B (4:00)

Yeah, absolutely. It's been amazing. And it's wild to see how time after time, we get into, you know, the data and what. What is uncovered is just like something that's, like, it's right in front of your face, but you don't see it. And so to your point, leaders are often looking to invest in a new channel or pivot or do something different. But we are able to see, a lot of times it's like, well, actually, there's something that's right in front of your face that's either massively wasteful or actually a huge opportunity that you're not even thinking because you're stuck in this old mindset of, like, really the hamster wheel. And, you know, those metrics that we hate so much.

A (4:45)

One more thing, too that I'm really realizing is that, well, I mean, some businesses are more sophisticated than others. Like, regardless of size or revenue, it just is what it is. But what I'm realizing is usually it's not even, like, a lack of data, right? Like, companies think, oh, we don't have the data. Like, I can't report on that. But what I'm realizing is it's less of a lack of data and more of a lack of the data in the format in which you need it. And so that's obviously where we come into the picture. And the thing that I love the most about Seto, but I mean, that has been a big eye opener for us and for me in recent months.

B (5:26)

Right, Yep. Makes sense. Well, give us an overview of some of the challenges that this company was facing and a little more context around the situation that they were in when they came.

A (5:36)

Yeah, okay, so just a bit about the stakeholder. So I know we had mentioned it's a senior director of marketing. It is the senior most person in the marketing team. So just putting that out there, this person actually reports into the cpo, not a CEO. But anyways, should be noted that there, in terms of like, you know, the levels of leadership above her, it's reporting right into the C suite. Anyways, interesting, because not unlike many people who work with us, they have been sort of in our purview for a while. Actually, this person came to us about six or seven months ago wanting to learn more about what we do and just like how we can get involved. And at the time that, you know, the timing didn't work out for. For whatever reason, but the first thing she said when we had a conversation, you know, like a discovery conversation, was, oh, my God, when I reached out, like six months ago, I should have just done this then. I'm kicking myself now. And that's not the first time I've heard that, by the way. But anyways, she's sort of like, newer to the organization. I think she's only been there maybe, you know, like a. A year, year and a half. And she resonates with us because her philosophy is, I want data to be able to make smart decisions. You know, we're doing a bunch of planning for 2026. You know, I know I need to scale demand, but, like, I don't know where to put my. My budget. And I'm not about to make a decision with a blindfold on. And I need some help. So can, you know, can you come in and help me? I mean, they were founded in 2000, so, you know, about 26 years old, this company. So they have years of messy historical data. Okay. Like, a lot of shifts in processes, a lot of, like, untracked stuff. They're on HubSpot and Salesforce, and there's a lot of, like, bidirectional sync issues with data flowing from each of those tools, which was problematic for them. But honestly, the biggest thing, the biggest challenge was just like, the inability to connect the dots between marketing and business outcomes and to really just understand what people are doing and how they're interacting with the stuff that marketing's putting out into the market and yeah, that's a little bit of a backstory. Maybe you. What about from a revop standpoint though, because you're, you are closer with their director of revenue operations, maybe something I'm missing.

B (7:47)

Yeah. Oh my gosh. I feel like I relate to that person so much every Revops, you know, leader out there, because it was clear based on what they shared with us, I mean, the RevOps person and the head of marketing had a real, really close relationship, which is amazing. It's just like they told us how much they had cleaned up in the last year since the marketing leader joined. Right. So like she's very data focused and really helped to unclog sounds like some projects that were just kind of in the backlog for a while that weren't prioritized. And so they, they got some things prioritized. They did a lot of cleanup. They really improved their opportunity. You know, pipeline process and even just trying to manage like a HubSpot Salesforce sync in and of itself and like setting up the integration, it's, it's just a huge undertaking. Which is what brings up for me is that as a Rev Ops leader, you're just so in the minutia even when you have a strategy and you can even make huge gains in terms of your data strategy. But then in the day to day you get pulled in so many directions just like any leader. Right. But with revenue operations, it's so hard to maintain that strategic focus while also being pulled into the weeds constantly on honestly, not just to this organization, but in general, like a bunch of low value work. Right. When you have high leverage, high value, like work that and insights that you can surface, but you don't have the time or, you know, or the resources to do it. So they had kind of made a bunch of improvements but still felt stuck in terms of the visibility that they needed. And I relate to that.

