← The Dave Gerhardt Show (from Exit Five)
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- [00:00]
A
Email, in my humble opinion, is still the greatest marketing channel of all time. It's the only way you can truly own your audience today. But when it comes to building those emails, well, if you've ever tried building an email in an enterprise marketing automation platform, you know just how painful that can be. I won't name names, but templates get too rigid. Editing code can break things and the whole process just takes forever when it shouldn't. That's why we love knack here at exit 5. Knack is a no code email platform that makes it easy to create on brand high performance, forming emails without the bottlenecks. If you're frustrated by clunky email builders, you need nac. If you're tired of hoping the email you sent looks good across all devices, just test it in NAC first. And if you're a big team that's making it hard to collaborate and get approvals on your email, you definitely need nac. The best part, everything takes a fraction of the time. You can see Knack in action@knack.com exit5. That's knock.com exit5. Or just let them know you heard about Knack from exit5. That's us. You're listening to B2B Marketing with me, Dave Gerhardt.
- [01:21]
B
1, 2, 3, 4, exit.
- [01:26]
A
Hey, it's me, Dave. Just quick intro before we get into this thing. I was still on the injured list with my hip. Hip surgery. Told you all about it. Whatever. This is a live session that we did with our team here. And in this one, Jess Lytle, who runs our marketing team here, she was with Morgan Cole, VP at Demand Gen at Red Canary, Lisa Cole, CMO from 2X and Jean Cameron, Senior Director of Field and Partner Marketing at Demandbase. And they had a great conversation about how they are actually using AI to drive revenue. Right now our biggest thing with Exit 5 is to help you separate the signal from the noise. And so our goal is to give you real conversations with real marketers about how they're actually using AI. This conversation, instead of it being traditionally focused on content or social, we try to really focus on revenue and pipeline generation and hear how teams are using AI in that motion. So you're going to enjoy this session. If you care about demand gen marketing ops, revenue and finding new ways to drive growth with AI. Shout out to Jess doing a great job as the host, holding it down. Here's this session.
- [02:28]
C
Welcome everyone. If you, if you haven't been to one of the Exit 5 Live sessions before, we have these twice a month and we like to keep the conversation pretty real and tactical and helpful. So today we're talking about the future of pipeline, how marketing leaders are using AI to drive revenue. And again, we like to call them live sessions. Really not, not webinars. I feel like the word webinar kind of makes people want to like do something else. So don't fold laundry, just be here, interact in the chat. There's usually a lot of like fun activity in the chat. I'll be pulling questions from there throughout and just hosting and then we'll do a Q and A before we wrap. So before I introduce the rest of the panel here, who is waiting patiently backstage, I'm going to do a quick ad read from our sponsor Demand Base, who really makes this all possible. So thank you so much to our sponsor who make these live sessions possible for us. So here we go. If you're in B2B marketing, you already know demand based. They're really the only pipeline AI platform that's built to help go to market teams drive revenue, not just activity. So they really give you kind of a unified zoomed out view of all of your data, all of your insights, actions, your outcomes so that marketing and sales are kind of operating off the same playbook, which is ideal. Thousands of companies are using demand based, they're tightening up their icp, they're understanding which accounts are truly in market, seeing what those accounts actually care about and then activating those across every channel without wasting spend. So it's great so you get all those intent signals, account insights targeting all of that orchestration in one place so your programs actually line up with revenue instead of vanity metrics. So great. Let's get the rest of the panel to join. Like magic. I just say things, it happens. I also like to include a quick poll at the end of anyone who thinks my background is fake or real. Let's see who gets that right. We have everyone here, so quick intro on myself and then I'll pass it to Jean Morgan Cole and Lisa Cole. Quick intro to me. I'm Jess Lytle. I am the head of marketing here at Exit 5. I've been in the B2B marketing world for about 14 years. I was most recently director of Demand gen in vertical SaaS. So trust me, I felt the pipeline pressure. It is not theoretical for me. So I'm excited about this conversation.
- [04:55]
D
Hi everyone, I'm Jean Cameron, Senior Director of Partner and Field Marketing at Demandbase. Thanks Everybody for joining. 20 years of B2B SaaS marketing have lived through it all. Has Struggled through it all, loving that AI is making my life easier and excited to be here and talk to everybody today.
- [05:13]
B
Hi everyone. I'm Morgan Cole. I run demand generation at Red Canary, which is now part of zscaler. And I own the go to market. I really focus on aligning our go to market motion across sales and partner and product and marketing. So my point of view is pretty simple. I think the belief system that I operate from is that AI isn't the answer on its own. Alignment is. And so I think AI is accelerating whatever truth already exists in your go to market motion. So I'm excited to dig into that with all of you here today.
- [05:50]
E
Hi everyone. I guess I'm the other part of this Cole world party going on here. I'm Lisa Cole. I'm the chief Marketing, Product and AI Officer for 2x 2x is a global B2B marketing subscription services firm that we focus on helping marketers scale impact without costs. My role is unique in the sense that when you think about the marketing resource paradox and trying to solve for that, I lead our own building awareness for this unique model. But I'm also shaping the new service offerings that solve the emerging challenges that marketing leaders are dealing with. But of course we can't reimagine marketing or what the next generation of marketing needs to look like without AI. And so how do you accelerate AI adoption in such a way that we're leading the rewrite of marketing rather than waiting for AI to disrupt us? So I have a super cool role. I get to work with marketers all day and my background about 25 years in marketing, I'm a four time CMO. The first time, the first three times I was on the hook for transforming marketing from these wildly underappreciated and overworked disjointed marketing functions into growth engine. That always meant marketing was going on the hook for a number. And so this topic around pipeline and driving alignment across the go to market function to accelerate pipeline growth and do so in a way that's sustainable is near and dear to my heart.
