Jeremy Balius: Welcome to Go-to Market Playmakers, where we bring you winning go-to-market strategies from the industry’s best. Each episode we sit down with B2B Tech and SaaS founders, executives and industry Playmakers who’ve mastered the art of taking products and services to market. Whether you’re scaling a startup, refining your go-to-market motion, or driving revenue growth through a channel program or a partner ecosystem, this is where you’ll learn the plays that work.

I’m your host, Jeremy Bayless, and today’s theme is Artificial Intelligence in Enterprise Tech Go To Market. I’m joined by Mark Viso from the Enterprise Edge, Mark’s the founder and CEO of Enterprise Edge, which equips B2B enterprise tech firms to grow, convert more funnel, increase m and a time to value and transform to sell as an advocate, not as a, he has an impressive 30 years of deep, full spectrum experience across.

B2B Enterprise technology ecosystems from software services marketplaces, right through to consulting. As a result, he’s a 360 degree operator, deep tech and operations VP practitioner, roots executive software, it’s services and tech vendor go to market experience, as well as analyst consultant advisory roles.

This is a fascinating conversation with Mark, the way that he’s articulating trust in the context of AI and what is happening with and through ai. Enterprise tech in their go-to market motions is, I think particularly illuminating because he is able to reflect on broader strategic moves happening in the marketplace between enterprise tech giants and strategic pivots taking place right now.

And also reflect deeply on how is that impacting enterprise tech more broadly and how it’s impacting go-to-market. As a result, I hope you get as much value from this as I did. Let’s jump straight into it.

Hey Mark, it is so good to have you on this show. Thanks for joining me today.

Mark Vigoroso: Thanks, Jeremy. Happy to be here.

Jeremy Balius: I’m really excited. Today we’re gonna be talking about AI intelligence in the context of enterprise tech and go to market.

But before we get into the nitty gritty of something so heavy, tell me about your origin story. How, how did you even get to where you are today?

Mark Vigoroso: Uh, I’ll give you the short version. Um, I’ve been in enterprise technology for almost. 30 years now, and I’ve kind of got this path that has taken me through kind of three, three patches, right? I guess one of them is sort of the whole vendor world, the software vendor services vendors that are innovating and solving for, um, various business challenges.

So I’ve six or seven of those companies, big ones like Verizon and Oracle, Qualcomm, and then even some smaller ones that. Um, you know, I joined a few that were pre-revenue startups, so everything in between as well. And, and the second stop is, um, sort of the end user, the practitioner, the people who are, uh, buying and deploying and using various technologies in an enterprise context.

So I spent some time at called NCR Corporation, uh, the inventor of the cash register. Um,

Jeremy Balius: Oh wow.

Mark Vigoroso: that was, that, that’s, they’re based here in Atlanta, Georgia, and I spent eight years there. So a chance to be kind of the end user, the end customer in many ways. and then I’ve spent some time as sort of a consultant slash advisor expert type of person in a couple different areas.

So I’ve got this sort of path. It’s given me kind of a 360 degree view of a lot of different stakeholders that are involved in the, the enterprise tech space, which is very much a moving target these days. And so. I feel like I can empathize a lot with people who are buying, people who are selling, people who are deploying and integrating and trying to figure out what to do with a lot of the emerging technologies like ai. In the context of their companies and their industries. Um, so yeah, I mean that’s, I’ve uh, now it’s sort of landed me where I am now, which is I’ve, I’ve got my own company. It’s called the Enterprise Edge. and we help companies, uh, software companies and services companies, go to market, um, more effectively, more efficiently in a way that drives growth. Um, very simply stated, but there’s a lot of ways we do that. But it’s really very, very much capitalizing on that. That windy path that I’ve traveled over the last three decades or so.

Jeremy Balius: That’s amazing. I really think the, the breadth of. What you’ve been exposed to in every facet. I think in this day and age is a real superpower.

Mark Vigoroso: Yeah.

Jeremy Balius: I think it’s such a rare thing because of the paths, of careers tend to be a lot more linear. And so having that breadth of expertise, I think would just add so much value in the way that you’re advising or guiding leadership teams.

, But looking backwards across that 30 year, of seeing it all, how does go to market evolve now into the space of the ai and in what ways is AI transforming go to market?

Mark Vigoroso: Yeah, well, you know, AI in all of its forms is disrupting and transforming almost every, every function, um, every industry, every company, and I’ve been in, go-to-market roles pretty much my whole career. It’s kind of where. I’ve, um, I’ve gravitated, I’ve been A-C-M-O-A couple times. I’ve been product management, um, alliance and channel development, sales enablement. so all, all on the sort of the revenue side, the growth, the go to market side. that’s kind of where I’ve lived, uh, in, in all these different roles and companies I mentioned before, I’ve always been in the, the, the sort of the front office of the business. And, and, and what I see now as I’m working with clients is that, um. Ai, I, I, I could say is, it’s hard to say it’s causing it, but there’s definitely a correlation between what’s happening now and

Jeremy Balius: Hmm.

