Welcome everyone to the Stacking Growth Podcast. I'm joined with my co-host here of our Friday Jam Sessions Cassidy Shield. Cassidy, how are you? I'm well, Carl.
Good to be back on a Friday. And what are the fact that we have some guests with us? I just, yeah, it's much more fun to look and talk to other people inside yourself. I think that has a weird compliment Cassidy.
So I appreciate you. Yeah, I'm pumping our guests too. So we've got Hayes Davis, founder, CEO of Gradient Works. And we're going to be hanging out with him.
And we're going to be hanging out with VP Marketing Jen Davis and co-founder as well of Gradient Works. So really excited to jump into the category creation elements of what they're doing, just the uniqueness of what they're doing, period. They're tackling actually. I think there's two sacred cows left in sale, two things that have been left totally undistrupted for maybe centuries.
I don't know, Hayes, if that's super dramatic. But since the beginning, there have been two things. 50-50 comp plans, which everyone knows and very passionate about comp. That has not been touched or innovated or disrupted at all.
It's a first sacred cow. We cast the eye top of that in other podcasts. But today, the second sacred cow is just this idea of Wild West territory carving. So Hayes, first question kind of to you.
I guess going back to founder's story a little bit here. I mean, you're about to devote the next decade, at least, of your life to tackling territories. I guess the easy question here is why? What happened in your past and previous roles?
Why tackle this? Tell me how this passion bubbled up. I didn't know this was going to be a therapy session. I feel like I need to unburden myself.
What's wrong with me that I would want to tackle this problem? Well, let me tell you how territories hurt me. How about that? But yeah, so I come to this for maybe a little bit of a different background from a lot of folks who find themselves in sales tech.
They're my career as a software engineer. And I started a company along with Gen. We co-founded a company called UniMetrix that we ran for about 10 years. And during that time, I always felt like we never quite got our sales team the way that we wanted it to be.
We had a really strong product like Growth Motion back before they talked about PLG. And we went through that process and never quite got our model worked out. We had the right quota capacity. We had our reps deployed against the right accounts.
That was kind of my first taste of this challenge. And then after that startup got acquired, we joined a growth stage startup that was had a much larger sales team about 60 folks. And started to see some of the benefits of the ways that you could be a little bit more dynamic about how you allocated accounts and opportunity. And it wasn't until I joined that startup was acquired by another larger publicly traded company where I ended up as SPP of RevOps.
And we had a few failed territory planning experiences and some things like that. And I started to realize, hey, we're spending all of this money on training. And we're spending all of this money on contact data. I think we all pay zoom in for way too much money.
We're spending a ton of money on, sorry, I hope zoom in for not like a sponsor or something that we have to answer to. Not anymore. Not anymore. Not enough of that.
And then we spend a much money on sales engagement. You mentioned at the top of the, like, you know, we spend a much money in all these areas. And we're still sitting in a world where about only 53% of reps actually hit their number, right? So we can talk about 50, 50, cons plans like most people aren't getting paid anywhere near what their OTE is.
And so if we're doing all that, we're still not hitting our number. And I had this, you know, personal experience with trying to figure out how do we deploy our 600 sellers in that organization. And it really occurred to me that the challenge is, how do you actually put that team into the market? Like, how do you put your sales reps out there so that they're covering your town effectively?
And it sounds like a deceptively simple thing. And it's a thing that people think they solved 100 years ago, literally, one of our favorite things to quote in any talk we give about this is there's a book on sales management from 1919 that talks about how, you know, maybe we should really organize our sales teams around states. So those are just like arbitrary political boundaries, right? And it's a, so it literally, I mean, you're not exaggerating, but it's been around for more than 100 years.
And, you know, I don't think we're selling the same things we were selling 100 years ago. We're all sitting on Zoom, having conversations like this all the time, you know, this is not, it just doesn't make sense. And three quarters of companies still use geographic territories. And they do this whole painful process to try to carve up the world.
And so just seeing that and, you know, tying all this back to my engineering background, it just, I saw these radical inefficiencies. You get a good rep, a bad territory. And they struggle, you get a bad rep, a good territory. And they don't make the most of it.
And it's, you know, it's no wonder that these territories don't really work out that well in terms of your, your TAM coverage. So we're setting out the solve that. And so it's a mix of just like, look, the math works, right? We're selling things in a completely different way than we have been in the past.
And then a, you know, personal experience of seeing how hard and difficult it is to do this today. So that's where the idea behind dynamic books, which I'm sure we'll give them to a bit more, you know, come to the play. So yeah, we're going after that sacred cow cause it doesn't need to be sacred anymore. Yeah, I love that one of the things that you said that really resonated with me thinking as a salesperson is just like this idea that historically when you miss quota, these 50% of reps that miss, the solution is typically like, or the accountability solely falls on the salesperson.
And it's either solved with, you know, like, let's fire them and get somebody else in or more training, more enablement. Let's call Sandler, let's spend all this money, all these things and cram all these new like methodologies down the throats of our salespeople. And you've come in and taken like a totally different angle and said, hey, let's wait a second, like these sales reps might be pretty awesome. We have a lot of technology that we've invested in them.