- [07:25]
C
Love it. I feel like if you are a CMO right now, marketing leadership right now, you're really kind of facing what talking to somebody about like the great kind of structural dilemma of modern marketing where we're being asked for measurable revenue growth but the capacity that we have on our teams is stretched in maybe you've got frozen, fixed headcount. So I think especially enterprise marketing teams have like historically how they've historically organized themselves and that traditional model is just like not really fitting this purpose anymore. And I think, like, right in a market, not in a market where speed, agility is everything. And it is really kind of a profound challenge. And it really forces us to ask a little bit, how are. How do we scale output without scaling fixed costs, without additional capital? And the title of the session, the Future of Pipeline, the reason why we framed it that way is because, like you just said, like these. The game has changed. Right. Marketing leaders aren't struggling to generate leads anymore, that old kind of traditional MQL model. The real pressure is moving into pipeline and revenue and doing it fast and doing it without more headcount or more capital investment. So it's kind of really forcing marketing to. What I've experienced too in the past is kind of spend money first, diagnose problems later, when marketing can only explain performance after the quarter's over is really kind of forcing us to be in a defensive position, all of this. So, you know, I think that's where the future is changing, you know, so.
- [08:54]
E
Yeah, but, you know, it's interesting, like, the constraints that we've been dealing with, those absolutely can turn. Those can be the very things that free us of, like, traditional operating models and actually might enable us to become the growth drivers again. Like, rather than be making, you know, doers of things for the organization that just never keep up with all the stuff we've got to get done. I think those pressures are the very things that are going to free us.
- [09:23]
C
Yeah, I totally agree. I feel like when you zoom out a little bit, a lot of this comes down to timing too. A part of this. Right. And we can't afford to wait until end of quarter or post mortems to really find out who was actually ready to buy. And AI gives us that ability to kind of spot that and spot that intent earlier. Like, hey, this account we're seeing, these signals are waking up, they're signaling intent.
- [09:48]
D
And.
- [09:48]
C
And we know there's only a very small percentage of buyers with 5% or less who are actually in market ready to buy. So if we were to start there, I'd love to hear from the panel here and folks in the chat too would love to get your questions connected to this. And I think this is pretty top of mind for a lot of folks. But how are you guys using or seeing marketing leaders kind of using AI and data to identify those in market buyers earlier?
- [10:18]
B
Yeah, I don't think that this process is new, actually. I think this evolution has been happening for a long time. AI has to be accelerating it. But the age old you have 20% less budget, no additional headcount, and a 20% growth target has been happening for many, many years at this point. And so when you're a leader that has an organization that you want to motivate, that's not an easy thing to do behind that, especially knowing that you have that line of diminishing return on their output. So, so I think AI has come in to help. And again, back to the alignment piece. The first place that I think you have the greatest impact is to actually find alignment with your go to market team on your ICP and accounts. And this is tried and true and it works, I promise you if you can find the right accounts that convert at a higher rate, that convert faster through your funnel based on intelligence and signals, there are platforms and tools out there that can help you do this. So if you need help identifying your icp, especially a dynamic one, if your product changes quickly, ours doesn't. So it's pretty stagnant. We're okay to leave our ICP alone for a while. But having that dynamic feature and then aligning your go to market team behind it is maybe one of the single best cases to drive the needle. And here's the magic of it. If you can get alignment with your team, with your sales leaders, your marketing leaders and your product leaders behind a finite list of accounts, we target all of our marketing spend all of our sales attention to those accounts and we use our product to underpin what problems we're solving. There vastly changes the game in your ROI and how you can get that return. So, so that would be where I would start. If we're giving very distinct examples of how we're utilizing it today from our perspective.
- [12:13]
E
I'd love to piggyback on that. So you hit on the problems piece. We look for three layers of signal, but the very first layer is around some sort of business change or catalyst or problem that would likely drive an organization or a team to actually start looking for a solution, a problem to solve. And so for us at 2x that looks like new leadership changes. It could be strategy announcements. You know, strategy shifts of an acquisition that somebody makes invests in a product launch. Like anything that would prompt a purchasing like I need to find a solve a problem. The second, and this is where tools like Demand Base and six Sense and others, that's where the AI driven intent comes in. At least it helps us like find out well which 5% is actually in the market searching for solutions and what are they searching for? Solutions around like what are the themes that they're searching for? And then, and this is one thing we really kind of had to figure out was all right, we've got business change and you can use AI to track major changes like that that would prompt a, you know, a need. The second, you've got platforms that can do this, this intent. But the third is our own first party behavior, right? The stuff that we used to call MQLs like the clicking, what content are they consuming, how are they engaging with us in events like this or in communities or how do you take those three? And what we have figured out is that when you've got the those three together, that's our version of in market alert where we likely would have a greater chance of winning. So it's not just any signals, it's like the, the presence of all three. You've got those three double down on that and that's likely going to get you to them before they pick their preferred vendor.
- [14:06]
C
So are you seeing teams kind of acting on those early signals and that that AI is surfacing kind of before a buyer even kind of comes in, declares themselves as high intent like before they come inbound?
- [14:17]
E
Essentially if you get those three types of signals to together related to an account, you can then make a decision on whether it's marketing is engaging in a more meaningful way. An sdr, AI, SDR or even your field sales. But like you are you looking for the. Almost like the alignment of those three layers of signals is an indication of you need to act on this. So this is kind of like the three signals work together almost like the old way we used to think about MQLs. When's the time to have a human or someone engaged in a meaningful way?