A (9:30)

Yeah. And like hats off to this organization. I think from a sophistication and like a skill set standpoint, these people like they know their shit. They just are at a disadvantage because there's a lot of, you know, gaps. But it's like they, they've got their eye on the prize. They know exactly what they want out of this exercise, which is a lot further along than a lot of other people admittedly. And so yeah, that was cool. I think they have a, like a really good foundation for them but unfortunately just A lot of shit working, working against them. Right, okay. So as we explain, you know, anytime we do this, our process apiceto companies come to us for a 14 day sprint. What that consists of is like some deep discovery, understanding their tools, their tech, how data flows between those different tools in their tech stack. And then as well we take all of their core data from their GTM tech stack, you know, CRM, marketing automation platform. You know, if they've got an attribution platform, it depends organization to organization, but we take their core data sources, we stitch that together in a basically like a really structured, simplified view to basically make some sense of their madness, that is their data. And then out the other side we produce some dashboards full of data and then interpret and give them insights and basically at the end of it to quantify the business impact of their highest leverage opportunities or things to fix. So let's get into some of the findings. Okay, so I'll go with finding number one, which is 80% of their pipeline in the last two years. So we did like a two year, 24 month look back. So 80% of that pipeline in that timeframe was completely invisible. And so with our data model, to simplify it as simply as I can, is that we know that most companies don't track pre pipeline activity, which is prospecting. Every B2B company has a prospecting motion and they have different triggers that would initiate that prospecting process to begin. Right? Whether it's an sdr, an ae, whoever's doing the prospecting, a sales, pre pipeline sales activity would begin when we identify a person and we start calling them, emailing them, logging activities in an attempt to connect with them, get a meeting, and eventually create an opportunity. So most companies do not track that. They track a deal source, which is the last thing typically that occurs before the deal is created. We track the trigger, what was the thing that initiated the prospecting motion to begin in the first place. And so when we look back, we look back at all of their data and you know, try infer what that trigger was for them. 80% of everything that they closed in that two years did not have a prospecting trigger. Okay. And so of the 20% that did. Now we're getting a little bit complicated here, but of the 20% that did have a trigger, half of those were unclassified. Okay, so that just in a nutshell means that there's a lot of unknown shit happening in their organization. So like no wonder they couldn't figure out what to do more of what to do less of when there's just missing data, like, that's a huge eye opener for them. And when we covered this with this, one of the biggest findings, when we covered this, this was for them the forcing function to go fix this like tomorrow, basically, because they were like, we can't have these unknowns. It was just not acceptable. Yep.

B (13:01)

And the way that we find that, like you said, we always walk backwards from pipeline creation. So we're looking at what prompted sales to, you know, do their thing. Like that is literally what a prospecting trigger is. That's our definition of. And so what we're saying here, everyone listening, is that 80% of the time when an opportunity was created, it looks like it comes out of thin air. So sales was not talking to anybody before they just created the opportunity. So. And there's a lot more nuance here in terms of, okay, well, what's their tech stack and how are their, you know, phone calls and everything being logged and emails and stuff like that. But this is the reality, right? Trevor is the one who, you know, transforms the data. And his technology that Passetto is built on is what surfaces this. But it's like, it's very clear the data doesn't lie. Like, and they were shocked to find this as well. Like, this is a nightmare scenario to be in as somebody who relies on data, just like to see that things are just seemingly coming out of nowhere. You can't repeat or scale something that seemingly kind of comes out of nowhere.