They're all been trained by every sales trainer on the planet. They consume more content on LinkedIn and through books. Any other, you know, you're consuming too much content and not selling it out. That could be out there.
Yeah, that could be part of it. But I would like to keep the accountability away from the salesperson if possible. But if like, so that, what I'm saying here is like, that is fascinating to me. And you're saying that, you know, like the RevOps team in theory or leadership now, you're calling that out.
You're saying, hey, leaders, it's not, I mean, even the language on your website, it's all like, you can tell like the voices towards like a VP sales or a director of RevOps or a VP RevOps or somebody. That's gonna ruffle a lot of feathers too, because you're saying, hey, your sales people are actually pretty good, but that one gal in Missouri, you know, is set up for failure and you're comparing her to the dude that owns the Bay Area, you know? And so have you found like in your sales processes or any kind of any of the feedback or research that you've done that there's a lot of resistance, the kind of that idea that maybe it's not sellers that are solely accountable or responsible for the failure of a sales or? You know, it's been interesting because it hasn't really encountered a ton of that.
I mean, look, there's this old school kind of sensibility in sales that it's a positive or a negative, it can go either way, but like the sales is awesome because look, you do control your own destiny a lot, right? Like you go into sales because you like the idea that you've got a lot of say over whether or not you're successful. So I don't wanna take that away from sales and I don't wanna take the like sales person ship out of the equation. But I think a lot of, you know, I've heard, I've heard a sales leader say, well, you know, it doesn't matter what patch you give a good rep, they'll turn it into gold.
And I don't like bullshit, right? That's not true. And so I think the, I do think there's a sense that sales leaders need to be held accountable for how they choose to use their sales reps, to give their sales reps opportunity. And I think that's on ops, that's on sales leadership.
And I think as we get into, you know, many of our customers are fairly high velocity sales orgs. They're not like pure transactional, just, you know, calls, but they're like selling into SMB and mid-market. And when you have that like high velocity motion, it's on you to build a system that can make, you know, hundreds of sales reps have an opportunity for success. And if you go stick somebody in Northern Arkansas and there's one company they can call in Northern Arkansas, you know, like you're not setting them up for success.
And my personal experience when I ran RevOps is I, you know, my team was responsible for sales enablement. And I really fell in love with sales enablement. Like going out and figuring out how to help reps be successful is a lot of fun. And it's awesome, right?
And the worst thing to do, the worst thing to see for me as a leader was a rep who is putting in the work, doing what they should be doing, learning, doing all those things and still failing. All right? That's terrible. And that's on leadership.
That's not on the reps. And so if you're still stuck in that mentality of like, well, then, you know, the reps should just try harder. Well, no, that's not gonna work. Right?
It goes both ways. Hey, why do you think this hasn't been a dress? Like, why are we still in this kind of archaic paradigm of just geographic territory planning? Well, so I think there's a couple of reasons why now is the right time to look at this problem again.
And before I answer that, Kastry, let me back up just a tad and kind of, we're talking about the enemy here, we're talking about geographic territory, but I'm not talking about the solution, right? So let me give a sense of how we view the solution. When you have, you know, when you take this kind of old school legacy territory model, what you do is if any of you, now they've ever been involved in it, right? Because you starting right about now, each year, you go through a really painful, like, three months long process of carving up the world and coming up with these like static lists of accounts, and then you assign a rep to each static list of accounts in Northern Arkansas, in Northern California, whatever it is, right?
Sorry to the Northern Arkansas listeners. But you do that, right? And that's how it's been done for a long time. What a dynamic book says, it flips that on its head and it says, look, we're gonna take the reps that we've got and we're going to allocate out our top fit and timing accounts that we've got right now out to those reps based on their capacity and essentially the prospect lifecycle.
They're gonna work in dynamic set of accounts that changes over time, again, based on rep capacity and prospect lifecycle. And so, you know, what that means is that, you know, a rep is gonna be working an account. They may find that they need to disposition that account in some way, maybe they're under contracts with a competitor, maybe that they're out of business. It may be that they've just done everything they can and it's just not a good fit right at this point in time.
And so, instead of having that sit there as like dead quote capacity, you take that out of their name, put it in a pool, give them the next best account, right? And so, what we found is we started developing the dynamic books approach is that a lot of companies were out there overlaying an element of this onto like a static model or something like this and they were doing bits and pieces of this. And, you know, somebody who's built products and built companies before, the best thing you can possibly see is a whole bunch of people doing roughly similar things, but all having to completely roll their own approach to it, start from scratch and like do bits and pieces of it. So, as we started to see that pattern repeat itself, it became really clear that, you know, people are kind of searching for a different way of doing this, but they all had their different take on it.
So, we needed to come out and kind of codify what that would look like. And the reason it matters now, and why we're tackling this problem now is because previously geography might have been really all you had, right, to try to figure out a way to come up with something reasonably fair. And also, it hasn't been until really post-pandemic, honestly, where everybody just took a hard look and said, do we really care that this person is in market with this other person? We've built these big inside sales teams, everybody's on Zoom, you don't need this idea of, yeah, maybe somebody's gonna get on a plane once or twice, but like, that doesn't really matter.
