RX 12 - How to build a unified account-based GTM that aligns marketing and sales around the right accounts and buying groups| Dan Sperring, CEO & Founder, Align ICP

In this week’s episode of the Revenue Xchange, host Davis sits down with Dan Sperring, CEO and founder of AlignICP. Together, they unpack why most companies struggle with ICP segmentation and how misalignment between marketing and sales undermines ABM programs before they start.

Key Takeaways:

1. Segmentation Must Include the Full Revenue Lifecycle: Most teams only optimize for win rates and deal size, but ignore retention, expansion, and customer lifetime value. This leads to acquiring customers that churn before payback, destroying unit economics.
2. Different Teams Define “Best Customer” Differently: Marketing and sales often select segments based on highest win rates, while CS and product prioritize retention and expansion. Without unified segmentation that creates wins for every function, your campaigns are dead on arrival.
3. Buying Groups Vary by Segment AND Revenue Motion: The contacts involved in an initial sale can differ from those in expansion or cross-sell. Overlaying a generic buying group framework without segment-specific analysis compromises your entire targeting model.

Closing Note: Dan provides a direct assessment of the data gaps and operational challenges that prevent GTM teams from making informed segmentation decisions. For ABM and demand gen leaders building target account strategies, this episode outlines the analytical foundations required to align teams around accounts that drive compound revenue growth.

Transcript

Audio Only - All Participants: 0:13

Well, thank you all for joining for another revenue exchange. I think, I'm not sure y al do we have, do we have two more on the year? I think this is episode number 11, so we're in double digits, which is also crazy since launching, and today. We have this, this, I think for you all will, you'll find it a, a lot of value in terms of there are conversations around the various different platforms and how to build your target account list, how to think about segmentation. but we wanted to bring Dan on because what he's building at Align, ICP is unique from a lot of the solutions we're seeing in the market. And so from a topic perspective, and even, even. Taking it back another level for some housekeeping. I know we have a, we have some reoccurring guests on here who know the flow. Again, this is, as relaxed of an event as possible. It is our live podcast. So interrupt me, interrupt Dan, ask any questions that you have. Our on demand recording will be on our. research hub and then the podcast will be available wherever you listen, whether it's Spotify, iTunes, apple Podcasts, but. So a couple big rock questions that we're gonna chat through. We are going to, have everything revolve around account based go to market, so thinking about how you actually align marketing and sales and getting into some of the non-obvious insights, thinking about. Qualified buying groups. This is a topic that has continuously surfaced this year. It is not new to a m but the way in which it is deployed specifically, and, and, you know, importantly from a platforming perspective and getting into some of the rev ops that is not talked about enough, the actual operat, understanding and then how to operationalize it. And then getting into the MarTech gap in account-based GTM in ABM platforms. So. This is why we had to have on Dan Sparing, who's the CEO and founder of a Align ICP. Dan, I'm so psyched to have you on. This has been a long time coming for the revenue exchange, so I'm gonna first pass it over your way for a brief. Intro. And then also, would I, I think, I think we really need to hear a little bit about Align ICP from a product perspective too, because I know we're gonna touch on this, but because it is such a, it's filling such a big gap. Well, thank you for having me, Davis And I, I do wanna say, since I joined the four X community. now I've learned a lot about the topic of ABM, but also connected with some really cool people. Haley McDonald being one of those, those people who's actually driving down from Seattle today, and she's gonna be participating in an event that we're hosting in Portland tomorrow. also we'll be connecting with Robert NorAm, who was a previous, previously on one of your podcasts. so yeah, the community is pretty amazing and, really excited to be a part of it and continue to, to learn from, you and the, the collective team in terms of Align ICP and kind of who we are as a company. We're an early stage, SaaS company. And, we're really focused on helping people like ourself who have been on the hook for delivering a number and helping scale revenue, and then have seen kind of the misalignment that takes place across, marketing, sales, customer success, and product, and that whole go-to market function. in terms of some of our observations throughout our career was, and, and some of this is very particular to me, was as a someone who has experience in sales, marketing, and then eventually account management, which turned into customer success. What I saw was that my ability to be successful from not only a renewal and expansion perspective was largely a function. Of who the sales team was closing, and when you kind of peel back the onion and you kind of look at. the sales team and, and who they're engaged with. A lot of those opportunities that they end up working and closing are ones in which the marketing team selected, as part of the audiences that they ran to, to generate, leads or, or opportunities. And so, what became very clear to us on our journey was that this audience, audience selection. is, is arguably one of the most important components that go into building a subscription revenue company because if you pick the right accounts, not only do your campaigns convert, but you end up creating much more predictable. and faster growing revenue streams. And, what we have seen since we founded the company and we've worked with a variety of different customers is that, today the market, we believe the market doesn't really have a great, way to think about segmentation analysis. And what we see is people, being forced to do a lot of work