The Rise and Fall of the MQL - Live Workshop Recording with Jon Miller

Speaker A: Foreign.

Speaker B: The rise and fall of the mql. A topic that is near and dear obviously to all of us, especially us marketers. We uh, love just talking about how much, you know, we, we hate the mql, why it does work, you know, why it isn't working, why the industry is so obsessed with it. And so we know that John here, um, who we'll introduce in a second, is very passionate about this topic, has a lot of lovely things to say. Um, you'll see that I've dropped in a lot of these illustrations that, you know, John's putting on his LinkedIn. I love them. And so I've scattered them throughout this, uh, this session today too. So welcome. Uh, we are Passetto. I'm Carolyn, um, I'm our co founder and CEO. We've got Amber here as well. She's one of our co founders. She's our head of Revops, our technical expert. And then of course our featured speaker, we got John, who is, as you guys all know, the co, the original co founder of Marketo, also the founder of Fave. We don't know a lot about Fave yet. Hoping we get to hear some of that today, um, which sounds very, very exciting. So John, thank you so much, uh, for joining our webinar. We had a lot of folks register very, very fast as well because I think everybody just loves hearing from you on this topic. Um, so I think it's going to be a great hour. John, do you want to give, uh, give the audience, ah, a what's up? And just tell them what you've been up to.

Speaker C: I think it's worth, by starting saying hello everyone, I'm glad you're here. So we started Marketo over 20 years ago at this point. I keep track of that because my son was born the same month that we started Marketo and he's now finishing up his sophomore year in college. Um, and I think part of what we did with Marketo was, you know, both introduced, you know, exciting new technology to, to automate and streamline a lot of things in marketing. And that also helped to underpin sort of what's become the modern B2B playbook. Things like generating MQLs, uh, nurturing leads, scoring them, passing them off to sales like a baton. And you ask what I've been up to in the last few years since I left demand base. And you know, really thinking about two things. The first is how and why a lot of that playbook that we've been using for the last 15 years doesn't work. Anymore or you know, and, or at least why? Uh, it's working less well than it used to. And also, you know, it's frustrating to see Marketo and the other marketing automation platforms not innovating, uh, really not keeping up with the new playbook as well as trends like AI. So my new startup Fave is I, you know, has been working on what does that next generation of marketing platform look like? What is an AI enabled marketing automation platform that uses reasoning instead of rules to orchestrate journeys and things like that. So that's what Fave is all about. And I'm excited to talk about MQLS and the Playbook and technology and all the other good stuff.

Speaker B: Amazing. I think. Well, I can speak for all of us when I'm very excited to see what uh, what the product looks like when it finally comes out into the real world. But it's really exciting because last time we spoke when I had you on the podcast, um, you weren't name dropping Fave yet. So we're uh, it's going to be great and I just love how much the industry is evolving and so just quickly about us, um, because there's new faces here came in through your network, uh, John. So welcome, we're Pesetto. We're hosting the event today and if you don't know who we are, it's not about us today. But marketing um, has evolved and Mo m, most of you here know that measurement has not. And so we are a tech enabled uh, consulting agency helping uh, buyers understand what's actually happening in their funnel. Where are people coming from, how do they go create more pipeline using the data that they don't have. And so that's us and we um, if you're around till the very end, we have a very exciting ah, little call to action for you guys, uh, who make it through the end. All right, let's keep us moving. So we've got an agenda for today. Um, one, we're going to talk about why the MQL has basically become gospel in marketing. Why did it become so irresistible? Not that we want to focus too much on the history of the mql, but just you know, context, setting for where we're going to go next. Um, we're going to get into this whole concept of non linear buying and you know, how, how this whole nonlinear buying has basically killed this analogy that we call like the gumball machine analogy. And I know that's something that John talks a lot about, so definitely want to hear from John on that. Um, we have A real MQL example. Right. So we've pulled this from our customer data. It's confidential, it's anonymous. But we want to show you what actually happens, um, when you can look beyond the MQL and see in many cases how unproductive that is and showing you what that looks like in the way of data, then we're going to talk about the way forward. We've got a really good sort of menu of KPIs that every leader should track. Um, and then also too, how the departure from MQLs, uh, will cause us to all rethink what's in our marketing tech stack. So I want to kick it over to John. Um, right. We know that MQL is sort of like this North Star marketing KPI. Um, you know, I hear a lot to people who come work with us and they're just like their initial thought is, I got to get, you know, I got to fire up the lead gen engine. We need more leads. You know, it is and has been for so long the North Star metric or like the sacred cow of marketing. And so I want to hear from you John, on just your perspective why that is. Why, why is leadership, why is the industry still so obsessed, you know, with this notion of MQLs?