And so, we're at this stage now, where we all just have to look at ourselves and say, does it make any sense to apply geographic overlay to a big inside sales team? And it doesn't. The other thing that I think is actually really contributed to this is, there's a lot of really interesting stuff going on that helps us understand prospect lifecycle a lot better. So, you think about intent data, things like that, there's a lot more maturity around that.
It's still early days, and it still sometimes doesn't work the way you want it to, and it may never, because it's based off of, you know, ad tech-type data and stuff like that. But at the end of the day, it's like, when you're in a mode where all you know is ICP fit, right, you just kind of cart up the world one time and give everybody the best accounts. But if you've then had that timing dimension of saying, well, it's not just ICP fit, but these guys are in market and these guys aren't, you only deploy them as much quoted capacity as possible at good fit, high timing accounts. And that means, you know, it changes over time.
So, you need to introduce that dynamic element to be able to address the market as effectively as possible given the data that you got. And we're only just now getting to a place where we've got that data, and now we need to operationalize that with our sales motions. Yeah, what I find interesting about that too, is like, this doesn't exclude geography. If that is a criteria that somebody needs to use, like, if you have a certain type of account that you need somebody who owns my, I'm sure the algorithm can just over time say, oh yeah, sign it to the car because he actually is in that market.
But it allows you to optimize for a lot of other factors too. I mean, kind of conceptually at least I guess. Yes, it does. And I think, you know, the best way to think about this is it's just freeing you out to say, what is actually a pharmacographic factor in my ICP fit?
And geography is rarely something that actually matters that much, except at a really, really high level like in terms of like, you know, North America versus something like that. You know, our friends in India do have more, I think, challenges around this, because there's like, there's skills that, like language skills and things like that, that definitely still matter, right? Like, I'm not, you know, advocating, you know, don't have somebody who speaks English to call your French customers, you know, like I'm not advocating like the death of geography, but it's just like, geography should not be your organizing principle, it should just be a factor in the decision. As an off-person, one of the things that immediately comes in my mind as you explain this, because I love these kind of optimization challenges, is that in the current state of the world, not only are you doing it by geography, but it's kind of independent of rep skill level or capabilities.
And I assume in this new world, you can also optimize for experience, maybe industry knowledge, maybe they sell better in enterprise accounts versus commercial, whatever. I assume you're taking into account the capability of the sales rep and kind of this optimization. Yeah, and so, you know, I think there's, you know, sort of separating out like product functionality and things like that, and really just like thinking about the dynamic books model. One of the core aspects of the dynamic books model is to start thinking about, you know, you don't have to throw out your segmentation that makes sense for your business, right?
Most businesses we talk to have a commercial mid-market enterprise type segmentation that usually aligns to rep skill levels and things like that. It's a fairly like gross alignment, but it's still alignment. You know, typically what you're gonna do is you're gonna keep that rough alignment in place, but you change what we consider to be a target book for each one of those reps. And so, it's a lot of what we talk about now with a geographic lens and a static model, but it's, you know, you have your more senior, longer-tenured reps, working your higher segment accounts.
You have them usually have a smaller book, you have your more junior reps, working your commercial or velocity segment or whatever that is. They have a larger book of accounts, typically, and those accounts may have more relaxed, you know, fit criteria. And then, you know, through all of this, you're circulating things based on timing. So, I think the, what this allows for is a lot more granularity there in terms of how you break that down.
And the other thing it allows for is, because there's so much friction and pain that goes into the static territory allocation, you don't wanna change it, right? You might do a true up once a year or you might, you know, you might consider doing it once a quarter, but it's this big heavyweight process. One thing that dynamic books does is it means, instead of, you don't have to see dynamic lists that people can work off of, and the expectation is they're gonna be changing adjustment throughout the year. So, it even comes down to, you know, customers use this approach to, you know, overweight certain types of accounts at certain times of the year, right?
So, it's like, we know that educational institutions really only buy in this window, right? So, we wanna spend more time on those. And so, what it allows you to do, all told, is really segment out those books based on rep, you know, rep performance, rep tenure, seniority, skill set, whatever that is. Some of that you may wanna retain, right?
It also allows you to much more dynamically match up that rep capacity with your, you know, different segments in your TAM to make sure that you're making the best use of it. Cause that's what this comes down to. I mean, the whole point of this is to better use your quality capacity to cover your TAM. And that's, I mean, that's the goal.
Like if we're talking to a VP of sales, that's the pitch. Hey, as you're working with customers, you know, an interesting thing that comes to mind is, I believe that a part of quota attainment and really the lack thereof, that is like a pandemic kind of in at least ass sales. Is that there's just too many reps, right? There aren't, there aren't, a company overestimates, their TAM, I guess, or maybe not their TAM, but just like the bucket of opportunity that actually exists, it really can be handled well by 50 reps, but they have 100 reps.
So naturally you get only 50% of them. You all, you find that you inform even like hiring decisions and you uncover all this head count, blowout and sales teams once you get in there. And like, how do you navigate that, I guess? Or, cause that's like, you know, 20 reps and you only need four, you know?