in spreadsheets and having to struggle through dirty data and siloed data. And so we ultimately built our company to really help marketers, have a much more holistic view of that revenue lifecycle from acquisition to expansion to retention. And so they can be much more strategic about. Leading the go to market function and doing so in a way that, allows them to really, more effectively articulate the value they're bringing to the organization outside of things like touches and responses, and to frame the discussion more under the lens of, Hey, this is how the marketing team is helping grow compound. Annual growth rates faster. And so it's, it's a big shift that we're trying to help out with. and ultimately our mission is really focused on this construct of, how do we help, transition marketing back into a strategic growth engine versus being viewed as simply a source of leads. And we think that's a huge travesty, and we think that the lack of understanding of marketing across the C-suite. It's something that is, is actually having a very detrimental impact on our growth rates and our customer acquisition cost. And so, we feel really confident in terms of, we have the ability to help companies grow faster without necessarily increasing their spend on marketing and sales. Yep. Yep. And when it comes to ICP segmentation, one of the, one of the big things that has really resonated with ABM leaders, demand gen leaders and, and VPs marketing and CMOs, is this whole concept of building a unified, account investment strategy. It's like, that's ABM at its core. It's not some. Campaign or a tactic or a siloed go-to market motion. It really is the underlying go-to market strategy, and it is how you are strategically making the investment and the bets into your accounts. And so when thinking about constructing your ICP and constructing the. analysis behind what segments should we be pursuing in which type of ABM deployment model one-to-one, one to few, one to many or what we refer to at Forge X as growth. ABM. How are you seeing companies? Build their ICP successfully. What are some of the taxonomies, what are some of the components that they should be thinking about? And, how are they, how are they doing this today? And how do you see, foresee this happening with AI or with other tools like in Allian IP? Yeah. What's the future? Sure. a great question. Potter or data, sorry. when we think a little bit more about this topic and, and we think about the different clients that we, we've worked with, what we see is that because there isn't a standardized taxonomy, people. address this problem from a lot of different, approaches. We see individuals leveraging a lot of, signals and signals. Obviously it's a very generic term, but, there's this kind of a false belief that the, you know, the end signal is gonna be the magic unlock for ICP kind of segmentation analysis. And the general theme in terms of what is missing is this construct of. thinking about variables that are associated with more than just win rates and average deal sizes, but thinking about this construct of. a customer lifecycle and thinking about a customer, over the course of, you know, for example, 5, 6, 10 years. And so, so just to kind of reframe this topic for a second, most, especially enterprise SaaS companies, ones that are doing account based marketing. it's very common for them, for them to have a customer retention rate of 90%. And if you're keeping your customers 90% of your customers, the, the implied lifetime for that customer is 10 years. And so when you take a step back and you say, okay, and a subscription revenue company every year, I'm, for example, getting, I'm making it up$120,000, but potentially I'm getting that for 10 years. And so what we tend to do is. We, we over index on this construct of where do we win? You know, where do I have the right to win? But we're not asking ourselves and we're not really thinking about what's the value of this customer over that 10 year lifespan. And what happens is we will end up, I'd, I'd say like in general, that's one of the biggest mistakes. And so what we assume is the customers who are easiest to acquire and measured by win rates. we assume that those are the same ones that turn into happy customers. And in this day and age, the CAC payback period, for enterprise SaaS, depending on, on the benchmarks you look at, are anywhere between 36 months and potentially up to 48 months. And so, there's many situations that that occur where we actually acquire customers. We celebrate the win, but then they churn and we end up losing money on them simply because they didn't stick around the payback, the cost of acquiring them. And so, so going back to this construct of, which customer segments, are happy with the product, expand, renew, and then ideally drive inbound. Those are some constructs that I'd argue would help us be much more strategic with, our account selection process. And I'd argue that today. Thinking about these variables in conjunction in terms of like, how do I source them? How do I calculate them at, at a segmentation level? it's something that's gonna be extraordinarily difficult to do within spreadsheets and it's gonna be really hard to even ask your finance team to, to calculate this because, there's just so many different variables and kind of permutations that you have to look at. so take this construct and apply it to a real life story and just to kind of. Show, how it, it ties back to this concept of, marketing sales alignment. one of our early customers was a$70 million, B2B SaaS company. we ended up doing a survey that span, that spanned marketing, sales, customer success and product. product management and we asked them to identify their best performing, industry verticals over the last 12 months. And what was really interesting is when we got the survey results back, what we saw was clustering meaning, the marketing sales team. They both selected two industry verticals, which was, just thematically, it was entertainment and travel. And then customer success and product, they both select retail. So that kind of piqued our interest. Like why are both teams looking at this problem, or, or why do they both have these different, perspectives on who are the best