Speaker C: Yeah, so I mean, again, I think it's worth starting thinking about like what marketing was like 15, 20 years ago when we started using the MQL. Because before that happened, uh, you know, I would say marketing was really seen as a cost center. Uh, it was seen as the group that threw the parties and made the color brochures. And it wasn't part of the function that drove revenue. Part of what was so exciting about demand generation coming around in the rise of the MQL was because marketing was able to actually really, for the first time say, look, I'm going to generate these MQLs and that's going to turn into this much pipeline and this much revenue. And the idea was a really good one, which is marketing being able to generally prove that it was actually having an impact on revenue. And so, uh, the MQL was born. And know, I think the original idea of the MQL was sound. Again, I mean it sounds like it's a really long time ago, but you know, Google AdWords really got up and running in say 2004. And again, I'm saying Marketo was really built in 2006, 2007. And so you, what you had for the first time in the early in the late 2000s was marketing was finally able to generate a lot of re of uh, digital responses, you know, initially from Google, but then it started being from webinars and content docs downloads and inbound marketing and things like that. But most of those responses, you know, were filling out forms. Not because they were saying I'm ready to buy something, they were filling out a form saying I want to read your content. They weren't ready to talk to sales. And so we realized as an industry that we needed something to indicate that, you know, not every form fill was actually sales ready. And that was the idea of the mql, you know, and it was like, no, we're only going to call things marketing qualified leads when they reach a certain threshold, a certain level of indication that we think that this is actually worthy of sales attention, that it's the right time to engage this person and their company, that they might be open to, you know, a sales follow up. And it wasn't every form field at the best companies were the MQL worked was it became a contract between marketing and sales. And this is exactly I think what Peter Fincher was just getting at. You know, when it worked, companies said, we will only pass you this stuff that we have agreed is hits the bar for being worthy of past. In exchange, sales would have a commitment to saying, and we will follow up on those things in uh, you know, with a certain time frame and a certain cadence and a certain quality in a certain way. That was a good idea. The problem is then how that good idea kind of really started to break down over time. And it broke down, I think, in a couple of key ways. We'll talk about one of the more profound ones in a slide or two. But it also just broke down because, well, first off, it was sort of too easy, uh, to play with this arbitrary M metric, you know, that where marketing got to be judged on the mql, but it also got to define the MQL M. And it was just all too often marketing teams would sort of game it a little bit to hit the goals. And eventually it got to the point where, you know, any responder would be an mql. You know, download an e book, you're an mql, attend a webinar, you're an mql. It became a lever for volume and not a filter for quality. And of course that's, you know, with the beginning of the end, right? Once that happens, sales starts cherry picking the good ones, uh, discarding the rest. The whole contract broke down. And I think that's part of what led to this kind of whole MQL's dead movement, plus a bunch of other things that we'll talk about in a minute.

Speaker B: Yeah, very much makes sense. Um, we definitely see that a lot. I mean, being like, being in the weeds and, you know, being the people that go in and look at the data, we can definitely see how, you know, marketing shows up to the qbr and their reports are like up into the right, great. We've hit our MQL targets. We've, you know, done what we, what we can do. Boom, boom, boom, you know, but pipeline is down, right? And so the mql in many ways, when we bastardize it and we game the system for volume, it doesn't really. It does a disservice to the business. For one, it's highly inefficient to send all of that stuff to sales. And then secondly, it doesn't, you know, it doesn't tell you anything meaningful if you're doing it wrong around how we actually generate pipeline. And I feel like in many ways like this industry marketing has evolved so much. Like with AI and the commoditization of the Internet and content, the industry has changed so much in terms of how we market and the platforms that we market on. But I feel like these metrics are sort of like a jar of jam. They just love to like, not move and stay still. And like, you know, when we think about like, our ego, our ego hates change. And so I feel like even though how we buy and how our industry buys has evolved so much, we keep coming back to this legacy metric.

Speaker C: Change is hard. You know, I mean, like, I spent years telling CFOs and marketers that, you know, the way to marketing success is to work backwards from your pipeline goals and say, I need this much pipeline, therefore I need this many opportunities, which means this many NQLs, you know, and like, you just that. And if I'm making those numbers, then like, protect my budget. Like we taught a whole generation of, uh, executives that that's the way things should work.

Speaker A: Mhm.

Speaker C: And you know, and it all broke down for a bunch of reasons. But yes, change is hard.

