Hayes Davis on this episode
Hayes Davis, CEO of GradientWorks, joins Eddie Reynolds to explore whether a mid-market account executive can produce $10 million in annual revenue through AI-assisted workflows. Davis brings deep expertise in sales efficiency, having worked as a software engineer, prior startup CEO, and leader of RevOps for a 600-person sales organization. His viral LinkedIn post sparked significant debate by reframing the "10x AE" challenge as an engineering problem rather than hype.
The core thesis is that targeted AI deployment in sales operations—particularly in account selection, deal management, and sales preparation—can materially improve AE productivity and close rates without requiring unrealistic activity volumes or AI avatars closing deals. Rather than pursuing brute-force activity gains (requiring 1,800+ touches per day and unsustainable meeting loads), Davis models a path centered on doubling opportunity creation rate (from 10% to 20% through better ICP targeting) and raising win rates (from 20% to 50% through superior deal context and disqualification discipline).
The conversation reframes what 10x actually means: not one rep replacing ten, but raising the baseline performance of sales teams through better account routing, ruthless pipeline hygiene, and AI-assisted deal preparation. Davis emphasizes that most SaaS teams operate at sub-20% close rates and carry bloated pipelines—creating massive opportunity to improve efficiency without exotic AI capabilities. The episode explores the limitations of current AI (email-only SDRs, legal constraints on outbound calling, LinkedIn automation risks) and the human elements that still matter: trust-building in commercial relationships, deal omniscience through context synthesis, and the discipline to walk away from low-probability opportunities.
What we cover in this episode
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1:24
GradientWorks and pipeline optimization How territory management and account routing drive sales efficiency for high-velocity teams.
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7:52
The 10x thought experiment Defining the challenge: can a $1M-quota mid-market AE selling 50K ACV products reach $10M revenue?
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13:26
Activity-based scenario and AI SDR limits Why 1,800 daily touches fail: email-only capabilities, legal restrictions on calls, and LinkedIn TOS violations.
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23:40
Higher ACV scenario and deal complexity Doubling deal size from 50K to 100K requires more meetings and human relationship trust, not fewer.
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36:50
Opportunity creation rate and ICP precision Improving from 10% to 20% through extreme account targeting reduces required touches and improves efficiency.
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44:02
AI co-pilot for deal preparation and context Pre-call briefing, in-call support, and post-call follow-up compress meeting time blocks and reduce rep error.
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51:40
Pipeline disqualification and win rate discipline Walking away from dead deals frees capacity, improves forecast accuracy, and enables focus on winnable opportunities.
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30:08
Trust and commercial relationships in AI age High-stakes purchases still require perceived human accountability and reciprocal relationship-building.
The lines worth sharing
The way you actually drive your throughput in any system is by identifying the bottlenecks and systematically removing those.
Hayes Davis · 0:45
If I'm actually not working on the right accounts, all that's wasted. The biggest bottleneck in sales is the accounts you work in the first place.
Hayes Davis · 2:10
People forget stuff. By the time you're six meetings deep at an opportunity, what did we talk about previously? There's an opportunity for a co-pilot that's with reps constantly.
Hayes Davis · 44:15
The best reps are ruthless with their time. They would walk away from something right in the middle of a call. They have fewer meetings but bigger deals and higher close rates.
Eddie Reynolds · 52:30
Common questions from this episode
Can one account executive produce $10 million in revenue in mid-market SaaS?
Theoretically yes, but only through significant improvements across three variables: account selection (ICP precision), opportunity creation efficiency (raising from 10% to 20%), and win rate (improving from 20% to 50%). Requires ruthless pipeline disqualification and AI-assisted deal prep, not higher activity volume.
What are the limitations of AI SDRs for sales outbound?
Current AI SDRs can only reliably handle email (legally compliant, multi-domain capable). Outbound calling via AI is largely illegal; LinkedIn automation violates TOS and triggers account blocks. True multi-channel sequences require human involvement or acceptance of significant compliance risk.
How can AI improve sales close rates?
Through deal omniscience: AI co-pilots provide pre-call prep (context, player mapping, questions), in-call support (relevant talking points, history), and post-call follow-up. This reduces prep time, improves deal hygiene, and allows reps to manage more high-value opportunities with better outcomes.
Why do most SaaS companies have 16-20% close rates?
Industry benchmarks (Ebsta/Pavilion 2025: 19%; Bridge Group 2024: 16% for 50K+ ACV) reflect pipeline bloat: unqualified opportunities languish, reps lack deal context, and disqualification discipline is poor. Better account targeting and ruthless pipeline pruning can materially improve this.
Does AI avatar closing deals replace human sales reps?
Not currently. High-stakes purchases ($50K+) still require perceived human accountability. Buyers want a named person standing behind the transaction, especially when their job is on the line. Cultural acceptance of AI avatars is possible but remains distant.
What's the highest-leverage AI application in sales today?
Account selection and ICP targeting. Directing reps to truly qualified accounts is the single biggest bottleneck in sales systems. Improving account precision before any outreach or messaging dramatically improves downstream metrics.
SEO meta description
Hayes Davis on how AI, better account targeting, and ruthless pipeline discipline can drive 10x AE productivity without replacing the human sales rep.