performing defined is, is like, is close one, opportunities and, and revenue growth. And so when we looked at the data, what we saw was that the sales and marketing team, they both indexed on the industry verticals where they had the highest win rates. And then the CS and product teams both indexed on the industry verticals where they had the greatest, retention and expansion. And so under that construct understanding like, wow, if we look at it from these different dimensions, the question becomes is who are our, our ICP. Yeah. And, and that, and that actually facilitates a really interesting discussion, which is what are the right variables to use to actually define our customer segments? And understanding that construct of, hey, we are building, compound. Annual revenue that we want to, you know, grow sequentially over time. I'd argue that probably the, one of the best metrics to use is this construct of customer lifetime value, which is things that it's, it's a, a variable that I've heard throughout my career, but never really saw it applied. And sure as heck never saw that variable in any of the things I would use to choose which customers to target. And so under that construct, we think that that, for revenue teams, like if you really want to create go-to-market alignment, what we shouldn't be doing is picking a segment that creates a, a win for one member of the go-to-market team. What we need to do, and we've seen this happen over and over and over, and so we, we have a lot of conviction that this is the answer to true go-to-market alignment is we need to pick segments where, where. we need to pick customer segments that create success for each member of the go-to-market team. And so what I mean by that is we need to pick segments that are easy to win, where we have high win rates, we need to pick segments where we have happy customers who renew and expand. And if we do those things, what happens? And if we show those numbers to sales, to marketing, to customer success, to product. What happens is we have go to market alignment because we're picking segments that creates wins for everyone on the team, and everyone becomes more successful, including our customers. And so we think that's a really kind of big unlock. and when you think, so when you take that contract and you apply it to like, okay, well what do we do today in, in terms of reality? Like in reality there's two approaches. One is we try to do an analysis in some spreadsheets. We work with finance potentially. We look at average deal size, win rates, and then what happens is the, the folks on like, I'll call it the post-sale teams, like CS and product. They'll, they have experience working with those various types of customer segments and they'll know in advance based on their experiences that, hey, these are not good segments, and these are ones that create churn, or these are ones that are gonna create a lot of feature enhancement requests. And these are ones who are not gonna buy more stuff. And so what happens is our, that. That segmentation selection process. If we don't include other team members and we don't show the data in terms of why these are the right segments, your campaigns are kind of dead on arrival because people will discount them. and we've seen it. a great example of a client up in Toronto who they hired consulting, who did an analysis, and Boston Consulting came to the conclusion that. Hey, how, what was it? Construction was an ICP segment, and the sales team didn't agree and never followed up with any of those leads, just because they, they had experience working with those. so the other approach, which is also problematic is, I would argue, when you, when you really dig deep into this problem and you think about it from more of a holistic perspective, The, the mar the MarTech tools that we use. And I, I, you know, let's ma let's focus on ABM. Those tools are all built in terms of their scoring. They're all built in terms of ICP accounts and non ICP accounts. They're all built on the construct of you knowing your ICPs. And what we see time and time again is kind of the improper segmentation analysis. And then, one story we heard of where people, an account took their stage two ops. Uploaded it into six Sense, and then a lot of the, the accounts that they recommended as target accounts were probably not the right ones. And so when I, when you think about it in a holistic perspective and thinking about revenue and LTV. I would argue that those tools were never really built to think about segmentation under this construct. and so I think we're asking too much of them, and I, like, I, I wouldn't say they're like, I think they're amazing tools and are very powerful, but they were just built to solve different problems. Yep. And who have you seen owning this process? There are all these data points and yeah, you need to unify. Varying competing or not competing, but you know, all these teams have different compensation structures or different goals and OKRs, which ultimately roll up into the overarching companies go to market goals. Mm-hmm. But how, how do you align these teams and who's, what are the different owners in terms of this process? Yeah. that's another great question. So what we've seen, Davis is a couple different things. One is that our buyer in most situation is A CMO, and typically she is relatively new within the organization. And typically the organization has realized that, hey, we need, you know, like for example, 2024 was a rough year and we want to change our approach. And so, you know, we want to go deep in the data. what we see is that, the, so the budget owner is typically the CMO, in terms of getting deep into this problem. What happens is the product marketing function, who's typically responsible for doing the analysis? I'd argue they tend to be an under-resourced team, and they do not have access to data scientists. They do not have access to engineers. And so they end up doing a lot of, more like qualitative analysis. and so we, and so what happens is that lack of product. Marketing kind of, capability. It, it creates a huge, huge problem for the, the ABM or demand gen leader'cause they're left kind of guessing. And, and so, so the demand gen leader often will, be kind