- [14:51]
D
I'll kind of chime in with, I get to be spoiled because at Demandbase we obviously have the tool that does it. So I get to talk to our customers and prospects all the time around what you could be doing or what you are doing. So not just detecting like declared intent because we've been doing, I mean that was kind of 10 years ago saying like oh, they are a company of this size in this industry with your firmographic, your technographic data that's going to be likely to buy because that's what our customers look like. But now we get to measure behavioral data and emerging intent by seeing like product usage. We get to see competitive, competitive intent because it's the engagement in your emails, your ads, your content. I mean obviously first party with your website, third party activity, go A level deeper where we, especially with our customers, talk about the buying group activity and buying group engagement, because that's one of the biggest things is one person can click and be in your like looking at your ads and consuming your content. But if you've got three or more people from the same company doing that, that's like massive engagement and a massive signal of like they're likely to buy, they're looking at something. And so I think when we can put all of that together with the technographic, with the firmographic data, we see our customers being like, here's our finite list, like what you said, Jess. And we're gonna put all of our marketing power into that and all of our sales power. And ROI is explosive with these customers that can do this.
- [16:18]
E
Love that you brought that up. This is where MQLs can get super dangerous, right? Because when think of an mql, it's based on a person. A person has done a thing. We send it across to sales. I've actually been, I've surfaced an account where I think it was 27 different influencers had all been engaging with our content on a theme. This was before 2x, so sent it across to our sales. Of course they went across as 27 MQLs because the sales reps are like, oh, this is all the same account. I'm going to reject like all these MQLs. I'll keep one. It created this infrastructure that rendered that amazing buying committee engagement around the same topic invisible. And it was like disqualified. You're like, wait, this should have been the thing that you doubled down on 27 people all on a similar topic from the same account. That's gold. Like that dual model made it like bad. It was crazy dynamics. But yeah, yeah, gold.
- [17:21]
B
Using this decision, we surface this at that level now too. We use our field marketers to actually do account level insights that say, look at this buying committee interaction. And what I love about it is whenever we do have that event run or a webinar or whatever, live event, Jeff we'll call it. But whenever you have that engagement from multiple people within an account, it's actually how we do our dispositioning across real human led versus AI. So if there's a group, a conglomerate within our list of accounts, that's ripe for our follow up of our sales team to actually go to that multitude of people within a buying account. So we actually use that as an indicator to say, okay, this is where we're going to do human first outreach versus AI first outreach via our other tech and tools. And the other point I wanted to also mention because it's just I think the signal piece that you both touched on is so critical. The other thing that I think also helps grease the wheels is you have this brand build that's happening too before some of these intent signals even occur when you do have spend against the finite lists. So often there's these accounts that are not in any signal or not in anywhere in any type of buying motion today. But you can choose to spend dollars in a finite capacity against accounts that you know are a high connection or a high propensity to convert with your business for future pipeline build. I'm talking like two plus quarters out. And that is the magical predictor of pipeline growth is if you can get your leadership team on board with the right metrics and that it is a pipeline, a predictable pipeline growth engine for you for future.
- [19:06]
E
I love that.
- [19:07]
C
Is that like we're talking about predictive analytics now, right? Where you could kind of tell which accounts like you said are just are showing that engagement week over week. Maybe they're all researching multiple folks from the same account. So the one it's giving us the predictability. Are you guys then taking that to your leadership team to say, hey, like statistically these folks are three times more likely to become opportunities. Are you connecting it and attributing it through having this model? Is it, is it easier, I guess to sell the value of that because of those, those analytics kind of showing that predictability so your forecast is more accurate?
- [19:46]
B
Yeah, definitely. I'll touch on it really quick. We do dissection of a deal. So we apply the analytics on three folds of the business. One is dissection of a closed loss deal. So why are we losing deals? Dissection of a closed one deal. So I'm not talking about attribution here. I'm talking about signals throughout the progression of an account and an opportunity like top awareness all the way down to closed one or closed loss. What does that look like? Where are the points of engagement? What does that tell us about our signaling across the board? And leveling that data up, I think is a huge predictor of saying, okay, here's where we can have influence when we work together and have alignment on messaging and how we're selling versus not. The other thing we do is a dissection of a churn deal. So why are we losing them? And we do that on a quarterly basis. Again using. We are working hard to use AI to unlock this at a higher level. It's pretty manual and at this point, anything that's manual is the bane of my existence. It feels like we can just fix it somehow. So it's like, how do we use our people to actually help elevate the strategy, distribute the strategy, do it better, but then take some of the heavy lifting of all of this data like clunkiness off of our plates and make it really automated.
- [21:00]
E
So that's a real value of AI, right? AI is great with unstructured data. And in the context that you were just talking about, a lot of the secret sauce, so to speak, lies in that unstructured data. Like the sales call if you're on Gong or you have Apollo and you get unstructured data, that might be the transcripts from the different selling interactions that they might have had across that whole buying journey. What we have found within that is that for us, when we win deals, it's not just the presence of multiple influencers within that organization that have been engaging. It's also we, we see a presence of. I heard about you from so and so in this community. Oh, this analyst happened to mention you. Oh, and I, I went to Gemini or I did a quick chatgpt search and it referenced you in the context. It cited you in the context. And so we actually see a presence of multiple mentions and references in the unstructured data that we wouldn't as marketers seen without AI actually reviewing all of this gold that's just sitting around us now, which is amazing.
- [22:12]
C
Gene, did you have something to, to add to that? I thought I saw you saying something.
- [22:17]
D
But yeah, I mean, second, no, I second what Morgan and Lisa are saying as well. And I think, you know, we do a lot of lookalikes. So we take our closed one deals, we take our current customer base, we see what companies are very similar. We score them so they get a zero to a hundred and if they're higher in our prediction scores of like this is most likely going to convert. And this is outside of intent, this is outside of activity that they've been doing. This is just any cold company that just hasn't heard of us. So we score them from 1 or 0 to 100 and if they're in the top, we put money into it. If they're in like a middle layer, we'll put some funding, but not much. They're a lower level. We just don't really care because they don't look like anything that's going to buy. And so we do try to go after cold accounts for future pipeline. Could be nine months from now it could be 12 months from now, but they're going to eventually hear, they're going to eventually become a customer because we can, we've built a model where it can predict who's most likely going to buy us.