Speaker B: I want to get into the gumball machine analogy in a second, but I wanted to share this visual diagram because we have Pasetta. We talk a lot about the pipeline black box. Right? What does that mean? Right? It means that in the industry on the left, we, you know, in marketing, we measure leads created by MQL volume or by different types of leads. That's what we capture. Where did they come from? What Channel drove them? Was it a webinar paid search? Right. These are the things that we love to track and that we bring to our QBRs. And on the right side, we have opportunities created, right? We track all opportunities created with a high degree of rigor and precision. And then we track lead to opportunity conversion rate. And it's not atypical that companies have, you know, a 2% lead conversion, but they can't figure out why. And then inside this pipeline black box, you know, is all of this stuff that we can't see, like why did we decide to work that lead? You know, did sales actually pick it up? How long did we have to work it for before it went anywhere? Um, is this our first attempt, Is it our tenth attempt to work this lead? What actually qualified and came out the other side? What happened to everybody else? Did they get recycled? Did they get deleted? Right. And so there's a lot, there's a wealth of data in between lead and opportunity where if your lead to opportunity conversion sucks. Well, there's a lot of nuance there and a lot of probably hidden reasons why that lead m maybe should have never been passed to sales in the first place. So all of this goes to say is that, you know, buying behavior in B2B SaaS like is inherently nonlinear. We talk about nonlinear buying all the time. It's chaotic. It's sort of more like the stock market or the weather system than it is a structured path.

Speaker C: Which means, though. Can I comment on your slide here?

Speaker B: Yeah, of course, go ahead.

Speaker C: I think implicit in your diagram here is another challenge of the traditional MQL model, you know, which is that, uh, the left side here is all about people and the right side is all about accounts and buying groups. Um, and you know, that's kind of broken, you know, that, that, you know, when we're creating opportunities, we're doing that, you know, recognizing that there are six, 16 buyers involved. And yet somehow we say we somehow we assume that it's going to be the simple linear process from lead in to kind of opportunity out. One of the biggest problems of the mql, now that we're getting into all the places where it's wrong, you know, is the fact that it is about people and not accounts and buying groups. So, um, we talked about it's too easy to game. We've talked about it's not account based. And then you were just about to get into the fact that it doesn't represent nonlinear buying. So please continue.

Speaker B: Yeah, no, it's a great point because a lot of times, too, is like, where MQLs, I think are misleading is like, theoretically you could have 10 mqls from the same account. And I think that's sort of why you often allude to, well, you know, why aren't we measuring marketing qualified accounts as well as marketing qualified leads?

Speaker C: One person all over your website may not indicate any buying intent, but that would light up most MQL systems. 10 people from the same account, all looking just at your product page probably does not light up any of your scoring systems. And yet that latter situation, I think, is way more indicative that there's something likely going on in terms of buying opportunity there.

Speaker B: Yeah, for sure. And I think, uh, not that I want to spend any, any, like, a lot of time on this, but if you think about how leads are captured too, in most CRMs or, you know, uh, marketing automation platforms, like, you have one lead record per person, right. And we're talking about nonlinear buying, which means that lead can become a lead, you know, move out of the cycle, become a lead again, move out of the cycle. It's very chaotic, nonlinear. And so what happens, technically speaking, is that one record constantly gets overwritten with the new data every time. And you lose so much historical context, I think, um, from. From that vantage point as well. But let's talk about nonlinear buying. Amber, can you shuffle the, um, deck along? So you talk a lot about the gumball machine analogy. Can you tell the audience, John, what that means and how we've conditioned leadership, uh, to think about marketing as a gumball machine?

Speaker C: Yeah, I mean, and it's implicit in what I just talked about, right? The whole idea of working backwards from I need this much revenue, this much pipeline, this many opportunities, Therefore, this many MQLs from there to that means I know I need this much budget, right. That tends to get people thinking that, okay, if I need more revenue or whatever, I can just put more budget in the beginning and I'll get more of the stuff I want out the other side. Right. It literally makes people think of buying and marketing like a gumball machine. And it's seductive. It's nice. Like, we want to think about marketing that way because we don't want to be the arts and crafts function. We want to be like revenue drivers. And if marketing were a gumball machine, that would make everybody's job easier. Right? But it's not right. There are six to 16 people going through a buying process. Much of that buying process is dark and not visible to us as they're talking to peers and doing research. Anonymously now increasingly they're asking their AI agents for advice and information in a way that's not easily tracked by us. And because of all this complexity and you, uh, you alluded to this and I like to talk about it, the simple linear gumball, uh, machine is not the right analogy. This is a complex nonlinear process. And other complex nonlinear processes are the weather and the stock market. And if you study chaos theory, that is the, the study of complex nonlinear processes, many of us have heard about the butterfly effect, you know, a, ah, butterfly flapping a swing in Brazil, causing a hurricane in Japan. Right. That is an example of what happens in a complex nonlinear process. So if you really embrace this idea that buying is also complex and nonlinear, right. That means that we're going to have the butterfly effect happening in marketing. This one conversation that this one person happened to have on a golf course with somebody else turns into a deal two years later in a way that you cannot track or understand. That is the truth, I believe passionately that is how B2B buying is heavily influenced and about these things. And as a result trying to give credit or attribution to. Well, this deal happened because of that one thing. Because you know, they clicked that ad and filled out that form on that one person I think is a fool's errand. You know, it's like trying to pick which butterfly flap caused the hurricane. Not possible.

