Stop Using Sh*tty Data. You CAN'T Achieve Autonomous Revenue Without This - with Elio Narciso

The current state of RevOps and CRM data is broken, plagued by a manual work tax where teams spend countless hours compiling, cleaning, and validating data instead of executing strategic go-to-market motions. Elio Narciso points out that even at top-tier companies like AWS, CRM data is often outdated and inaccurate, leading to massive inefficiencies. The CRM industrial complex has failed to solve this foundational issue, forcing reps and operations teams into tedious spreadsheet work just to figure out who to target. With the rise of AI, the solution isn't just to automate outreach—because automating bad data just creates more noise. Instead, GTM teams must focus on automating the orchestration of data hygiene, enrichment, and prioritization. By deploying AI agents to absorb the repetitive grunt work of de-duping accounts, establishing hierarchies, and prioritizing leads, companies can unlock an autonomous revenue engine. This empowers revenue leaders to dynamically adapt territories and campaigns based on real-time, high-confidence insights rather than relying on an annual, manual planning cycle.

Discussed in this episode

• How the manual work tax forces RevOps and sales reps to spend hours manually validating and enriching CRM data.
• Why the traditional CRM industrial complex failed to maintain data accuracy and establish a true source of truth.
• The danger of rushing to automate email outreach without first fixing the underlying foundational data model.
• How AI agents can autonomously handle tedious tasks like de-duping CRM records and assigning contacts to correct accounts.
• Why CROs must treat RevOps as a highly strategic function rather than a reactive ticket-taking or IT support role.
• The necessity of using AI-driven workflows to filter, de-anonymize, and prioritize high-volume product signups for sales.
• Why continuously recording and analyzing customer calls with AI is essential for pressure-testing ICP and messaging.
• The shift toward the CEO as Chief Marketeer and the growing trend of founders building in public to cut through market noise.

Episode highlights

1. 0:00 — The manual work tax in go-to-market teams
2. 2:30 — AWS experiences and broken CRM data
3. 5:00 — Why the CRM industrial complex failed
4. 8:15 — Leadership's misunderstanding of the strategic RevOps role
5. 11:00 — Automating orchestration versus automating bad data
6. 14:20 — Delegating boring CRM cleanup tasks to AI agents
7. 18:45 — Using AI to filter and prioritize product signups
8. 22:30 — Why GTM frameworks fail when leadership delegates too early
9. 26:10 — AI as a foundation, not just a bolt-on feature
10. 30:00 — The evolution of the CEO as the Chief Marketeer
11. 33:20 — Rapid fire: Overrated tools and dead SaaS advice

Key takeaways

• Automating bad data only scales your mistakes and generates market noise.
• RevOps must be a strategic partner, not just a reactive ticket-taker.
• Delegate tedious CRM deduplication and enrichment entirely to autonomous AI agents.
• Record and analyze every customer call to continuously pressure-test your ICP.
• AI orchestration should solve data hygiene before automating sales outreach.

Transcript

Welcome back to another episode of the Bridge the Gap podcast powered by Revenue Remagine. Today's guest is Elio Narciso, the co-founder and CEO of Scalesac, where he's leading a team building what he calls an autonomous revenue engine. It's a system that doesn't just automate GTM work, it actually eliminates the need for most of it altogether. He's run GTM for startups at AWS, sold companies, advised high growth teams, and now he's focused on killing the manual work tax that slows revenue teams down.

This isn't going to be a fluff episode. We're going to talk RevOps, AI, what GTM could look like if we actually got out of our own damn way. Elio, thanks for joining the show, man. Thank you, Adam.

Great intro. Uh, nice to meet you both and, uh, happy to be here. Awesome. Elio, thanks for joining.

Um, I love that the first part of the intro that I really like sparked my interest was the manual work tax and, and what that is. So, you've called the current state of RevOps a manual work tax tax. What does that look like in most companies today? I think it applies not just to RevOps but to many, many go-to market teams.

