For years, we’ve heard about AI transforming software development. But what if that same level of agentic, AI-driven collaboration could be applied not just to writing code, but to writing your entire go-to-market playbook?
Agility requires that your go-to-market teams operate at the speed of insight, not at the speed of manual data entry and fragmented workflows. This means empowering them with tools that don’t just provide data, but automate action based on strategic intent.
Today, we’re going to talk about the concept of an ‘agentic’ go-to-market platform, where AI doesn’t just assist, but actively collaborates with sales and marketing teams to automate entire workflows, from strategy to execution.
To help me discuss this topic, I’d like to welcome, Marcio Arnecke, Chief Marketing Officer at Apollo.io.
About Marcio Arnecke
As Apollo.io’s Chief Marketing Officer, Marcio Arnecke brings a visionary approach to scaling high-growth B2B SaaS marketing in the AI-driven sales landscape. With over two decades of experience driving revenue acceleration across global markets, he has consistently transformed early-stage technology companies into market-defining brands. His expertise in AI-powered go-to-market strategies uniquely positions him to accelerate Apollo’s mission of empowering sales teams through intelligent data and automation.
Previously, he played a pivotal role in scaling marketing functions at SaaS giants like Intercom and Zendesk, where he drove remarkable growth from $40M to $1.7B, culminating in a successful IPO that raised $100 million in 2014. Leveraging his comprehensive background in demand generation, product marketing, and strategic storytelling, Marcio is focused on positioning Apollo as the go-to AI sales platform for SMB and mid-market teams.
His approach combines data-driven insights with targeted narrative strategies, translating Apollo’s technological capabilities into practical business value. Drawing from his global experience across Silicon Valley and international markets, Marcio aims to expand Apollo’s brand and demonstrate how AI can meaningfully improve sales engagement for growing businesses. Marcio holds advanced degrees from Stanford University’s Graduate School of Business and Golden Gate University, complemented by a BS in Business Administration from Universidade Feevale in Brazil.
Marcio Arnecke on LinkedIn: https://www.linkedin.com/in/marcioarnecke/
Resources
Apollo.io: https://www.apollo.io
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Transcript
[ 0m49s638ms ] Greg Kihlstrom: For years, we’ve heard about AI transforming software development, but what if that same level of agentic AI-driven collaboration could be applied not just to writing code, but to writing your entire go-to-market playbook? Agility requires that your go-to-market teams operate at the speed of insight, not at the speed of manual data entry and fragmented workflows. This means empowering them with tools that don’t just provide data, but automate action based on strategic intent. Today, we’re going to talk about the concept of an agentic go-to-market platform, where AI doesn’t just assist, but it actively collaborates with sales and marketing teams to automate entire workflows from strategy to execution. To help me discuss this topic, I’d like to welcome Marcio Arnecke, Chief Marketing Officer at Apollo.io. Marcio, welcome to the show.
[ 1m37s202ms ] Marcio Arnecke: Greg, thank you so much for having me over. [ 1m40s1ms ] Greg Kihlstrom: Yeah, really looking forward to this conversation. Before we dive in though, why don’t you give a little background on yourself and your role at Apollo?
[ 1m46s8ms ] Marcio Arnecke: Absolutely. So I’m Marcio, you know, CMO here at Apollo. As you can tell, I have an accent. So I’m Brazilian born, but I’ve been working in marketing for well over 15 years, mostly in the Silicon Valley. So you’ve been, you know, working with AI for at least the past five years, to be honest. But my focus here at Apollo is to translate Apollo’s product innovation, especially around AI, into real go-to-market strategies, you know, and I’ve been here in the world now for at least ten, yeah, 10 months.
[ 2m13s832ms ] Greg Kihlstrom: Yeah, great, great. So yeah, let’s, let’s dive in and want to start with the strategic view here and and just this this idea of this shift to agentic go-to-market. And so Apollo’s CEO said that until now, GTM, or go-to-market, has been too disjointed, too complex, and too manual. So from a strategic standpoint, what’s the fundamental flaw in the traditional go-to-market tech stack that an agentic platform is designed to solve?
[ 2m44s482ms ] Marcio Arnecke: It’s a great question. The core flaw, honestly, is fragmentation. Traditional go-to-market stacks are built as collection of tools. You have CRM here, you have engagement there, you have data somewhere else, is all held together by people doing manual work. And that makes go-to-market slow and reactive, mostly. An agentic platform changes that. Instead of humans is teaching systems together, the system’s understanding intent, the context, the goals. And actively help, you know, execute all the projects. It reduces the complexity, but not adding another tool, but really by orchestrating, you know, the work end to end. And honestly, it saves dollars as well because having the maintaining the tech stack is quite expensive.
[ 3m31s962ms ] Greg Kihlstrom: Yeah, yeah. Well, and and including that term agentic in there certainly implies AI as an active, you know, participant, collaborator, not just a passive tool. How how does a shift like this how does it shift the strategic role of a human sales or marketing professional and you know, what do they stop doing and what do they get to focus on instead?