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10x account executive AI
Hayes Davis GradientWorks
sales efficiency AI co-pilot
AI SDR limitations outbound
account targeting ICP precision
sales close rate improvement
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deal preparation AI
SaaS AE productivity
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Read the full transcript · 54 KB · Hayes Davis
HAYES DAVISthe way you actually drive your throughput in any system is by identifying the bottlenecks and systematically removing those. Anything that happens before a bottleneck won't change the outputs, right? And so I say all of that to say, one of the biggest bottlenecks in sales is the accounts that you work in the first place. Because at the end of the day, if I have the best well-crafted message in the world as a rep, and I do everything right to reach out to the right personas and to say the right things and work my ass off, if I'm actually not working on the right accounts, all that's wasted. Welcome to Go-To-Market Science. There's an art and there's a science to
EDDIE REYNOLDSgo to market. And in this podcast, we talk about the science by interviewing CROs, private equity investors, and other sales and marketing experts, as well as talking about what we learn every day in the trenches helping to build go-to-market engines. Welcome to Go-To-Market Science. Today, we have Hayes Davis, the CEO of GradientWorks with us to talk about the 10x AI-powered account executive. Hayes wrote an incredible post, an article that went viral on whether or not a mid-market account executive could produce $10 million in revenue and generated a lot of buzz, a lot of different opinions. And I wanted to dive into this because this is near and dear to my heart, because this is really about the science behind go-to-market, specifically sales, and how something might be engineered such that an account executive could produce 10x the results that they are currently producing. Super excited to dive into this with you, Hayes. First, let's start. Can you give a
EDDIE REYNOLDSlittle bit better description of GradientWorks than I might do myself? Yeah, absolutely. So great to be here. Thanks for having me. I'm Hayes Davis, co-founder and CEO at
HAYES DAVISGradientWorks. And what we do is we have a pipeline platform for commercial sales teams. So think a large, high-velocity sales team that needs to make their reps as efficient as possible. Our platform helps you figure out which accounts to go after, manages the way you assign those accounts. They're a dynamic model we call dynamic books. It's really a replacement for legacy territories and then gives you all the analytics you need to see how that's working. So it's really intended to be a way of driving much, much more efficient pipeline. And so efficiency is always on my mind. It has been. My background is first as a software engineer, then as a CEO of a prior startup, then as a running rev ops for a team of about 600 sellers. So, you know, through all of that, it's really been about how do we use technology to make people as efficient as possible when it comes to go to market? So that's a little bit of the background of why I'm interested in the topic in the first place.
EDDIE REYNOLDSYeah, it makes sense. And I thought that'd be helpful for our audience. And I'm always, I try to be careful and I appreciate you doing the intro that way. And it wasn't very salesy. I don't ever want to like plug products, including our own on this podcast, but I wanted to give folks some context. Like you're thinking about like, how do we get the right territory? And this is also near and dear to my heart because simple math, if you call accounts that aren't a good fit for your ICP, then you're going to have lower conversion rates and you're going to generate less pipeline and close less of that pipeline. And you're going to churn more of those customers because that's literally how you define ICP. And so since your company is already focused on how do we help reps target the right accounts, it makes sense that you might be one thinking like, well, how do we use all this technology to make the same person 10 times more effective via AI? And so that's what we're here
SPEAKER_12to talk about today. And I wanted the audience to have that, uh, that background on you.
SPEAKER_10Yeah. Awesome. So let's see here. Let's just start off. Like, why do you think this went viral? I, by the way, I will say you had like, I heard about the post before I read it and then I read it and I was
EDDIE REYNOLDSlike, the hook was really good. Like, could a mid-market AE hit $10 million? Cause I was like,
EDDIE REYNOLDSah, 10 X, like whatever. Like, why did that go viral? And then I read the, then I actually read it and I was like, ah, now I get it. Yeah. But why, why else do you think that this like resonated with people so much or didn't? Well, I think the, the reason is the hook is, you know,
HAYES DAVISLinkedIn hooks are important for LinkedIn stuff, but the hook is actually really important for the thought experiment. So I think that, you know, just backing up a little bit, what I was really trying to do wasn't go viral. I was really trying to take a step back and find the sweet spot between like AI boosterism, like AI is just going to solve everything and it's going to make us all incredibly
HAYES DAVISproductive. And, you know, question mark, question mark, right? I don't know how, but it's just going to do it. Right. So kind of between that and the, like, you know, the posts you see on LinkedIn every day about,
HAYES DAVISuh, oh, use this particular tool to do this particular thing to send 10,000 emails or whatever. Right. And so what I wanted to do was kind of back up and say, let's think through this. We're saying AI is going to make us, us, our sales reps, you know, radically more efficient. Let's treat it as an engineering problem, as a science problem. Let's work backwards. Like what would have to be true to make some kind of outlandish outcome happen, like a $10 million quota for a mid-market AE, right? And so in order to kind of engineer that, like I said, my background is as a software engineer. And so, you know, a lot of it is problem solving and trying to kind of project out what, you know, might be true if you solve X and then Y and Z. So I needed an end state, right? And so, you know, really thinking about it is you could just say, well, 10X more productive, but that's not really super useful. Like you said, if we just say 10X more productive, well, you look at any sales team and, you know, one rep is not very good and another rep is really good. And then probably one probably produces 10X more revenue, right? Like that happens. We see that. But what I really mean is can we raise the bar globally to say that the standard for your classic SaaS AE and I have this kind of definition in the article about my classic SaaS AE. It's like your mid-market rep with a roughly million dollar quota selling a 50K ACV type product, right? So the question is, could that rep have a $10 million quota? And so it turned out to be a really good hook, right? But it also turned out to be kind of the foundation of the thought experiment because it anchored it in a sense of like, we're trying to go from X to Y and not just kind of hand wave. And so the rest of the discussion is really about what are those things that have to be true or would need to be true for that to be the case. So that's really was my goal. But I think that's what resonated with people, both good and bad, right? Like it was cutting through a little bit of the bullshit of just like AI is great, right? But also because there's some actual numbers and a bit of a model that I put together, people were able to like pick it apart and say, well,
HAYES DAVISI don't know if I agree with this, you know, kind of parameter, right? So then became a good discussion. Yeah, I really liked it a lot. And I'm excited to like break each element of that down, but I will