Um, the, uh, inspiration for this was born, uh, out of my time at AWS. Um, which, you know, I joined after a couple of startups, companies that I created and before joining AWS, I thought, okay, I'm going to join like one of the best companies in the world. They're going to have everything figured out, every system, every tool is going to work perfectly and data will flow magically. And then it wasn't the case.

Um, we had the same problems. Uh, I mean, obviously there were certain things that they do and they were doing like extremely well, um, but also a lot of the things that I had experienced in my own like companies were like, uh, similar. And so, for instance, I run, as Adam said, like a program to support the go-to market for middle-to-late stage startups. Uh, they were customers of AWS and we were supporting them in their go-to market.

Now, in order to decide which startups would deserve, uh, more support, would deserve more resources, more AWS credits, marketing, et cetera, we basically had to prioritize. To prioritize, we had to look at a huge list of startups. Um, and like, uh, decide based on a number of criterias, which were like, uh, worthy of our attention and support. And I tried to do this on Salesforce, which is, uh, AWS CRM.

Uh, the data in the CRM was terrible and, uh, it was outdated. Yes, yes, yes. I tell you, unique. And, um, and so basically what I started doing is a spreadsheet.

So I put together a spreadsheet manually, uh, with like some Zapier connectors to Crunchbase and to LinkedIn and to ZoomInfo in order to map the market and understand like what startups would be worthy, um, of that support and additional, um, marketing and sales or co-selling, uh, support by AWS. And the list became huge. Tens of thousands of companies. I mean, imagine startups, uh, that are created every year like, and then prioritize them and trying to make sense of this data, and it became like a huge mess.

And that was, uh, the point where for me, um, you know, the idea that this is not just me at my startup or growing companies, but this is also me at like AWS, one of the best companies in the world, then like this must be true for a lot of other people. And, and so it's not just RevOps, it's like reps that need to do research on their prospects, or like marketing teams that need to make sense of, uh, leads and signups and decide which one should be sent to sales. Because if you send them all to sales, like, you know, um, unenriched or unprioritized, sales is not going to work on them. Uh, or RevOps teams who are tasked, um, with making sense of all of this data and build sort of like a foundational model.

And so, um, that's what the manual work tax is. Is like the time that I had to spend building that spreadsheet, the time that the rep needs to spend like researching stuff on Sales Navigator, which is not like the easiest tool to use and you can spend like hours. Oh, come on, it's easy. Yeah.

Down the rabbit hole. Yeah. it's it's it's a Microsoft product, y'all. Down the rabbit hole.

Yeah, it's funny you say this because um, I worked at Oracle and I had that same aha experience moment where it's like things should be working much more efficiently or effectively. And they own their own CRM and they own like they're like it was just it's very it's the same thing. Um, why haven't all the RevOps tools actually fixed this before like this problem? Like shouldn't have this already been fixed?

100%. And I think that the CRM industrial complex should have fixed this. Because, um, you know, like we call CRMs, people call the CRM like the source of truth. But if the source of truth is full of like uh, outdated and or bad data, then, you know, what source of truth, um, does that, you know, represent.

Um, so I do think that, uh, the CRM, um, should have solved this. They haven't. The problem is complex. And I think that AI presents both the catalyst for understanding that the old model where like, you know, you laugh when I said like, oh, the data in the CRM was bad, you know, this is true for every company.

And like, until very recently, um, there isn't much that you could do about it, right? So, now with AI, your competitor will start getting better at data in their CRM and will start like prioritizing their sales and marketing efforts better and it will become a competitive advantage. So, in the age of AI, data will impact outcomes disproportionately. So if your data is bad, then like even if you feed it to the best AI, the results are going to be bad.