Like, how does that conversation go? That's a tricky question. But let me talk about the underlying cause of that for a second and then, so whenever I think about this problem of like, why do you have to over hire reps, right? Like, anybody who's ever built a capacity model knows that you know, you generally peg your attainment rates at around 70%, sometimes lower, sometimes higher, right?
So your quota capacity, mine large is, you know, already kind of grossed up in that regard. But, the other reason that you tend to over hire reps has to do with your territory design, and I like to use an analogy with a grocery store for this. So, what happens is, you know, if you go to the grocery store, you know, it's usually the express lane, right? The express lines where you have one line that feeds into four or five different, you know, either people or machines that you're checking out, right?
And then there's the other lines where, you know, so you just line up with a particular cashier, right? And the reason the express lane is organized that way, because that is the most efficient way to process a queue of people or anything else, is to have multiple people working off that same individual line, right? The reason that applies to this discussion is, now imagine if you went to the grocery store and based on what zip code you arrived from at the grocery store, you got assigned to a particular lane, right? Well, at any given point in the day, you might be lining up behind 20 people in cashier number one, and cashier number two has nobody in line, right?
Because you're segmenting your quoted capacity in that way, you're pre-segmenting the quoted capacity, you're basically acknowledging, like there's gonna be some quoted capacity that's underutilized, right? I gotta put somebody in, I've decided that I have to have geographic territories, and I gotta put somebody in Northern Arkansas, even though I know that Northern Arkansas is not a good territory, right? So, quoted capacity doesn't really come in, you know, fractional increments, it's a person or not a person, right, in that regard. So, what you're ending up doing is, when you do this model, you have to over hire, right?
Because you have to apply quoted capacity to different segments that you've pre-built that you know is not gonna be as effective, right? And if you have a more dynamic model where you're taking your whole quoted capacity as a pool, it becomes fungible. This little bit of quoted capacity over here can be applied to accounts over here, right? And so, I think the math problem works out where the bigger the pool of quoted capacity that you can allocate to any accounts, the better.
So, then the question becomes, like how does that impact a hiring plan, or does that mean that we're over hired, or whatever? It may not mean that you need fewer reps, because you may have a, if we see the opposite a lot, like you get a rep that's in a good territory, and they cover their top 25 accounts, but really somebody should be covering the top 50, or 75, or 100 accounts, right? And so, until you really get that allocated out appropriately, and you're actually saturating your quoted capacity, you don't really know what the answer is, whether you're over hired or under hired. It may turn out, you have the right number of people, if you actually just expanded out the accounts across the whole quoted capacity.
So, a lot of times I would say it kind of nets out where it's not like, hey, let's get rid of people, let's reallocate people. And if you're just completely, grossly overestimated what the demand is, then you're already in trouble regardless of how you segment that stuff out, right? So, that's kind of how I look at it, is it's a over hiring, or misallocation of quoted capacity as a function of geographic territories, or static territories in general. And so, you're guaranteed to have an incorrect capacity model that you then apply to an incorrect hiring model.
How do you think about the measurement of success in this model? Like in the old world, everything is probably geared towards, yeah, this is a really good territory, so maybe the targets are set a certain way, even if it was informal, there's some view of good performance or not. And now you're kind of going to another model, which makes a lot of sense, but how do you then know, how do you measure kind of rep performance in this model? Well, I actually think it gets simpler in many cases because a given role of reps, like reps who are all largely in the same role, should largely all be working off of an equivalent book of opportunity, right?
And so, it levels the playing field. We were actually having our head of sales used to run a large SDR team, and we were actually talking recently about coaching SDRs and trying to, there's sort of two, this goes back a little bit to our neighborhood conversation, but there's two things that you want to look at, is one, are the reps doing the right thing, doing the work, and then what opportunity they have to be successful, do they have good at that, right? And so, I think one of the things that gets simpler here is you're normalizing the good at bats question, like do they have the opportunity, like is everybody have a roughly equivalent book? And you don't have to sort of get people a handicap because they have like a less good territory, right?
So, you're not having to figure out that like so-and-so who's in Northern California, well we're gonna kind of discount their performance because they've got San Francisco and their self-attack, right, versus the person in Northern Arkansas who's got like, okay, we gotta think they're doing a little bit better, so you don't have to do as much grading on curve. So, that's actually, I think really important with this, because it starts to put sales person, ship, and effort and all that stuff into the forefront. But the metric that we actually think is super important to look at here is something that we call book productivity rate. And so, a lot of folks in the, especially in like the SDR community, they use a little bit of like misleading shorthand.
They always like, how many activities does it take to set a demo, right? Kind of, but activities don't set demos. Activities are an ingredient to set a demo. The thing that becomes a demo is an account, right?
So, the question is, how many accounts that you're working, do you turn into pipeline, right? If I'm some sort of absolute master rep and I can send one email to each one of those and turn them all into pipeline, then that's fantastic. That doesn't mean that it only, you know, that the average rep's gonna take one email to do that. So, we look at that book for activity rate and it's measured as a percentage of the accounts worked that turn into pipeline, right?