A (14:11)

Yeah. Here's the other thing that I want to bolt onto that. One of like the biggest key findings and really like the highest leverage opportunity for them in this whole analysis was that their win rates, well, they're at a record low in the most recent quarter that we looked at, but it was like declining consistently by like 5 to 10% every fricking quarter, getting worse and worse and worse and worse. And in the most recent quarter, actually in it went for, you know, most recent quarter was 5%. The quarter before that was 5 freaking 3%. A 3% win rate. Okay. And so like, that is hugely problematic. That's like, you know, 80% below the median benchmark range for SaaS companies, enterprise SaaS companies. And so that was really problematic because that's an unacceptable win rate. It is extremely inefficient. That is putting so much pressure on unit economics to operate that way. And so the biggest like, connection between, well, like your win rate is this. And you're also have like 80% of pipeline that we don't know where it came From. So like, if you got to fix the win rate, you obviously need nuance and detail and data to figure out what to fix. And if you're trying to make decisions like this, you're literally making decisions with a blindfold on. There's just no way other than gut feel and guessing of how to fix that win rate. And so the other thing I'm reminded of too, Amber, is that when we say 80% of pipeline was invisible, one thing that we had realized when we surfaced, that was just around their process and just like lack of best practice, which was sometimes this company would go create opportunities to know who to go prospect to. So they weren't, they weren't opportunities. They were like just like target accounts. And so they were creating opportunities, which is obviously why their win rate was low because they weren't ever opportunities for one and then two, there was no activity that happened before that they would just create an opportunity. And so like that just totally bloated a lot of the metrics and didn't really allow us to get a really true picture. Like what is truly the win rate of this company.

B (16:19)

Yes. Very inconsistent. What is an opportunity? It was very inconsistent. Depends on the team that you're talking to. It depends on the month, depends on how the wind blows. I mean, yeah, this is where the cross functional structure really comes into play. Because marketing leaders not going to be trying to get their hands in the pot. Like what's the definition of an opportunity? When do we create that? A rev Ops leader absolutely. Should be a sales leader, A CRO, absolutely. But this is where things just break down. It's broken for sure.

A (16:50)

Yeah, that was a big one. Okay, what about this next one, Amber?

B (16:54)

Yeah, so in line with opportunities and how we track that, we leverage opportunity contacts when we do the analysis. So there's so much inference that we can do. It goes a really long way to showing what's actually going on in the data. But there's a line like there is a line where we're not going to, you know, infer to an extent where we could be like making something up like ChatGPT. Right. So we're really have a hard stance on this. Like we need to see a contact associated to an opportunity in order to say everything tied to the journey for that contact is related to that opportunity cycle. Right. And what we saw with this company was that half of their opportunities have no contact associated to them. So that makes it really hard to say even in the magic that we do at Pesetto. Yeah, this contact and this Engagement cycle and this prospecting cycle led to this opportunity with this outcome. So while we were able to get them some awesome, awesome opportunity cycle information, it was also like, hey, you could get so much more visibility here even if you simply associate your contacts to opportunities. And then we also saw in terms of gaps, before we get into some more like strategic recommendations here, we have a lot of signals that we tracked for this company across engagement, prospecting and closing, but half of those signals had no channel associated. So again, it goes back to like foundations here. And we're not saying you got to go do like all this stuff manually and blah blah, blah, like boring. You can automate, you can have a framework for capturing these things, but it's table stakes.

A (18:39)

Yeah, it's so funny too because it's not funny, but like most companies are really struggling right now to create and capture demand and they want like channel level tactical recommendations. But it just becomes really challenging when you don't even track your existing channels because channels work differently for every business for a number of different factors. And honestly I have yet to see a company tracking, you know, more than 60% of their channels in, you know, all of the stuff that they're doing, which is just so. It's just a massive blind spot. It really is. And it seems so simple, but nobody does it. Well, unfortunately, yeah, out there grasping at.

B (19:22)

Straws because you don't have the foundations in place, you're grasping at straws. Meanwhile, for example, if you're on Salesforce, Einstein can do a lot of this. Like you can automatically associate your contacts to opportunities, even with the role. I mean really, this is so important when it comes to leveraging AI in your business as well. Because if you don't know who is the champion on this deal, who are we consistently selling into? These are things that you have to know. You can't just outsource all of this to a data analyst or a CRM admin or even AI to go give you insights if these consistent things are not connected.

