Trevor (5:38)

Yeah, we spent a lot of time thinking about this and talking with companies about this, getting into the weeds with them and trying to understand where they're at today and where they need to be. And there are some recurring themes, of course. I think a lot of it is things were built in silos. I mean, we all know that there's a legacy of sort of point specific problem solving which is just sort of natural, especially as these individual organizations or pieces of the organization have built out over time. You know, the last 15 years or so has been very transformative and sort of a lot of change in things like marketing ops, sales ops and the functions that they support. It's changed a ton. The technologies have changed a ton. And I think you end up with a lot of legacy thinking, legacy build out of systems. We see of course, a lot of point solutions having been implemented with the promise of solving very specific things. I think we've all seen those diagrams that float around the Internet about the modern marketing tech stack or whatever that have hundreds of things on them. And I think there are organizations out there that have added a lot of the things that are on those diagrams, not always to great benefit. It ends up becoming too complicated, too focused on individual little pieces of the problem and pulling it all back together. Taking that step out of the weeds and getting that full picture view becomes not impossible, but it feels impossible. And sort of taking the time, taking the sort of focus away from the day to day weeds, the operational problems that you're trying to solve and zooming out becomes just really hard to do. And I think that's just what we see. There's just all this baggage of too many things going on, not enough big picture view and you end up trying to measure a bunch of stuff. And you are measuring a bunch of stuff. But it's not all in this one context of how does go to market work? It's point specific, it's maybe legacy driven by how things used to work or how they needed to work just to solve an immediate problem. And I think that's where a lot of organizations are stuck and the change to get away from it is scary and it's actually work.

Carolyn (8:09)

I think that you said something that really resonates and I think we should maybe perhaps explain a little bit more. But this idea of like no full picture, unified, like we say a lot unified view, right. Historically, I think the way we've been taught to like architect the data infrastructure, like in CRM for example, is that you have marketing, you have sales and then you have post sales. But the reality I think now with the way buyers buy and the way teams sort of like architect the buyer journey to becoming a customer is cross functional and it's like deeply integrated. Yet the way we sort of configure systems, they're not like that. They're architected to support individual departments, not like a cross functional journey. What's your perspective on that, Trevor?

Trevor (8:59)

Yeah, I think that's true. I also think that a lot of teams, roles, organizations actually know that they should be doing something different there. I think if you got into a conversation with them, they'd say, oh yeah, we do know that we should think of it as this whole thing, full GTM thing. And we understand that they're all working together, all these different roles and functions and teams. And so I don't think it's like a resistance to the concept. Like I think people know it. I don't think that they actually live it day to day though, because they never did take time to take a step back and think about, okay, how do all those parts really fit together? So I do think that you would end up finding a lot of teams that sort of think it's what they're doing, but they're not really, really living it to the fullest. And yeah, I think to my point about point solutions earlier, I think that has contributed to the problem where these individual teams get sold on this very specific thing to solve a very specific problem. And yeah, you get lost in the weeds and that perpetuates this. Hey, we solved this this way, we solved this this way. We have these different ways of thinking about the world when we have these little pieces of the problem. And I'm not saying point solutions are bad. All I'm saying is that I think often they get plugged in to solve a problem that's too specific without regard to sort of the bigger picture. I think that point solutions are designed to solve point solution problems and measure those point solution problems. And so you know you're going to get some pretty good reporting inside the point solution, but from the perspective of that solution and it doesn't ever really ladder up to that full picture view, at least not cleanly, not in a way that has this sort of everything fits into its place sort of view of the world.

Carolyn (10:55)

Yeah, I think that's where we like talk about the single source of truth a lot. And I think that's why a lot of times leading up to board meetings you have like these fire drills, you don't have the single source of truth. And so like everybody within a team is like scattering to come up with the story. And that's why I feel like it's needlessly complicated and nobody can really clearly answer the question of like, well, how is go to market performing? Because you're cobbling together like, you know, if you've got say six to ten different point solutions that your marketing or sales team is using and you're sort of trying to produce a story, you're taking this story from each of these solutions and like piecing it together and it might look okay. And I think that that's where a lot of times teams almost feel like they've got to defend the stuff that they're actually doing day to day. But then it's like, well, what's the story? Because if like our growth rate is down and CAC is going up, like something's not working here, why can't I just get a clear picture of go to market performance overall to like really understand where, like where, where is that friction or bottleneck coming from? Where are we losing and why can't I see it really, really clearly? So I think you've explained that pretty well. I think I have my perspective on why this exists, which is the way historically we architect systems is just not built for the way that modern go to market works today. Like you're seeing the disconnect in the way that we build things and configure our data and configure our tools versus the way buyers buy today. They just don't match up. And so I think there's sort of that view is that we're doing a little bit of catch up to sort of bring people into what we would call like the modern age, even though it doesn't really feel that way. But there's also this piece that it's just inevitably complex. Right. And easy to get buried in the weeds. But like you're in the weeds, Trevor. So can you explain, like, why is it so terribly complex to figure this out?