EDDIE REYNOLDSsay it's ironic. I heard this and I just finished reading a book titled, if I remember it correctly, 10X is easier than 2X. And this is written for entrepreneurs, not necessarily salespeople or sales teams. And the author makes this point and he goes, you know, if you want to get to 10X, if you go to 2X actually, which is incremental growth, there's probably like a hundred different paths to get there. But if you challenge yourself to ask, like, how do I get to 10X? There may be only one path to get there. And so that really narrows and focuses your energy. And he also pointed out, he's like, well, hey, like if you grew your business and your first year you were at 200 grand and now you're at 2 million, like you've already done 10X or you're an employee and you make 200 grand a year and your first job out of college was 20 grand a year or whatever, like you've already done 10X. So there's this concept of like, how could you go 10X? Like this is crazy and unrealistic. And like he points out and granted, like the guy's a good writer and a good pitch man, uh, like, hey, you probably have already done this once. And then he talks about how a company grows. And then you think about, you know, just from a business perspective, well, yeah, of course, like Salesforce is doing, I don't even know off the top of my head how many tens of billions of dollars of revenue that they're doing. Well, how did Benioff do that? It's because he's not closing every deal himself. He hired a sales team and then a manager and then, you know, a manager of managers to have multiple teams and kept replicating himself as a salesperson and very, very quickly, you know, in the case of Salesforce. And so you think about it and you're like, oh, well, yeah, I mean, if you are 5,000 salespeople, it makes sense that you could close millions of dollars of business, but you're talking about how does one person do this. And I think part of this is by delegating out these activities that are not the area of genius for a salesperson. This is what the book talks about. It's like, if you start your own business and I'm talking about like my kind of company where you like bootstrap, it's like the first person you hire is like an executive assistant or a bookkeeper, because as a CEO, you shouldn't be doing this stuff. So who's the first person you hire or the first AI bot you build for a sales rep, right? And like, I like starting at the very top. It's like, well, if we can identify the absolute best accounts to go after, like that's a great start. And this resonates with me so much because in every job I've ever had in sales, I go into, you know, my territory and I've got 2,000 accounts and I have the capacity to maybe call on 200 of them in a year. If I do everything right, don't skip any steps. And now I got to figure out like which 200 accounts of the 2,000, they gave me to call. And we see this with like almost every company we talked to. And you just think like, by definition, if we just identify the best possible accounts for an account executive, they're going to generate and close more business. But this is like a massive gap that I've seen in every job that I've ever had. And so, you know, you delegate the activity to AI or even not AI of figuring out those accounts. And it's one less thing for the account executive to do. And now they're able to apply their area of genius on that best set of accounts. And so I think this concept of going 10X really resonated with me because it really begs the question of what are the things that sales reps are best at doing that only they can do that AI can't do. And what are all the other things that we could get off of
SPEAKER_27their plate and how could AI help us do that? Is that kind of what you're thinking? It is, but I approached it kind of working backwards from the goal, right? So ultimately,
HAYES DAVISI do come away and I'll share it as kind of I go for the reasoning, but I come away with a set of things that AI needs to do. And I'm not necessarily saying that these are specific products or what this is going to look like in the future, but just these are the areas that I think AI needs to be responsible for in order to get this type of outsized productivity. And one of them is is exactly what you said is there is so much leverage in the accounts that we work in the first place. And honestly, right now, from an AI perspective, that's probably the absolute highest leverage place to apply AI. I gave a talk on this at the Pavilion CRO Summit. And one of the things that I went through in that talk is a bit of an explanation about how the difference between a rep that gets a thousand accounts that are moderately qualified and a thousand accounts that are, or a much smaller book that is really well qualified. And I won't go through all the math here. It's helpful with a visual, hard to see on a podcast. But the gist is, I'm a big systems guy and theory of constraints kind of person. If you've ever read The Goal, which is a really weird book, but is well known. It's from the 80s. It's actually
HAYES DAVISabout manufacturing. I highly recommend it, but it is written by this guy, Eliyahu Goldrat, who was this
HAYES DAVISbig thinker around lean manufacturing and that kind of thing. Long story short, it's a business novel, which means it has a plot and all this other stuff. But what it comes down to is he ends up saying, this guy ends up saving his factory because he realizes that the way you actually drive your throughput in any system is by identifying the bottlenecks and systematically removing those. Anything that happens before a bottleneck won't change the outputs. And so I say all of that to say one of the biggest bottlenecks in sales is the accounts that you work in the first place. Because at the end of the day, if I have the best well-crafted message in the world as a rep and I do everything right to reach out to the right personas and to say the right things and work my ass off, if I'm actually not working on the right accounts, all that's wasted, right? And so one of the things that I kind of look at this and say, that's a really good place to start. But going back here, I actually laid out three scenarios specifically.
SPEAKER_21Well, before you do that, Hayes, I want to jump in here just because
EDDIE REYNOLDSthis resonates so much. And I don't mean to toot my own horn here, but I personally experienced what you're describing. In my first job out of college, basically, I was that 10X sales rep. And I'm not trying to brag. My competition just wasn't very sophisticated. I worked at Wells Fargo as a small business banker. And the folks I was working with just weren't great salespeople. So they just wouldn't even probably call themselves salespeople. But we had a sales goal before all the congressional hearings and everything like that happened at Wells Fargo. I think I was at 504% of my quota and most of my colleagues were at 50%. So I was quite literally 10X. And one of the ways that I did this is we had just no real CRM. And so everybody had 4,000 companies they were covering. And I found this analyst in a back room somewhere that somebody told me about it. To this day, I have no idea where this person was. And he basically did the equivalent to run Salesforce reports for me. And I was like, give me these reports with these people that have these types of loans and debt, et cetera, with all these parameters. And he gave it to me and I started calling down on them. And then as it started to succeed, I started getting these lists from elsewhere. And I was in Colorado at the time, outside of my city, elsewhere in Colorado. And then I started calling California. And all of a sudden, I'm producing these 10X results. And the only real reason for this is because no one else that I was competing with had this level of focus on the right prospects. And then, you know, I go work at Salesforce and it was a lot harder to compete with those folks. I didn't have that. It wasn't quite as much of a layup to be a top AE there because they have that system worked out. But it's really interesting just to see, like, especially if an organization hasn't worked these things out, how much of a difference it can make.
HAYES DAVISIt is massive. And, you know, the thing you're describing, I know you and I both talk to a lot of RevOps folks and sales folks and sales reps, right? And one of the things that I think I see just kind of across the board is there's so much energy and effort that everybody puts in to the work. But it's kind of like the sort of, you know, old story about the person who's so busy
HAYES DAVISchopping wood that they won't sharpen the ax, right? Like an Abe Lincoln clove, right?