of a huge champion of this because they're given this huge budget. They're creating all these leads and then they find themselves in a situation where. parts of the organization don't necessarily feel like the leads are of high quality. And so when we bring in, when we do our analysis, we kind of do a first cut, and then what happens is the, the marketing team will bring in the, the sales leaders, and then together, we kinda shape and tune the models, to arrive on an ICP that everyone believes in. going back to your point, I'll, I'll keep it really quick here, is, if we, so when you think about how teams are measured, and so a great example is, you know, on the marketing side, it, it's kind of, you know. marketing qualified lead to sales accepted, you know, or some variation of that. if everyone agrees is upfront what good looks like, you will see, more opportunities get, you know, sales qualified. you'll see more opportunities get, closed one and it, it feeds through the entire system. And so going back to kind of this construct of, hey, we need to be thinking about more than just the booking. when everyone sees what the, you know, certain segments, you ultimately have stronger product, market fit and message market fit, and those are the ones in which you want to target because they create wins for everyone. So the underlying assumption that, that we make today is that the customers who convert are the ones that, are happy. And renew and expand. And if we challenge that assumption, then we challenge our entire segment approach to our segmentation. So glad you brought up, product marketing. The, it is so underutilized in a lot of companies and the ABM leaders or sometimes demand gen leaders won't even have the conversations with them when they're thinking about their segmentation, building their target account lists. Yeah. And you'll even have, we, we've seen this in some of the larger organizations where the product marketing team is conducting some of this analysis. They're enabling the sales team. If they're having these conversations with the executive team and the board about where to prioritize for next year. Mm-hmm. And that never made its way into having an alignment or a conversation with the ABM team or the demand Gen. I believe it. And, you know, another piece behind this too that I'd love your perspective on Dan, is intent data. Mm-hmm. Specifically third party intent data. Yeah. Where, where does that fit in, if at all? Because we will often see, programs where they're using or over-indexing on third party intent, where they're seeing, okay, these accounts are. Our in market, let's make sure that we add them in the target account list without even conducting some of the analysis, like you had mentioned. And, does intent data, does it play a role in this? Yeah, and so we do, a lot of work with intent data and definitely have a lot of observations on the journey. And so review intent is simply, it's a. A timing trigger and we view intent data as not really having much, if anything, to do with that construct of fit. And so, if you were to take a step back and, and kind of go into our, our segmentation textonomy, by the way, we have a 20 page paper on it, that it's a white paper published, you know, it's ungated and so I'm happy to share the link if anyone wants it. But the, the construct is. We wanna identify, when we think about segmentation analysis, there's three core components. One is message market fit, meaning does our message resonate with that audience? And do we have high win rates and, you know, healthy deal sizes. And, really I ideally short sales cycles in comparison to our other segments. the next thing that we're interested in is product market fit. Meaning do the clients get value and renew and stay over time? And then the final thing is the construct of, it's probably more of like a Sam Som but it's, it's market sizing. and then within that we also think about segment health. Like is this segment, growing or contracting? and then looking at individual accounts and how they fit. You know, are they growing faster than that segment or are they contracting? And so that's kind of the core of how we think about segmentation analysis and then intent. Is simply a layering on that, that model to tell us which ones are in market. And, you know, going back to like some of the 95 5 kind of constructs, chances are there's a very small percentage of your ICP that is in market and those probably should be treated differently. Depending on the stage. And then we will add, kind of a taxonomy about like marketing ready or sales ready, depending on where that account is in the journey. and so I don't know if that's that's helpful, but that's how we're, we're, we're thinking about it. Super helpful. And I think, I think it's, you know, the foundation. Is that segmentation analysis actually rooted in company data? And to your point, yes. The intent data is layered on top to help inform, but it is not the, you know, it is not the foundation. It is a tool. It is a signal versus that segmentation analysis. Is the base that should be, you know, at the, at the core of when you're building your target account list or when you're building your account investment strategy. mm-hmm. And, and I'd love to transition into buying groups mm-hmm. And where that plays a role. So you've done the segmentation analysis. Yeah. You, aligned with your product marketing team after hearing your insight around why we need to do that. You build your target account list. How do we think, where do buying groups play a role behind this? Because historically there we all understand the serious decisions 2006 or 2012 version of the Demand Waterfall, which yeah, the majority of financial backers like VCs, PE firms, and a lot of executives are still, very much rallying behind. So you have that on one end, and then you have on the other side some vendors who pushed purely transitioning off of M qls to account based reporting. Yeah, where you're using, you're not using any contact based m qls, but you're actually just using full on account, marketing qualified accounts and moving accounts through a account based funnel and, yep. We, we kind of missed in between where it's, yes, looking at both contact level, not