Trevor (12:48)

Yeah, you know, I think some of it is a problem that has just developed over time as tools, systems, platforms, whatever you want to call them, have evolved and they've evolved sort of in parallel in a lot of ways, sometimes creating competing ways to think about things. So like the introduction of marketing automation, for example, it changed the game in a really big way. Especially in a world where you were using Salesforce, for example, you had this sort of legacy concept of quote unquote leads that I think, if we're all honest, has never quite worked the way we wanted it to. It was sort of hard to manage. And then, you know, you introduce marketing automation. You now have this idea that in theory, a contact contact that you don't have this idea of a lead anymore. You have some complexity created by trying to sync those two systems together. You end up hacking some things together, both physically in the systems and sort of also just like conceptually how you think about it. And you end up with these cobbled together systems that were the best you could do at the time. There were system limitations, there were sort of general knowledge limitations as all this stuff was really new. And, you know, obviously you build something like that out and then it becomes really hard to change what you did. Teams are embedded in those things. It's how the organization thinks about those things. It's even if it was maybe always acknowledged as imperfect, it's still really hard to say, okay, that's what we've been doing for the past six years. We need to do it differently now. And so I think you end up with a lot of barriers there, just organizational change problems. It's not that we don't have the technologies now we do. You've got Salesforce, it's so much more flexible than it once was. We can do the things we need to do with it. You've got some great developments in HubSpot. It's a pretty competitive system these days. I know every system has its limitations and quirks, but they all can do the things we need them to do today. But you probably built something out a while back before these things could do the things that we think they really should do. And trying to justify the cost to do it, the impact on the team, which is a cost in itself and so on. You gotta find a way to tell that story about, well, yeah, those are costs and it's going to get in the way of other progress and so on. Here's how it is worth it really. And I think we need to learn to tell that story better. And it's something we work with many people to try to do. Carolyn talked about it at the beginning. Even if there is a great champion internally, they are working pretty hard to get everybody else on board and willing to make that investment.

Carolyn (15:46)

Yeah, totally. I know we're not the only organization to feel this, but I think we often see two sort of categories of companies that come in. You see sort of like newer companies maybe around like 10 million ARR in revenue or even lower than that where usually they're sort of like a forward thinking champion that understands, hey, like we want to basically set the right foundation from the get go. And I think the appetite to do that early on in with a smaller, leaner team, they're more nimble. I think it becomes easier to build processes when there's less technical debt, there's less legacy thinking, there's less legacy processes in place. And then you have of course, you know, even a company that's like 150 million ARR, they've probably accumulated a lot of technical debt by that point. A lot of people who have been around used to doing things a certain way and I think it becomes a heavier lift at that point to introduce these kinds of changes.

Trevor (16:40)

Yeah, as we said, it's all super complex too. So hard to summarize that up to the people that need to be convinced that change needs to happen. Because you can't go into the weeds when telling that story to that executive team that needs to sign off on it. You need to find a way to boil that down to really clear benefits instead of really getting stuck in the weeds that are the very real weeds. And you're going to have to solve those weeds. But that's not going to make the case you getting into that level of detail.

Carolyn (17:11)

Right. Okay. And so what this sort of touches on the next question that we have in our notes here, Trevor. Why aren't revenue leaders equipped to properly solve the problem of their own? And so I posted actually something on LinkedIn earlier this week that had said I think oftentimes the problem with core go to market performance isn't necessarily the people. And yet you see companies like due to investor pressure, executive pressure like rip and replace teams overnight, let's just get new leadership in, we'll fix the problem. And honestly, like I might have my own opinion, you might differ from me, Trevor, but I really think that they're having the right architecture in place to be able to like Track data to make smart decisions that these leaders can then execute on should be the foundation. And a lot of times it's not. And so somebody had said to me, well, like shouldn't that be the responsibility of the person who owns Go to Market? And theoretically, I think the answer is yes. But I think it also requires a certain way of thinking to recognize that a certain type of data architecture is critical to doing that. And I think not every CRO or whoever owns Go to Market thinks that way. So I think that sort of feeds into the answer here.

Trevor (18:21)

I think that's true. And I think even if you have this super visionary leader at the top, maybe even the whole executive team is aligned, the making it real gets pushed down to a functional, more functional leader, sort of tactical. You've got your RevOps team. This stuff gets thrown over the wall to a RevOps team or somewhere similar, some corner of it or whatever, someone that has the technical skill to go make this happen. But I think there's problems there. They're often given this sort of vague goal of like, help us measure everything. Like, okay, what does that mean? And it means different things to different people within the organization, which causes this sort of scope creepy just problem with defining the true consistent, cohesive endpoint. And I think you also see I know this firsthand from my own Rev Ops journey. Yeah, we could sit and talk about these great things all day long, but at the end of the day I'm getting day to day urgent, tactical things that need to be done or you know, my team needs to think about. Instead of taking a step back and having these great whiteboarding sessions about all the big picture, how the pieces fit together, everything's an emergency. Operational roles end up thinking about the weeds all the time because that's what people expect of them. And to keep things running day to day, it's necessary. You can't get out of those weeds long enough to really take the time to put this architectural view of everything together. I personally have felt it. I've had these conversations with my CFO in previous roles where yeah, we agreed conceptually, yeah, we need to solve this problem. We need to be able to understand what's driving revenue, et cetera. I walked away with an agreement to say, yeah, we need to solve this problem, I am going to go solve this problem. But then the day to day reality hits and you just never make the progress that you're hoping to. And I think the other thing we see, you know, again, I've seen it my own self and every organization we talk to you end up also with this sort of organization specific baggage that is like, oh well, our org works differently and so therefore we have to do this very unique thing to address the things that our org needs. And I think while that is true that the org specific requirements need to be considered, I think you get so bogged down often in those details, the sort of what is now in these orgs that you just don't have the opportunity to take a step back and say really is that the most important thing? Do we have to bend over backwards to do exactly that or can we reimagine it? And I'd say we often see that the power of that baggage almost always wins. Like you're going to end up doing a bunch of hacky things to maintain the status quo. Even if your stated goal is to get to this cleaner reimagined architecture, you just never quite get there. And you know, I think we even see that as the third party coming in. We have to figure out how much of that baggage we can sort of push against and say no, like really rethink it. And you don't always win that battle. Even when we have us as a third party saying no, we have this bigger plan. We've seen this a million times. You just don't always quite get there. And so it's a really powerful force in unfortunately the opposite direction of where you're trying to get to. And it's hard to solve.