SPEAKER_34Yeah, right. And so that's kind of the gist is what I feel like I see a lot of. And so that kind
HAYES DAVISof goes back to the three different models that I put together to think about this problem.
SPEAKER_18Because the first model is basically the 10x the activity model. And a lot of the idea behind,
HAYES DAVISyou know, what you see people talk about on LinkedIn and talk about AI is it's kind of like, well, we're going to use it to just do more, right? And so you look at the idea of like an AISDR or something that's going to send a bunch of emails that are going to be, you know, personalized, whatever. So that's really kind of the idea of can we brute force this, right? So that was one scenario. And that kind of leads down certain paths, but I'll lay out the three scenarios. Scenario number one was let's just do 10 times more. Scenario number two is let's charge more, right? The classic way of turning somebody into, you know, a $10 million quota if they had a $1 million quota is to get them selling, you know, million dollar deals, right? So that's one path, the second path. And the third path is really this idea of like, how do we just maximize efficiency? How do we maximize the rate at which
HAYES DAVISyou create opportunities, maximize the rate at which you can win? And honestly, like when I set out to do this, I actually thought the answer was going to be, you can't really have a rep like this
HAYES DAVISat a $10 million quota. I came away after doing the math feeling like, okay, this is within the realm of the possible, and I'll just spoil it here in that efficiency realm. But before I get to that, I think it's important to kind of think about the, like, you know, wood chopping version of this, right? So could we just do 10 times the work? Now I'll spare you the whole kind of like math that works through this, but I did a little back of the napkin kind of pipeline math, pretty standard stuff working
HAYES DAVISbackwards from how many, you know, how many deals would need to close at a, you know, a 20% win rate, how many deals would you need given a certain, like what I call opportunity creation rate of how efficiently you're able to turn engaged accounts into opportunities. Like you can kind of work backwards to say it's standard reverse pipeline math. How many accounts do you need to start with?
HAYES DAVISLong story short, the math works out in this kind of 10x scenario that you probably need to do something like 1800 touches per day, like 1800 activities per day. And so, you know, not wanting to just put, you know, just to say, Oh, that's insane or whatever. I said, Okay, well, what, what would make that possible? What would you need to make that possible? And that's really where kind of the first set of AI capabilities came in when I was writing about this, which is, that's probably going to require some kind of AI SDR, right? That's going to require some kind of AI that's like sending this out. But it also requires, to the point that we've been talking about, a massive supply of ICP fit accounts, right? Or else your response rate is just going to be trash, which it usually is in these scenarios. And
HAYES DAVISyou're not going to, you're going to have to like suddenly do 100x the activity to actually get anything to happen. So long story short, you got to have a good supply of in-market ICP accounts. I
HAYES DAVISthink that's really where AI can play today. Then you got to have good data around those accounts
HAYES DAVISfor relevant messaging. I think AI can help with that data. It could maybe in certain cases do the messaging now. But the thing that I really got hung up on here was, if you look at any like significant
HAYES DAVISoutbound motion, like it's multi-channel, right? Like you don't really set that many meetings via email most of the time. You set them because it's the result of the emails, the calls, the LinkedIn
HAYES DAVISmessages, like all of those things you're kind of doing at the same time. That's why we have sequences,
HAYES DAVISyou know? So the problem is for an AI SDR, an AI SDR basically can only email right now. And the
HAYES DAVISreason I say that is because email is the easiest one. You can burn through a million different domains. You can do that. It's pretty much illegal to make outbound calls with AI. Like that's just flat out true. Whether you try to get around it or don't care or whatever, that's the case. Like go for it, but it's hard. You probably shouldn't. And then finally, yes, people can automate things on LinkedIn with AI, but it is completely against their terms of service. They block people all the time for doing
HAYES DAVISthis stuff. You're going to put in your account and everything else and, you know, at risk by doing that. Yeah. I've had my account blocked without doing that. Yeah. So, right. And once you get to
HAYES DAVISa certain scale of account anyway, it's just like, you know, you're probably at risk for stuff that looks fishy, but so all of that tells me like, you just can't do this many touches a day even and have
HAYES DAVISit work for you because you can't do it efficiently. So to me, I kind of said like, look, that's part of the death knell of the activity, like 10X kind of motion. But it does say that like, what if we had an AI SDR? Could we use that in some way? And we'll kind of put that aside to come back to it. And we also need some AI to help us qualify. So those are kind of first two categories. But I decided to follow this, you know, logic, right? So let's say we do 1800 touches a day and we set a decent number of meetings. Well, if you start setting enough meetings at a 20% win rate, like you're going to have to have 12 plus meetings every single day to actually like manage this pipeline. I did some math to kind of get to that number. I won't bore you with that, but probably that means you're going to need some kind of AI avatar type person thing that can like join calls where maybe you can't sometimes. Remember, we're trying to get one person here to have a $10 million quota. And so that to me is going to require just a tremendous amount of acceptance by people. Maybe we'll get there. Maybe we'll get there fast. I don't know. But people are going to have to
HAYES DAVISget used to the idea that like your avatar is going to show up and talk to them and it's not really you. Right. And I think that to me is another thing that just feels like another nail in the coffin for this. Like, let's just 10x the activity. Right. So we got to have AI to get us a bunch of accounts, truly astronomical number of accounts that are really well enriched. Then we have to have an AISDR that's going to go do all the work of doing the vast majority of this outbound. That's an insane thing. And then finally, we got to have somebody who's going to like be on some calls for us because there's just not enough hours in the day. So those are kind of the three pieces of AI. But if you put them all together, it doesn't look like you're going to get there to this 10x quota by doing more
HAYES DAVISactivities. So that was kind of dismissing that first scenario was the kind of the first task here. And before you move on to the second scenario, I want to break that down a little bit because like
EDDIE REYNOLDSthe first, my first reaction to this is, is like, okay, you share some limitations that I think are really valid, but even ignoring all that, let's just say like we get around all that stuff you mentioned, who cares to me? Like you're just talking about generating meetings and whether there's one rep or 10 reps that are handling those meetings. Yeah, sure. Like one rep is cheaper than 10 reps. And I think in your post, you talked about this concept about like the 10x developer in Silicon Valley that gets paid 3x and is happy to like deliver 10x value. And the company makes a lot of money off of that person. And that's really cool. And as a business owner, like I love that, but I don't know, it doesn't excite me that much. It's like, okay, if you tell me that I can use AI to generate all these meetings, whether it takes one person or 10 people to manage those meetings, I don't care that much. Like I care whether or not each of those people is profitable and what our overall CAC is. And so if we could solve for that, and I recently read Jason Lemkin's post about how they built their AI or SDR as a co-pilot and how they got that working, it's really exciting. But at the end of the day, it's like, that's not your 10x AE, that's just generating more meetings. And to your point, like, unless they're willing to like have this avatar, you can't manage those meetings. And then I think in your article, you touched on PLG as well. And I think if I remember correctly, you said like, nobody's buying a $50,000 product via PLG, because ultimately at a certain price point, like we're recording this on Riverside, never spoken to anybody at Riverside. We have Zoom, never talked to anybody at Zoom, but I'm not risking a lot of money. I think I pay 30 bucks a month for Riverside. That's fine. But if I had to sign off on 30,000 a month for Riverside, I'm not doing that without talking to a human being. Maybe one day I'll be comfortable with that AI avatar. But I think we all have really struggled to like wrap our heads around that idea, especially like, if it's my money, that's one thing. If it's my company's money and my job is on the line, that's another thing. I'm not sure which is scarier. Either way, it's really scary.
