## 23:21 — Modeling decisions to align the exec team

**[23:21]** you model out potential decisions into the future. You model out potentially what you think will happen if you make decision A, B, or C. And then you can clearly see what you know and what you don't know. And then make educated guesses on some of those components that you don't know. It makes it so much easier to make a call, feel confident about the call. Also communicate it to the rest of your executive team. But when you're just saying, hey, we should go out market, enterprise is better. Why? But if you break it down this way, then I think it helps get everybody on the same page to see exactly where you can win and then you can measure it.

**[24:06]** Hey, after we made these decisions, are those things I didn't know about actually holding true or do we need to adjust our decision-making model for the next quarter or the next year? - Exactly, yeah. And I think too, what I love about this framework is you could hone in onto any of these pieces and really try to figure out is there something we can improve here?

**[24:28]** Obviously, you could potentially have 100% win rate if you lowered the ACV. If you're just like, we'll give you this service for free but companies aren't gonna do that. But you can try to figure out how do I increase my conversion rate? How do I win more deals? What actions do I think could happen? Maybe I have some data around it already that rep-wise, maybe certain reps are winning more and I can use, I don't know, Gong or other tools to figure out what are they doing that's succeeding. And then I can try to replicate that but we can also do the same on deals and we can figure out are certain types of companies better fits for our service within the SMB

## 25:05 — Putting EV into Salesforce and HubSpot

**[25:05]** and therefore we can have higher ACVs if we kind of pointed our reps toward those and so on and so forth. So I think what's really cool is you can hone in to all of this. And so as you, like you said, as we start to be more aware of this in our thinking, we can capitalize on it and use it for a framework for almost everything that we do. - Very cool, very cool. I love conceptually and I love seeing this on Lucidchart and on paper, how do you take something like this and put it into a system? Do you take this concept of estimated value and get this into Salesforce, get this into HubSpot? How do you take it from paper to in the systems you're using every day?

**[25:54]** - Yeah, great question. So we've been talking super theoretically but this isn't that helpful to a rep to be honest, right? They kind of don't care. They wanna win more, they wanna make money, they wanna succeed, they want the company to do well but if you can get it into the system, Salesforce, HubSpot, whatever you're using and have it show them, these are the deals that are the worth the most to you. These are where if you maximize your chances here by investing your time more on certain types of deals or something like that, you're going to make more money. You're gonna be more successful and your boss is gonna be happy.

**[26:35]** So I absolutely, I've built it into both systems and it can be kind of involved but the idea is once it's done, it's just a set it and forget it sort of thing that it's a calculated formula that's kind of just working and humming and telling them what deals to focus on. It can't quite get it the why very well because it's just a big math formula although what I would use for reps wouldn't involve salaries and some of the other costs we expect to make 'cause it gets a little too complicated but you can absolutely use these and build these into HubSpot and Salesforce. The way that I've done it in HubSpot involves kind of a workflow

**[27:18]** and a couple of workflows, some custom properties and then some calculated fields which do all the math so that it can just display what I call white space, kind of how much a company is kind of worth to me and then I can when I'm trying to look through my account set or my open deals that are closing this quarter and I'm trying to decide which ones do I need to really press near the end of the quarter, I can filter by that and say show me the ones that are the most likely to bring me the most that have the highest expected value. - I think that's really interesting and something that we do often for our customers is we'll do a TAM analysis.

## 27:59 — TAM, territories, and quotas with EV

**[27:59]** We'll get the TAM into Salesforce or HubSpot. We will put an account valuation and they will use that to build territories. Now, something that we haven't really incorporated is throwing in the conversion rate, expected conversion rate of that particular segment to come up with that expected value and then looking at territories that way. We normally just look at the gross dollar value but I think that's a much more impactful and honest way to look at a territory. Like hey, we carved you out of $10 million territory but we only expect 1% of this to potentially convert versus like we carved out a $5 million territory and we expect 50% of it to convert.