A (20:02)

Yeah, and one thing I want to mention too for this company that we didn't put in the background or at the beginning is that this is a low volume, high ACV business. Like their average contract size on their deals, you know, 200k, something like that. Their sales cycles are, I want to say, over 300 days long on average, really long sales cycle. One more thing, in the last two years, I think it's like couple hundred, not even opportunities that they closed. So think about that type of like volume on a quarterly basis. It's like, you know, a handful of deals in a quarter. This in my opinion, associating all of the contacts, their Personas to an opportunity is absolutely critical because these are like super multi threaded deals with a lot of Personas involved in like the decision making process. Which means marketing has a huge role to play in nurturing all of those folks for one, in educating them, in building trust with them. It's not just like one buyer buying, you know, a 5, 10, you know, 15K product. These are high stakes deals where people matter more than everything. People are the heart, they're the DNA of what makes a deal close. And it's such a missed opportunity to not go track that not only just for reporting but also just understanding from a marketing pov who is going to be involved on average in these deal deals. Like you know, from a job function standpoint, what do they care about? How can we serve content that speaks to their function in an organization? They're going to come in usually not like the champion stakeholders going to bring them in. They're probably going to come with objections naturally, psychologically that is what happens. So marketing needs to arm those Personas and help with deal velocity. So that's my rant. This is close to home for me because I come from that world and it's just, I know how, just how frustrating it is when you, you're like who, who am I marketing to? Nobody's on the opportunity, like who are these people? Right.

B (22:07)

Yeah, it makes makes sense too why it's not a priority to track it if you're not leveraging the data. Like you know, you didn't have a clear use case to like go measure. As you mentioned, signals in the closing stage across different Personas on the buying committee. Like if you're not aware that you can even do that, then it's not going to be a priority.

A (22:26)

But it's so like it's just first principles. You know, it's just so ironic that in the industry that it's, it's not widely accepted yet. You know, we over complicate everything. Yeah, I know. And these, these are just such straightforward observations. Okay, so getting into more of like the tactical demand gen stuff, we did look at marketing influence across the entire funnel in all three stages. Engage prospecting and closing, which is an active sales cycle. And we looked at signals that are generated from marketing across the full funnel at every stage. And the one thing that jumped out at us right away is just how misconfigured their paid search program was. And so what we could see, I think I don't have the data right in front of me, but quarter over quarter this company was generating about you know, around 50,000 signals per quarter. Right. So those are like the raw individual interactions that a person was having with their brand, you know, visiting their website or attending, you know, attending a webinar or downloading content or filling out a form, you know, any sort of signal, first party signal like that. Right. So about 50,000amonth. And when we look at the channels driving those signals, we could see paid search showing up a lot in just the, the raw signals that you know, were being produced in a period. But when we connect the dots down, the funnel paid search was literally non existent, like contributing a negligible amount to actual pipeline and revenue. So right away what we had seen is listen, you've set up your paid search to contribute very heavily to like top of funnel content instead of any like pages that have like a CTA to like book a demo, which is typically what paid search is, is utilized for. And so like a lot of wasted spend to like using paid search for like the blog and other assets like that. Which was really wonky for us to see as well too. Big mistake that I think a lot of companies are doing is leveraging performance max to basically optimize the campaigns. So right away we're like, you guys got to stop using that because it's driving people to like your content pages. Cool. Might be good for brand awareness, but it's literally showing up nowhere for anybody who converted to pipeline and revenue. Meaning are those even your ICP checking out those pages, are they people who will ever be in market? Probably not so low results. A lot of wasted spend on paid search. We didn't recommend that they kill it. We just said listen, you've got to shift your paid search to be more like bottom of funnel focused, capture high intent demand and then pause that investment until you've got a really good partner in place to execute. We had learned as well that the person running that wasn't necessarily like a designated performance marketing or even demand person. They're sort of like taking that on. And so yeah, definitely our recommendation always there is there like and you got to get somebody really skilled because paid search can work, work really well if it's done really well. I've seen it work really well. But it's also one of those things that's really fucking hard to get right and it's really easy to blow a shitload of money. Pardon my French, that one fired me up a little Bit.