SPEAKER_29Right. And that kind of dovetails into the second scenario a little bit, which is like,
HAYES DAVISokay, so it's the purpose here to like get reps to like basically sell much bigger ticket items, and maybe the rest of it becomes just PLG or something like that. Which by the way, I never quite, I don't know that we've hit like what people are willing to buy in a PLG scenario by any stretch.
HAYES DAVISLike I think that keeps stretching and stretching and stretching. I mean, I've always found it bizarre that people will go and just buy a car site unseen on eBay or whatever, you know, like, and people do that. Right. And that said, I do think that there's a difference between buying a car for yourself. Right. And dealing with that. And then like, you know, putting your job on the line for a hundred thousand dollar piece of software. Yeah. I bought a car on the side unseen one time. Cause I was just like, whatever, you know, like,
EDDIE REYNOLDSyou know, if the transmission is broken, then like, you know, it cost me a couple hundred, but like, whatever. It's like, uh, it was also a $1,200 car, but, uh, you know, that's probably the important point, but I like, and I don't want to keep interrupting you from your flow of going into these scenarios. I will just say, like, I could potentially see myself buying something substantial 50 grand, a hundred grand, 200 grand. If I could ask the AI all my questions and get them all answered and have a like a hundred percent confidence that the company stands behind everything that AI says. Yeah. But we're a really long way away from that.
HAYES DAVISYeah. And, you know, I think about all the high five figures, six figure kind of deals that I've been involved in and not a single one of those have happened. I can't think of without like a texting relationship between me and the person that I'm, you know, I'm dealing with who's like the ultimate decision maker. Right. Like, yeah, there's a sense of, are you as a human, like standing behind this? Like you're saying, right. And I just think there's, I think you can, you don't have to be in person necessarily, but I think there's gotta be a sense that somebody is really, really standing behind that. And so I don't know. I don't know what the limits are of that. And I do think, you know, it wasn't that long ago that people were a little squirrely about being recorded on a zoom call, right. Or having like a note taker in a zoom call, like that hasn't really been that long. And so it's entirely possible that people will adapt faster than I think to, you know, being fine with an interaction like that. It's not apples to apples, obviously, because it's a big difference, just like having somebody record what I say on a, like a sales demo versus somebody, uh, like, you know, me talking to a robot until I pay him 50 K. But like the end of the day, I do think people get used to stuff and there are companies out there that are pushing the envelope on having these AI kind of reps. So I don't know, I'm skeptical. I don't think I'd do it, but you know, maybe, maybe I'm out of the norm. I don't know. Yeah. I don't think you're out of the norm. I think we, it's all TBD. It all comes down to like,
EDDIE REYNOLDSdo I want to risk my job over this 50 or a hundred thousand dollar purchase? Because I trust the AI to answer my questions. A and B you raise a really good point. Like when hits the fan, do I have somebody in my corner now? Granted, like, do I think that account executive is going to go to bat for me? I've been that account executive going to bat for a customer before, but I don't know. Do I want to bet my job on that? I guess it depends on the little of trust I have with that account executive, but it does help you sleep a little bit better at night knowing that there's a human being on the other side of the table who hopefully is a good person. Yeah. And you know, has probably proved it through a series of interactions, right? Like
HAYES DAVISthey probably, you know, you handle things fairly with a sense of reciprocity. Like, yes, it's a commercial relationship that you're building. Yes. Person A is trying to sell person B something and
HAYES DAVISthere's money on the line and that kind of thing. But you know, there's a reason that people
HAYES DAVISmeet through a commercial transaction ultimately become good friends. I mean, my head of product, somebody I know really, really well now and have become good friends with, I met him originally when I was running my first company. We're doing social media analytics and he was at a company that ultimately got acquired by Twitter called Gnip at the time. And they basically got tapped by Twitter as like the owners of the commercial fire hose essentially. Right. And so I met this guy because one day he called me up and he's like, Hey, you need to start paying me money. I'm like, who the hell are you? Right. But we eventually like work together over many, many years and, and, you know, trusted each other and got to be friends. And now we work together and you know, it started from a commercial relationship. And I think those things do matter, especially when there's large amounts of money involved. So, but that does kind of lead to the question of, yeah, like, is that the path? Is it just like, just put humans in an expensive transaction? Maybe that is the case. We're already talking about a 50K kind of ACV type deal here. This second scenario that I went through is really like, at the end of the day, I basically was kind of saying like, look, if we're talking about mid-market rep, like you can't just have them suddenly start selling million dollar deals, right? Like if you go from 50,000 to a million dollars, like that's not a mid-market transaction anymore. You're not selling to the same kind of companies. You're not doing the same types of things. Maybe you can double or triple that number, right? If you sell in 50K ACVs, you can probably get it up to 100K and still be selling to the same basic personas and accounts. So the end result ultimately is that like the actual amount of activity that you need to do and the amount of meetings that you need to do don't actually change that much. In fact, the way I looked at it, the amount of meetings that you'd have to hold probably actually doesn't change at all because you would probably end up having to hold a lot more higher stakes meetings throughout a slightly longer sales process. Yeah. And I appreciate you trying not to get too deep