Speaker B: Yeah, it's this other, this. When we were thinking about chaos theory, I read a lot about you know like quantum physics and, and all of that. And there's this, there's this concept called the attractor pattern which is what you're saying it's all about context. It's like being in the right place at the right time and then this switch happens and usually it's that invisible switch or just a thing that happens that tips the buyer the tipping point. Right. And so yeah, I mean it's very hard to capture that with Last touch attribution or anything like that, which basically forces us to put our money in many of the wrong places and not the right thing, which is brand investment. Curating a, uh, curating the environment to create the context where somebody will want to tip and will want to talk to a seller.

Speaker C: The MQL is the exact wrong thing to measure that.

Speaker B: Mhm. Exactly. We have an example we're going to share in a sec. But I do have a question, John. And what is in your opinion the tell that an MQL obsessed organization is actually breaking? Have you seen any examples of this in, in your World.

Speaker C: We've already referred to some. Right. Sales ignores the MQLs. They're cherry picking the ones that they want using extremely low conversion rates because marketing, sending over stuff that actually truly isn't qualified yet, you know, and then finger pointing, those are all, you know, tells. The finger pointing point is actually an interesting one that's worth at least touching on briefly. Like ultimately, I believe pipeline creation is a team sp. It worked, you know, because it's complex and nonlinear. It works best when marketing and sales and SDRs are working together as a unified team.

Speaker A: Mhm.

Speaker C: Rather than a relay race, baton pass metaphor, I like to talk about the soccer team. Right. Sure. You have forwards and fullbacks and the rest. So there's players playing different positions, but they're passing that ball back and forth. If you follow the path of the ball, it's very nonlinear on its path towards that goal. But at the end, when a goal is scored, sure, yeah, maybe somebody was the one who kicked the ball into the net. But it's the team that scored the goal and it's the team that gets the point on the scoreboard, not any individual function or department.

Speaker B: Absolutely. But I think coming uh, back to just like the way we measure things. Right. And our uh, obsession with these legacy metrics, well, because they're so one dimensional and they don't reflect the chaos that is B2B buying. What ends up happening is that you take a metric to a board and they want to, they want a one dimensional answer for where this deal came from. Right. And so that I think in many ways perpetuates the behavior to claim credit because for much of us, well, that's how we keep our jobs, that's how we defend that. What we're doing is working. So it's like the way we measure needs to evolve. And it's not necessarily, in my opinion, we'll talk about this killing the mql. It's that there are other metrics that can share, you know, how the business is performing.

Speaker C: Agreed.

Speaker B: All right, so we've got a quick example here. Um, I'm going to leave it to you, Amber, to sort of shuffle down as I talk through it. But um, here is, I want to show you an example of this is a company, ah, that on the surface they're, sorry, they're 1,100 million company. They're a CLM software and they were heavily invested in, into sending MQLs, uh, to their sales team to go and work. And so we're going to show you how that looks on the surface and then what was actually happening underneath it. So scroll down, Amber. All right, so first things first. You can see here, this is a volume of prospects. These are the volume of people that sales was working on a quarter over quarter basis.

Speaker A: Right?