And so, AI represents a catalyst for change, but also the reason why we can now work on that data, because the Scalestack platform would not have been possible like four years ago. Yes, we could have done like, you know, automation and workflows and all of that, but without the agentic component, I mean, we have agents that go into the CRM, decide like what data source is best for any data point, that decide, you know, like when they have enough confidence level about that data point and when they need to release other agents to do research to complement and improve the confidence level about that data point. So, all of this was not possible until very recently. Uh, and now it is.

And AI represents as I said also the catalyst for change. I love that. So it is a big catalyst for change. But when you look at, um, specifically like why the CRMs haven't fixed this, um, and where AI is or isn't being used.

Is this more of a tech problem or or is this more of a leadership problem? So, uh, I I've done like a number of like uh roundtables with uh CROs, um, over the past like six months. And I have to say that it is not always clear to the CROs what the role of RevOps should be. RevOps is really important and it's like, you know, the core of systems and processes and technologies, but also it's a very strategic component of the go-to market machinery because it owns the data model.

And so, I've heard CROs like, you know, talk about their RevOps as like systems or processes or like handling tickets. And that's the wrong attitude. You want RevOps teams to be strategic. You want to rely on them for like the data that will be used to prioritize sales and marketing efforts.

So, like, CROs know that they have to distribute an equital book of book of business across the sales force, right? So they know that and they do that, but they do it like very manually. They do it like once a year like everybody's rushing to like say, okay, how do we distribute the accounts? In order to do it well, you should rely on our RevOps team that is empowered with the tools and systems and the data to say, okay, this is what this account is worth.

And so, how the way I patch the territories or the account or distribute the book depends on what is the value of each account and so I can distribute that equitably. And so, I think that there is a leadership problem in that sense that sometimes there is like a misconception of what like the RevOps role is. But then there is also, um, a technology, uh, gap. I think, you know, until very recently, essentially there was either data, plenty of data out there.

ZoomInfo, Crunchbase, LinkedIn, you know, but the key is how do I align that data to my ideal customer profile and to my go-to market strategy, which will change, you know, for each of us, right? 100%. And that ties exactly into where I want to take this for a moment. So, we talk a lot when it comes to AI and go to market about automization versus orchestration.

And I think a lot of folks just think, oh, we're going to automate it. We're going to automate it. And we say all the time, I I think Dale, you posted about it this week, if not two or three times. Automating, forgive me, shit, is just going to get you more shit, right?

If your ICP's wrong and you automate outreach, you're you're reaching out to the wrong people. If your buyer persona is wrong, it's the wrong people. If the RevOps data is wrong, you're automating bad data. Where where do you come in when you look at what you're building specifically?

Where do you automate versus where do you orchestrate? So, we believe that the orchestration should be automated. Tell me more. I think that the instinct, um, in the go-to market space has been, oh, let's automate like sending emails.

Let's automate like, you know, let's let's say the rush to create like AI SDRs, right? So, to automate a lot of like the last mile, uh, elements and, frankly, a lot of the things that humans should be doing, like, you know, a good email or like a good outreach or a good engagement should be, and it is like, like what humans know how to do. And instead, we haven't devoted enough attention on like automating all of that like, frankly, boring work that goes into cleaning your CRM data, removing duplicated accounts or leads, or like uh, building better hierarchies between like accounts, or assigning contacts to the right accounts and then calculating the time in each account, or like de-anonymizing leads, et cetera, et cetera, et cetera. All of that, frankly, is extremely time consuming, uh, repetitive, boring work that I don't really want people to do.

And so, to me, like, if we can achieve, and that's why we call Scalestack Scalestack an autonomous revenue engine, because we want to automate all of that, which is an orchestration. And so, we have agents that compose and then run workflows to achieve like that cleaning, that enrichment, that prioritization of the data across the CRM. Are there tasks that should never, ever, ever require human intervention at all? I mean, a lot of this stuff, I think that can be and should be delegated to AI.