EDDIE REYNOLDSinto the numbers for people that are just listening to this. Well, we don't actually put the whole video on YouTube, so that wouldn't help either. But the way you broke it down, if I remember correctly, is you doubled the ACV from 50 to 100, which in theory, best case scenario is, you know, well, actually, no, it's not half as many meetings. It's five times as many meetings, right? So 2X times 5X is 10X. So now you have to have five times as many meetings. It's just like, okay, that's still untenable. And to your point, maybe it's actually 10 times as many meetings because these are bigger deals that require more meetings. And also, like, this is something like my team has been talking about for a long time. It's like a 10X AE is possible. A 10X customer is not. Ignoring inflation and things like that, like companies are not going to spend more money just because we're better at sales and marketing. It's just going to get more competitive, as it always has. So we can improve the efficiencies with which we attract customers. That doesn't mean in an aggregate that they're going to be willing to spend more money. Yeah. And so, you know, ultimately,
HAYES DAVISthat's the biggest constraint on this. You know, just the simple math would say, if I can sell for twice as much, I need half as many ops, right? Which should mean I need half as many meetings. But the reality is it's not linear like that, right? Like you're saying it, the number of meetings is going to go up because it's a larger deal. So the net result is that actually this looked to me like the worst possible play because you essentially have to do something that looks like an AISDR to generate enough opportunities still. So, okay, 1800 touches a day. Now it's 900 touches a day. That's still going to be like something you can't manage. And the meetings ultimately get to be about the same or higher, like you said. But in that case, I think it's even less likely that somebody is going to want to engage with your AI avatar. So you got to actually be in all those meetings or you have to, you might could have an avatar, like run some early discovery or something like that. Again, I'm trying to think like, what would be the application of AI here to make that happen that
HAYES DAVISpeople are, you know, maybe not expecting. And that would be, that would be it. But it was pretty
HAYES DAVISeasy to dismiss this one out of hand, which ultimately, you know, and we've been obviously foreshadowing this in the conversation, but the efficiency one is the one where things start to get possible. But it's efficiency at like every single level. So we've talked about efficiency of the accounts that you work, you put AI on that. And then it's how you work those accounts. But there's a couple of things that I included in this particular part of the model. So two rates that I said would change that represented efficiency. The rate number one is, I mentioned it earlier, is what I call opportunity creation rate. Really simple metric, but it's proven really valuable for our customers. And something I really like to use, which is, look at all the accounts you engage throughout Bounce, right? What percentage of those accounts produce an opportunity? Right? So if you want to know if your messaging is working, if the accounts that you're working on are good, right, then that number is going to go up for every 100 accounts I touch. Do I create 10 opportunities or do I create one opportunity? Right? It's a good way of looking at that. It encapsulates a lot of stuff. So that's one. And so in my prior examples, in those other scenarios, I said that opportunity creation rate was 10%. Now I'm saying, what if it was 20%, right? And the way that would get to 20% is by extreme accuracy in your ICP and the accounts that you're going after, right? That's really probably what would be the highest leverage point there. But if that's the case, then the number of activities that you have to do goes down quite a lot because each activity is essentially carrying more load. It's more likely to yield something good for you. And so it's still a lot. It's a few hundred a day, like two, three hundred. The idea here is that opportunity creation rate, improving that. And the way I think about opportunity creation rate is pretty simple. It's the number of engaged accounts as the denominator and the number of opportunities you create as the numerator, right? So 10% opportunity creation rate is pretty efficient. What I have in this particular model is saying, what if we got to 20%? And the reason we could get to 20% might be because we're radically improving how we qualify the accounts that we work in the first place. So every activity I do is more effective because it's probably reaching somebody who's more likely to have the problem that I'm solving. So that would reduce the number of touches that you would need down to something that is semi-superhuman, right? Like 300 touches a day, right? And when I look at that, I say that's maybe possible. Good reps I've met can do a hundred high quality touches, more than that, actually. I've seen it with my own two eyes, but it's hard work. It's really hard work. But I think this is where there's a variation on the AISDR. And this kind of comes back to what Jason Lemkin has said, you know, or said recently in that post that you mentioned, which is we basically got, you've got to have something that works alongside people to do outbound, right? And so- Yeah, it's a co-pilot. It's not a set it and forget it. So you need that kind of system. And I think of it as like human in the loop, right? So like, can you serve up the 25 most critical activities that a human should be doing and have the AI do as many of the others as possible? And when you serve up that activity, can the human have all the context given to them that they need to have the right thing to say at that point in time, right? And so in that case, it started to look like, okay, this is at the outer edge of possible. It'd be really hard work, but with some AI assistance and human engagement, you probably could get to that level. Then the big one, the big ratio that a rate that, you know, people did roast me about on LinkedIn a little bit was the win rate. I basically bumped it up from 20% in the other scenarios to 50% in this scenario. And so, you know, the gist of the feedback on that is like, oh yeah, a $50,000 ACV with a 20% or 50% win rate in SaaS like just doesn't happen, right? And, you know, that's not entirely true. I've seen pretty high win rates. Now people monkey around with their win rates a lot. If you ask somebody for a win rate, I'm sure you've done this a ton. Two things happen every time. First, they give you a range, which I always think is funny, right? Because a win rate is an actual average. It's a number, right? It's not a range. Your win rate is not between 20 and 30%, right? Your win rate is a number in there. But the other thing that people do is they'll give you their like stage three and we've got docs already win rate, which is like, oh yeah, we win 70% of the time. And you dig in and it turns out they're like ignoring the vast majority of the opportunities that they ever look at. All right. Yeah. We had a client, we were running this report for