Mark Vigoroso: that I see from I would say is sort of feature driven, go to market motions towards more outcome driven. Right. And what I mean by that is, um, a lot of the, uh, selling and marketing organizations that are, that are, that are bringing technology to the, to the market. Are focusing at least as much on that they’re impacting as they are on sort of features and functions that they think are differentiated. Right? That always, that hasn’t always been the case. I mean, there’s always been, um, good sales training, always talks about, um, you know, what, what are you solving for?

What’s the why, why, why are you, uh, relevant in the context of a, you know, a

Jeremy Balius: Right.

Mark Vigoroso: But now it’s become very pronounced because. With ai, there’s this sort of, I might call it, um, or skepticism, distrust that I’m seeing amongst the technology buyers. people that the go-to-market professionals are targeting, there’s, they’re basically facing a, almost like a jaded buying, buying community that’s basically says, I don’t believe anything you’re telling me. Right? I think it’s all theater. I think it’s all propaganda. Um, and I’m being a little, I’m exaggerating only a little bit, but the reality is that there is a lot of unknowns with regards to trustworthiness of AI models, large language models, um, with regards to some of the autonomous use cases with ai, where, you know, the future state is very much idea that you can run business processes somewhat hands free without human

Jeremy Balius: Hmm.

Mark Vigoroso: Not,

Jeremy Balius: Hmm.

Mark Vigoroso: certainly not. Tomorrow. I mean, there are some use cases, but a agentic AI is still evolving. And so now go to market has become almost like a, um, like a risk mitigation exercise. Like you, you have to convince the buyer that not only is there value, there’s business outcomes, also you’re not gonna do any harm, right?

You’re not gonna bring risk to, the organization, whether that’s regulatory risk or operational risk. Competitive risk, strategic risk, employee risk. so it’s, it’s, it’s quite a more complex motion, go to market messaging motion, um, that requires you to cover off. Uh, not just, here are the things that make my product better than the others.

No, no. This is what I’m solving for. This is why it matters to you. This is what it’s worth to your business. This is proof that I won’t do harm to your business. Right. And it’s, it’s, it’s like you’re now facing, in many cases a committee of up to 20 to 25 people. Right. You know, the, there’s data out there that says there are buying, bigger, complex enterprise tech deals, where you have 20 to 25 people that are involved in making a purchase decision. you have to somehow navigate that as a go-to-market organization, a selling organization, a marketing organization, a product organization. That’s not easy to do. That’s not easy at all. So that’s, there’s a lot, a lot that has changed. Some of it related to ai. I think just some of it. Um, you know, I think there’s been enough, bad headlines with regards to security breaches and various things that, that people are just a lot more vigilant regards to deploying technology.

Jeremy Balius: Would you say that this, what feels like a seismic shift in go to market is impacted by AI such that even enterprise tech that doesn’t have AI baked into it is having to adjust as a result of the sheer amount of noise in the market about ai.

Mark Vigoroso: Yeah, that’s, so, yeah. I mean a couple things there. One is that it’s, it is almost. A box checking exercise now that if, if you do not, if you’re a, if you’re an ISV, an independent software vendor and you don’t have an AI strategy, chances are you’re, gonna be marginalized, um, in one form or another.

You’re at risk anyway. So, but if, if it’s not, if it’s not central, if, for some, I’m trying to think of an example, like if you’re. Uh, you know, it’s hard to pick an example, but if, if AI is not a big part of maybe the initial buy or the initial decision and you’re focused in other areas, um, a lot of what I just described in terms of buying dynamics still hold true, right.

In terms of potentially the number of people involved, the sort of the cynicism, the mistrust, distrust, um. the prove it show me kind of mandate. Right. Um, not a lot of people have patience for, um, you know, vaporware anymore. Right. I wanna see it. I want to, I, I want to, I wanna know it’s real of whether there’s an AI story.

Right. But, um, yeah, I would say so.

Jeremy Balius: Yeah, interesting.

Mark Vigoroso: Mm-hmm.

Jeremy Balius: really fascinating to consider how much that affects across the go to market.

Mark Vigoroso: Yeah.

Jeremy Balius: Now, when we first started talking, prior to the show , we were talking in the context of some strategic shifts that are happening in the market, and I’d like to shift our focus and our conversation into that.

You published a point of view that really resonated with me, and it was around the SAP and NVIDIA partnership, and you were describing it as. A real strategic pivot for both of them.

Mark Vigoroso: Mm-hmm.

Jeremy Balius: Um, could we drill into what that specific partnership is about and what about it makes it so significant in your point of view?

Mark Vigoroso: Yeah, it’s a

Jeremy Balius: Yeah.

Mark Vigoroso: it’s a great point. Yeah. It, it’s, um, it’s, I mean, two massive players, right? SAP, Nvidia, um, Nvidia as, as, as you know, as kind of a. Probably one of the most, most headlines on, you know, an an AI success story. They’re just sort of fundamentally enabling so much of the AI infrastructure and sort of actualization working

Jeremy Balius: Yes.