Carolyn (22:14)

Yeah, I think that summarizes it. It's hard to solve. So I think there's a technical component of it. Everything you had just mentioned about being bogged down and sort of like the day to day I am reading the chat dialogue, which I'm loving right now. I love to see the chat on fire. And that's exactly why I wanted to sort of keep it to like a small curated group because I was hoping something like this would happen. I want to read out a comment in the chat that I think summarizes what we're talking about now really well and then leads us to where we want to go next. And so the comment is when you see an integrated time series view of engagement concepts like MQL attribution and pipeline source metrics, they make absolutely no sense. What is needed are metrics that support cross go to market orchestration and buying center insights across lead and opportunity sources. And I think that that is so true. So partially one of the reasons, just to reiterate what I was saying, why revenue leaders aren't necessarily equipped to solve this on their own is they could simply sort of not view go to market in this way. They might still be sort of stuck in this non integrated view of okay, what are my MQLs, what is, you know, last touch attribution, telling us who sourced the deal, blah blah, blah. And so I think if the revenue leader does not understand the concept of an integrated or unified go to market architecture, it's never going to be solved. You will like forever be stuck in sort of this old legacy way that is not going to serve you. The KPIs that you need to see or that you need to have visibility into to be able to actually surface the things that are really effective in the journey and the things that aren't. Like, it's not as simple as well, what did that marketing event, what ROI did that yield? We know, and I think everybody here recognizes that that is not the reality of today. It may have been at one point in time, but we have evolved so far away from that old way of operating go to market. So the next question then is what is the best solution for solving this problem fast and effectively? I think I want to spend some time, Trevor, to describe the basic concept of the architecture to. Let's sort of try and explain it. Assuming here that we're talking to maybe a CEO or, or somebody who is totally unfamiliar with a topic, almost like we're explaining it to like a two year old, for example. Let's go there.

Trevor (24:46)

All right. Yeah, let's see if we can pull that off. Absolutely. So I think the overall statement here to start off is that we want to think of Go to Market as a factory. We talk about this here and there a lot actually. It is a factory. There are defined stages to it. You know, it's funny, in this chat we are talking about the difference between hardware manufacturing and the factory process, that they have this rigor because they have to. We want that same rigor in the Go to Market factory, so to speak. And so there are distinct stages to that production process. If we think of it as this assembly line, we can define very clear inputs and outputs to each of those pieces. And it's not about just those pieces though. There are some operational and sort of strategic things that you want to know about each of the pieces. But really the point is in the factory, something comes out the other end. It's not really about those individual pieces, it's about how they all flow into that one outcome. That is, here's what we were trying to create and in the go to market world, what we're trying to create is revenue. And so we like to break it down into sort of digestible bites that are these very clear pieces of the process. At the highest level, we want to make sure that we're thinking about things in terms of what is the factory that is heading towards new logo in software or sort of subscription recurring revenue type of business, which is a lot of what we do and what we think about that. Acquiring that new customer is key. It's the most important part of the overall calculation. Of course, retention is the other half of that because you acquire the customer and then you have to retain them and have that recurring revenue for as long as possible. But to start that process, you have to have that new logo, you have to bring on new customers and you have to keep them. And so breaking out into these very clear views of what, what are we doing to generate new logos to achieve that revenue from those new logos, that's one piece. What are we doing to make sure that we retain those? So are we successfully renewing them and then separately, are we successfully expanding them? Because those are all important pieces of the puzzle. They are different motions. And though there are sort of recurring measurements, you know, things that are common to those different groups, some of them have different ways of measuring outcomes. And the inputs and outputs can be a little bit different depending on each of those objectives. So that's your first thing. Make sure that we can break it into essentially separate factors, separate production lines. I guess I'll say, to follow metaphor.

Carolyn (27:43)

They're not necessarily broken out by department. Right? It's not necessarily marketing.