EDDIE REYNOLDSand one of their, one, if not more of their salespeople had an 85% close rate. They weren't like crushing quota. They just weren't putting their opportunities in Salesforce until they got a verbal. It's like not rocket science. Yeah. And I actually made that comment on your post. Somebody said, he's like, nowhere in the history of B2B SaaS has anybody ever had a 50% close rate. And I'm like, this is the easiest thing of this entire scenario. You just change your definition of qualified sales opportunity. Right. But you know, in my case, right, you know, I am taking the simplistic win
SPEAKER_21rate. What I think was the raw win rate, the true win rate is like, if you've created an op,
HAYES DAVISwhat percentage of those things close? Like through whatever stage progression, right. That's what I'm talking about here. So it is high, but I think that the way it could be high is through giving reps, what I think of as kind of this deal omniscience, right? Most reps, and I'm sure this has never happened to any rep that's listening or to anybody, any sales leader that's listening to any of your reps, but reps forget stuff. They lose context. They don't follow up in a way that they should. They forget that like this person is like off in the background as an important decision maker. And they should reference that person, like all of those things that kind of come up across, you know, by the time you get to your sixth meeting of the day, you're like forgetting details left and right, those types of things. Right. Or by the time you're six meetings deep at a particular opportunity, it's like, what did we talk about previously? And you can go look at like searcher, you know, note taker or whatever, and kind of figure those things out. But it's still pretty tough to like load all that context into your brain and then use it properly in a meeting. Let alone
HAYES DAVISremember like that product detail that you need to know and like the new thing that product marketing told you last night or whatever. Right. So I think there's an opportunity here for a co-pilot
HAYES DAVISthat I do imagine is probably going to be with reps constantly. I think there was a point in time, year and a half ago and like the very first surge of AI excitement that everybody's building co-pilots, but they were kind of just this simplistic like chat interface, like go tell me so and so like, what did they say? Like a few emails ago or something. But I think there's a room here for something that's going to help you with pre-meeting prep, something that's going to be there to help you while you're in the call and something that's going to help you with follow up. So that those meetings that you have don't it's not a 30 minute meeting that takes an hour of prep, you know, the beginning
HAYES DAVISand then post follow up. It's a actually like maybe a 40 minute meeting, you know, 40 minute time block
HAYES DAVISwhere you can have the meeting, you've got everything you need to pre-read, then you've got to follow up. And that starts to get to a place where reps make fewer mistakes. They know who all the players are. They do all of the right things in a deal. And I think you can start to see where the win rate might start to increase from better. And I might add, like, I'm already doing some
EDDIE REYNOLDSof that stuff for myself. So I'm not using AI for this yet, though. I really couldn't tell you a good reason why. But I hired an assistant a few years ago and she does a lot of this for me. I spend about five minutes prepping for each call because she has like a three page sheet ready for me and I scroll through it and it's got all the answers to all the questions. Who are the players? What are their titles? What's the link to their LinkedIn? Everything all on one note, including like the questions that I'm supposed to ask. And so I could very easily use AI for that. I just haven't. I will say one concern with AI today, as of the date of this recording, which could change tomorrow, is that you still just don't trust the responses that well. And so there's always the question of like, did it really summarize the notes accurately? And is this really what I should be saying and talking about on this call? That's always a concern for me. But it's really obvious what you're saying that especially as AI improves that this concept of a co-pilot to digest all this information and summarize it and feed it up to you. I mean, at least I shouldn't say at least for me. I think this is true for every sales rep on earth. Like prepping for calls is one of the most time consuming aspects of the job. Yeah. Especially if you want to do a good job. Right. And I think, uh, so I think
HAYES DAVISthere's a big part of that, that can be better, but the other, the, so if I think about all the pieces that would go into a much higher win rate, I think it's, there's two big components to it. One is this improvement in deal management. And then the other is the improvement in quality of the qualified accounts, the qualified opportunities that should work. Right. So you would end up naturally, if all of this is true, we're super qualified accounts are the only ones we're talking to. We've got a compelling message. We're really, really prepared. Um, we have all the context, all of those things together should probably yield like material increases in win rates. And so is it 50%? I don't know. Right. But I think it's kind of sad that the, uh, prevailing standard in SAS is something south of 20%. Like, I think we could do better than that if we had fewer marginal opportunities that just kind of sit around in the pipeline because they were never really qualified to begin with.
EDDIE REYNOLDSWhere do you get 20% from, by the way? So a couple of studies, a couple of, um, I can actually cite them if I can find that.
SPEAKER_21Cause I believe you. I'm just curious.
SPEAKER_10Yeah. No. And I, you know, I hate to, uh, cite facts without some kind of backing. Uh, so
HAYES DAVISa company called Ebsta and Pavilion published their 2025 GTM benchmarks. They pegged it. And that's a big survey of a bunch of Pavilion folks. So a lot of go to market folks, they pegged it at 19%. Another, uh, study that I, from a group I respect called the bridge group, um, they publish every two years, these like really robust SAS AE metrics, which I really like for 50 K and above ACVs. They actually pegged the win rate in 2024 at 16%. So that's kind of the, you know, so we're talking ballpark, like that's a pretty right now is pretty standard. And this includes companies that don't operate very efficiently. Right?