Mark Vigoroso: like SAP. So what happened with this, with this, and I’ll, I’ll, I’ll try to boil it down. So, um, there, there’s, there’s long been. You know, if you can recall, just a few short years ago, people were still talking a lot about cloud computing and moving to the cloud, and even SAP itself. Has been on a, a measured pace to try to move a lot of their legacy, what they call E-C-C-E-R-P cus customers to cloud, right?

Either public or private cloud and, um, and, and there’s this sort of notion that it was cloud first ask questions later, right? We’re just moving to the cloud. It makes, it makes sense for everybody, right? TCO security latest capabilities, right? You know, cloud first, ask questions later. And what this partnership, um. I think signifies is a little bit of more of a, what I’d say, a sort of a nuanced approach, which into account, um, some of the finer points underneath that cloud first mandate that existed, uh, up until very recently. Such things as sovereignty, right? So there’s a concern in many cases about where data is residing geographically, geopolitically, And how data is managed for multinational corporations that are operating in many, many different areas of the world. of which have, um, of unique data sovereignty

Data which basically means sort of like in-country, data sovereignty and storage requirements. Um, and I think what has happened is that there’s a lot of. Work to date that has gone on in the AI space. has been in sort of a pilot sort of proof of concept. Um, um, you know, because, uh, you know, some of the, some of the traditional cloud-based AI solutions that have been deployed, they, they. They kind of conflict with some of the realities that exist from a regulatory perspective, right?

So a lot of these projects have been sort of stuck in what people call pilot purgatory, right? They, they’ve, they’ve not gone mainstream. They haven’t been operationalized and scaled across corporations because, because they don’t comply with the realities of. Data regulations and data, data sovereignty requirements.

Uh, in many industries, healthcare providers as an example, they can’t send patient data to external AI services financial

Jeremy Balius: Right.

Mark Vigoroso: Um, um, they, they have compliance hurdles that make pure cloud-based AI deployments much impossible. then government agencies have their own, sort of airtight requirements for, for data, right?

And so. Um, you may have a successful pilot, very much ring-fenced in a cloud environment that is not gonna go anywhere if, unless you address, these sort of unique regulatory requirements that, um, underpin these major industries.

So what’s happening is that, so Nvidia sort of, um, embedding and Nvidia is, is, is a. Sort of a complex organization. It’s a lot of pieces to it, right? We’re not gonna be able to go into all of it, but they’re basically embedding what they call these sort of, um, nim microservices into the architecture of SAP.

They’re basically solving tension between AI innovation and then the control that’s required by enterprises and these, some of these industries. So it’s kind of like. Thinking about this as more than just a technology partnership. It’s like a enabling a new business model that acknowledges that the future of true enterprise AI is local, controlled it’s compliant by design. Right?

All, you know, these are, these are all loaded words, but none of those things are easy to pull off in sort of a one dimensional. Sort of cloud strategy, right? So, so we’re seeing a lot of focus around AI sovereignty. Um, and what this does is it’s positioning at these, both of these companies sort of a ahead of some of these regulatory trends. Uh, there’s, there’s definitely going to be other moves like this.

It’s an acknowledgement that, you know, a lot of the investment that has gone into ai. Proofs of concept has stalled because of these issues. So it’s very much a sort of a surgical, surgical strike. Um, very well timed uh, by SAP and Nvidia.

Jeremy Balius: I deeply appreciate the way that you’re describing this and. The way that you’re articulating this, because I think this is something I think listeners really need to grasp, is it’s, it’s logical for us to say that data needs to stay on shore for a whole host of reasons, right? We need data sovereignty.

It’s, it’s. Easy for us to say that,

Mark Vigoroso: Yep.

Jeremy Balius: in the world of the hyperscalers and different infrastructure as a service providers, it’s really hard to make that happen. And you’ve got different players who’ve gone out and positioned themselves as that in the cloud compute space. , But the way that you’re talking about the.

Not just the go to market of this strategic partnership, but the very DNA that’s being rewired

Mark Vigoroso: Mm-hmm.

Jeremy Balius: at a reason for existence for these companies, I think is deeply fascinating to think about and consider.

Mark Vigoroso: I mean, it has implications that are, um, the magnitude of the implications are, you know, entire global industries fin services, healthcare,

Jeremy Balius: Yeah.

Mark Vigoroso: private, private, uh, sorry, public sector. It’s, it’s enormous. I mean, it’s, it’s just enormous. It’s not, it’s not necessarily a silver bullet, but it’s, it’s a very strong enabler.

Jeremy Balius: It’s interesting to think that something so consequentially core to businesses isn’t getting the earth shattering attention that one would think it. It, it is phenomenally powerful this shift.

Mark Vigoroso: Yeah.

Jeremy Balius: you, you mentioned in the context of the highly regulated industries that you were just men, uh, talking about and the challenges that AI has in those spaces.

Mark Vigoroso: Yeah.

Jeremy Balius: You framed it as local ai.

Mark Vigoroso: Mm-hmm.