Trevor (27:48)

That's. Yeah, great point exactly. In each of those cases, maybe there is sort of primary, sort of prevailing set of roles or teams or whatever that are really driving those. So New Logo, for example, of course is heavily marketing and heavily sort of customer facing closing deals, salespeople expansion. That is definitely some marketing. You still need to nurture that relationship on the marketing side, but that's going to be more selling, customer success and so on renewal, again, some marketing, but a lot of customer success. A lot of just making sure the customer is happy, that you're giving them the resources they need. And so, yeah, you're thinking about the coordinated set of things that everyone is doing to achieve that outcome. And you need to be able to measure again, inputs and outputs, what are you producing and, or investing in to achieve that goal? Are you achieving that goal? Are you achieving it efficiently? And what are those individual components that are driving that? So that's a little bit of a Preview of where I'm headed next in explaining the moving parts here. Within each of those production lines in the factory, there are stages to that line. So new logo. We spend a lot of time thinking about new logo because again, it's a really important piece of the process. It sort of involves all of the teams and roles and so on and we break that down into component parts itself. We think about the engagement stage. This sort of first, you're meeting that person, they're meeting you, you're meeting this potential company customer that could buy from you, you're meeting as many people that represent that company as possible and you are investing in things that are very top of funnel. How do you introduce yourself to those people in that company? How do you then give them things that will nurture them toward becoming someone that sales cares about? And so that is this engagement phase, that or stage that is really all about let's produce the right marketing assets, let's produce really good approaches to nurturing, automating all that stuff to make sure that these people are learning the things they need to know about the product, about the company and getting warmed up. We don't want to do a lot of truly cold outbound. We want to give them the information they need ahead of time. We know that that's how buyers work these days and more and more. So the expectation is people want to have access to sort of self serve that stuff. It needs to be the right stuff, it needs to be easy to get to and that can all be used to push those people through to the next stage which we would call prospecting. So this is sort of your lead process. The term lead and prospect sort of get used interchangeably depending on the systems you use and so on. We're going to use the word prospect here though. If you were to go to HubSpot, they'd call it a lead and so on. But I'm going to use the word prospect. So we call this stage prospecting. And this is sort of this record, very clean, clear record of all the times that sales has said, okay, I'm going to try and connect with this person. I'm going to try and determine if there is a sales opportunity here. And so many things drive people into that piece of the overall production line. That is the things that marketing is doing to drive people to ways to raise their hand. So you know, you've got your contact forms, you've got booking, meeting calendars, you've got all those kind of tactics, web chat and so on. You've got contact Scoring, which is looking at all the more individual little engagements that are happening in that engagement stage and trying to decide, yes, it's now time to talk to sales. You might have intent data, you might have other internal data that the teams, both marketing and sales, are using to identify the potential prospects that need to go through that prospecting cycle. We think of that as separate from the deal process. It's not a sales opportunity yet. It's the possibility of a sales opportunity. But the conversion rate, the qualification rate of those prospects is not going to be 100%. You're going to go after stuff that turns out to not really go anywhere. It's not a deal, it's not in the pipeline. It's not ready for that. Some may be ready someday. You disqualify that prospect for now, they, they may come back in later. And we want to know those individual cycles that it goes through. That's a thing that we see not so measurable in most organizations, this idea that you might actually prospect to a person multiple times and not every time's going to work. And that's okay. We just need to know why it didn't work every time so that we can analyze. Is our scoring too optimistic? Is there some incorrect expectation that these people are coming in that turns out they're not a good fit? By the time we talk to sales, all these kinds of things, we need to know that. And we need to know it really clearly. And we need to know it every time we attempt, which, like I said, is rarely measurable in the organizations that we work with. And that's something we work to help.

Carolyn (33:11)

Them solve and think about how inefficient it could be for a company that doesn't measure this, and then they go to measure it to see, well, we maybe reached out to 10,000 prospects in this given quarter and only 6% of them became qualified opportunities. You can see how inefficient that is. But more importantly, you'd want to know why. And most times you can't. Like, we don't have the data to know that. Right. And so think about how damaging that could be for a company that you invest, say in, you know, a 20% BDR team or SDR team or whatever. And to know that those are the results that you're getting out of them, yet you don't have any data to potentially make that process more efficient. Anyways, I digress.

Trevor (33:58)

Absolutely. That's a really important point. And I think it leads me to another point I'd make here is when we See organizations sort of half attempting to address this piece of the puzzle. You end up wandering into spreadsheet land very quickly. You see that a lot. You know, you have SDR teams that are sort of making do, pulling data from different systems, trying to cobble them together in a spreadsheet, trying to track their prospecting efforts in that spreadsheet, and then just do periodic analysis that ultimately ends up being too high level still to be all that useful. And it's just chaos and it burns a bunch of time. That's what we hear from a lot of these teams. Like, yeah, we spend so much time just like trying to find data in different places. Managing a manual spreadsheet. The SDR leader has to wade through random spreadsheet data that is poorly structured and not always accurate, updated, et cetera. And they know this pain. Like they know it's pain, they know it's not right, but they're just sort of cobbling together what they can because they're desperate. They know something needs to be done and they throw together a spreadsheet. It can be better.

Carolyn (35:10)

Do you see commonly that that's just not tracked at all, that we're just making dials and sending emails and we're not actually creating like a standardized processor, like using a definitive record to track that.