- [23:15]
C
Are there specific signals? And we might have touched on this, but I just want to highlight it again, like anything specific, like signals or behaviors that have turned out to be the most effective for predicting like, that you're seeing.
- [23:30]
D
Oh, that's a good question. I mean, a big one is competitive intelligence.
- [23:35]
B
Right.
- [23:35]
D
So if they're going to searching like, yeah, like a G2 or they're looking at like comparison pages, you're just like, okay, got some major intent to purchase. But you may not know about us, you may know about our competitors. And so that's a brand issue that we may have. And so how do we get out to those groups of folks? So we've got an entire orchestration and automation for anyone that falls into that category. So I think for us it's, you know, a big thing is looking at our competitors and what they're doing.
- [24:04]
B
Yeah.
- [24:04]
E
And for us, it's the combination of the, like, you see alignment between those three different types of signals, for sure. It's almost like it gives you what is the context for their search. And it also likely surfaces whatever mandate that committee is that's doing the searching, it's likely surfacing that too as well. So the things you might use to shape your ICP and identify those accounts and lookalike accounts. For us, it oftentimes is the presence of some of those mandates. You know, you'd see companies that experience certain performance or pressure points or they're at a certain size ready to scale up to the next level. And you'd see that in that data too, as predictor. But it's the presence for us.
- [24:51]
C
Yeah, I'm sure once you kind of bring that, the tools and that predictive analytics into the mix, you start to kind of see also that not all of the engagement is important to look at. It's not created equally. Right. The AI can probably sift through thousands of journeys and kind of start to identify the exact, exact pattern of behaviors that is really consistent, which kind of would give us those signals that really us as humans could not be able to detect like that, that quickly in real time. And I think that that's where really marketing starts to shift from being more reactive in our reporting and in our decision making to more proactive because we're really focusing on the signals that matter. We can, we can predict those we could forecast more accurately. And then we could deploy our sales team or BDR teams or resources more strategically in real time versus trying to like readjust for the next quarter based on the learnings. You could kind of stop it in real time and make adjustments mid quarter, make changes.
- [25:47]
E
Eloqua used to have this amazing book called Digital Body Language. Not sure if you. I think it's digital body Language and it would, it was training marketers how to look for these digital breadcrumbs. The challenge was there were so many of them that we only use them after something had happened as a way to justify our attribution. Like, you know, it just happened. It. We went. We could go backwards and say, look, the, you know, the presence of these digital breadcrumbs, this body, this digital body language, that's why they bought from us. And it justifies all the spend now with AI, we can use it to be more predictive and we can use it to direct where our investments are versus an after the fact confirmation. Like, oh yeah, I totally had that. Right.
- [26:29]
C
Like, no, no, right, right thing. So yeah, I think it also positions us better in our conversations with our CEOs and CFOs for budgeting and requesting capital and justifying that spend too, because we have real clarity on. We're speaking their language and then they understand that. So maybe it's not as hard to defend.
- [26:52]
B
I think that's a huge unlock. I think that we're on the precipice of this. It's like pattern intelligence where we're not talking about pipeline generation tactics and channels anymore, but our ability to look at those breadcrumbs or the patterns across the life cycle and remove the latency of like, here's what impacted this in the future. It's more, you know, how are we unlocking this today? How are we experimenting and failing faster? Like using AI to actually understand what's not working and then implementing that I think is a huge element. And I don't know if you're feeling this too, Lisa and Jean, but a lot of. I'm already seeing this collapse of tech and tools. Like now with the introduction of AI, there's so many tools that used to have independence in our tech stack. They served a very specific purpose and all of them are starting to introduce some of the same things. So how are we consolidating that to get to intelligence faster is something that's hugely top of mind for me and my team right now.
- [27:55]
E
Well, one of the things that used to keep us from Getting a real payback on our tech, right? So look, I used to have tech stacks that rivaled the budget of my CIO in past lives, right. But what was like kept us from actually realizing the full potential of that stuff was this swivel chair syndrome. You know, data as it moves from one tech to another and being able to have that holistic picture to make smarter decisions rather than just justify our existence after. Well, AI in and of itself could be the glue between this technology eliminating that swivel chair so we can get there faster. What that looks like in three to five years relates to the number of tech that we have in our tech stacks. I don't, I suspect we're not going to have fewer technologies. Anyone that's got multiple AI licenses for all their preferences know that that's not going to be true. But at the end of the day, I do see that consolidation like much stronger glue in between if you smart about how you use it. So we might actually be able to get a payback on the stuff that we've been investing in now because of AI, you know.
- [29:00]
C
Yeah, I really, I was talking about this in the newsletter literally this week, where there's really no department quite like marketing quite like ours, where we're using so many tech tools on a daily basis and also just like learning new ones and new AIs every day. It just, it is really, it's impressive.
- [29:21]
E
All right.
- [29:22]
A
It's that time of year. Everybody's scrambling to wrap it up, justify budgets, get those plans in last minute, and quietly hope that the numbers are going to hold going into 2026. But here's the uncomfortable truth. Most marketing teams still don't actually know what's driving real results and what's just taking credit. There's a difference. And you can't make smart contracts calls for next year if you're just guessing about what's working, what's not, and where to put your next dollar. Paramark has built something to fix that. It's their free incrementality calculator. And it takes two minutes. And it's going to give you a simple reality check on one question. If you stopped a campaign, would the results still happen anyway? I can think of a few ideas in my head right now that I would like to run this through. Maybe branded, Branded search would be one of them. Anyway, that's incrementality and it's how the best marketers are cutting waste, tightening budgets, and figuring out which programs actually deserve to make it into next year. You'll get A quick read on whether you're ready for incrementality testing and how much money you could be saving right now. So go and check it out. Completely free, free tool from Paramark. It's Paramark.com calculator that's Paramark.com calculator.