And that actually allows you to kind of normalize across a lot of these metrics. And so, if somebody has a, you know, if somebody's book productivity rate is vastly different from somebody else's in a dynamic books model, then you can probably say that they're not working the accounts effectively, right? And then that becomes an interesting question because you wanna, if you have somebody who requires a high volume of accounts to be successful, they're using up a lot of your supply in your channel, right? And this is an opportunity cost to somebody like that.
And so, you wanna look at that productivity rate. So, you can say, for two reps who might both be on quota, one rep might be consuming a lot of your possessions, you know, I think, when it's sports and out, to go like a lot of your accounts. And another rep might be doing it much more efficiently. And you wanna lean towards that level of efficiency, which is one of the reasons by the dynamic book model starts with the idea of a maximum capacity for each rep.
They should have a certain number of accounts at any given point in time. And then you have to manage how you allow as a customer to get in and out of their books. But that book productivity rate, I think is a really good way of normalizing across different books. That's a really fascinating, oh, sorry, Cassidy, go ahead.
Or I can go. But just let me add one question on top of that. And that is, and just to kind of finish off this thought, and that is, how does this work in a high inbound model? So, you know, you may have a massive market where maybe not all accounts are kind of pegged out.
And so you got inbound coming in. The territory world is pretty easy. I'm gonna route it to map because he has the Midwest and this came in from the Midwest. And then this world is dynamic.
How do you do that kind of near real time? Yeah, so that's part of what our product does, but the settings side, the product piece for a second. It's really all about capacity, right? So there's two, everybody wants to talk about inbound as like speed to lead, is what matters, right?
Like if you respond quickly, that's better. And that's absolutely true. But it's one dimension, right? There's also the idea of if I hand this thing to this lead as a value, and if I hand it to a rep that is like wildly overloaded, then they're gonna drop everything that they're doing to get, you know, a good speed of response back to that person.
And they might, you know, they're gonna be like, oh, inbound, then I'm not gonna do the outbound that I was doing or I'm not gonna follow up with what I was following up with just a minute ago, right? And so it's this sort of interrupts for the rep. So you also wanna think about not just speed, but are you handing it to a rep that has capacity to take this on? And so the first kind of cut of this is usually a capacity weighted, well, a capacity capped round ramen where you basically say, I'm going to, this needs to go to a mid-market rep, and I'm looking at my mid-market reps, and there's two reps that have capacity and two reps that are at max capacity, right?
And you give it to a rep who has capacity to take it, with the same like speed to lead type SLAs, right? So the way it actually ends up being implemented in a lot of cases is either a pure round ramen where because you just decided that's the model that you wanna go with, it sort of sits on top of the book, like you have your normal book and then you do a pure round ramen assuming that'll be kind of even out. It's not my favorite, the one I prefer, which I think is the most effective is that you have, you treat these inbound as part of the book capacity, right? And we talked about, like Carl mentioned at the top, the idea of like a Wild West, right?
So a form of territory design is to choose not to have territories, but not to have any central management at all, right? You know, if you're a early stage company, Series A or whatever, and you're just trying to get things done, what usually happens is you're adding reps relatively slowly, initially. You're maybe being more inbound driven than anything else, so you're just kind of ramen-robbing stuff around, but those reps that stick around for a while suddenly you realize like this tenured rep, that your first one or two reps, they now have 2000 accounts in their name, right? And every new rep you add is like, well, we're gonna find accounts to have them work.
So in a heady inbound model, you still wanna think about circulating accounts or having like capacity-capping, right? Because what happens in that Wild West model is you get these hoarders who basically, the ROE, you know, allows them to hang on to anything that comes into their name forever and essentially have an option on any kind of inbound activity from that account ever again, you know, in perpetuity, right? And so I think it actually fits, a key part of the dynamic books model is, again, thinking about that target book and thinking about how you route inbound into a target book and keep the characteristics of the target book in place. Makes sense.
All right, Carl, you're up. So many questions, Master's fascinating. I wanted to talk about the productivity rate, because that's like a really awesome, like, leading indicator, whereas close rate is like a lagging indicator, right? And so like how you balance these is, I think, fascinating, but maybe we can talk about that separately if you really want to.
I have a new question now based on what we're just talking about around inbound routing. It feels like your dynamic books model would incentivize reps. I'm trying to think like a rep, I had this territory. It seems like it would incentivize them to work harder at working their accounts because I want to create capacity to get nice, hot inbound, right?
Or to go find stuff outbound, whereas the geo model doesn't really incentivize, like, because I can just say, I mean, you're just saying, I don't have to worry about losing them, or I don't worry about the opportunity cost of having them in my name. So this, again, incentivizes a more aggressive working of your book, which obviously is going to result in, there's not a question there, I guess, but it was just like a cool insight. I mean, I guess the question is like, do you find that that is true? It was my assumption true.
And how do you feel like that impacts just the vibe and just like the motivation of a sales organ general? Yeah, so I mean, we do find it true. We've got a case study on our site, if you go to gradient.work.books. There's a case study from where our customer is omnipresence.