Speaker B: So like 25,000 prospects in a quarter. Not atypical. We see that all the time. But look at the percentage coming from person scoring. That is basically a lead that reached a threshold. And they said, marketing said, hey, sales, go work this. Okay? So while it only makes up about 10% of the total, that's still 2000 mqls m per quarter. And that number was growing. And so when you look at just MQLs, you take that to a board and the board says, great, you know, 2K 2000 MQL is a quarter. That's awesome. Marketing. Keep, you know, keep pouring your money into creating MQLs. But what we measured for them was the qualification to pipeline. How many of those MQLs were actually making it out, uh, the other side with an opportunity. Right. You can see here that the MQLS are materially dragging down their overall efficiency to convert, you know, people to deals. And if you look on the right, you can see that the lowest out of all of the different, you know, triggers or why reasons why uh, an SDR would call into a person or an account. Well, the lowest qualification rate came from, um, MQLs. This was sort of news to them. They didn't know that and they didn't know how that compared to some of the other reasons that they were pushing, you know, people into, um, into a sales conversation. All right, let's keep going. Average days to qualify. Well, not surprising, but the ones that came from an MQL took way longer, 6.4x longer in Q1 versus high intent hand raisers. So we're going to come back to this, but one of the reasons why we always say that the hand raiser is the gold standard because they convert way more efficiently. They're ready, they've told us that they're ready with explicit intent to talk to sales. But here's the thing that sort of is like the hidden drain is the average days to actually disqualify them, right? So if you have a low conversion rate, think about the resource drain that it is to go and work those people anyways, right? And so this situation, this company said right away, hey, what if sales just isn't working? These leads, like our first sort of inner first instinct as a marketer is to say, well, maybe sales isn't picking them up. Well, we dug deeper and we said they are and they work them for two months before they disqualify. So right away think about how much wasted potentially time that is calling people when really they could just be nurtured or be, you know, engaged within marketing much, um, more creatively or personally before being passed to sales. So, and so I'm excited to talk about that because I know John, you have some really good ways to think about that. Um, here you can see the volume of those leads that were MQLs that were being disqualified over time. That's an average of 32% quarter over quarter growth in the MQLs that were basically going back into the recycle bin. We'd work them for two months. Great. They disqualified, right high resource burn here. The reason that the majority of those got disqualified in the first place, they were unresponsive, they didn't want to talk to a bdr. We slammed the phones for two months because we thought they were an mql. Great. Nobody responded to us. And then finally just showing you what came out the other side with pipeline. So in the last three quarters you can see that MQL is account for just under 6% of total pipeline created. Um, web forms obviously make make up a much higher, you know, proportion of that. And then going down to closed 1 revenue, uh, MQLs make up about 8% of revenue driven primarily by that little outlier that you can see in Q4, 2025 hand raisers. On the other hand, when you compare the quality of what you're sending to sales and what actually results in revenue, well, they qualify 6.5% faster and with an 83x higher conversion, um, and account for, you know, 39% of total close one revenue. So not surprising. I think in marketing we all want to strive for the high intent, uh, hand raisers and push those through to sales. But this is just meant to illustrate the resource strain, the inefficiency that just creating MQLs for the sake of hitting a target, uh, creates for your, for your company. It costs you time, um, it costs you, you know, your attention and all of these other things to produce very, very little. So with that said, any thoughts on that, John, before we jump to some of your like, you know, recommendations for how to circumvent this kind of stuff.

Speaker C: I think we'll get to all the points I want to make when we get to that. So.

Speaker B: Awesome. Great. Well, hopefully that was a good example. I'm sure a lot of this really relates to uh, what you're all feeling this company specifically just for some context. Well one, they, they didn't really have this visibility to, to know that MQLs were this efficient, inefficient for them. And two, um, a lot of pressure coming from leadership as well. Right. Legacy metric MQL were wired to push for more volume from marketing and so this really changed how they went to market. They actually just recently um, stopped sending any MQLs to uh, sales whatsoever. Totally reorchestrating what they actually do with those MQLs to um, you know, nurture them. So that brings us here, lead tiers. You recently put this on LinkedIn, John. Right. So we have three tiers of leads. I'd love if you could walk us through what these mean.

Speaker C: Yeah. And just to call it the, the typo, the left hand one obviously should say tier one.

Speaker B: Oh yeah, my bad.

Speaker C: We'll fix that because I think what Tier 1 is what Omer just threw into the chat. Right. Like and your, and your client did here. Like, like many companies, you know, as they throw out the MQL have only said we're only going to focus on hand raisers and of course we're focusing on hand raisers because you know, those are by far going to be the best.

Speaker B: Mhm. I think.

Speaker C: So let's all just 100% agree. Hand raisers are a really good thing and they should be the top tier that we want to focus on. The problem is I think that that over corrects, um, first off, it's a little bit to me too passive. It says that we only wait around until somebody decides to come to us, which is very buyer centric. But it relates to the second problem which is it's arguably too late. 6 Sense has done a lot of really good research on this. They found that 94% of buyers are putting their short list together before they ever fill out the form and say contact sales. And 95% of buyers are buying from that short list. Six Sense also has found out that most of the time there's a first choice and a second choice who are the first ones contacted and the most likely to win. So if we are sitting around and waiting until somebody raises their hand, they've already formed their preferences and we're competing for a spot that on a short list that probably built without us. And then perhaps most importantly, waiting only for the hand raisers forfeits the first mover advantage. Michael Bosworth, who wrote Solution Selling a classic, found that, you know, if you can engage the buyer while the pain is still latent you actually have a 90% chance of winning when you actually bring that account and that account actually goes to an active evaluation. So there, there is value to reaching out to people who are not yet hand raisers. The nuance is in how do you do it? So, so that's why I introduced these other two tiers, what I call Mark, you know, MQX or M& Mex. So first, just to note on terminology, to me the X is sort of waving my hand at the fact that we probably shouldn't be talking about leads. Right. I prefer buying groups and accounts. So whether you call it an MQBG M or just a qbg, um, or an mqa, these are evidence that, you know, you have reason to believe that this account might be in a buying cycle. You know, I don't know if we have time to get into this webinar, but I'd say as a rule of thumb, if there's at least a 10% chance that the account might be in a buying cycle, it's probably worth reaching out. I'll leave it at that for now. And then the nex, this represents your future pipeline. This represents the deals that you would like to sell to in the future. There's no reason to believe they're in market now. They're the 95% passive buyers. If you just reach out to them and say, hey, would you like a demo? Would you like a meeting? You're going to burn the bridge.