- [30:32]
C
I've got some good questions here too. In the chat I want to kind of weave in the ones that are relevant to the topic we're on right now. There's so many good ones, but kind of connected to this. Lindsay asks, are you still using lead or account scoring methodologies? Right, so we're seeing these intent signals, these patterns. We're using it for predictive analytics, forecasting, but also quick action across our teams. So how do we use those signals and score them or structure the accounts in a way where folks can act on them immediately or have we replaced that lead scoring account scoring with something else?
- [31:11]
D
We don't use it at all. So it's definitely old school model like MQLs. It's honestly like maybe a year from now I see it being completely dead. Like I said earlier, we do pipeline predict scoring so that space of all the signals, their behaviors and so it'll predict what we think is going to become an opportunity to become pipeline. But no, we don't do any lead scoring, any account scoring right now or we will never do it. I feel like even my last organization we didn't do it either. I think that's kind of a giant thing.
- [31:49]
C
How do you bring those accounts to the top of the list? So if we're seeing those indications happening within an account, how would you surface that to someone?
- [32:00]
D
Yeah, so I mean like we score them based on their behavioral data, technographic, firmographic. So everything, every signal and layer combined into one score. So it's not just oh, they did, they downloaded a white paper, they went to a webinar, they registered for this event, they went here, score, score, score, score. They did. 20 engagements are ready to be followed up on. It's, they look like this, they have this technology stack, they're engaging here. This person, the CMO is doing this, the VP of marketing is doing this. It's the whole buyer group. So you've got multiple people in the buyer group engaging so they get a higher score. And so it's the entire ecosystem world that they live in. And, and then, and then with this pipeline predict we'll put them in a funnel stage just to say, you know, they're, they've got pretty low pipeline predict. We're going to say they're still at the awareness phase or there's three of the people in the buyer group that's looking at it. They're still kind of determining. So we can. We surface that stuff with our ease all the time. But we don't say like this person did this many activities, go follow up on them. It's this account is doing this, they're more likely to buy. We're predicting that they will. Marketing will swarm that account. Here's the context. We know where they're located so we know who to reach out to. So you guys start prospecting into it.
- [33:19]
E
So it's scoring, but scoring in a non traditional sense.
- [33:21]
D
But scoring in a non traditional way. That's more holistic, predictive. Yeah, yeah, yeah. More modern.
- [33:30]
E
Yeah. Gardner had was it their CMO summit this summer. They basically brought out and said, look, we care about the buying network versus the buying influencers because they've recognized there are a lot of people outside an account or an org that are influencing the way that buying committee is making decisions. And so now you need to map that ecosystem and maybe scored in the context of whatever that that opportunity might look like, that particular need that needs to be solved. But nonetheless you're still scoring in the sense that you're, you're treating things differently. And so there's, there's some presence of things that kind of. You send it down the path.
- [34:10]
C
Yeah. Some good questions.
- [34:11]
B
I was going to say we did a lot of engineering on the back end. I don't know if this people find this helpful, but at a technical level we redefined that all of this scoring into one machine learning scoring. So a lot of the same trends happening across the board. I think what was powerful is that we aligned it to Salesforce on the lifecycle object and we actually applied earlier indicators at the top of the funnel in terms of how we're seeing that convert from early stage before it even becomes an opportunity to piggyback on Jean and Lisa, you're still elevating people within accounts. It's buying committee. You're still scoring it, you're still adjusting the scoring. Hopefully with a committee, not just a single person that is constantly coming back to look at it, make sure that those are predictors and indicators of the right pipeline. But we found a lot of synergies with our SDR and 8 and AE teams. A lot of what we were hearing in the day and life of MQLs was there's never enough, we need more. What are you guys doing over there? And the alignment of this One view of high top of funnel, what we call before opportunity stage did for us, we'll say, oh wow, there's a lot of activity happening. And then what it's doing is it's actually consolidating the behavior scoring that activity, also the buying committee and the account activity into one score. And we can actually see, okay, are these the right accounts? Because they're converting to working, meaning our SDRs are actually doing active outreach and then they're converting to meetings so they're showing up and then is there an active opportunity in place? So we've been able to build intelligence early in the funnel to show predictability of future pipeline based on who we're engaging with and what that predictive scoring looks like. So that's been a huge unlock for us in terms of alignment. We got out of the how do we get more of these things to, you know, I know every salesperson wants more hand raisers. There's only so much you can do. It got us out of that and into okay, how are we taking what we have and actually driving it through top down through the funnel and forming the accounts collectively? Marketing and sales together.
- [36:24]
C
Yeah, I think that's the key there. And there's a question in the chat from Diane suggests when you say marketing will swarm that account showing intent, are there specific marketing tactics you're executing? And I'd love to hear also the panel's thoughts on this, but I think it also depends on your, your GTM and your motion. But I think there's a variety of, of ways that both like you said, Morgan marketing and sales are approaching these accounts. Obviously there's like your, your account base, your ABX account based experience where again this is not for every organization but where you're able to kind of target those high value accounts with like hyper personalization through a variety of ways. But then there's also that like the simultaneous real time audience segmentation that's happening across 50 different micro segments with personalized messaging and all of those segments across four different channels like social and email and display and that happening also in real time. Are you guys seeing like a marketing and sales kind of united approach in that way?