Uh, there was an artist, uh, I forget her name, unfortunately, that recently, like a few months ago, like became viral because she said, I want AI to do my laundry, not to write my poetry and stuff. And that's sort of true, no? So like, if I push onto AI all of the stuff that people frankly don't want to do and find boring, I think that that's a good place to accelerate a lot of the stuff and and and relief people like RevOps. If a RevOps team needs to spend like three months to clean and de-dupe the data.

Their mental power. I'm going through this with a client right now. It's driving me nuts. Right.

And so, at the end of that process, you're not going to have like the same energy that you had when you started. And so, maybe to the most strategic last mile component, you're going to devote less energy. Instead, what we aim and what our customers achieve is that they input the business logic and the criterias that they want to achieve or the use cases that they need to solve. We absorb all of that complexity with the platform and then they, they, meaning the customers, monitor the outcomes.

Has the data hygiene increased? Do we have like a good hierarchy? Have we removed all of the accounts that are duplicates, or like have we reassign contacts to the right account and then clean all of the contacts of like bad, uh, data and updated and added like new data only when the foundational data model was done right? So, we think that all of this can be done by agents.

Right now, the platform is heavily run by agents, but supported still by like humans, like ops people that like uh run the workflow and make sure that everything is running smoothly. I see a future like, you know, around the corner, literally where like our workflows will be composed and run autonomously by agents. Awesome. Um, is there is there a place and is there a place to make sure automation doesn't create too much noise?

Is it like are we generating too many noise pieces? And and along with that, as you were just saying, people still need to like strategically think on the the input to put into these systems, because I think that's where people are like, I'm just going to download something and we're just going to run it. They haven't done the strategic thinking part of it. But and and maybe maybe they combine together where you may be getting noise if you don't do the upfront work.

Right. So, I think that until now the instinct has always been, oh, our CRM data is terrible. And so, let me add more data, which adds noise. Let me create a new list.

Let me add like new prospects. Let me add like new companies. Let me add more data and signals and intent and all of that stuff. And that creates a lot of noise.

Our stance is that like, and mind, you know, like we work with larger go-to market teams. We work with companies that have at least like 15, 20 reps and up. Uh, companies that have a few years in market, already way beyond like product market fit. So, they have like already an established presence and go-to market in the market.

At that stage, if you don't figure out like the prior data first, just adding more data will add more noise in our opinion. And so, first figure out the data model, like figure out like what worked in the past and how and what are the best customers and how to prioritize the efforts of the sales and marketing teams going forward. But then once let's say you've cleaned your data and built that data model, I think that we believe, you know, like strongly that like in the new world, the spray and pray is gone and so the best teams are those ones that really know how to prioritize. And so, to prioritize for larger companies, you need to rely on data.

And so, how do I equip the sales and marketing teams with great data to tell them, these are the accounts that you should focus on today, this week, this month, which will dynamically change. It's not something that you only do once a year during the sales, you know, annual sales planning, but will dynamically update itself over the course of the year, depending also on your changing like marketing strategies or go-to market like uh strategies and all of that. And and so, it's all about prioritized. For instance, we just deployed like a fantastic, super like uh complex agentic workflow for one of our customers, um, MongoDB.

And they have a, uh, free tier product called Atlas. Atlas is super popular, and so they let anybody without a credit card register because like they've used it historically as a pipeline. But the way they have used it is that like there are hundreds of thousands of people that register on Atlas, developers. They would not really act on that data until like somebody would raise their hand and say, hey, I want to talk to sales.

But what we have done for them is deploying like a workflow that enables them to first filter and de-anonymize profiles at scale, leveraging data from multiple data sources, internal, external, third-party data, agentic research that is done within the workflow, and only a very small subset of these signups are then like fully enriched with a lot of insights and signals around like the company, the person, if we find value in those signups or leads. And then this becomes a subset that sales can work on, or marketing and sales can collaborate on, or they can do like social media campaigns or ABM campaigns and all of that. And so, it's not sending an email to the hundreds of thousands of like Atlas signups, but only to those for which like you have a high degree of confidence that could be an interest and why. People buy from people.