Speaker A: Mhm.

Speaker C: That's not good for anybody. This is where you actually reach out and build a relationship over time. The act of doing this feels a lot more like brand building than it does demand generation. Um, these touches might pay off if you do them well, six months from now, two years from now, which somebody in the chat alluded to this, that makes it hard for sales to take care of reaching out to the, to the tier threes. Because if your typical SDR is only in the job for a year, they may never even see the pipeline from the deals that they're reaching out to, you know, in that last touch. So why would they do it? So I think organizationally we need to think about, you know, whose job is it to develop and nurture those tier 3 accounts? Doesn't mean that it's not something that's worth measuring and tracking and driving. It just may not fall into our traditional marketing and sales boundaries. The last point I'll make here on this framework, which is I think a really important one when you're deciding whether or not to reach out to an account or a person. You have to take into account the marginal relationship between the cost of a false positive versus the cost of a false negative. What I mean by that is a false negative is I did not reach out to somebody who was actually in market, you know, and I potentially lost out on a deal. A false positive is I did reach out to somebody who wasn't in market. And you want to sort of balance those costs against each other. But the part that most people don't think about that I think is so critical is the cost of that false positive has a lot to do with. It's not just the time of your SDR doing it. It's the reputation and brand damage that a bad outreach can cost you. Them hitting the spam button or opting out or just being annoyed, you know, and whereas a really great outreach, you know, that's useful and valuable and educational brings the cost of that false positive way down because it's actually, it's almost negative because you're building, you know, contacts and relationship over time. So that quality of the outreach on your tiers, twos and tier threes is to me more important than hitting any volume, games or numbers.

Speaker B: I love that when I'm hearing you say this. This is definitely a different playbook, though. It's a long game, right? Like, we're focused on relationship building, educating, trust building, staying top of mind for that customer for when they are ready, that we are the preferred option. But how do you shift the mentality, though, at the board level, at the leadership level, when, like, this is not how leadership is thinking about marketing? We think of marketing as a gumball machine or a slot machine. Put the dollars in, pull the lever, you get the outcome. Like, how do you convince leadership to play the long game?

Speaker C: I, first off, I do not want to minimize the challenge. It's hard. We spend years teaching them it's one way and now we're trying to educate them it's another way. It's part of the reason I'm so vocal about the change, because I'm trying to create air for as many marketers as possible. But if you're in the seat and you're at a company and you need to convince people that we need to sort of change how we measure. The best tactic that I've come across is to kind of approach it socratically. Go to that cfo, for example, and ask them about, you know, the recent, you know, HR system that they just purchased or, you know, what, whatever new thing, that recent thing that they actually bought. And asked them like, well, did you buy that thing because you attended a webinar downloaded in an ebook? How did you first hear about that company? What shaped your opinions about that company? And I think the more you ask them about their buying process and their more their journey, I think the more they'll realize that the traditional ways that they're asking you to measure their marketing doesn't match the reality of the way that they understand buying to actually work. And if you can get a meeting of minds about that, then you're in a position to say, okay, so what should we track? And by the way, you know, bring something like this, three tiers to the table. Like, I have a point of view maybe that this would be a better approach. You know, we'll show some other metrics, I think on the next slide. But trying to do it Socratically rather than just coming to them saying, we're not measuring MQLs anymore suck it, uh, is probably not the right answer.

Speaker B: Yeah, I agree. And I would never recommend either. Like, just throwing away MQLs is as much as many of us don't want to use them because we find them so destructive. Right. Like you're. These metrics are hardwired. They're deeply ingrained at a very deep level with leadership with boards, because it's what we know, it's what we've been taught, it's what's been institutionalized. And so I love the idea of layering in new metrics as well. But one thing, and speaking of new metrics, the one thing that I, uh, usually find really profound is when you can actually look back and see what's happening upstream before pipeline creation. When you can really look and say, okay, here's how long on average our buyers are like in our metaverse, poking around, engaging with our brand, engaging with our events and content and all this stuff. When you can actually quantify that and say, guys, this is like a 300 day journey. It's not a two week thing. Right. I think quantifying that with data helps a lot in terms of setting expectations just around what the buying journey actually looks like in reality. Here we have a, what I would consider like a KPI cheat sheet. You might call it something else. John. But this came from John. We added in some of our own Passetto metrics as well, and we can't go through all of them. Um, I'd love to talk about, you know, a couple that are really important to us at Passetto, but John, what would you, you know, if you have to Focus on a couple of these. What would you say are the most impactful KPIs that you know, every marketing leader should consider bringing up to leadership?