- [37:26]
E
I think we're aligned. Well, I don't know if you were directing that question into one person, but marketing and sales knows it's harder to not only be visible at this point, but chosen and so there, there is more willingness to work together to swarm accounts. What I think when I, you know, when I see the question of when you say marketing will swarm an account. Are there specific marketing tactics that we're executing? I think the secret answer to that depends on your organization. But it comes down to two things. Are you visible or findable and chosen wherever your buyer's questions are being asked and that should likely isolate what your tactics should be. So for example, a CMO might be asking someone in an Exit 5 community for advice on who could help them solve a particular problem around account based marketing. Are you visible and present? Are you adding value into that community? What if that Same CMO loves ChatGPT and loves actually having conversations with GPT about how to solve this particular problem and would expect that you get cited there? Well then you've got to actually have some sort of AI visibility strategy. Maybe they are old school and your audience believes that in person events are more important than anything and which events are. So you're going to have to make sure that you're findable and chosen wherever they're asking their questions. So talks about AI answer engines. My response to that is you've got to be thinking about search everywhere, not search engines, not answer engines. And if you were thinking search everywhere then the very next question is well who's answering your buyer's questions? And that's it. And from there then it's a matter of okay, well what tactics will work for me in the context of those two things? For us it is the presence of communities, it is the presence of PE firms and their value creation of debt and the tech partners. Right Again marketing marketers love tech and so our tech partners that are in your tech stack talking about us and if we don't have those three things we're likely not going to be visible before they select their preferred list. So those things, you know and I.
- [39:49]
D
Would say from our standpoint, I mean in using AI to help with this and help scale it is we have put in automations into demand based but we've put in automations that when we know we have to swarm an account they automatically go into an automation to say okay they're going to get fed advertising to all through all these different channels.
- [40:10]
B
Right.
- [40:10]
D
We will then alert alert on Slack our evangelists who then will go out to the communities and they will start talking about will alert our sales reps to go looked on LinkedIn sales nav who's connected tell the marketers in our organization. So if we're talking like a to a digital person or we need a demand based or a demand gen person like we I will do active outreach on LinkedIn to have conversations with people, I will see, you know, what they're posting and where they're talking. And so I think it goes back to Lisa's is go to where they are. So like it's hard to say like, oh, you've got to put ads out, you've got to do this, you've got to host an event, you've got like your tactics are really what's best for your org, what you can afford too.
- [40:52]
E
Right?
- [40:52]
D
Right. Because I've been at tiny, little, small startups and it was we're going to grind this out and like put out some ads and I'm going to just do some outreach myself. But I think it's just, it's more around like it's using every resource. You have to get to where they are.
- [41:08]
E
Right.
- [41:09]
D
You get to where they're talking, where.
- [41:12]
E
They'Re asking because it changes.
- [41:14]
B
Right.
- [41:14]
E
Like think of all of our own buying behaviors. I mean the way I buy stuff today is wildly different than I did three months ago. A critical investment you make is making sure you have access to your buyers to ask some questions about like what's evolving about where you're doing your research and search and how are you selecting vendors today. Like just make that commitment and then at least you're always directionally sound.
- [41:38]
C
Yeah, I think that's such a good point, Lisa. I think if we keep the focus on the buyer versus always, you know, on us getting to the buyer, but more about putting ourselves in the position of buyers, which we all are in our own way, even B2B buyers are still human buyers. You know, how is their buying journey changing and how are we showing up effectively through that? And I think that a big topic that I always hear anyone leading demand gen or CMOS marketing leaders is under this pressure of driving pipeline and revenue. How, and we in the Exit 5 CMO Council, this is a topic that comes up a lot. But how are, how are folks balancing the long term brand building with the short term pipeline pressure? How is AI making that easier? Because we all know that that's something that has to be done. We've all seen the way the story goes, that that's not happening. You know, that long term brand investment is not happening alongside of that short term pipeline execution. But how, how is that? How, how are you guys balancing that?
- [42:42]
B
For me this isn't a balance, this is a must. It's funny to me that the, the pendulum consistently shifts from all brand to all demand capture and I really think that we have to break this cycle. If you are looking to build a predictable engine, you do not sacrifice one for the other. And I'll give you a. I'm not talking like massive commercial ads or huge out of home buys. That's not even what it needs to be. I think in the context of the last question that we just answered, when it comes to your audience, how are you adding value? So as a low cost, I guess this is a high cost from the people that you probably have to engage, but a low cost in terms of actual dollars and marketer execution. One thing that we instituted, you could take a spin, you could spin this off into anything that you particularly want. But we do a 30 minute session with we particular, we try to talk to security operations leaders, so CISOs. And so what we do is we actually take our internal people and every week they do what's something that you should know this week, why you should know about it and how it's 30 minutes, we show up every week. I pushed on this so hard internally because it's not easy to put an event like that on week over week over week. It does, it has a cost, it has an internal cost. We are seeing massive build in current pipeline now several quarters out from that because we added value early, we built trust and connection early. We got it out to the people that mattered early in the cycle. So this is very much a brand generation thing. Like when I think about it, it's brand gen, then you have this demand gen. How are you building that thought leadership, connection and then true demand capture and move on. But it's something like that that I think is such a huge predictor of future pipeline for you. And if you can set expectations early with your team on what, how to measure it differently, why it looks differently than other tactics that you run and then keep that clarity and alignment throughout, eventually it will come to terms and you will see that output. But it takes time. You know, I've had to battle with the biggest people that are trying to put this on weekend and we get out to keep it but the consistency shows up and and we're all in now we're bought in.
- [45:06]
E
So yeah, view the first investment like brand building. I'm with you 100% aligned. Like it's not a decision between these. If you do the first investment well, like if you invest in your long term brand building you don't find yourself in the second problem like you don't find yourself under short term pressure on pipeline because you've been findable right. And chosen exactly. What I love about your example is that I Tend to think about brands as having gravity. And the gravity, the stronger the brand, the stronger its gravity, the greater the, the the influence of attracting buyers to you when they launch into a search and keeping them with you until they are ready to engage in a more direct way with your organization. And that requires, what does gravity require? It requires mass, so it requires digital mass. And so your example of having this 30 minute really valuable, what are the things you should know now, wherever you might be publishing that, if that is findable after that 30 minute conversation and it's findable online, right where anonymous searching is happening, then my guess is that you probably are building up so much digital mass that when buyers actually figure out they have a problem to solve, they get pulled towards you and they stay with you until they're ready to actually make a, you know, move forward and select their finalist list and have conversations with you. But that, that digital mass is critical to building that brain. Gravity and AI, you know, AI can be used a number of ways, right. It can let us know when companies launch into orbit to start their search. But candidly, thankfully, as marketers it can help us actually scale the production of that, those assets that give us that footprint, that give us that gravity.