Jeremy Balius: What is that?

Mark Vigoroso: Yeah, so it’s a great question. The, the, the, um, you know, it, it’s, it’s kind of like, I’ll, I’ll answer it this way, lo, local ai, especially when you think about these regulated industries that I just talked about, healthcare, financial, government agencies, right? These guys have, had to choose between innovating and complying in many cases.

Uh, historically, they’ve had to say, either we’re gonna comply we’re gonna innovate. We can’t do both, and they have to comply. Innovating is sort of an optional thing, I guess. Um, but it’s not really, if you wanna remain competitive. is like black and white. You either comply or you’re out of business, right?

So, um, what local AI does is sort of starts to eliminate that trade off, the risk reward, if you will. And, and it just, basically, it’s just the whole idea of data sovereignty and AI sovereignty, having that control locally.

In some cases it’s literally geographically speaking, um, within country or on shore. you know, examples would be, you know, a healthcare. uh, a healthcare provider could run sophisticated diagnostic models, ai, models on patient data. Without that data ever leaving a controlled environment. Right. That’s sort of, that’s, that’s now possible.

In finance, you could deploy, um, things like fraud detection, using AI while, while maintaining data residency, which is another way of saying local data, right? In government, you know, you can leverage AI for a variety of, they call citizen services meeting security clearance requirements.

So it’s an and now and, and, and not an or. Um, and so of these, these entities now, um, it’s no longer a sort of a yes no question. Are we going to be able to take advantage of ai? It’s how fast can we scale ai, Knowing that some of these compliance constraints are going to begin to disappear, adoption timelines can accelerate. Um. And we’re seeing already in the SAP ecosystem, of their healthcare and public sector customers, some of the data out there.

I, I don’t have the source on this, but I, I did some research and some of the data says that, um, with local deployment models, these sort of controlled, sovereign data models. The AI IMP implementation cycles are between 40 and 60% faster for these companies because they’re able to comply out of the gate a lot of these regulatory requirements, um, which is, which is powerful, right.

Um, and, and it just, it’s just gonna be like this of like this snowball, right? As soon as those. use cases are gonna prove out, and there’s gonna be more and more testimonies that, this is, this is working, that they’re, that you’re innovating and complying across these highly reg regulated areas. the economic impact, um, like I said before, is just, don’t think we’ve ever seen anything like it.

Certainly not in my lifetime. Um, so it’s pretty, it’s pretty exciting, exciting times.

Jeremy Balius: Yeah, man. I, I feel like the way that you’re talking about local AI and local deployments and the, the speed to deployment, this, this seems to me as if it’s not just a, a. That the strategic partnership between SAP and NVIDIA isn’t just changing or affecting or evolving their core mission as such in isolation, that this is evolving enterprise tech go to market more broadly speaking, would,

Mark Vigoroso: Yes.

Jeremy Balius: is that a fair summary?

Mark Vigoroso: Yeah, no doubt. No doubt. It is, and it’s, it’s, um, it’s another layer of the, sort of the bringing it back to the go to market sort of remit, right? Is a lot of, I would say. Enterprise software, enterprise application categories like ERP or CRM or PLM or or MES or all, you know, all, all the, uh, three letter acronyms. they are, many of them are taking a much more deliberate verticalized meaning that they are. Um, trying to empathize with the vertical uniquenesses, right? So think about the three verticals we’ve been talking about. Then there’s manufacturing, automotive, aerospace and defense,

Jeremy Balius: Hmm.

Mark Vigoroso: tech,

Jeremy Balius: Hmm.

Mark Vigoroso: retail, all the major industries. A lot of the enterprise apps providers are design, going to market by vertical. Meaning they’re, they’re building products, they’re making acquisitions, they’re acquiring talent all by vertical, right? And be, and there’s, there’s economic reasons for that. There’s also competitive reasons for that. Um, and, and so what that means is that, um, you know, many of these industries are regulated.

They have unique. Regulate regulatory requirements. they have unique constraints on how data is handled how identity is verified or how end customer data is protected, how chain of custody is, um, and is managed, right. All these things. so they’re building these sort of verticalized competencies within their organizations. so they’re looking a lot like, Not just technology companies, but they are fairly well, um, experienced operational companies, meaning that they can empathize with the operating challenges and the business challenges of the industries that they’re solving problems for. Right? And that’s, that’s earning them a lot of market share in many cases.

Because at the end of the day, people are buying enterprise software based on. I would argue thing, and that’s trust. And the more, the more trust you can generate and earn amongst your target market, the more success you’re gonna have. And that trust comes a lot from, do you understand the industry that I’m in?

Do you understand the uniquenesses of the pains that I’m experiencing? can you solve them in a way that, um, will stand the test of time and can scale? Um, that’s hard to do if you’re sort of a generic horizontal application provider without a heck of a lot of professional services that cost a lot of money and a lot of time.