m qls, but looking at a contact level is still very important. The account based buying journey stages are also very important, but it's not a either or they are. Both important. So when thinking about buying groups and how to transition off of that MQL style, contact based measurement and reporting, where do buying groups fit in? Where do qualified buying groups fit in, and how do you actually operationalize that in an account-based strategy? Yeah. Wow. Lots of, dimensions of that question. And so, yeah, I'll definitely, I'll share the work that we've done thus far. And this is a huge focus, for us moving forward as a software company. And so the first thing, that. I want to just kind of reiterate and because, so our belief is if you don't have your segments like really, really dialed in, your ability to understand a qualified buying group is gonna be compromised. And so the segment is like the anchor and what we see, and we've done the work, with some clients, what we see is that the, the buying group varies dramatically by segments. And when I say dramatically meaning, the titles, and so a great example, One, one of our clients that we work with, they sell across, I don't know, call it something like the, their ICPs probably within like three to four industry verticals. and as you drill into those verticals, what you'll see is that the, the titles of the buyers are in media are foundationally different than they are in retail. and so not only is there a different construct of who the buyers are. but in addition to that, like in terms of their titles, and even seniority, but the other dimension that we never hear mentioned, We think it's foundationally important, and I believe this is also supported by the work from Forrester, is the construct of a revenue lifecycle. and to double click on, you know, well, Dan, what do you mean by revenue lifecycle? So, in a subscription revenue business, you're gonna have these foundationally different motions. You're gonna have acquisition, you know, acquiring new customers. And then so, so that primarily will make up a very specific buyer group by segment. But in addition to that, you're probably gonna have another, maybe a slightly different buyer group for expansion in renewal. And then you're probably gonna even have, especially if you're in a large organization where you're, you've maybe evolved to like multi-product or a platform where you're gonna have a cross sell motion where you're targeting a foundationally, a foundationally different persona. One who does, isn't the initial buyer of your, of your. Core offering. So when you start to think about this, what, what you invariably end up with, it's, it's a, think about this decision tree where we have the, the ICP segment identified, and then from there we have these different lifecycle revenue motions. And then for each one of those, we have, maybe a slightly different iteration of the buying group. And so, so, okay, Dan, this seems really complex. How, how do we simplify and operationalize this? So the way in which we do that. Is by, this is something that, that, as a CS leader I used to do every quarter was a lot of win-loss analysis. And so the way in which we're thinking about this and the way that we're approaching this. incorporates data, first party as well as third party data. The first party data is gonna be sourced from the CRM. And so once we have the ICP segments, we look at, acquisition opportunities. And then on acquisition opportunities, we'll look at, for example, 50 close one opportunities, 50 closed loss opportunities. The closed loss opportunities have to, at a minimum. Reach a certain level of maturity.'cause otherwise the buying group won't be fully formed. And so you call it like stage four, stage five is gonna vary depending on your organization and how you define your stages. But what we look at is, Within, with within the opportunity there's contacts associated and you know, especially in an account-based motion, there's contacts associated with the opportunity. What we see is those are incomplete. And what I mean by that is the sellers, often are not adding all of the right contacts on. and so there's other ways'cause we have an API that connects to A CRM, so we can also look at contacts. Who've been touched, within certain timeframes, and within certain, and even though they're not on the opportunity, they're, they're being touched. and maybe they're responding. And so point being is we can start to create. I, I, I describe it as more direct directional analysis on this is what we think a qualified buying group looks like by segment, by revenue lifecycle. And then from there, the next piece is that third party in, intent data. and what can we source from, vendors that we, you know, we work with or partner with. And so one of the intent providers that we work with, you know, very well known. they have an API that's just about out, that is going to allow us to do look backs. So we can take an opportunity and, kind of the timing of, of opportunity. And then we can look at not only the account, but at the contact level we can see the intent. and with the contact level intent data we get, we have kind of a, a rubric or taxonomy for. function like sales, marketing, cs, and then also for, like seniority, VP C level staff. And then we can see what other, contacts are showing intent, who were not listed on the opportunity. And then together that information helps. Us create, I'll call like a pattern matching for, closed ones versus closed loss. And then from there, it's something we're still building. So it's, a lot of the things I'm talking about are a little bit servicey. It's like a mixture of tech and service. But, where I see this going is that, there's the world of data enrichment and especially with AI, has foundation changed over the last maybe 24 months. And there's an opportunity for us to hit APIs, to pull in net new, members of the buying committee or maybe like a short list that our clients can select within our UI to add to those, buying groups to build out and create a qualified buying group. When they're missing is, is where, we think this is gonna be going from a product perspective, which is so important and that. I guess when it comes to the buying