And the key results of that case study, I'll spoil it for you, so I guess you don't have to give us an email and download it. But key results of that case study are as they adopted this model and adopted gradient works, their SDR team was the team that adopted about 37 SDRs. And so a 16% increase in meeting set. But what the real cause of that was they touch 20% more accounts.
And the reason they touch 20% more accounts is in large part because the rep spent an hour and a half less per day per rep spending time trying to figure out who to do outreach to within their book. Because they now had a much more tightly constrained book. And they knew that everything in that book was the highest fit, best timing stuff that they could be working at a given point in time. A lot of reps have an element of analysis paralysis.
And you hand it a territory that's got 2,000 accounts in it. And you walk in and the more like, who might reach an ounce of it? And so the earlier point about working your book better, I think a few things happen. One is the carrot and stick aspect of this is like, look, we're committing as an organization to ensure that you are going to have the best possible accounts that exist alongside all the other reps to be working.
You're not going to have a bunch of dogs. So we're committing to that. We're committing to giving you a smaller book. And we haven't talked about this, but there's typically a user who loses aspects of this.
If you're not actively working accounts, there's a process as part of dynamic books called the retrieval, where we'll take accounts you're not working out of your name and redistribute them. And so the trade off here is like, you're going to have awesome accounts. As an organization, we expect you to work those accounts. That's it.
It's simple. And from an energy level perspective, there's two things that happen. The reps know who to be reaching out to at any point in time. It's not like there's a bunch of time to figure that out.
So that's great. What you're doing, when you walk in in the morning or walk down in your chair in your home office or whatever. And then the other thing that I think happens is, yeah, there's a strong desire to disposition accounts quickly and figure out, there's an opportunity there. There's not an opportunity there.
And go work those accounts aggressively. Now, I'll go ahead and preemptively say, one of the pieces of discussion that usually comes up in this is one of the kinds of dispositions that we want to encourage, but encourage in the right way, is an account may be, we've worked it to a level of completion. We've done a bunch of outreach and we're just not getting anywhere. This is always the tricky one, because not getting anywhere can be a lot of cases.
It could be that that account has had a bunch of POC changes or something that's just not going to buy any time soon. It could be that you as a sales person just didn't do a good enough job of reaching out to them. And so one of the things that is always like an element that we want to help companies think through is, how should I allow a rep to disposition an account and have it removed from their name? Because one, if you put your rep hat on, one thing a rep might do is just go ahead up a bunch of accounts.
They don't get anything back immediately. Then say, well, these can't be worked anymore. So give me another 100 accounts. I'm just going to get a blast of those.
So you usually want to have a clear ROE around that for what counts as any of these kind of dispositions that you get to that would allow you to take an account out of your name other than success, like I've said a meeting or whatever. So from a activity rate would surface that, because your productivity rate would be really low, because you're melting through a thousand accounts to get four ops. Correct. So that would be a thick one.
Yeah. And then that becomes a coaching thing. In fact, we actually just put out an SDR leader toolkit to help them kind of coach through some of these things. So it's even got like a nice flow chart.
Like, OK, ask these questions and to help diagnose. Like, are they blowing through too many accounts? And so they're not working those accounts. Or is it that there's quality of the account problem or rep quality problem, like all those things?
So you need to be able to keep an eye on the flows of accounts as well so that you can understand whether or not certain reps are, you know, just their rate of usage of your accounts is just way too high. And they're both productivity is too low. OK, I've got an objection for you. Perfect.
So here we go. Buckle up. What happens, it feels like this model will incentivize high volume kind of short term thinking on accounts. Like, if they're not ready to buy now, trash, recycle them, get them out.
But in some industries or with some reps, I'm going to be at, you know, refined lives of grading. It works for a long time. Like, I may have just talked to Cassidy, and he's not ready to buy now. But I'm building a relationship with him.
And I'm going to close him in Q2 of 2023. But I don't want that to sit in my book either, right? Because it's like, there's opportunity cost there. And I don't really know what Cassidy, you know, might get fired before that or something.
Like, I don't know. So do you feel like this would incentivize short term thinking? And how do you balance like, I have customers and I'm building relationships that I'm confident are going to buy their good fits. And I uncovered a lot of really good timing and information.
Like, I did good work. I started a good conversation. But it's not an opportunity yet. Right.
Does it disincentivize the value from that, you know, starting those sales conversations really, really early? So there's two answers to that. Number one is if you think there's really an opportunity there and you think you're building a relationship, then prove it by keeping it in your book, right? And working that account, right?
So that's one. But then the other answer, which is a little less pithy, I guess, is one of the motions that we talk a lot about in this model is, so we talk about reps dispositioning things and kind of returning them to the pool. One of the things that's really awesome about this model is you want to reward reps for getting information. I mean, this is like, sales cycle information is super valuable.
It's first party information. Nobody is going to go like, no third party is going to tell you that, like, hey, we're going to hire this person in 90 days and so and so it's going to be in seed and then we're going to have budget and blah, blah, blah, blah. That stuff you don't know, right? So there's a particular type of disposition that we think of as a get back to me, which is like, I'm going to take this out of my name.