So, yeah. So, uh, the long way around is saying, um, yeah, and, you know, the way these companies are going to market now, by vertical is sort of in line with some of these industry specific regulatory requirements for ai. It’s almost like that motion was already started. Years ago, some of these application providers went nearly kind of made big bets on verticalizing their go-to market motion.

Jeremy Balius: It’s really fascinating to hear you talk about the currency of trust and um, you know, we on our side spend a lot of time talking about, uh, vendors in their channel plays. Ultimately they’re selling trust that they’re not gonna turn around and burn their partners.

Um, and it’s fascinating to hear that in the go to market, in the sales cycle and enterprise tech, that that’s a fundamental currency, not just that you’ll do what you say you’ll do, but that you’re not gonna turn around and disappear or leave me hanging when things go awry.

It’s fascinating to hear you talk about that.

Mark Vigoroso: Yeah. It’s, it’s

Jeremy Balius: Hey, uh, wanted to circle back. Um, you were earlier talking about how NVIDIA’s microservices, uh, containerized microservices, uh, um, in the context of SAP and the, the changes that were being affected there. But if we could pull back and talk more broadly what, what.

In your view, what’s the importance of these containers, microservices and, and its effect in terms of time to value for the buyers as well as go to market more broadly?

Mark Vigoroso: Yeah. So, um, yeah, I think there’s a couple things. One is that if you think about historically, um, of, you know, there’s really not a lot of history for ai, right? I mean, things that are being renamed AI that have been around a long time, like predictive AI and ML and things like that. But,

Jeremy Balius: Yes.

Mark Vigoroso: a, a lot of the, um. Deployments that we’ve seen at scale have required fairly significant infrastructure st changes, right? To support solution. Um, whether that’s data center or, you know, architecture, um, footprint and, what, without getting, I’m, I’m not a, I’m not a, um, I’m not an expert, deep expert in sort of the infrastructure side, but what Nvidia is doing.

Uh, with these sort of containerized microservices, it basically means that architectural infrastructure disruption, um, is no longer a factor, right? That basically you can, by embedding those or integrating those containerized microservices the existing SAP environment, it essentially. Um, removes that disruptive factor that has cost and time and risk, um, associated with it, right?

So there’s huge to value implications. and, and so there’s, there’s tremendous flexibility there. There’s, there’s risk mitigation. it checks a lot of boxes. and you know, I, I, I think what, what happens is also that. Um, the, the bet that an SAP customer is making, um, and this, this gets into, I mean, we could, this is, we could talk a long time about this particular partnership, but I mean, with a, basically what they’re doing is they’re gonna get access to of different, uh, proven AI models through this partnership between SAP and Nvidia. what that basically means is that that are, that are going to, um, be working with SAP and Nvidia uh, deploy enterprise scale ai, they’re gonna basically have, it’s almost like a, a portfolio, like think about it as the difference between investing in a mutual fund as opposed to buying a single stock. is you’re, you’re gonna, you’re gonna be able to take advantage of a portfolio of AI models that are proven, that has some sort of built in, um, optionality and risk mitigation. Um, that doesn’t come if you’re betting on like a single AI approach or a single large language model. so it’s, there’s some flexibility there in the infrastructure can evolve. As the technology advances, which we know it will, we, I mean, we’re watching every day, this technology advance faster than any previous category of technology known to man. so it’s, it’s a very forward thinking. I don’t like the word futureproof, but it’s, it’s, uh, as, it’s pretty close to that, it, it, it, it’s future accommodating, I suppose. and so basically. If you want to be a somewhat sensationalist about it, it transforms AI from sort of high risk, high friction lower risk, value, much closer to operational scale and operational impact, which is really the only thing that matters, right? Is this actually going to my business in a meaningful way? That improves my profitability, experience, my customer experience, my competitive positioning. Right. The, you know, the things the CEO cares about. Right. So it’s pretty, it’s, yeah, it’s, there’s lots of layers. Lots of layers to it.

Jeremy Balius: Yeah. Yeah. Well, to speaking of the competitive positioning, I think it’s fascinating to think about CEOs, leadership teams, and. Go to market leaders wrapping their heads around the positioning impact of this and how they are transforming their own go to market, their own positioning and their own competitive pitches and, and how they’re differentiating within that.

How, what would you advise them to think about as they’re grappling with their own differentiation and positioning?

Mark Vigoroso: Yeah. Yeah, it’s a good question. So I think, you know, and this is something you, you know, you learn in, in business school, right? The differentiation is word that gets thrown around, but it’s, it’s mathematically correlated with profitability, right? So, you know, there, there’s, there’s a. Statistical relationship between the degree of differentiation of a company and its profitability, Because it, it stands to, it stands to reason that, you know, the more different you are alternative choices, the more you can charge for one thing, you have pricing power. Um, the, the, the more sort of, the longer the runway is, if you will. in terms of retention and expansion, and you have a, a longer time to, to earn more share of wallet at each customer.

So there’s a, there’s, a, it’s a very sort of mathematical relationship and so differentiation is something that think gets glossed over a lot and, and not, um, interrogated enough. At a lot of companies, um, by, and there are, you know, I think people who are trained in strategy, people that this spend a lot of time thinking about and barriers to entry and, and competitive moats.