That's why companies who invest in meaningful connections win. The best part, gifting doesn't have to be expensive to drive results, just thoughtful. Sendoso's intelligent gifting platform is designed to boost personalized engagement throughout the entire sales process. Trust me, I led sales for a Sendoso competitor and I could tell you, no one does gifting better than Sendoso.

If you're looking for a proven way to win and retain more customers, visit sendoso.com. Yeah, that's um, I I really like that that that flow because there is places where people are getting too much data and they don't know how to act on the data. So like getting really specific.

And this And it goes right back to what you were talking about earlier is like the structure and the the real thinking up front because you have to do the thinking and the strategy up front before you build the system or else you're not going to get the data you want out. And then people are like this AI stuff doesn't work or it's not working the way I, you know, I see all this stuff on YouTube, whatever it is. Um, so it's it's very interesting. Um, let's let's transition a little bit.

You you've worked at a bunch of startups. Um, and you've worked at AWS, so you've worked in many different places. Um, when GTM isn't working, what's usually behind this like what's usually broken behind the scenes? Uh, I mean like, uh, there is a wide range of options, but I do think, I mean, first of all, it always starts with leadership for sure.

And and that's why I think that if we talk about like B2B startups, for instance, um, why do we say like, oh, the founder should be like, you know, the key seller until at least like a million dollar in ARR. So, I think that that's for many reasons, but one reason is that like, you know, the leadership, which is for startup is like the founder, needs to develop like that knowledge about the market and the customers and like include that knowledge in motions that become more and more established. So, I I take the example because like I do think it's always like from leadership, like, you know, so if like, um, a founder doesn't do a lot of sales or like delegates this too quickly, like probably things are not going to go and work out. Uh, or if in a larger company, um, the leadership is not like setting like uh a goal or like uh, you know, like uh a vision for what they want to accomplish, probably there it's not going to work out.

I mean, at Amazon, what I appreciated, for instance, is like one of the great things about Amazon is that like uh writing culture. Amazon doesn't move unless like for any product launch or new program or initiative, unless you write a doc. That doesn't need to be a PowerPoint, it's actually a long form, like typically six-pager like Word document, where like people go crazy and in in a sense that like, you know, they debate a lot around that document, but that generate a lot of us alignment about what to do. And I think that that's very important, especially for larger teams, um, because you always have to have like, you know, a North Star.

And I think that this changes every year. So, like uh, leadership needs to lead by example. Number one, the example of the founder, and then like they need to set like a clear like vision and mission and goal, which will change, will change during the year also, but like for sure like every year. But it needs to be clear, understood and hopefully simple.

You cannot have like a myriad of goals. You need to have like probably one or two goals that are the North Star for the action of all of the team. And then I do think it's all about like the data. I really believe that like, especially at scale.

So for sure at scale, but like in any go-to market situation, like once you have good leadership, once you have like a good vision and goal, like it's all about the data and knowledge about like who to target in order to make everyone very efficient. And so, like, do we have for marketing teams? Do we have like a clear understanding of what's the ICP and what are the buyer persona? I mean, many times companies have like a wide range of interpretations and lack of clarity and maybe, you know, maybe somebody in the go-to market team knows, but the product team doesn't.

And so there is a lot of misalignment that generates problems. And and it hasn't been changed for two years, right? So it's like they're working off of old data, like, so, so to follow up on that question, um, and I seem to be asking this every time, um, how often should your RevOps, your go-to market team, whoever it is, be pressure testing those what we're calling GTM foundations, which is ICP, buying persona, value proposition. Like what does that pressure test time frame look like?

Yeah. I think that with AI, for instance, we are implementing now like, you know, very simple workflows that anybody can do, so you don't need to buy ScaleStack for this. Well, like, we record every sales call, we record every customer call, and then we have like simple workflows to get the transcript, analyze them, and like, you know, what are the pain points? What are like the things that resonated?