SPEAKER_30Well, I mean, it includes, it's supposed to be a reasonably representative sample. So it should
HAYES DAVISinclude lots of companies that suck. Yeah. So that's what I'm getting at is like, I, I have the figure of 25% in my head. I could even
EDDIE REYNOLDSmaybe go to 20%, but like anything below that. And I think like, there's just something really wrong with the way you manage pipeline. And so what you're talking about in this way to improve close rates. I think there's two aspects to this. One is running a better deal cycle, closing more of the deals that you actually can close. And another aspect of this is walking away from deals that you can't close, whether that's just having a better human sales process, which we figured out like decades ago, or it's using AI to get an additional edge there. And I think like, when I look at most organizations, especially, and we have a poor sample size, a lot of times people are coming to us because they know this thing is broken and they're looking for us to fix it. But I look at it and it's like, they don't have a sales process. It's not implemented in their, into their tools. They don't have any way to review that and provide feedback to their reps, which are all things that like AI could help augment. And it's just, you have a bunch of reps chasing a bunch of deals and they kind of all have their own process. And then they have a 15% close rate. And you're like, well, that's not surprising. You know, I can immediately just go in and say, Hey Bob, like half of these opportunities, like they're not qualified. I mean, I can do something as simple as just look at like, okay, like half your pipeline is twice the age of your average deal cycle. Meaning you have almost zero chance of closing this deal and yet you're still chasing it. So one of the constraints that you had in your model was the amount of time that a rep has to do sales meetings. Well, one solution for that is just have less sales meetings with things that are highly likely not to close. And then two, when you go into those sales meetings, do a better job with the ones that you actually could close. And I believe that there's an incredible application for AI, especially as it continues to improve to help with that. Um, and this idea that like we have a 19% close rate is, is very illustrative for me of just incredibly broken processes. And one of the reasons I wanted to do this podcast is not necessarily to like sell anybody in our audience on this concept of actually hoping for a 10 X mid market AE, but more just thinking about it. Like, well, if I were to try for this, what would we improve and how would we improve it? And we talked about like identifying better accounts. It's like, is that going to give you a 10 X, a 10 million dollar mid market executive? Probably not. But is that something that could have a substantial impact on your target this year? Absolutely. Right. And so then we move that into, we say, okay, well, how do we get rid of these deals that we can't close and how do we do a better job of closing the ones that we can close? So many organizations I talked to have like incredible
SPEAKER_27opportunity on the table for both of those things. Yeah. And, you know, I think it's going back to the
HAYES DAVISwin rate for a second. And I, I really, I mean, I'm biased because it's part of what I've built a company around and spent a lot of time on. I, I do firmly believe that most of the downstream issues with poor quality deals, uh, low win rates, low ACVs, long sale cycles, a lot of that has to do with just not talking to the right, the right companies in the first place. And so I do think the, the accounts matter a lot. I also think that I wanted to touch on the, the efficiency that you're talking about with disqualification. Cause there's a couple of things that I think are interesting within that. One is, you know, one way to really improve your win rate, right? Is just disqualify everything, but the things you're absolutely going to win. Right. But then that you've got to play both a efficiency and volume game, right? It's like, you know, in sports statistics, I'm a big basketball fan. Right. So like you've got to have some level of volume and some level of efficiency, right? The guy who shoots two threes and hits one of them through the course of the year, isn't all that helpful, even though they've got a 50% three point, you know, shot, field goal percentage, right?
HAYES DAVISMm-hmm
SPEAKER_82Person like Steph Curry, who's going to shoot, you know, 40% on, you know, thousands of shots. That's
HAYES DAVISwhat you need. Right. And so that kind of efficiency is efficiency times volume is what you want here. And so you can only get efficiency through ruthless disqualification. Like you can only, you can improve your win rate. You can't get the volume unless you have the work going into having the accounts in the first place. And so I think it's the combination of those two things that's really important. But just to piggyback on one other thing you said is like that disqualification, I think that a lot of people feel like, you know, well, I'll just leave this pipeline here. And it's just, sometimes it's just, you know, we kind of lie to ourselves that we think a deal has legs and it really doesn't. Right. But it's not free. There's an opportunity cost to that. It's every, you know, forecast call, you've got to talk about that op. It's like, I've got to communicate with that op. I've got to send them a note periodically. I've got to just keep pushing on that. And so there is a sense that like everything we let languish isn't just sitting there and like lowering our win rate. It's also taking away from our ability to go out and work with the best possible
HAYES DAVISaccounts to create more deals that we could. I think it's even bigger than the way you're
EDDIE REYNOLDSdescribing it. So first you're talking about these deals that are just completely dead and they're like beyond like that last stage. I'm more worried about the ones that are going through like the later stages of the sales cycle that you're not going to win because each step in the sales process is exponentially a bigger investment. You start with like the five minute cold call and then you do a 30 minute, like initial call. And then it's an hour long call. And then it's like, we got to do a demo and like, we have to customize the demo and now it's three hours. And then we're doing a proposal and we're going back and forth. And now we invest five, 10 hours in that. And when I worked at Salesforce, what I saw is the best reps were ruthless with their time. They would walk away from something like right in the middle of a call. And these were the folks that were making less calls, had less meetings and had less number of opportunities in their pipeline, but they had the biggest deals, the highest close rates because they were talking to the right people in the right companies about the right things. And they just would not spend any time on anything else. And the flip side of this is you see these reps struggling. And at least what I saw at Salesforce and other organizations, like they have the highest call volume, the most meetings, but they're meeting like the wrong people in the wrong companies and they're meeting them again and again and again and chasing these deals. And then what happens is they run out of time to prospect. So now they can't generate their own pipeline, which I understand that nobody, no AE and B2B SaaS is ever supposed to generate their own pipeline. But in theory, if one were to do such a thing, they run out of time to do that. And then now they can't walk away from their pipeline because they don't have any pipeline that they're generating. So if they close out that deal, that's never going to close, then they can't hit their target. They can't hit their target anyway, but it's just this vicious cycle. Yeah. I realize we're at time. Do you want to go over a little bit or do we got to wrap for you? I do need to wrap up, but I really enjoyed the conversation. Likewise, Hayes. Thank you so much for joining me on this. I think it's such an exciting thought exercise in just how any company can improve their overall production of their salespeople, whether it's 10X or 2X or whether they're using AI or more basic tools. What you've outlined is an
SPEAKER_27incredible way to look at this. And I appreciate you taking the time to join us to share your thoughts on it. Yeah, absolutely. Thanks for having me, Eddie.
EDDIE REYNOLDSThanks for listening to the show. If this resonated and or you'd like help with anything we talked about in the show, please reach out to us. You can find us at unionsquareconsulting.com and the info will be in our show notes.