Speaker C: Well, I think first, you know, brand is important as we sort of talked about. That's a very brief story to illustrate that. So I work with a company called Illumio, which is a cybersecurity company. You know, their positioning in the marketplace is called contain the breach. Right. A point of view that like there will be a breach. It's going to happen. The cybersecurity hackers are just going to get better and better. You need to be prepared when that happens. So contain the breach. That is their unique positioning in the marketplace. Their CMO has convinced the CEO and the rest of the executive team that one of the most important metrics they can track is do CISOs think about breach containment? Because they know if CISOs care about breach containment, then Allumio is going to be well positioned. So he runs a quarterly survey to CISOs asking them and measuring that metric over time. And his board cares about that metric because they understand how important it is. So surveys are still the best way to measure brand. They don't have to be super expensive. The key is to make sure you're measuring the key question that matters for your business. On pipeline, I really want to call your point the attention to the third one down from the top. Total new pipeline. In a world where you believe in nonlinear buying and in the butterfly theory, you don't try to assign credit to marketing pipeline versus sales pipeline. You only focus on the total pipeline. Um, just like you only have one score on the soccer team. Um, and then lastly on the right hand side, I think way too many marketers have only focused on net new business and yet so much revenue for so many companies happens over time in subscriptions from our existing customers. We have got to focus our marketing metrics on post sale things as well as the, the, the top of the, you know, new customers.

Speaker B: Oh, I think that's so important. In fact any uh, in most audits that we do epicetto, when we look at like total ARR and where that's coming from, the biggest lever that a company can pull is usually fixing their churn problem. And when you even dig in deeper sometimes you see that marketing isn't even touching those accounts, uh, isn't even touching your renewal opportunity. And so I quite love that. I think we totally overcompensate in many ways on new logo growth when there's just so much leverage, um, with our account base or our customer base that gets overlooked. Um, I think a lot of people here I'm seeing in the chat like really want to understand how to go about calculating these metrics. So maybe even a part two of a workshop where we can actually put pen to paper and do some of that. So leave that with us and we'll see what we can drum up. Two things that really stand out to me and we talked about this a little bit. John is just like on the pipeline column there m thinking about pipeline velocity I don't think and all pipeline is created equal. You have a lot of different deal types, some that convert uh to a customer much faster. Uh, there are larger opportunities, uh, better win rates. And so sometimes we see you know marketing really pouring their budget into things that might look good on paper at a surface level like product trials. Right. They contribute high level of deal deal volume to pipeline. But when you actually look at the other side, well you might feel, you might see that you know those take two, three times as long to close. They're half the size of our other average deal sizes. And so I think for a marketing leader to be really strategic in understanding where their levers are in terms of like quality of pipeline. I um, think that there's just so much important stuff uh, that can be measured there.

Speaker C: Agreed.

Speaker B: So what does this mean for mar for your martech stack? I forgot actually we dropped this in here. But I would love to hear from you John because I know you are evolving uh what you're doing in the market with AI and everything on the scene. So how should we, how should we adapt as marketers in terms of our tech?

Speaker C: I'll briefly touch base on this. I mean and the short answer is I really do think marketo and the other marketing automation platforms are not prepared for this new world. They are still MQL generating machines that are optimized for somebody filling out a form to becoming an opportunity. And if you're thinking about how do I move M beyond MQLs, how do I move into the AI age? You know I think you do need to be thinking about, you know is you know what other platforms out there including perhaps the one I'm building the couple quick considerations I'll just plan for you besides you know, just obviously being AI native. First it cannot be just a lead based system. It has to understand accounts and buying groups, you know as well as just leads. Second, it needs to be able to think about the entire customer journey before somebody fills out a form to when they're post sale. You know and beyond. And then lastly, you know, the more of those things you take into account, the more rules fall down and the more we need AI to reason how to orchestrate each customer's journey. I'd love to do a whole other conversation purely about what the future Martech Stack looks like, but that's a good starter for now.