groups, mm-hmm. They will. Absolutely vary based off of what your average deal size is. You know, and a hundred million dollars deal is gonna be very different than a more trans, not transactional, but a a$20,000 deal. Yeah. When it comes to buying groups, size, different roles within the buying group, even thinking about how buying groups differ based off of. Industry. and so what are you seeing and what are some buying group attributes that ABM leaders should be thinking about in terms of how many people are in the buying group and, and also what the different roles are and, and how that all comes together? Yeah. And so the, based on the work that we've done, And, and this is, so in some of the, the, the work that we're doing relating to, the third party intent providers, The contact level intent is relatively new. and so there's still some of that we're figuring out, but the, general themes that we see when we're sourcing data from the CRM and we're looking at the opportunity is, gosh, and I wish I could show you some of our dashboards, but, so, so imagine this construct of, I'm thinking about the one client in particular where we have tier one, tier two, tier three accounts. and I wouldn't say that maps perfectly to like one, to one, to few. but thematically it's very close. What we've seen, within the data sets that we worked with is, and this client, they're very, they're ultra, enterprise and so they're, they're large customers are seven figure deals. And, kind of the tier twos are more of like two to$300,000 deals. Believe it or not, we're not seeing a lot of variance in the contacts and opportunities like the, the absolute numbers. Coincidentally, I was looking at it today with our CTO and, and I, I can even just give you the ex exact number. so for their tier one accounts on average, And these are opportunities that reached, a stage four maturity. It had 2.7 contacts on, and like, it's it because it's average over, you know, probably hundreds of, of opportunities. So, so on the surface that seems really light to me. and, and I'm someone that's, Been the seller and one that's, you know, worked in kind of ultra enterprise with really big deals. And so, that seemed really light to us. And then we looked at the tier two accounts and it was like 2.4, which again, was really light and we would expect a much larger variation, like variation in, in groups. And so, So in tier three, it was like 1.2, and those were like, I think on average like$40,000 deals. And so, so there's a real data problem is, that has to be solved first. And when you kind of double click on the data problem is, and I'd say a weakness in some of the, the previous work that we've done on this is that, we're too, we're overly reliant on sellers adding context to opportunities. And because the, like, when you start to think about in an account-based motion and how we think about, I hate the word attribution, but when you think about how marketing is influencing deals to drive them towards close one, if the contacts aren't on opportunities, the contacts are almost like, these foundational placeholders to measure touches and responses. And so what happens is the whole. Data model starts to, be compromised. And so there's ways of solving this problem. and we're still exploring some of'em. I know Demandbase, does a lot of work around, connecting with sellers, calendars and kind of scraping that information, which I think would be incredibly valuable. but I also know that there is ways in which we can get to contacts who are not necessarily on opportunities since we're connected to a CRM. And, and so, we still have a lot of, a lot more work to be done on this, but, I. What ends up happening and, and why we think this is so important is, if this is done effectively, meaning that, that all of the, the members of the buying committee are on the opportunity, what happens is it opens up a foundationally different approach for marketers to have that discussion related to attribution. And it, and it's a discussion that doesn't, Get us into a channel discussion and trying to say that it was this touch that drove the conversion. And so, So this feeds, like a lot of the core tenants here, feeds into another Forester model. we kind of refer to it internally as the Forester Lift model. I'm trying to remember the exact name of it. I think I'm struggling with it right now, but the, the Forester paper, it's like a 1920 page paper and it talks about this idea of, A different way for marketing to articulate how they're driving growth. And it's one that takes the construct of touches and then puts'em in different bands and shows how interaction bands are, are improving. It's three variables. It's, win rates, average deal size and velocity. And we think that that's a, a, a much better discussion because the marketer is. Is using that construct of touches, but really what they're doing is they're saying, Hey, we have this investment. And that's part of the, of the Forrester model is you look at the, the marketing spend, over overall, and then you tie that back to, the engagement on the marketing side, that that touches responses. And then you can start to, you basically have a holdout group of an audience that didn't participate in marketing campaigns. and then you contrast that to the ones you did, and then pretty soon you can have a really good discussion around how marketing is contributing to growth without having to say it was, you know, tied back to this channel or this person. And that's what we, we've built it out for one client and that's what we're, we're in the process of productizing and, and go back to buying groups briefly. You one, completely agree on if there is some form of automation or even changing the culture and process so you can get more than 2.3 or 2.4 contacts who are part of the buying group associated to the opportunities. Now, one of the pieces within this whole buying group model, mm-hmm. Which I don't think is spoken on enough, is it is really easy or. Easier to associate buying group contacts to an open opportunity. Yeah. But free opportunity. Yes. How have you seen some of your clients or the market. actually being able to tag and identify within their tools, those potential or buying group contacts even