I'm going to have captured a bunch of information about timing for when is the right time to reach out to that particular account. And then in an ideal dynamic books model, you can set that account aside because you've done what you needed to do. Your job is either to create pipeline or learn something, right? You've learned something that helps a future sales cycle.
And then in the future, you're going to get that back. It's going to come back to you, right? So the canonical example for that is always you learn that somebody's under contract with a competitor, right? So I'm glad you can't get out of it.
They're under contract for the next two years. So one year and six months later or something, we just start calling them up again, right? It's not that kind of thing. And so that's where the idea of get back to me comes in.
It's like you would send the reps to gather information, real meaningful sales cycle timing information, by saying that, hey, you can free up your query capacity now. We'll put that in a nurture sequence. Marketing will take care of making sure that they still know we exist. And then at a certain time, that's going to go back into your name.
It's not the easiest thing in the world to do. I'll really admit that. You've got a tag on that, and then you want to make sure you manage that through that process. But that's how you tend to incent it, right?
So short term, it's like, are you really building a relationship or not? So the whole opportunity cost really allows the rep to make a real decision about whether they're actually really building a relationship or whether they're using that as an excuse. And then longer term, it's building the incentives in the model to say it's going to come back to you if you've done what we ask you to do, which is learn something about the timing of this account. Yeah, it's fascinating, too, because if you're stamping this stuff in CRM, these disposition times, if you've got a big stamps going on, which I'm sure is totally comparable, you could over time measure the close rate or the opportunity rate of certain things.
And then you've got a benchmark, and then you can break that down maybe by rep. And so you can kind of, that's a coaching moment, right? You just position 10 accounts, get back to me, and none of them close, and then you get one with another competitor or something like that. So yeah, I love how this model, obviously, it does a lot of great things.
But it also creates a culture of coaching, where it doesn't just pin a rep's performance based on a lagging indicator. You already missed. You're close rate is already trash. It's in the past.
There's so many positive signals early on that surface coaching moments. It feels like this really elevates the pressure. Point that made in the beginning. It elevates the pressure for frontline sales leaders, like myselfs of the world, or executive sales leaders like Cassidy, to we now share accountability.
And there's really no excuses at this point, because we've got all these signals way before bad close rates happen, or loss deals happen, or missed quota happens. And we can choose to take action on that or not. So man, it's fascinating. I love it.
One last question on this bit. Maybe I'll be great to get into how do you build this category. What do I need to do this at the start? So for example, what's going through my head now is, man, I'm a small early stage company.
How much data do I really have to be able to do this efficiently in terms of the dynamic kind of account prioritization? Well, and so this is the thing I really like about dynamic books, right? Is that there's a couple of answers to that, right? So some people look at this and they think about the operational overhead, like moving stuff around, right?
If you're small, that operational overhead's not too high, right? So the next question we get from people, and by the way, if you're big, like you have ready works, if you're big or small, right? Reducing the operational overhead. But the other thing is data.
Like people bring up the data question. And one of the things that I think is really important in my time as a RevOps leader is, and then in the 200 plus conversations I've had with RevOps leaders and sales leaders since then, you cannot go to any human being in a sales organization and say, hey, how's your data? And get the answer back. Oh, just pristine, right?
It's so good, right? You will never hear that. You will get a long sigh. And like, well, we're still working on it.
We're trying to improve. So everybody's data shit. Full stuff, right? And to varying degrees.
And so what you have to build, you have to build processes that I think of as like self-cleaning, right? So if your process breaks down because there's some missing data here or there, then the process is too brittle, because that's just going to happen, right? And then you don't have a process. You just have a series of exceptions, right?
And so the thing I like about dynamic books is that it can be self-cleaning. And what I mean by that is you start out, if you're an early stage company, you've got a real rudimentary sense of what an ICP fit might look like, right? So and you probably pay into your info a little bit of money or whatever to get that data. Or somebody's a little cheaper than them to start with.
I don't know why I'm writing it on the Zoom info so much. But so you've got a little bit of the firm graphics, right? So do your first set of distributions. Like get that out into your rep's names, right?
And then you're going to call those folks. And I mentioned the whole idea of like, part of this finding data, right? And so the reps are calling those folks. And then one of your disposition reasons might be like bad data.
Like this company, we thought they had 500 employees. It turns out they have five employees, whatever, right? So you disposition that. And that goes into kind of a review bucket, right?
And then, you know, your off-sillics are going to be responsible for that. And like go take a look at that and decide whether that should be de-cued forever or whether like we need to put it back in the circulation, right? And so that cycle aspect here is, it actually helps to clean your data. And where people get stuck is like, we don't have an account score, we can rank things, or whatever.
Of course you don't. You're a brand new startup. You're still figuring it out. If you had one today, it'd be different tomorrow, right?
So like acknowledge that. We've got some resources on building like just a simple basic like ICP fit, right? Like just start with that. You've got a few attributes.
Use those. Get those out in your ref's hands and have them, you know, figure out like, is this right? We learn stuff here. Like is the data wrong?
Is our idea of what is right and correct? And then disposition those things. Use that information to clean the data. Now the trick is, of course, if you just have nothing, right?