**[28:42]** On paper, without bringing in estimated value, you'd say oh, the $10 million territory is better but when you look at hey, what we actually expect to achieve, the $5 million territory is better. So I just think it's a really interesting way to think about building territories, setting TAM and then having a rep look at a set of prospects and deals and think which one should I go after and prioritize first. - Yeah and I mean, on top of that, imagine I haven't been at a company where I could convince them to fully do this but if you're confident in the data and you have it set up in such a way, you could build quotas based on the territories

**[29:19]** that they have and the expected value within those accounts. - Yeah, probably culturally. People want the sales team pushing regardless of what happened in the past, like the past is the past but I do think it would help before you assign their quotas to use that as a data point to see are you close? Is it fair? - Yeah, exactly. - And if you're 10, 20% off, maybe that's okay but if you're like 5X off of what you expect, then maybe you should reevaluate. - Yeah, exactly and or at least you should have some reasonings that you expect the win rate or the ACV to increase. If you just increase it and say it'd be nice to,

**[29:56]** if we could increase the value by 20% with this subset, but it would be nice, we have no reasons really that we expect it to, then you're setting unreasonable goals but yeah, I definitely think it's another data point that can be used for things like quota, territories, everything. - Well, Spencer, this is a super interesting approach that you take, really unique. I haven't really heard of any RevOps professionals looking at their go-to-market data the way you are. What's your background? Did you end up in a professional poker team? Or how did you end up running RevOps this way? What's the story? - Yeah, that's a great question.

## 30:36 — Spencer's background: Alaska, teaching, and poker

**[30:36]** So, no, I only, I casually like poker but I actually got passionate about poker because of my passion for estimated value. I actually was a teacher up at a Catholic classical school in Alaska and I would teach in the winters and then I was a tour director up in Alaska in the summers. So I would take people around on my bus all throughout Alaska. I'd stay with them for seven days and kind of tell them where to eat, what to do. And it was a really, it was a good gig with both jobs. But when COVID hit, I couldn't tour direct anymore. That kind of ended all the Alaskan tourism for kind of multiple summers in a row. So I needed kind of a life change.

**[31:18]** And I already had been, I taught like seventh and eighth grade math. And I had been passionate about probability even then and kind of teaching it to the students. And I love that kind of stuff because I love board games basically. And so even then I had kind of started learning and thinking about expected value. And I then once I got into the business world, so tourism ended, I needed a change. And I basically jumped at anything I could do instead. So my wife and I moved down to Tulsa, Oklahoma to be closer to her family for more of a support network. And then I took a job cold calling kind of just the bottom of the barrel, sorry, SDRs.

**[31:59]** But yeah, I had to start somewhere. I could, you know, did anything. I would do anything to kind of make ends meet. And it was as an SDR that I started applying some of this probability stuff that I was aware of to my life. And this was maybe kind of weird, but my boss had given me access to export data and things like that. Maybe you should or shouldn't have done that. But I was able to and was obsessed with trying to export my data into Excel and then figure out if I'm the best. I wanted to be the best SDR that we had, which to be honest is like a very important skill in an SDR because you have to have something driving you to keep getting those no's.

**[32:44]** But hopefully expected value is helping realize that too. Because you can get hung up on 95% of the time and that can still be a very good bet, right? But so I was obsessed with knowing am I the best SDR? Like, and I was really trying to figure out like what were everybody else's conversion rates? What were they getting once they had booked a meeting? Did it result in a deal? I just really wanted to know. And so I started doing more and more calculating and my boss just started realizing that I was passionate about this and he just gave me more and more ability to kind of keep taking things off his plate and essentially just kind of,

**[33:18]** I kind of worked my way into sales operations and I've just been loving it ever since. - That's amazing. Well, I'm sure the math teacher role definitely helped with a lot of the RevOps work for sure. Alaska is beautiful, by the way. I absolutely love the state. I spent, before I was in tech, I was in healthcare and I actually spent a couple months working along the Aliaskan pipeline doing medical equipment deployment. So I spent a lot of time in the state and it's just stunning. So I'm sure some of those tours were very interesting. - Oh yeah, it's definitely worth a visit. - For sure. Well, Spencer, this has been awesome. I really appreciate it.

## 34:02 — Where to connect with Spencer

**[34:02]** Before we wrap up, what's the best way if people want to learn more about your approach or just get connected with you? What's the best way to get in touch? - Yeah, so I like to be really active on LinkedIn. I connect with everybody. If anybody sends something over, just linkedin.com/SpencerHodgson. I post things there. You can DM me if you want. I'm happy to chat, especially nerdy numbers. Maybe this is weird, but I put, I have estimated value in there on my about section. And if SDRs or people were to have mentioned that, I would take a meeting way more frequently. So if people are interested in this kind of stuff, hit me up. Happy to chat.

**[34:41]** Happy to walk through on a more one-to-one basis, like how I built it in HubSpot, how I would go about building it in Salesforce if I were doing it again. 'Cause I'm not on Salesforce right now, that sort of stuff. - Love it, love it. Well, thank you so much. I appreciate the education. Love the approach. And hope to have you back soon. - For sure, thank you, Anthony. - Thank you.