Trevor (35:23)

Yeah, I think what you usually see is either almost nothing in the CRM, which is like, okay, yes, we're just like going through at random. Okay, random's not fair. There's logic, there's expertise being applied within the SDR team to decide who they're going to call. But there's very little evidence in the systems, in the data of how that logic was applied. And this sort of point in time fact of what's happening, very little historical record of what did happen in the past. I'd say that's the most common. You know, a lead status field on the contact that says right now we are working this. Okay, that's useful, but it doesn't really tell that bigger story about, hey, we actually worked this one three times before over the last couple years. Here's why they keep getting disqualified. You're never going to know that, not accurately and not in the level of detail that you think you'd want to know. We want to know much more detail. We want to know about the prospecting cycle overall. Like how long does it take us to know those things, how many activities, you know, how many calls does it take, what sequences that we're using usually result in a more successful outcome. All these kinds of things that I think everyone knows they want to know, but they don't typically really know it because at best they're cobbling together that information from a bunch of different systems. Again, probably in a spreadsheet, probably done by a desperate SDR leader that just needs to produce something. But that's not their skill set. They're supposed to be out there thinking about strategies to get their team to sell, to qualify. They're not data people, they're not systems people. They shouldn't be expected to be. But usually I think they end up out sort of on this island by themselves trying to solve their immediate problems. And yeah, you end up with something that's sort of cobbled together to no fault of these leaders. They are doing everything they can, but they're not the person that should be doing it. They're perpetuating that. Everyone's got a different piece of the story problem that we talked about at the top of this discussion. Sure, they're pulling some stats for the next QBR board meeting or whatever, but it's sort of in a vacuum and they're investing maybe hours pulling that together. And it's probably a little different every time and so on. And that's what you end up seeing. And it's not in the context of the bigger picture.

Carolyn (37:53)

Yeah, bigger picture. I think that's always the thing that we come back to.

Trevor (37:55)

Yeah.

Carolyn (37:56)

Okay. For people who say, well, we've solved this because we've introduced stage zero, we don't consider it a qualified opportunity there where you recognize it's just an account that we're actively working and when we're measuring our conversion rate from opportunity creation to close one, we pull that out. And what's your stance on that? Because I see that all the time. Stage zero solves this problem.

Trevor (38:21)

Yeah, it's a noble attempt at solving the problem. I understand what people are trying to do with it. I think it's better than what things have been before. But it's not the right solution. And so I think there are a few problems with it from my perspective, deal ownership being handed off to multiple people through the lifecycle of the deal, that's just overly complicated and not ideal. In general, in orgs that have multiple roles, the sort of prospecting SDR type role and then an AE type role that is actually close of the deal, this requires this sort of mid process record handoff that can go sideways. Ends up requiring someone to do something semi manually in the wrong place in the system and it just creates a sort of convoluted who owns the record now? Whose view is it going to be in, et cetera? So that's one thing I don't really ever like, that the overly complex processes that you end up seeing put in place to measure, quote, unquote, qualified pipeline. I think that's one of the big complaints we usually have when we see this is this complex set of rules around like, well, it's an opportunity, but it hasn't made it past this stage or this other thing hasn't been done yet or whatever. And so we're adding this layer of complexity just to be able to say like, hey, what's our pipeline? It shouldn't be that hard. Yes, there's some nuance to measuring pipeline correctly even when it is real pipeline, but that's not this, this is not even pipeline at that stage zero point, you know, it's just the wrong tool for the job. I think that's really the main statement here is even in the real world, building something, going to build a house, whatever, you want to use the right tools for the right parts of that task. Same with these things. You don't want to use a hammer for everything. So I think sort of to the same point around qualified pipeline, there's a bunch of sort of sales cycle metrics and whatever on the opportunity side that you'd want to make sure a really clean, you know, win rates, sales cycle itself and all that. You add this idea of stage zero, that is this, as we said in the chat here a minute ago, that becomes the dumping ground for just anything that might sort of be a deal. You end up having to jump through a bunch of hoops to tell the story about, okay, how long did it really take for us to close a real deal? What was our real win rate for Opportunities that were actually opportunities. These things all just get completely muddied when part of what that data set is, is actually prospects. It's not deals. There's nothing to do with win rate yet. It was never a deal to begin with. So you didn't win or lose it. We go back and forth a lot with organizations on win rate. Especially like everyone's got a different way of calculating it. Sometimes it's overly complex. I don't believe it needs to be overly complex. If you have good processes for defining real deals, for pushing them through stages that make sense in your actual sales process rigor around hygiene. Close those deals when you know they're going to be lost, just lose the deal, Just be honest about it, be real about it, and then you get real data around how much you're really winning, how long it takes and so on. We find, in my opinion, most orgs don't really have an accurate view of that and they make big decisions based on these metrics that I just don't think are typically really actually telling the real story.