What are the things that didn't? What are And so this constant learning is so important. And so, for sure for like a company like us, like, you know, let's say seed to series A stage, is like essential because every three, six months we'll need to rethink this and make sure that we are like pressure testing ourselves that we're focusing on the right companies and people, et cetera. But I would say for anybody is like, you have to listen to your customers and like we have so much data now that it's easy to be processed with AI that not not to use that data is a sin.

And I'm learning, I mean, we just launched, uh, relaunched our website recently. A lot of the content of the website is the byproduct of like spending a lot of time on customer calls. We have recorded hundreds of customer calls, distilled them into what is that they said? What is that is important?

What are the pain points? And then take them and transform them into like some of the copy of the website. Um, and so I think that that's basically something that you have to do all the time, but maybe like in a more structured way like, you know, every quarter. I love it.

I I agree. So so many people don't. Like we we talk to so many people who like we have a client now, no joke, they don't record any of their calls. And to me, like whether you're using that to create your website or like it is a sin in go to market to not be recording your calls and understanding what works, what doesn't, what are your customers asking for, what are what's the product feedback?

Like I I literally I I don't want to say nothing shocks me, but like holy shit, this one shot like wait a minute, you you've been in business this long, you have ten reps and you don't record your sales calls? Well, there are industries like finance or healthcare where like that is very difficult. No, not that. Yeah.

But if it's not, then like it is like problematic. I mean, but I find this even in consumer. I mean like, you know, when like they send you an email and you reply and like it's do not reply. I find that like so crazy, like, so those same companies that send those emails that have do not reply spend millions and millions of dollars in like, you know, marketing campaigns to target and then when a customer wants to reply to them, oh, this inbox doesn't like get, you know, doesn't get like analyzed.

It's like crazy to me. You want to gather every customer input and so if they want to reply to their email, let them. Don't say do not reply, which is crazy. You common sense is only common to those who have it.

Um, so AI in your view and in our view as well, isn't a feature. I think a lot of people right now are thinking AI's a feature. And I think we all agree that AI is much more of a foundation, um, as we're halfway through 25 going into 26, it's not something that you're bolting on top of your workflow. You're actually building from AI as a core.

What's different in the building approach in that sense? And, you know, as you all are building, like, where does it where are you finding AI breaks most in that GTM stack that it's requiring more effort to really get it right versus just like plug and play? Uh, I don't know, I haven't heard like, you know, like, oh, it's a feature. I've heard like, I think it's a systemic change to the way we work.

And I I believe that like 100%. I think that like it will completely transform the way people work. And it is already. Um, I started my career in mobile technology.

Like in the early 2000, I I'm Italian originally, so I started in Europe. In Europe, we had mobile phones before the US. This is the only like technology, uh, like recent technology that like Europeans got like earlier. Then, you know, the iPhone came in and like, you know, basically they own like Nokia and Ericsson, all of those European companies that have been formed before then.

But it reminds me of that. So like the sea change that there was when mobile phones were introduced, but at a much faster clip and like, you know, instead of replacing like some communication methodologies that were used before, like landlines or like uh, fax or all the stuff, um, it's re replacing and completely reimagining the way people work and like uh, process data and so many, many more things. So, I think it's uh, uh, an incredible opportunity. It has like a lot of risks, obviously.

Um, But the speed is what's impressing me. I mean, our platform, you know, let's talk about my little world that I know well. Our platform has made like an incredible progress over the past six months and every week there is something else that we couldn't do like a few weeks before. Uh, oh, this is now like finally we can do this or we can like, you know, automate that, or we can like, you know, increase the speed or even reduce the cost because also there is so much competition between all of these big platforms now, much earlier than say the competition that started to come from like AWS versus uh Microsoft versus Google.

Now like all of these platforms are competing head-to-head. Prices are going down, speeds are increasing, capabilities are like enormously advancing. Um, so, I think it's gonna, uh, radically change everything, um, and very, very fast. So, Yeah.