Speaker B: Amazing. Yeah, I think the whole buying group account based approach is very applicable. I strongly agree, we at Pasetto strongly agree that it can't be lead based. There's just so much more nuance. Okay, one more slide and then we're going to shift over to Q and A. So one thing that we like to offer, one thing that we want to offer you guys here in our audience is if you are all here and you're thinking, man, this is just, you know, so applicable to what we're facing in our own organization. So what we're doing is we're opening a small number of sessions, um, to a select few, um, here. And we want you to definitely go apply if you think it's a fit. But a lot of what people want to do is sort of like jump to the conclusion and how we're going to fix this. It could be highly technical. And so what, you know, our perspective is is that a lot of these KPIs we shared with you today and we just had on the previous slide, those are already there in your data. And so it's really just surfacing it in the way that you need to get your hands on in the format that you know, your leadership wants to see. So we do a small number of one to one working sessions. They're one hour, um, with core members of your GTM team, um, where we actually give you a revenue visibility score. It's a quantifiable third party validated score. And then we help you understand why you can't answer some of these questions and help you chart a path forward so that you're not just jumping into the solution. You sort of understand why you are where you are and what it would take to, you know, do something different. So if you want to do that, these spots are going to fill up super fast. Anytime we do this, they always do, um, and we're only doing a few limited, uh, number of them. So if you want to do this, uh, you can go to pasetto.com forward/working session, fill out that form. It's a little bit of an application process, it doesn't take long. But if um, that interests you, we'd love to sit down with you, that would be the, uh, Pesetto team and, you know, help you solve this problem. It's why we exist. So with that said, um, this has been a great session and I know that there's been a lot of Q and A. Not sure if we'll get to it all, um, but if we want to pull that open, open. Amber, um, can you, uh, can you, you know, relay some of that to John?

Speaker A: Yes, of course. I think, John, you, you answered a lot of these as, you know, they're coming in. But real quick, John, you have, um, a landing page as well. Do you want to tell the attendees about that?

Speaker C: About Fave? I mean.

Speaker A: Yes.

Speaker C: I mean, I've given some hints. Right. You know, ultimately we are reimagining the marketing automation category for the AI future. Um, so if your market automation renewal is coming up anytime in the next six or seven months and you want to consider what the new, you know, what else is out there as a new option, then throw out a form fill on our site and we'll follow up.

Speaker A: Awesome. And that's fave P, H A V E. You can put it in the chat. Okay, great. So I think the common question, um, that we have time for here in two minutes is really around, how are you? Maybe it is another, you know, session and the nitty gritty around, how are you measuring and what signals are you really pulling in and from where? Around engagement. Uh, I think there's the question around at the account level. What are you tracking and how are you doing that? Is it all coming into the CRM or, um, maybe fave, you know, would have a, ah, role to play in this in the future. And then also buying committee, like, where, where's that information coming from?

Speaker C: So those are both really good, important questions. Um, so first answer is, you know, yes, most of the engagement signals happen at the person visiting a website, opening an email, attending an event or something like that. And you do need a platform that can roll that up at the account and the buying group level. Fave would be one of those. But there are other signals that happen at the account level. Right. People visit the website, but they're anonymous. You don't know who they are yet. You can figure out what company they work for. Usually depending if they're in the U.S. maybe you can use technology to figure out who they might be, but you can usually at least match it to the company. So that's additional engagement signals at the account level. Also, if you're using third party intent data from G2 or any of the ABM vendors, that's typically data at the account vendor. So you want something that can bring those together, score it, and then aggregate it at the right level. Now, when I say scoring, traditionally that means points. If they open the email, add one point. If they hit the website, add two points. That's fine. But also to my general point about AI moving from rules to reasoning, I'm more excited about the opportunity for AI, uh, to look at all that engagement activity together at the person and at the account, at the buying group. And they have AI determine, hey, is this hot or not? Should this be an MQX or not? The models are pretty sophisticated in their ability to do that today in terms of the buying groups. Almost every company doing buying groups today is using the Opportunity object to track it. And so effectively you're scoring the opportunity. You can create opportunity stages that exist before sales opportunity and then measure them accordingly. There are vendors out there, including Demand Based, Mild Company and Lean Data, that can help you to sort of try to map people in your database to the right contact roles. That's all important work to do if you're really going to embrace the buying group. But at a minimum, using the Opportunity object is a good way to start tracking.

Speaker A: Yes, absolutely. That aligns with exactly what we recommend as well around getting those contacts in your CRM so that you can associate them with opportunity. And it is amazing how much simpler it is to do that in 2026 than it used to be via, uh, some of those amazing tools that are out there to automate that for you. So thanks for dropping those very tactical insight, John. All right, I think that that's it,

Speaker B: but we have a lot of other questions.

Speaker A: I know John is always, uh, very active on LinkedIn as well as Carolyn is. So look out for them on LinkedIn and, you know, perhaps they'll create some content or we can get John back on to dig into some more of these nitty, gritty, gritty questions. Thanks everyone for the engagement. It's great to see you and have you here and thank you so much, John and Carolyn, for the amazing workshop today.

Speaker B: Amazing. Thanks everybody. We had such a good turnout. Appreciate you all being here. But most importantly, John, thanks so much for, for sparing, you know, an hour of your day and being here.

Speaker C: Happy to chat is obviously I filled up a lot of the time and we ran into the end, but that's because I'm passionate about this stuff.

Speaker B: Love it. Awesome, guys. Thank you. Great. Well, uh, thanks for being here, everybody. See you next time. Sam.