before that opportunity is there for sales to add them on. Yeah. And so the way in which, we have a client that does this, pretty effectively, it's, it's not perfect, but. They have the construct of, they, they referred to as a zero zero, opportunity, which effectively it's a six sense six qa. And so once a company reaches a certain level of intent, they have, an opportunity created, which is a zero zero opportunity. And what that does is it becomes a container, and it's a container to start to understand engagement, defined as, not only third party signals, but also some, you know, touches and responses. And then if it, once it reaches a certain level of maturity. then the SDR will reach out and then try to kind of marketing qualify it effectively. But the problem with that, there's, there's multiple problems. One is that they end up with thousands of opportunities and, because going back to this construct of the buying journey is not linear. And so, so some, an account will surge and then the zero zero opportunities created. And then what will happen is the surge will go down, but then you're left with this kind of container. and so, so under that construct, I, I don't really have a perfect answer for you. and it is something that I think we should be thinking about in terms of our product, product roadmap because to your point, there's so much happening, you know, before, you know, like Kerry Cunningham has a lot of amazing research that he publishes from Six Sense. About, you know, a huge percentage of the buying journey is happening before you even have that first kind of, contact. And so, I do think there is some really interesting things that could happen there. And, and I obviously am not a, you know, six sense or demand base expert. I'm assuming that they have some answers and opinions about this, that I'm probably unaware of. But it is, so if, if you added that on the ver on the roadmap, that would be amazing. This is just such a big challenge and you know, to your point, some of the large analyst and advisory firms, that stage zero opportunity is what they are pushing for a solution to solve this and, huh. What we're seeing in the large organizations who have attempted to implement it is, you know, they'll go through this whole change management process for about six, nine months. They'll try to implement it and then just revert back to the way in which they were doing it before. And then they have all of this, these stage in their CRM, these, the stage debt or just, you know, debt in terms of, the technological architecture to build it. And one, one unique way that, that we're seeing companies solve this, and we have this as part of our account based arrow, our unified data model, is having a priority contact field so that when you're going through the process and you're partnering with sales throughout that pre pipeline. Or the pre opportunity process, instead of just looking at M QLS or the singular people, it's how do we build a process so that the SDR team or the AEs, can actually partner with marketing to tag these contacts as priority contacts? And then instead of looking at engagement and touches of, across marketing, sales, customer success. Yeah. In terms of first party engagement across, the entire account as a whole, that fall under that marketing qualified account. Mm-hmm. Here are the priority contacts, who we believe based off of historical analysis, like maybe we used a align ICP to uncover that, yes, we know that these are most likely part of the buying group. They're engaged, let's mark them as priority contacts. And then once a opportunity is opened, let's take those associate them. To that open opportunity and what that also allows for is flexibility in terms of maybe there is one business unit that shares a overarching executive who is, might be part of a buying group for both that business unit and another business unit. In that pre opportunity phase, you can have that executive. and be mapping and tracking their engagement in their touch points. And then let's say an opportunity opens up in this business unit, but then it'll, another one also opens up in a separate business unit. Then you're able to, associate that priority contact with the relevant opportunities and it creates less, less mess and less, to your point of, you know, a thousand open zero zero or stage zero opportunities. Yeah. Mm-hmm. And so. This whole buying group association, the change management internally with the sales teams, with marketing as well, and having ABM leaders demand gen leaders think about buying groups as a whole versus just merely personas is so important and it is a part of ABM. Buying groups is not the new ABM you should be thinking about. Mm-hmm. Buying groups. If you're an ABM practitioner, you should have previously and you should now. So it is, it is not replacing, it is merely a part of, and I think that is also important to think about because there is no marketing change happening where, oh, now we're just focused on buying groups. You should also have a focus on the accounts, it's accounts and the contacts that fall inside of them, and those contacts that fall inside of them are part of buying groups. If you have a large enough. Contract value, and it's not just, you know, really, really, what's the word? transactional. Yeah. Yeah. One of the things that you said, Potter. It's really interesting. I just had a discussion about this yesterday and the, the vernacular I used was to describe it. It felt very clumsy. and the reason is, is'cause it's rooted in more like sales. Methodology and process, which is when you think about a prospect account, chances are there's like the term that I was using that that kind of I get stuck on is this idea of a champion. And so within an, like within an account and within a buying group, there's probably one person in there that's feeling the pain most acutely. And if you could solve that pain, they're gonna rally a whole team of people to actually help progress the, the sales cycle and the purchase. And so the, the question really becomes is who, you know, who is that? That potential, kind of priority individual that we know that if we engage with, they'll kind of, it's almost like a domino effect and they'll help us move