B (25:46)

Yeah. And that was, I know that they had said that was something that was really helpful for them too just to kind of see. Cause they did have a lot of the team on the call on these, you know, the sprints and really cool to see how the team works together and also for the leader to be able to say, okay, now I'm able to kind of understand what are the potential like softer areas on my team that I can help beef up and empower the leader to do that really quickly. I just wanted to touch base because when we say signals, that can mean a lot of things in today's day. So for that we are simple, we look at table stake signals. You don't have to be complicated, complex. I'll use all these far reaching, you know, signal providers in order to have growth. So we look at web visit as a signal. Right. Like a first party web visit web form. So submitting a form, you know, in the prospecting stage, or even the closing stage, whatever kind of form, that's what we were looking at for them. We also look for this company specifically event attendance, registration, those are signals, hand raises, stuff like that. But they didn't really have like a huge diversity in signal types, which again, that's fine. We were able to see massive insights with that. But I just wanted to clarify what, what kind of signals we were looking at for this company.

A (27:03)

Yeah, totally. Okay. So we talked about paid search. Thanks for clarifying that. All right, you want to cover the next one, Amber?

B (27:10)

Yep. So we talked about some gaps around closing and then we also surfaced a big opportunity for them when it comes to the prospecting cycle. So before the opportunity is created. But we know sales is working a prospect, there are no signals for 80% of those prospects, which is a huge indicator that marketing has an opportunity there to go influence when a sales conversation is happening. So that, that was a huge takeaway for them in terms of how do we leverage marketing more across the full life cycle and not just as a, you know, lead generating machine.

A (27:48)

Yeah. The other thing too, just like putting the pieces of the puzzle together is that we know where we can't see a sales trigger, that the win rates on those opportunities were like way lower than everything else, really driving down the average win rate a lot. So when we saw that, we sort of like put the pieces of puzzle together and say, well, it's probably a lot of like cold unaware ICP in your TAM that you're trying to like cold call, get on a meeting and things like that. And the fact that marketing Never had any level of engagement, even a page visit before they move down the funnel just indicates that that motion potentially for this company is like pretty inefficient. So it really does require a lot of optimization around that. And that's not like rocket science, that is just data. You are less likely to be effective in converting and creating and converting an opportunity when it's just like totally, like a totally cold prospector account in your tam. So we definitely saw some of that. And then too, just to add on that, when we say like the demand engine was pretty narrow, the other thing is that like, no, I think 6% of opportunities in the last two years that did make it to pipeline didn't have any corresponding like marketing influence on that. And we also had realized too that was likely due to the bidirectional sync from Salesforce to HubSpot. So like the marketing team was using HubSpot to do their marketing, but when contacts were added to ops after the op was created, they weren't syncing back to HubSpot. So like marketing was doing some great marketing, you know, some running some events, doing, you know, all kinds of stuff, retargeting on LinkedIn, all of this. And they were reaching 6% of everybody who was in the funnel, which is right, Right.

B (29:33)

Like sales is creating opportunities. None of those are sinking over to your marketing platform. So marketing has no way, like talk about cutting off your marketing team at the knees. I mean really. Yeah, yeah, like low effort, low friction, things you can do to change to really completely pivot the capabilities of your go to market function.

A (29:55)

Yeah.

B (29:56)

So yes, narrow, narrow demand generation, we were able to see like some amazing things around that they didn't know. Hand raiser opportunities from, you know, high intent hand raisers were up from 18 to 23% year over year. They had no idea.

A (30:17)

Yeah, they had no idea because they were only looking at form submits and like, oh, you know, the volume of form submit seems down this year. They were really excited to see that. In fact that was a really big bright spot for them and it really empowered them of like, hey, we gotta go do more of that. And so remember their win rate overall was like, you know, between 3 and 5% in the last few quarters. But when we looked at hand raisers, the win rate on those was actually 14%. Okay. So like, I mean that could be improved upon. Obviously we would want to see like a win rate between 20 and 30%, but it was their most efficient and effective way of generating pipeline. Just like totally under leveraged. Yep.