- [47:04]
C
So that should be your, your second book there Brand Gravity.
- [47:09]
E
It's out there.
- [47:11]
C
Oh, it's good.
- [47:12]
D
Good.
- [47:12]
C
There it is.
- [47:14]
E
I think that might struggle with getting alignment from your sales leaders to care about brand building. There were like four studies last fall. What's interesting is they weren't related to each other at all, but they were all on the buying journey. Like how did the buying journey change? And all four of these, when there was one, there were a number of studies that came out. All of them said the same thing. This buying journey is much longer than you expected. You don't control it in any way, shape or form. It requires nearly like a thousand interactions with your brand and they make a decision as to when they're going to reach out and talk to your sales rep. And they're only doing it after they've already selected their preferred vendors and they likely already have a favorite. And guess what? 85% of the time they buy from that favorite. Before the an all sales job was to validate what they had found throughout that anonymous search. And like that if you need, no sales rep thinks it's easy to sell today, but that any one of those four research reports go out and get it, bring it and say I need your help. I need like we need to be findable in chosen before they reach out to talk to you and I need to be able to protect some investments in my brand.
- [48:29]
C
Right. All the right conversations to be having. Are you using AI? Anyone on the panel using AI to help to better attribute brand, which has historically always been difficult to attribute versus demand capture channels. But using AI to better attribute what you can with with brand to prove connection to revenue. Like this person interacted with our content X times this person engaged with Dave's LinkedIn post and did this thing and now you know, we're also creating predictive analytics connected to that. But is anyone using AI to help to prove that out?
- [49:07]
D
I don't know if it helped to prove it out. Definitely using AI. So I guess a little background of me, I have historically worked at very small startups so you had to have everything that I've ever done in marketing, every tactic had to have a dual purpose. It had to have a brand part and it had to have a demand part because I just couldn't, I couldn't afford it. I was by myself. I had $10,000 for the quarter and that's what I got. So I think where I'm using AI, it's great. Demandbase has a brand so we can escalate this even more. Is helping to develop the content and the assets that you need in a scalable way to put that thought leadership, customer stories, customer videos, put all that out into the ether and then being able to measure all of the interactions and engagement on it. But for me from that standpoint, AI is just helping scale it massively.
- [50:03]
C
And we're coming up already on time so I want to make sure that we have time for Q and A. We've only got 10 minutes left, so I'm in the Q and A tab here, just kind of scrolling through to make sure that there isn't anything connected to these topics that we're on right now. There's one follow up question in the chat. Follow up question, what channel are you using to deliver the things that you should know now? Is it the partner, community or end users? Morgan, how is that information delivered to potential buyers? What you need to know, why and how. Thanks Julie. Great discussion, appreciate that. Any thoughts on that on those questions?
- [50:40]
B
Team? Yeah, I can, I think what I heard was how are we distributing the weekly topic? So I heard that this notion from a friend of mine that we work with, it's called, she calls it the content turkey and it's because you can carve it up so you don't have to use like one meaty topic of content. You can literally just cut it up and use it across channels. So there's a few things that we, that we use to do this one is again to Lisa's point, how are we going to make ourselves more findable? So how do we take snippets of this and deliver it where our audience would want to find it? We actually get a huge number. I think it's on, it's up leveled a couple of things. One is it has indicated that our customers also hyper value this content. So when you talk about churn reduction, 50% of the people that show up week in, week out are current customers of ours. That was a huge unlock. So when we're talking about brand build, we're also talking about retention. The other thing was our internal people show up for this. They also want to know. And so we actually use this content and others to highlight things that might make our sales team more successful in their outreach when they're talking about adding value. Lisa was talking about curiosity. How do we come from a place of curiosity rather than solution selling? So we use a lot of that. Another engine that we have used again in tandem with our sales team, we call it Pipeline Wednesdays. Hyper Creative. I know, but this is a huge. I believe that marketing is also a co owner of enablement because enablement is yes, onboarding of sales teams, but it's also how are we helping them deliver the message that we're packaging and also making sure it is landing. It doesn't end with here's this campaign thing output. It's also is it resonating? What does this look like? So we use that time to also distill the weekly insights that we have from that topical virtual event. We use that Wednesday with our sales team to say here's what we're hearing. How can you use it in market and connect it to the signals that we were talking about at the beginning? So if you're expecting that your sales team is going to be able to go in and attach messaging to signals, they don't. So help them. Like we literally show up every Wednesday and say here's something that you can attach to these types of signals. Here's where they live. How can we help you? So that's been a huge unlock for us in terms of delivering that message to our sales team and working in partnership with them, not in silos and like throwing things out into the ether.
- [53:22]
E
I love all of that. One, one little AI. I wouldn't say hack, but one little AI tip here. I created a custom GPT, trained it on our positioning, our messaging and all the signals, the three different types of signals that we track and I have it, it's basically meant to be a sales enablement coach. If you've, if we've identified an account that you know it's showing these, these presence of these signals what would be an appropriate approach and messaging and offer strategy and the offer is usually something of value. A no ask something of value. It's hinting at our content library basically. But I was struggling with sending across qualified accounts based on these signals and they're like well what the hell do I do with that? So I created a custom GPT that could at least provide them with guidance on key messages and an outreach strategy for them. So. And it's pretty easy, right? It's just context and instructions that you can give to now. Yeah.
- [54:26]
C
I love this comment in the chat said absolutely must applaud the elbow grease to get the sales folks to tie messaging to signals. We had PMM sit in on our demand gen pipeline reviews. A good, good call out.