You don't want to turn your reps into like data quality. People whose job is just to clean stuff up for you, right? In the early days, maybe everybody's kind of all hands on deck to figure those things out. But you know, people let bad data be a reason to not do stuff way more than I think they should, right?
You need to try to figure out how to work with bad data because it's never going to go away. So what I like about this is that you can start with the hypothesis. It's not like you're locking it in for the rest of the year. Like you will an aesthetic territory model.
It's part of a dynamic process. And that dynamic process can then contribute to the quality of your data going forward. That's good to hear. I was hoping that would be the answer.
But Carl, I mean, Carl claims he has great data. Does Carl, Carl, the upgrade data? Best data. I definitely don't.
I'm higher up workers. Back and other things, data, but definitely not me. I was going to round this out by saying the amount of times I've heard Carl bitch about his territory yet, a hub spot. Oh, hey, before engine, when we had a pre-call, I was like, man, you all need a prospect in a hub spot ASAP.
Because again, I felt this as a rep firsthand. And I felt my pain. I can only imagine the pain and torture that the RevOps team has to go through to carve territories. We're not talking about master carving here.
We're talking about butcher level carving. And so it was geographic based. And we had capacities. And I think the capacities were way too big.
Because you would get a lot of, again, people would hold things for forever. The capacities back when I was a hub spot, they probably shrunk now for negative reasons. They probably shrunk because they're more reps, less per rep. But I think capacities were 700 or something accounts.
And it's like, you can't work that, man. It's so many companies. And most of them are going to trash. And hey, you said it.
Like when logging into your computer, you'd be like, what am I going to do today? That hits it, man. So many reps feel that. And it's like a dreadful feeling.
It's like you feel like it's hopeless. Like you're going to just drown in a C of accounts and CRM data and maybe be productive for 40 minutes today. So all that stuff really strikes a chord with me in a weird PTSD kind of way. So you're definitely solving a really important challenge.
We'll wrap up here on part one, Hayes. Anything else that you want to get out that is super critical to the work that you all are doing, that you want to share with the sales leaders and rev-offs leaders that might be listening? Well, I think I'll end with just a quick thought on territory planning because that's what a lot of people are doing right now. I touched on it before.
It's a really tough time for a lot of people. It's tough time for ops folks too. You've mentioned the butchering aspect. And I would say that they're doing their best to try to carve.
They've got really, really blunt knives. If we're going to continue our analogy here. They're really struggling to do that. And it's such a, everyone hates it because it's such a high stakes process.
You know your data's not great. You know you're going to carve stuff up in a way that's really not going to be that good. And so you're struggling to try to get more and more data and do all this analysis. You go through this high stakes, like political exercise.
You do your first cut. And you go talk to the RVPs. Then you go get everybody's feedback. Like, oh, you can't possibly move that account.
You can't possibly do all this, right? And so it's just this whole big painful exercise that you know no one's going to be happy at the end of doing it, right? And so I think the way I would love for people to start thinking about the job here isn't to, isn't it going to carve up the world? But it's to go look at everything you know today and figure out the best kind of place to start.
And those sort of general rules of the game that you want to have people execute on as they go. Like your job is to build a system that deploys your quota capacity as effectively as possible. So instead of this one time high stakes thing, which you get it wrong, you're going to get below the whole year, right? And so I would say for folks who are in that high stakes mode right now, you know, realize that there is a different way to think about this that allows you to adapt and be agile throughout the year that takes some of the high stakes aspects about this, you know, out of the running so that you can actually focus on how do I continuously make sure that my reps have the right things to work?
And when we go and talk with customers and introduce the model to them, I think it's like a sigh of relief a lot of times because it's like we're trying to do our best, but we've like been set up to fail. And I think that this provides a way of still having control of like directing folks towards the right things of being fair in terms of your allocations. So it's not just like, hey, everybody go fishing in the pond and whatever you catch, like that's yours, right? But it's a really good place, I think, for ops people to be and for sales leaders to be because they realize that, hey, we can keep this fair, we can be dynamic, we can change, we can allocate throughout the year as needed when things change.
Like I guarantee you, everybody felt like at the beginning of 22, a very different year than they feel like 22 is now, right? So everybody was building their core capacity models and thinking about territories and stuff and the world where everything is just going through the roof. And now everybody's like, well, I don't know what's going to happen, right? And who knows what 23 is going to be like?
So that's the, so I'd say like think about being agile in 23, and this is a good way to do that. Hey, hey, it's Jen. Thank you all for joining us. For anyone listening, where do they learn more?
It sounds like you've teased a kind of like some pieces of content that are pretty awesome. Where can they kind of find some of this stuff? And how can they get in touch with your sales team to obviously make a purchase as soon as you know possible? That's right.
Well, we want everybody to get educated about dynamic books. So we've got a really, really rich dynamic books hub on our site, gradient.works. .books. A bunch of resources to go learn about there.
You can see how some other companies have done it. You can look at detailed implementation guides. You can watch a nice little video that summarizes it all. And if you see yourself in some of these challenges, there's a nice little orange requested demo button up there that talks about how Gradient works can help you actually do the process.
So gradient.works. .books. Love it. Thanks, Hayes.
Thanks, Jen. Thank you.