And, um, you can really get trapped in analysis paralysis if you’re not careful.

Jeremy Balius: Yeah.

Mark Vigoroso: but it is something that. It has huge implications in terms of the financial success of your company, right? And so anyway, the long way around is saying is that with, with, especially with ai, if, if you’re, and, and if, if you put yourself in the shoes of, of a couple different stakeholders, right?

You put yourself in the shoes of software vendor. Think about it as an enterprise software vendor. That is selling an enterprise application, let’s say human capital like Workday or UKG or you know, some, some of these, um, HR platforms, right? And they, they are a differentiation perspective, they have to come up with why is AI an enabler of. A stronger, unique selling proposition for us. And then the people they’re selling to who also have a similar question to answer is, how is AI embedded in this application? Let’s just stay with the example of HCM or hr. How is this going to a differentiated employee experience? For my company, which more and more people and researchers and consultants are saying employee experience, um, is also a pretty strong predictor of financial, ex financial success and customer retention and all of that.

So you have these sort of questions that have to be answered, which is AI is nice. There’s sort of a halo effect that’s wearing off, but how does it differentiate? In terms of the selling proposition for the vendor, and call it the operational proposition or the financial proposition for the buyer, for the end user, the customer.

And I think what it comes down to is for the vendor, are nuances architecturally that say, okay, you can say that AI is embedded in our platform. It’s not just a bolt-on. is truth to the fact that. it’s better if it’s built in, it’s baked in than if it’s bolted on. Um, but you, but, but you have to tie it back to my earlier point about outcomes and say, okay, well I still have a very similar set of requirements as a buyer with regards to the experience outcomes that I’m trying to drive, whether that’s retention, whether that’s, Um, internal NPS scores or whatever it is that’s used to measure employee satisfaction, um, you know, career mobility, all the things, right?

How connect the dots. Tell me how, how is it, how is it doing that better, faster, cheaper? and, and that

And that that has to be credible, trustworthy, trustworthy um, and sustainable. For that vendor to be able to convince that buyer that, that that’s, that, that that’s all gonna be true. Right. So think it’s just

it is just an, you know, it’s, it’s kind of like a, an, you know, differentiation has always been important. Now with all of, with all of the groundswell around ai, you have to sort of be e especially vi vigilant that what you’re saying is not just propaganda and theater and marketing.

But it’s, it’s grounded in some of the very same that have underpin, underpinned, um, these types of transactions for many years, which is basically what are you solving for and what’s it worth to solve it? and why are you the best one to solve it for me? Right? And, and, you know, and, and by the way, can I trust you back

Jeremy Balius: Right.

Mark Vigoroso: you know, can I trust you?

Are you, you know? Right. And, and that is one of the reasons why. You know, I don’t necessarily buy into this sort of rise of the machines, um, terminology because, um, you know, relationships drive trust. Human relationships drive trust.

Credible, empathetic relationships drive trust. People who listen actively drive trust. Um, people who advocate with empathy drive trust. The, that, that’s, that’s hard to replicate with, with some of the best AI tools, gen AI on, uh, agent AI on the market.

So there will always be, not always, it’s hard to say always. There will be for a long time, a, a, a vital role for the humans. Uh, to play um, building these differentiated value propositions establishing these sort of bridges of trust, that drive these transactions that are in the millions of dollars.

So,

Jeremy Balius: Hooray for the humans. We,

Mark Vigoroso: not dead yet. Not dead yet.

Jeremy Balius: there’s still, there’s still a role for humans in go to market. That’s a relief.

Mark Vigoroso: Yes.

Jeremy Balius: Hey, what I’m, what I’m really reflecting on though, as you’re talking about that is what you mentioned earlier around, not a buyer, but 20 to 25. Individual humans each with a perception of value and each with a degree of technical or non-technical nouse and or, or, or experience and articulating value and differentiation to that many people.

To different degrees in ways that are not only addressing risk mitigation at organizational level, but at their individual role level, I think is a, uh, monster of a conundrum to, to grapple with.

Mark Vigoroso: it is. And it’s, it’s not necessarily, new. It’s certainly not new. This idea

Jeremy Balius: No.

Mark Vigoroso: buying committees or buying groups. However, um. It is. Some of the newness of it is that, you know, with, with, um, desktop ai, some people call it shadow ai, everybody has ai. There’s a lot more research that’s being done by the lay person, early in the process.

Right. And, and, and I think there’s always been some data out there that says that. Quite a bit of research is usually done before any vendors are engaged by the buyers, um, that are looking at enterprise applications or services. Um, but now it’s just more pronounced because you have more people with more access to very robust data. Um, that’s pretty reliable. Not always a hundred percent, but it’s pretty reliable and getting better. Um, so then you have this problem of a buying. Cycle that is multi-stakeholder, non-linear, has also been true for a while. It’s not a straight line. It’s not like there’s just one guy who gets more and more and more convinced until he finally makes a a purchase.