Carolyn (41:58)

Yeah, that's a really good point. Muddying the waters for getting the clear story. Yeah, because how can you optimize when you're not even working from a true set of data? So when we're talking about the stages, engagement and then prospecting, then of course an active sales cycle with qualified deals only when you break it out this way, the main thing I think that you combat right away is, is this sort of like view of one or the other sales or marketing who sourced the deal. Because when you don't have all of that tracked, what you're really doing is you're creating a deal and then you're sort of retroactively trying to figure out how it got there. When you can't definitively track the process of the prospecting efforts that were required over multiple attempts, multiple years potentially. And then all of the stuff that marketing is doing out in the market to nurture them, to create affinity, to build trust, to educate them, you end up sort of saying, okay, well, it's one or the other, which one was it? We know it's not that simple. I think we all wish it was. But the reality is that when you're prospecting somebody, whether it's an AE or an SDR or BDR or whatever, they're also probably interacting still with marketing at the same time. And so I think being able to see the correlation between the two and sort of what's happening when versus one or the other, oh, you know, they registered for a webinar before they became a qualified opportunity. Let's give the credit to marketing. Yeah, I think the interplay of all of the different things that happen throughout that journey just aren't always linear or easy to measure when you don't have the right way to measure them, I guess.

Trevor (43:43)

Yeah, I think the attempts at deal source are sort of misplaced. Like the objective is just not quite right. We don't really, we shouldn't really care about marketing sourced deals. It's not about that, you know. So the way we want to think about it is there are some clear questions that we can and should answer. We do want to know on that prospecting side of the journey, we want to know why we thought we should prospect to this individual so that is a question that you do want to know. Did our scoring model in marketing automation suggest that this should be worked by sales? Okay, great, we should know that. Did this end up coming through as a hand raiser through our contact forms or web chat or so on? Did we use an intent platform to suggest that this thing is ready to prospect too? Did we get this prospect from a partner? Did this come from a referral from a partner? All I could list off a few others, but I think you get the idea. We're trying to say like here's a prospect. Why did we think we needed to prospect to them? That's an important piece of the question. It's not so much like oh, they view to white paper or whatever. Like that's not the question we're answering here. It's the what caused us to believe that sales should invest their resources in this specific prospecting cycle with a specific person. And you do use that when you look at that flow from prospects to deals and start to understand, okay, well here's these deals, here's the ones we're winning, here's the ones we're losing, here's the prospects that are driving those deals. And can we see patterns in say for example, our contact scoring is throwing a bunch of stuff that's low quality and it's not even making it to deals. Okay, that tells us something. There's all these other. I won't list off the millions of things you could ask about that data, but there's all these things that do give you these sort of operational tactical insights about, okay, we need to change something about what we're pushing through the process. Why do we think we are supposed to prospect to this person? Was it worth sales time to do that and how could we make it more efficient in the future? So I think there's that really important piece which frankly we just don't see that measured in a way that we think is really doing anybody any good. And so we always like to solve that separately. There is that sort of multi touch engagement story that is as I said, separate, parallel maybe is the better term to all this sort of prospecting to deal life cycle stuff. Underlying all of that is this story about engagement. What are those things that you're investing in in a lot of cases is going to be investments from marketing, of course, because it's the production of assets, it's the building out the website to make it actually push people down the journey correctly. It's putting events together, it's hosting webinars, it's all those things that produce that sort of real engagement with that person. Now, of course, we acknowledge that you can't track everything. Some stuff's going to be sort of dark, quote unquote. And we have to accept that you're never going to solve for all of that. So you do the best you can. You execute things in a way that is the most trackable for that way, even if there's limitations. And then you gather all that to tell the story about. Okay, when we see someone start their journey, and when we see someone in a specific piece of the journey, they're in the engagement stage, they're in prospecting, they're in the sort of closing pipeline stage. What are those engagements that are most common that lead to the sort of success path that is closing new business? You want to be able to tell that journey story. And this leads into sort of the idea of attribution. There are tools that do this, there's a few different takes on how it should work and so on. But at a sort of foundational level, we're saying we want to know what people are interacting with. We want to be able to tell the story about when sort of what position in the greater journey, those types of things are happening. And we want to have some kind of sort of repeatable, consistent method for telling that bigger story about how those things lead up to hitting that milestone, the next milestone. What's happening in the engagement stage that leads to prospects. What's happening in the prospecting stage that leads to pushing things along to deals. What are people engaging with during the deal cycle that suggests, hey, those things are really showing their value. Those assets that we've produced that actually help someone make a decision to go with us are really working or they're not, and you want to know either way. And so that is an important piece of the process. And it is parallel, separate from this idea of deal source, which is often trying to tell like that one thing out of the great bigger set of things that source the deal. That doesn't really tell you enough. It just doesn't. It's an interesting tidbit. You can make some decisions based on that, but at the end of the day, it's just not enough to make a really informed decision about all the things that are happening on that journey. If you over invest just the last thing that happens before a deal is created, what happens, all that other stuff that brought those people in to begin with at that top of the funnel or beginning of the engagement journey, you end up under investing on those things and your pipeline's probably going to slow down. You have less people to do that one thing that creates the deal, that's going to be a problem for you eventually.