- [54:39]
D
I was just going to say we, we've got, we call them pod calls. So every other week we meet with every AE SDR group. So it's one AE with their SDR and we go through what are their target accounts and what funnel stages. What's the strategy we're going to go after for the next two weeks. Here's the enablement session. So my, I mean my, my field team's a team of two and so they are taking a lot of time to sit down but the payoff and the return is exponential is when you can get everybody aligned on this is the message to this signal or to this stage in the buyer like in the funnel they, they really. And then they start getting it and so then it's less of us telling them what to do and then being like so I've got this account, it's not quite yet but should I do this and should I do this and invite them here and do this and you're like yes, like you're getting it, you're getting it.
- [55:27]
E
That's awesome.
- [55:28]
D
Such a great feeling.
- [55:29]
C
That's amazing. That's awesome. Well just to maybe quickly wrap this up. There's so many good questions in the chat. We'll try to get, get to but kind of want to have like a zoomed out last thought or consideration for marketers on just maybe a skill, a mindset that's going to become a non negotiable for today's marketers to have with this with this transition to how the future is changing for the better for us as marketers. In a lot of cases, if used right with AI.
- [56:03]
E
Look, we are in the age of AI. I know that sounds cliche, but I think the phase of us being able to use our constraints as excuses for why we can't do more or you know, grow pipeline or accelerate revenue growth because we don't have enough people time or budget, I think those days are over. And so if I have any advice for anyone, is it now it's time to actually think and use your constraints as ways to free yourself from all these unreasonable expectations. And so that would be things like prioritization, that is invest in accelerating your adoption of AI. That is thinking instead of thinking about, I need more headcount, think about, well, what are other ways to get this work done? And there are so many different operating models to do that. But like we're, it's kind of over. We have people that don't know marketing that are suggesting that we replace all humans with AI like they, they have no idea how complex this job is. And if you're in that situation, if you're in a boardroom or someone's telling you you should just have AI do it without a human, that's because we keep showing up with all these excuses and constraints of all the things we can't do. Start to actually think limitlessly. It's probably the give.
- [57:21]
C
Right, Right.
- [57:22]
E
New levers now that you've got to carve out some time and think through how to flip the constraint into a strategy to free yourself of it.
- [57:32]
C
Right. And more of the humans are, the value of us is more strategic and the AI is picking up all of the grunt work and the manual work that would normally take days or weeks to get the outcome. But the subject matter expertise is still required. Right. We have to know the outcome that we're driving towards. We got to know the right questions to ask. We have to know the decisions that matter and we have to know how to direct the AI to do that manual work to get us to those outcomes so we don't have to be in the, the day to day of that grunt work anymore. Which allows us to be more of the, we're moving up on the, on the chain of, of strategic focus. You know, the human side of it.
- [58:12]
E
But I mean if you get enjoyment from clicking the button 21 times, you.
- [58:16]
C
Get email out, right.
- [58:18]
E
You're kind of over. Yeah, but that's a new career now. Can use AI like a superhuman like superpower to do more impactful things which really fun stuff. So.
- [58:31]
C
Exactly. Exactly.
- [58:32]
B
Yeah.
- [58:33]
C
Awesome. Well, thank you guys so much for down to our last minute or two here. But yes, for folks asking about the recording, it will be emailed to you later today and for folks who will be watching this later, it'll be. You'll be watching it because it was emailed to you as well even if you were not attending today. So thank you everyone. Thanks panelists. Really awesome engaging discussion and honest with a lot of tactical feedback and use cases too. Thank you guys so much for joining. Thanks demand based for our sponsor and have a great rest of your week.
- [59:04]
E
Thanks for the opportunity. Have a great week everyone.
- [59:07]
B
Thanks everyone.
- [59:08]
C
Bye bye.
- [59:13]
A
Hey, thanks for listening to this podcast. If you like this episode. You know what, I'm not even going to ask you to subscribe and leave a review because I don't really care about that. I have something better for you. So we've built the number one private community for B2B marketers at exit 5. And you can go and check that out. Instead of leaving a rating or review, go check it out right now on our website, exit5.com our mission at Exit 5 is to help you grow your career in B2B marketing. And there's no better place to do that than with us at exit 5. There's nearly 5,000 members now in our community. People are in there posting every, every day asking questions about things like marketing, planning, ideas, inspiration, asking questions and getting feedback from your peers. Building your own network of marketers who are doing the same thing you are. So you can have a peer group or maybe just venting about your boss when you need to get in there and get something off your chest. It's 100% free to join for seven days, so you can go and check it out risk free and then there's a small annual fee to pay if you want to become a member for the year. Go check it out. Learn more exit5.com and I will see you over there in the community. This episode is brought to you by our friends@customer IO remember when a personalized message in marketing meant just putting someone's first name into the email? And that was magic. Hello David or hello Gerhart or whatever fake name I put into the form? Well, those days are long gone. AI has raised the bar for life cycle marketing because now you can deliver smarter context aware communication that actually feels personal and you can do it at scale without hiring five more people. Today, personalization doesn't just mean using my name, it means actually having the right context. But there's a problem because even though this sounds great in theory, most teams can't actually do it because they're stuck with broken reporting, siloed data and outdated tech stacks. It's often easier to just keep doing things the way that we've always done them. So our friends at Customer IO recently surveyed 600 marketers like you and me to figure out what's working and what's broken in lifecycle marketing right now and how the best teams are actually solving these problems. The report breaks down 2026 priorities, where budgets are moving and how to tame the measurement mess that we're going through. Real world examples from brands like Notion and Monarch Money that are using AI personalization experiments and understanding the next chapter of AI what's on marketers wish lists and how customer journeys can get smarter, not just faster. So this guide is packed with examples, data and strategy that you can put to work right now if you want to get smarter about lifecycle marketing. This is a great free resource. So where my email marketers at my lifecycle marketers listening to this. Go and grab it right now customer IO exit 5 and you can grab this and learn how to build lifecycle marketing that keeps up with today's expectations. That's customer I.O. exit 5.