There’s multiple people on all different stages of maturity and understanding and knowledge acquisition and, the go to market organization for the vendor. Maybe they know six of the buyers. They don’t know who the other six or seven or eight are. Oftentimes they’re called hidden buyers right here.

These are these hidden buyers that may come in the last minute and they may pull the rug out from under the, under the deal at the last minute. To everybody’s surprise, you never knew who they were. They apparently had more influence on the deal than you ever thought. Um, but you didn’t get to ’em, you didn’t capture their mind, you didn’t capture their, their soul, their heart. Uh, may maybe, maybe they never heard of you. Maybe you didn’t do enough upstream branding.

Jeremy Balius: Mm-hmm.

Mark Vigoroso: kinds of woulda, coulda, shoulda have, but a very complex process. And, and what, what I think the shame is that, and this is one of the areas that we’re focused on with our clients, is, is that the alignment between. Sales and marketing organizations. If you think about go to market, is I, I like to simplify it

Jeremy Balius: to sit.

Mark Vigoroso: of three legs. There’s, you got sellers, you got marketers, and you got product people, right? So they’re kind of all part of this three-legged go to market stool. And they’re not always very well aligned.

In fact, they’re usually not aligned in my experience, not as well as they could be. And so what happens sometimes is you have. Uh, marketers who are doing their job, they’re generating leads, sales leads, top of the funnel, and they’re throwing ’em over the wall to the salespeople and then hoping that sales, those, those leads are all properly prosecuted and, and qualified and nurtured. and. There are great tools out there that help with this. There are great marketing automation tools and nurturing platforms and, but the reality is that there are a few metrics in, in sort of go to market effectiveness or even more specifically funnel conversion effectiveness that haven’t changed.

Right? They’re the best enterprise tech companies in the world are converting. Low single digit percentages of the top of funnel leads, top of funnel, pre pre-marketing qualified lead to an actual sale. So let’s say three to four to 5%. Um, it’s a pretty low number, right? And the average, some data says is between one and 2% of those.

Of those top of funnel leads ending up as. booked sales deals, customers, that’s a lot of leakage. That’s a lot of not, you know, it, um, I guess you could say missed opportunity. So, so what’s the ceiling on that? What, what should that number be? And, and so been looking at things like, okay, well let’s look at sales and marketing alignment.

What if after that sort of place where marketing throw those, throws, those leads over the wall to sales. What if marketing stayed involved to some degree or another, and they played a role in deeply understanding that buying group, making sure that those 21 people understood. Making sure that if there are three or four affinity groups aligned to things like finance and operations and technology and risk, that, that, that marketing sort of. Envoy is focused on nurturing with

Jeremy Balius: Treat

Mark Vigoroso: calls to action, with personalized, situationally relevant, industry relevant, credible, empathetic content so that you’re nurturing those to the point of either them down the funnel or out of the funnel so you’re not wasting time on the ones that are never gonna be deals. But you are spending the time on the ones that will and should become deals, But I think it’s a lot to ask most pure selling organizations to do that on their own. even with the help of automation platforms and sales automation platforms and email automation platforms. Um, and I’m not, I’m generalizing because there’s a lot of variability in what I’m saying, but in my own experience working where I’ve worked, I’ve seen cases where, that dysfunction or disjointedness between sales and marketing has, really been reflected in. The, the fruit that comes outta that funnel and the fruit that you get from spending all that money on top of funnel lead generation. Right. So, anyway, I got off on a tangent, but, um, that’s, that’s, um, that’s, uh, that’s a, a huge, a huge problem that we’re trying to, we’re working with a number of our clients on, on that specific problem statement.

So.

Jeremy Balius: I don’t see it as a tangent at all. I think it’s given us a real insight into, uh, the enterprise edge and your methodology and, and your thought process. And so I think you’ve really painted a strong picture there of assessment and, um, and consideration around what, uh, what is and what. Could potentially be versus what should be, and,

Mark Vigoroso: Right.

Jeremy Balius: and the rigor required to figure that out, I think is really strong.

Mark Vigoroso: Yeah, that’s right. That’s right.

Jeremy Balius: Speaking of enterprise Edge, where are you headed? What’s, what’s the roadmap? Where, where are we going with this?

Mark Vigoroso: Yeah, that’s a great question. It’s, it’s, um, let’s see. So today we have, um, five, uh, very clearly defined products that tackle some of the issues I just talked about. Um, there are five more that are in development sort of for next phase of the company, that all have sort of adjacent, problem statements, opportunity statements associated with them all in go-to market, all in. Sort of think about that three-legged stool I talked about. I’m, you know, working with the CMO, the CPO, the CRO people who are, um, responsible for. Uh, building the right products, marketing them correctly, selling them effectively, and growing the top line. That’s profitably as well. But, um, that’s all, that’s the sort of the true north.

We’re trying to accelerate growth. that is the vision. Um, you talk about differentiation, I’ve spent quite a bit of time thinking about. What’s different about the enterprise edge and is that gonna change over time? is it sustainable? Um, and I don’t have, so I, I’ve spent a lot of time thinking about it.