The recommendation is that any go-to market teams embraces this change because otherwise your competitors will. And I do think like that RevOps is an interesting area. I see many companies coming to us and say, or like RevOps is going to be the playground for a lot of AI initiatives. Because like, you know, it's central to that foundational data model, it's central to go-to market, to revenues and so like, we want to start from there, rather than say customer service, or rather than say, I don't know, finance and all of that.

Yeah, I was um, when I was at the gym this morning, Dale will be shocked that I said that. Um, but when I was at the gym this morning, on Squawk Box, uh, the CEO of Lattice was talking and it was all about the effect that AI is going to have on jobs. Not so much again, eliminating, but like if you are not embracing AI, if you are not using AI, if you are not deeply learning AI, for everyone who sits at night and just scrolls through Instagram on on bullshit, like take that time and like upskill yourself. Um, you are going to be at such a competitive disadvantage for for for forget six, 12 months from now, I would argue three months from now, um, that you're going to have major, major problems.

Yeah. Sorry, Dale. I cut you off. No, no.

Um, and and I'm curious as we as we progress like where's where's GTM headed next? So fast forward a couple of years, you know, what's one part of GTM that's going to be completely different um than it is today, besides, you know, besides what you're doing within ScaleStack and RevOps, like where's another place inside of the GTM playbook that's going to be completely different? Well, I I think that we are seeing it, um, at the startup level, like the old playbook of go-to market of, I don't know, like uh, uh the white papers or like uh, the um, you know, marketing campaigns or like search, um, you know, paid search and all of that, has been like uh quickly, uh, changed for the CEO is the chief marketeer. And and some examples came from the larger companies.

Think about like Mark Zuckerberg. He's the chief marketeer of Meta. And and, you know, it's not that obvious. It wasn't like that like, you know, 10, 20 years ago.

Right? But like, we have this like CEOs that are chief marketeers. And so they need to embody and represent like the company, the brand and the message. And then in-person events are super important and like uh, humans will keep buying from humans.

I think that that's will stay the same and we just need to become better at like optimizing those experiences. I think that there is gonna be lots of interesting stuff around like events. Um, the events industry that are going to happen over the next couple of years. Uh, because people are craving for like uh, true like connection and better understanding and, you know, understanding the landscape, understanding what's like noise, what's important and who are like people from whom I want to buy.

Um, and then like uh, I think that, uh, we're seeing, and this is already probably very advanced, that like a lot of companies B2B SaaS are like uh, content machines now. And content is king, um, in like, you know, that's why we're doing podcasts. That's why we are like, um, you know, ourselves like uh, we have our own podcast. We do like clips and we do interviews and we do like roundtables and all of this stuff, um, because like if humans keep exchanging this knowledge, like, you know, will continue to represent what's like great about humans, which is this like connections with other humans that generates ideas and then like can get implemented maybe by AI.

You know? That's probably, um, that's how I see it like, you know, for us like uh, I wasn't the chief marketeer of my last startup. I was actually pretty quiet. Now we have like CEOs building in public.

Yeah. Uh, and that's interesting. It's an interesting trend, no? So like, you know, I don't think it's appropriate for like a company like ScaleStack that is like more enterprise focus.

I don't want to like, you know, clean, wash my dirty laundry to my enterprise customers. But, I mean, for other companies it's very appropriate and it's very interesting and it generates like a lot of attention and interest because there is a lot of noise and so how do you raise yourself above the noise, which is the goal of go-to market, no? How do you make sure that you identify people that will, uh, understand your message and feel that it resonates with them and they are interested in knowing more. Yeah, I I I agree with you 100%.

I don't know how I feel about the whole building in public thing. It's not I get it, but I I regardless of, you know, whether it's enterprise or SMB, I'm not a big fan of airing my dirty laundry to anyone. Um, but that's just me. Um, and I I think I'm pretty open on like things like LinkedIn, but like they my customers don't need to hear when Dale and I, you know, have a massive disagreement about something and like it it doesn't matter, or when one of the AI agents that we're building broke for one of our customers and now we had to scramble to fix it.