Carolyn (49:41)

Wow. I didn't realize how long we've talked for, which is awesome. So I think we've covered a lot of stuff, but I don't want to wrap this up without asking a few more questions, which is, so whose responsibility is it then to fix this? Like where have we seen the most successful? Certainly some companies have solved this, obviously. Like there are fast growing companies, they have mature, go to market functions. But for those who are struggling, like who's going to fix this for them and can they fix it in house? Is that possible? What's the path? What's the success path?

Trevor (50:17)

So I want to acknowledge up front that sure, an organization could fix this on their own. They absolutely could. There are organizations that have the teams, that have the skills, et cetera. We don't want to make it seem like you absolutely couldn't do this yourself. If you are really clear about the end point and in our opinion, if you align with how we see the world, we think that's the way to go. But if you could get there and you could invest the resources, get past the organization specific baggage that may be holding you back, really accept that you have to not focus on some of the day to day chaos. You're going to have to resource it in a way that gets the job done without being pulled away all the time. Yes, you absolutely could do it. But often in the real world that just doesn't happen. And so we find that our role typically in this is to sort of bring that perspective. We are coming in. When we engage with organization, we know the endpoint that we want to get to. And so that's how we often talk about it is yes, there are organization specific things that we're going to have to learn about your business to make sure that we're addressing those things. But for the most part, those things aren't going to change the end point that we're trying to get to. They just influence how we get there in certain cases. So who should own that? Obviously we think that having a third party to just sort of bring a fresh perspective is helpful. But even then we can't actually achieve that without the right people in the organization being full champions of such a thing. And so I would say it requires quite a few players to definitely be on board. Your executive team needs to understand that the problem exists, that they need to understand the vision and be aligned with it. The individual sort of functional leaders that own their parts of that factory or that production line also need to be very clearly ready to invest the time and effort, energy, brain power into bringing their part of this in line with the greater vision. It can't be seen as a chore. That is sort of the last thing to think about for the day. It needs to be very clearly understood that investing in this now gets to an easier life later. And I think you end up with any of those players. You know, marketing, sales, development, sales, rev ops are similar underneath it all. Like if you have any of those not sold on the vision, not brought up to speed on the details of the vision, not willing to make the time to actually solve the problem in their piece of the world, you probably won't be successful or at least it's going to take a really long time. So, you know, that's just sort of organizational change management in general. Like, I don't think I'm saying anything really abstract here. I think that is very definitely true. And so what I'm really calling out is those are the key roles. They've got to be engaged, they've got to be sold on the vision. And that involves having some very clear stories about what each function gets out of the deal too, which is sort of when we get involved, that's partly on us, but it also requires that champion internally to really be armed with the information they need to tell the story internally too.

Carolyn (53:43)

Right. So to like sort of end on a positive note. Right, because that can feel heavy. Right. It feels like for somebody who might sit in marketing, who has the appetite to do this, well, wow, I got to get all these people on board against all of the inertia that we're facing. But how quickly can companies start to realize the operational benefits once they begin this work?

Trevor (54:04)

You know, it's a journey, that's true. But there are some immediate term things, very operational things initially. Like the prospecting process is one that we see as sort of like these very clear quick wins. You probably have active pain in that area today. And so providing that structure, building this piece of the production line in a cleaner, clearer, more efficient way does produce immediate term impacts. There's some change management to do, of course, so, you know, it's not just magically all in place and everybody's happy, but you go through that work, you do it right, you get everybody trained up and design your process in a way that works for the business but produces the outcomes that, that we say are Sort of the standardized way you want. You now have a well oiled machine pretty quickly in that space and that leads to very quick, soon near term ability to measure the operational day to day. Of that you can very quickly start to understand, okay, where are prospects coming from, how long is it taking to determine if that's qualified or disqualified, why are they being disqualified when they're disqualified, where are they generally coming from originally, et cetera. So those are things that you don't have to have this months or years of data to start to understand some of those dynamics. So I think that's sort of your sort of immediate term quick wins there. Longer term, of course you have the benefits of bringing all the things together. Now that takes a little bit of time. We need a little bit of historical data or just need time to be able to say, okay, here's some trends that are telling this bigger story about how we're driving to the pipeline, are we closing revenue and so on. But again, even then in this near term having that really clear defined vision of here's the process, here's the metrics that we're measuring, you can start to see the trend pretty near term and it just gets better over time. It will definitely get better over time as you have more data, longer term data, especially if you have longer sales cycles, but you're getting pretty immediate benefits. And finally, I think in the immediate term, also giving a structure around all of this gives the marketing side a really clear blueprint for how they should execute, what are their sort of and goals for what they're executing and why, and the ability to measure whether they've actually achieved that. I think again, near term you can begin to measure things you haven't been measuring at all or well in the past. And longer term you start to be able to see those patterns and trends.

Carolyn (56:54)

Amazing. Yeah. I think with a lot of the times when we go down this path of work, I think we're seeing these sorts of things be sort of stood up and operational within just a few months typically. And seeing teams sort of operate in a new way I think was really reassuring. And then usually when you start to collect one quarter of data and then another quarter of data, it becomes easier and easier to start to isolate and surface where things are breaking in the go to market. So that's a, I think sort of like KPIs that we can start to measure once this work is done is a topic for a different day because we could certainly go down a rabbit hole if we were to talk about that. Right now.