I’ve come up with a few things that I think, will be true for a while anyway. One, one is that we do have this 360 degree, um, domain experience, right? So we’ve, been vendors, we’ve been. End users who’ve been advisors and consultants, have an advisory board of 12, 13 people that come from all walks of life.

15 different industries, three different continents, 350 years of collective work experience. 60,000 strong global network of buyers, vendors, and investors. Um, that hard to replicate, um, and will be something I leverage and have leveraged. but we’ll leverage going forward. Uh, is that sort of the network, the community?

Right? The, the o The other thing is that we have, um, points of view. We sort of have this notion that you mentioned the, uh, the SAP Nvidia point of view. We, we do a bit of, um, social network engagement.

So we’re publishing points of view, um, quite frequently, almost every day, every week. Uh, engaging with the market, putting our points of view out there on why we think stuff matters, what people should do about it. Um, everything we write ends with something that says, what’s your edge? Which basically means do you do with this? You know, if you’re a CFO, if you’re a CIO, if you’re a CDO, if you’re a ciso, what do you do with this information? Right?

It’s not just reporting. Its analysis and its perspective and its recommendation. and what that does is allows us to stay very deeply engaged with, um, stakeholder in the enterprise, tech space, investors, integrators, ISVs, GSIs, um, people on LinkedIn. They come outta the woodwork, right? We publish something. I published something today on, um, on, um, SAP. What was it? Um. See, I do so many of them, I can’t even remember.

But it was about SAP and it was, it was, uh, um, gosh, I’m gonna have to find it. But basically you put it out there you, almost like you’re, it’s an offering. It’s like, does anybody have any ideas or thoughts or feedback on this? This is our thoughts. And, and it, it engages the community and it actually drives our business.

And so our tagline is. AI native digital, first community driven, kind of speaks to the differentiation, right? AI native, everybody’s saying that, but we truly are. AI is sort of built, built into everything we’re doing. Community driven is unique not a lot of sort of pure consultancies or advisories have invested in a, a community like, you know, a network. And it’s almost like we are, we are slotting into the influencer marketing programs. Of a lot of the ISVs that we’re working with. In many cases, influencer marketing is its own budget line next to ar. Endless relations, public relations, corporate communications, corporate affairs, public affairs, right?

And now there’s influencer marketing, which is not always its own line of budget, but it’s its own thing now. And so we kind of can play that. We can swim in that lane a little bit. Because we have this network, we sort of are kind of an influencer, but we also have these core products that, that we’re selling to the go-to market organizations of technology companies to help them grow faster. Right. Which is, which is very, um, sort of a targeted, almost a productized consulting offering.

Um, so we have sort of this, sort of a few different logs in the fire and where we’re headed is. know, there are areas that, um, are unaddressed in the ways that buyers and sellers in enterprise tech interact. There’s a, there’s still a lot of inefficiency in how buyers make the decision about why, and how. To deploy various types of enterprise tech there’s inefficiency with the, with the way information is gathered. AI has made a huge difference there. But there’s still, you know, think about the RFI process, right? And the RFP process, right? Where, um, there’s been some advancements and advancements made, but there’s some more AI assisted

Jeremy Balius: AI.

Mark Vigoroso: that could be made in. How and sort of think about compressing sort of a lot, a lot of those back and forths between a buyer and a seller where an RFI or an RFP has been issued and there are being given, and then there’s a valuation of those responses and then there’s scoring of those responses. And you can start to think about all the AI applicability. In everything I just said, you know, writing the response, scoring the response, right? AI could assist with a lot of that and compress that timeline tremendously so that’s another little sort of kernel of opportunity maybe down the road for us to play in. Um, and there’s, and, and be honest with you, there’s a whole catalog of things that we could do for. The buyer community.

Right now, all five of our core offerings focused on the go to market teams of the technology companies. We’re helping them grow, we’re helping them market and sell and grow. We’re we right now are not contemplating any revenue or commercial relationships with. The buyer side, the CIO, the ciso, the COO of corporations, right?

We’re not, we interact with them all the time. They come on our podcast all the time, but they’re not paying us for anything. So that could change down the road. But lots, lots of, uh, lots of runway ahead and, but it’s exciting times to, uh, add some value and, and help some, help some people that are innovating in ways that. deserve more attention than they’re getting and we can maybe help them with that.

Jeremy Balius: Yeah. Exciting times for sure.

Mark Vigoroso: Yeah.

Jeremy Balius: This has been so fascinating. We’ve been wrestling with some really big talk topics, but I really appreciate the way that you are talking about it, articulating the complexity just in a real refreshing way as well, and, and providing practical and practicable advice. Really appreciate you coming on the show, mark.

Thanks so much for that.

Mark Vigoroso: Oh, it’s great. Thanks Jeremy. I appreciate it. And um, I’ll have to return the favor, we’ll have you on our podcast next time around.

Jeremy Balius: Done. Let’s do it