Like, no one needs to know that shit. Um, all they need to know is it works and we're doing great. Um, all right, let's go into some rapid fire as we wrap this up. Um, I have some we both have some questions that hopefully will, uh, spur the brain.

Ten words or less. Uh, the goal is to get through as many as we can. What is one GTM tool that you think is massively overrated? Clay.

You're not the first, second or even tenth person who's told me that. Yep. Yeah. No, I let let so let me so Clay, we compete with Clay.

And Clay I need to thank Clay because without Clay, I think the need for ScaleStack, um, would not have been understood. I think that like last year we were fundraising, Clay announced like their huge round and, you know, some investors came to us and, oh, like, but then the Clay raise. Actually what it generated is more curiosity around what we were doing because often we say, oh, we are Clay for the enterprise. And so, I actually like them, thank them for what they've done and they are actually based in New York like me.

So. But on the other hand, I think that like uh you cannot be everything for everyone. It's not like um it's a great tool for like startups and smaller companies. I think it's not the best tool for many other companies.

Um, and then like their strategy of like uh increasing the awareness through like uh the agencies and the promoters and the influencers, paid or not, you know, like uh it's been a little bit too much, um, frankly and like uh the advantages of the product are clear but they are not everywhere. Um. And so, I think it is a little bit overhyped right now. Yeah.

Um, what's one GTM task no human should be doing in in 2025? Cleaning the duplicates in your CRM. Uh, I love that that one came up. What's uh what's one piece of SaaS sales advice you just wish would freaking die?

One piece of SaaS advice? SaaS sales advice that you just wish people would stop throwing out there. I don't know. I'm seeing a lot of uh stuff about pricing and like, you know, uh It seemed that for a long time, uh, like SaaS pricing was very stable.

It had like a per seat and then like, you know, some additional features and like, you know, discounted pricing if you commit for like X amount of time. I think that like all of that is like being, uh, thrown out of the window right now and I see a lot of people now like, um, suggesting lots of different pricing methodologies. The reality is that like, you know, we don't know yet. We it's very hard like uh to understand like where we will land.

If we will land to the same place as like, oh, it's uh SaaS is priced per seat and that's it. You know? I don't think we will land that way. I see like, you know, we are pricing based on workflow plus like uh usage, um, but like evolving quickly.

I think around outcomes, so like we'll see where we land. So, a lot of people are like uh sending advice around the pricing of AI. I don't think that we know. Yeah.

I'll trap up with a uh a bit of a lighter question. What's your dream vacation destination? Dale loves this question and he doesn't travel anywhere. Really?

He doesn't, Adam doesn't know me. I just don't travel now. I used to travel a lot more. Yeah, that's what happens when you have teenagers in college.

He'll learn that soon. Yeah. I love traveling. I'm from Italy.

I'm lucky that I get to go to Italy like uh a couple of times a year. Um, and I've been in many, many countries. But my one of the most the best places I've been recently is St. Lucia.

I think I'll be back, you know, soon to St. Lucia. Um, and, um, so it was it's an incredible magical place and like uh beautiful uh sea and water and like climate and all of that. So, I'll be back.

Nice. It is a gorgeous place. I'm sensing a scale stack meeting in St. Lucia.

Yeah, an offsite in St. Lucia. Elio, thank you so much for joining the show. Where can people find you?

Where can people go learn more about ScaleStack? It's uh scalesack.ai. Actually super proud, we just released a new website which I spent like three months obsessing about.

So please go see it and uh, and um, and check it out. And then uh, my name is Elio, E.L.I.

O. Narciso, N.A.R.

C.I.S.O.

And uh, and thank you for having me. Thanks for being here. Cheers. Thank you.