everything, down the line. So, no, that's very insightful and There's a lot that I'd like to like, follow up in a, in a next discussion to kind of learn more about. Yeah, we have to. And the interesting piece around the champion side too is for companies who are really PLG focused mm-hmm. And they're trying to build, enterprise sales. Strategy or sales motion, and go more up market. The, the PLG people will, we, we've seen this a few times, even in, even in the organizations where you would look at and say they have some of the strongest product led growth. Mm-hmm. strategies in the market. When they're trying to go and build an enterprise sales process, and even bring on, let's say an ABM manager convert someone inside to build out an ABM program, they'll have their target account list. Mm-hmm. You can get people. Mm-hmm. using a product-led growth approach to sign up. But the challenge is the people who are usually signing up are most likely, they're not the decision makers. They're the ones who you want to be champions to almost act as, an intelligence, age, agent to help you. If they love your product and they're using it and it's helpful for them, they will help you identify and uncover. The other people within the buying group. Mm-hmm. So that's how we encourage people to think about PLG and ABM and, you know, how that champion plays a role amongst that. No, it's, it's pretty fascinating. yeah, the, the PLG stuff, believe it or not, we've spent a lot of time studying that, and I don't, we can, I don't wanna take this off course, but yeah, the, one of the real cool insights, and actually potentially it's a good segue into the next topic, which is companies, if you compare PLG versus sales led, what you see is that the PLG, the cost of acquiring a customer, it's almost 50% less. And so you stand back and say, well, why is that the case? Then you start to look at the tools and applications in which, PLG uses, and almost every single PLG organization is either using Amplitude or Pendo. And what's happening is there's a massive amount of data related to customer segments that's being captured within those tools.'cause that's where the conversion's taking place. And so then you take that construct and you apply it to SLG and you're like, okay, I got a CRM. And so, I laugh because the CRM, it's an incredibly helpful tool that every company relies on and has to have, but. I argue was never designed for us to really understand our customers segments and select audiences. And the crazy thing is that what we see time and time again through our data is that, if we select the right audiences, we'll grow much, much faster and more efficiently. And, and ultimately what we're building, it's a, a parallel. a database that connects to A CRM and other, applications to help you do segmentation analysis. And it's basically sidestepping the gap caused by CRMs in terms of visibility and understanding of who are our best and most profitable customers. We have two minutes left and we have a whole topic that we re I don't think we really got into enough. No. But in a quick synopsis. When thinking about the MarTech tools, and you mentioned the CRM specifically for PLG, but also thinking about segmentation and some of the components that you are working to solve at Align, what is the biggest challenge with existing MarTech tools and. How should organizations be thinking about how to solve them in 60 seconds? Yeah. To make it super quick. So yeah, I would argue every MarTech tool, and I, I've, majority of my career has been spent at selling MarTech tools. they are dependent on basically client data from a segmentation and targeting perspective, what a hundred percent of them are missing it's revenue data. And so what I mean by that is. Some of'em are able to capture some bookings information, ar arguably the CRM. But what drives a company valuation and ultimately the success of the go-to-market team is your ability to create predictable compound annual revenue growth. And today we, we as practitioners don't have any of that data that we can operationalize to actually build better audience and, and better list. And so. Because of that, we're simply trying to empower marketing leaders to give them the data they need so they can actually think about their roles as more of an investment. A portfolio manager where they're making bets, and when they make those bets, they have an idea of what the return will be. And if you're measuring the return based on a booking, you're, you're just seeing like one 10th of the value of the customer. And so chances are you are. Potentially making bad decisions based on incomplete data sets. And so, that's really why we exist is, is to help marketing teams really have the insights to get the alignment across the go to market team and get everyone excited about targeting accounts that it's gonna create more success for them and their customers. Couldn't agree more, Dan? Thank you so much for joining. For everyone who joined live, thank you for joining as well. Dan, where can people go for the ones who were online and offline to ask you questions? Yeah, I can be found. my email address is really easy. It's my first name, dan@alignicp.com. also I'm very responsive on LinkedIn. and then our website is align icp.com and there is a really cool 20 page doc on segmentation analysis and, I. We think that as teams read that there's an opportunity to get kind of mutual agreement on the best way to segment and, and help companies be, you know, much more successful. So, thank you for having, us on the show and yeah, I'm a huge fan of the community and we'll continue to engage and, and, learn. From you guys. Thank you. Same, and thank you so much for joining. We will also link out to that report in the community. we'll try to get it on Spotify and Apple if we, if we can do a link in that description. But again, Dan, this was an awesome conversation. I have a, I have a bunch of notes from it and we'll definitely have to run one back. Next year, and it'll be interesting too to chat through the buying group side. But again, thank you all for joining. Dan, thank you for sharing your insights and psyched to see you all next week on our next revenue exchange. Awesome. Thank you. Take care. See ya.