B (30:56)

It's the split the funnel. That's what we've been advocating for years and Chris really championed that as well. This is why it's so important to split your funnel. Not a four funnel model, right? Not to be confused with that terminology.

A (31:11)

Yes.

B (31:13)

All right, so just wrapping this up, I mean, they had so many, like, immediate takeaways that they were excited to go work on and amazing timing for them. Everybody that got a sprint in before the end of the year, shout out to you for the, the rush at the door. But yeah, it seems like it's really helped them to be able to craft a strategy. And also what we're seeing out of these sprints, Carolyn, is leaders mostly in marketing, you know, Revops leaders coming and saying we need new measurement, like we need. My CEO is asking for a measurement system and KPIs and like, what's our North Star? And then they go through a session sprint and they say, okay, this is our North Star. These metrics that you're giving us around these three life cycles, conversion velocity signals, activities, this is our North Star. So that's really great to see that. It's really helping immediately to get some direction there.

A (32:09)

Mm, cool. Okay, so we have this just around the transformation and sort of like, what's happening next. But before that, the one thing I do want to call out is anytime we do these analysis analyses, we uncover just a lot of like, the devil's in the details, right? So it's like very detailed, highly analytical. And what we want to do for the folks that are in the weeds, you know, heading up Marketing and RevOps is how do we make this digestible, that you can bring this to your CEO and have them understand, like, what does this all mean in terms of like dollars and cents. Right? Because we know that that is the problem that most marketing leaders have is taking this and making this data in a format that is going to resonate with leadership. Right? Because leadership doesn't care about all of the nuance. They just want. They want the story. What does this mean for the business? So when we modeled this out, we wanted to quantify the business impact, basically. Right? And so when we can look at, you know, the last, you know, year or so and we see just how much pipeline didn't have, you know, a known trigger and just how low win rate was, and when we basically apply sort of like their average deal size and all of those dynamics, we had basically said, listen, if you simply lifted your win rate up by like 10 percentage points, right? It's a realistic Lift. Right. If you got your win rate up to like 15, 20%, you are basically have the ability to generate at least a million in revenue. Not even from having to go hire more people, get more pipeline, do more of anything. This is just like, listen, with your current, like with your current pipeline, you could just get so much more revenue out of it. Right. Be more revenue efficient, as people would call it. And so we help them put the story together and the narrative around how that is and what it means for the business and basically how to fix it. So that's always great when we can quantify that. And that's just specifically coming from, you know, the 80% of revenue that doesn't have a trigger. Right. We still have, you know, like hand raisers and other contributions to revenue. But this is just like that black box of like unknown stuff that's coming in.

B (34:25)

Yeah. Who doesn't want to improve win rate? I mean, a lot of companies would kill for a 3% lift in win rate, but what you'd end up doing is you just set a goal of, oh, let's improve win rate next year by 4% and then you just go do a bunch of disparate things, try to improve it. So but with this, it's very clear and prescriptive. Like you have a black box focus right here. This is your high leverage opportunity. So, yeah, it was amazing working with them and look forward to doing more of these and sharing the insights with you all. We hope this is helpful. Let us know. We've been getting some feedback that folks are seeing themselves in these examples and it's good to just get this stuff top of mind and hopefully give you ideas around what you can do in your organization to look for some of these and find some of these problems and maybe uncover some of these solutions yourself as well. So anything else as we wrap up here, Carolyn?

A (35:21)

Well, yeah, I thought maybe we could drop in a quote from the senior director of marketing just on their comment around like the whole engagement overall. So what she had said was Passetto quickly connected the dots across our entire GTM motion. They validated things that we had long suspected, which I thought was interesting, but couldn't quantify. And they also uncovered new issues and growth insights we didn't even know to look for. So I consider that a huge win. Obviously we keep all of these confidential for obviously the sake of the company and their privacy. But they were a great company to work with and I know that they got so much value from it. And so this was great. We learned a lot from this, and we know they did, too, so that was. That was super exciting.

B (36:01)

Yay. Cool.

A (36:03)

All right, guys, thanks for tuning in, and we'll do this again very soon.

B (36:08)

Thanks.