Trevor (57:32)

You know, I think just as a side note here as well, you know, we've alluded to it in this conversation, but we haven't really talked about it in detail. And that's around the sort of investment side as well. You know, we talked about the architecture overall, the factory, the production lines. And, you know, for the sake of time, I won't go into the weeds here, but I think it's important to leave it with a little bit of background. You know, when we're talking about breaking these things down into these very discrete pieces of the production line, we're also using that same structure to start to change how we think about how we're investing. So what are we spending structuring that in a way that can tell this greater story about there are these pieces of the production line and the overall factory that we do invest in. How are we deploying funds to do those things, going sort of that top level of what are we investing in engagement, in prospecting, in closing deals, what are we investing in expansion and renewal, and then being able to go one step down and talk about when we invest in these stages, where are we investing, what channels are we investing in, what specific types of investments are we making, and all those things. That is another layer to this sort of big view of everything. So that you can start to say that you talk about that efficiency story. How are each of these stages of the production line and the overall factory producing the results compared to what we're spending to do it?

Carolyn (59:09)

And I think what we've learned, right, like Passetto, exists to solve a few different problems. But I think part of our core offer, obviously, is that we have a technology platform that we have built that pulls in operational CRM data, also with financial data and what we want to produce, There are some KPIs around go to market efficiency across that whole revenue, factory engagement, prospecting, pipeline, acceleration, or closing logos, right? And I think we discovered really quickly that you can't really produce a reliable ROI metric basically without the necessary data underneath that. And I think that's what we're really getting into today is the data part of it. We want reliable data. At the end of the day, that's what finance, our investors want to know is sort of like, why is our CAC so high or what is our return on our investments? Where can we get more leverage? What type of things that we should cut? And I think the data architecture piece is so critical to be able to do a really good job of producing, you know, that efficiency metric or that cost of growth metric, right?

Trevor (60:18)

Yeah, absolutely. And I think what you also see when you start to get into sort of spend data, it actually becomes very clear very quickly how little structure there is in how organizations are sort of tracking and executing today. We put a lot of effort into taking a fairly chaotic general ledger and turning it into a set of categories and channels and objectives, you know, these stages that can overlay over the ideal state. But it's always a lot of work because there is no structure. Well, that's not fair. There's structure, but it's not consistent with the structure of how you would want to think about go to market. It's in sort of the way finance thinks about the world. But even finance would benefit from shifting to being able to more cleanly overlay this idea of the factory on their go to market expenses. And that's part of what we're doing in our platform is providing sort of a data layer on top of that to say here's how operational metrics and financial metrics fit into these buckets of that overall architecture. And that's how you get to efficiency. Because otherwise it's just sort of a jumble of spend and unstructured results or.

Carolyn (61:44)

Figuring out like why a company's cost of growth is so high. And I think, you know, I'm mindful of time here, but to close it all out, maybe just giving a quick sort of customer example of this, somebody that we've worked with and a company whose pipeline is sort of steadily increasing. The trend's not terribly bad. But New Logo is going down and the cost to acquire New Logo revenue has been increasingly going up. And so that was a really big concern for this company. I think they're currently in the most recent quarter, their cost to acquire New Logo revenue is about $7. So it's quite a bit higher than, you know, we would want it to be sort of around $1.50, $2. And for the longest time they weren't really able to figure out like what is driving that. Is it marketing, is it sales? And so when we were able to fix their underlying data and then be able to measure their go to market efficiency better, we could see sort of efficiency by engagement, by prospecting and by closing New Logo and really quickly found out that the bottleneck for the inefficiency was really in like the active sales cycle process. And so when you have that insight, one, I think it's really hard to like arrive at that conclusion when you're not really like boiling it up to a High level story like when you're in the weeds, I think it's really difficult to see that. But once you can see that and then you have all of this operational data that you're now tracking, you can see how quickly teams can actually start to make adjustments in real time. They're seeing the data in real time for the most part and then having the operational insights to isolate why that might be happening. And then, you know, of course you see improvements happen a lot faster because you're not really looking back after the fact and trying to figure out why something happened. You're sort of spotting issues fast and optimizing quickly. And I think that's really what our objective is, is to optimize, go to market.

Trevor (63:44)

And I think, I know we go on forever about this, but maybe final point here, you know, I think finance teams have been doing a version of this for a long time. Like they have always wanted to tease out some version of this information, but without the sort of in the weeds context that is really required to get into the moving parts, the actual moving parts. They can tell this sort of overall efficiency story with the data they have available, but it's rarely detailed enough to send. Then double click into that and say, okay, we see the big problem. How do we start to look at those individual moving parts of go to market as a whole? And that's the layer that finance teams do want. And you usually have to go work with individual go to market leaders to try and cobble together some version of that story, but it's manual and pretty unstandardized.

Carolyn (64:40)

Right. Well, on that note, let's close out the show today. We'll be back so soon with. Obviously we go a lot longer on this topic, but thanks for covering all this, Trevor, and big thanks to the people who came out to listen to us today.

Trevor (64:53)

Absolutely. Always a good time.

Carolyn (64:55)

Cool stuff. All right, see ya.

Trevor (64:58)

Okay, bye. Sa.