[ 3m57s112ms ] Marcio Arnecke: Yeah, you know, you’ve been before I talk about agentic, you know, I I always talk to my friends, you know, that at this stage, if your entire organization, sales and marketing are not enabled to lease on AI 1.0, which means, you know, everyone is using AI to write content, to manage their projects, emails, and so on, we’re really behind. And from there you go to the AI 1.5, which is agentic, which really helps with the focus of low leverage coordination work, you know, pulling lists, updating fields, stitching workflows together, checking whether something is happened or has happened, right? And that said, you know, teams can actually focus on strategic and creative work, which it really helps drives more innovation, ROI, and how it really drives, you know, business, you know, to to to to drive revenue to the next level. Agentic means, you know, AI is handling the how and humans are handling the direction at this stage.
[ 4m50s572ms ] Greg Kihlstrom: Yeah, yeah, got it. So let’s talk about then putting this into practice. So I will confess, I’m a a bit of a vibe coder myself. Um, been playing around probably too much lately with some of those things. You’ve talked about the idea of vibe go-to-market or vibe GTM drawing a parallel to to things like vibe coding for for developers. Can you walk us through maybe a a practical example, you know, how does a sales leader translate a strategic idea like finding more accounts that look like our top customers or things like that into an automated workflow?
[ 5m27s510ms ] Marcio Arnecke: Sure thing. Imagine if a sales leader just says, find me more accounts that look like our top 10 customers, a very, you know, often asked by our sales, you know, leaders and and friends. Uh, in a traditional stack, that might take hours of analysis, uh, uh, filters, exports, handoffs, and likely a few meetings through the day, you know, to pull the list together. With an AI assistant, or an agentic AI approach, the leader can simply state the intent and the agent is able to pull together, analyzes the top 10 accounts, identify behavioral patterns, build a target list and actually launch a campaign align to how it has worked historically. Which this is quite of an it’s absolutely fantastic for a market that’s been doing this for a while, you know, and a amount of working people that you needed to have in place to be able to achieve this in a matter of minutes, but not hours and back in the days, honestly days and even weeks. And the most interesting thing of all of these is that the agent continuously refines your campaign and engagement based on the outcomes. So for me, that’s what vibe go-to-market is, is expressing intent, but not spending hours building the actual workflows.
[ 6m43s367ms ] Greg Kihlstrom: Yeah, yeah. And, you know, to to that end, your your platform Apollo unifies outbound, inbound, deals, and and data. So a lot of the things that you’re you’re talking about here and and more, you know, how do AI agents work across these often traditionally siloed functions, you know, for instance, what is an AI powered handoff from an inbound lead to an agent assisted deal cycle actually look like?
[ 7m10s477ms ] Marcio Arnecke: So the key share context. For example, an inbound lead comes in, the AI evaluates intent and feet, enriches the account using data, decides whether the is sales ready or needs nurturing, connecting to previous outbound efforts. And hand to sales who contexts, why this lead matters, why they why they should care about and how similar accounts have converted. Which means sales is not starting from zero. They start mid-conversation. That’s the connection that we can see now connecting inbound and now outbound motions by creating this strat and this context for the sales organization.
[ 7m51s677ms ] Greg Kihlstrom: Yeah, yeah. Well, yeah, and I mean that’s it’s um, it’s a challenge when the human teams have have silos, but I I can imagine, you know, with automation if that context isn’t shared, it’s gonna be, you know, it’s it’s hard to for the AI to explain itself when it’s confused, right? So I mean just having that context is going to be key.
[ 8m12s227ms ] Marcio Arnecke: It’s going to be key and it helps you with conversion, it helps you with ROI. There’s many benefits there that helps you uh, just accelerate your overall pipeline, you know, and and conversion.
[ 8m28s703ms ] Greg Kihlstrom: So let’s let’s talk about measuring success here and and proving ROI certainly, you know, going to be going to be top of mind for any organization. So some of the the testimonials for Apollo, for instance, mentioned saving hours or even a a full day’s work. You know, beyond even, you know, with considerable time savings, what what are some of the key performance indicators that marketing or sales leaders should be tracking to measure, you know, true business impact of an agentic GTM platform?
[ 8m59s763ms ] Marcio Arnecke: Yeah, absolutely. I mean, time saving these days is table stakes. It goes back to my, this is AI 1.0. The real metrics, you know, that you should be tracking is pipeline velocity, conversion rates by stage, ACV and expansion, win rates, productivity per head. So agentic go-to-market should show up in better economics across your sales organization, your sales cycle and business, and not just through faster execution at this stage.
[ 9m30s673ms ] Greg Kihlstrom: Yeah, yeah. And so another key thing here is improving results over time. So, you know, it’s great to get those initial results, but you know, executive stakeholders keep keep wanting more for some, you know, boards keep wanting more and and shareholders keep wanting more, right? So what kind of feedback loops are are built into a system like like Apollo to, you know, again, continuous improvement and and and really lean on AI to to help in that regard as well.
[ 10m0s113ms ] Marcio Arnecke: I think just this is where things are becoming very interesting. The system this system leans on outcomes. So what converts, what stalls, what closes, what expands, and now and it learns from itself, right? Quite fast, right? More faster than I think humans could do at this stage. But transparency really matters. Leaders need visibility into what signals AI is using, what recommendations it’s making, what those recommendations might map to results, right? So trust come from seeing the feedback loop, I believe between the leaders, you know, and the agents, uh, but not treating just AI as a black box. However, the outcome, you know, from all this connection and all this integration, it really supports uh, this acceleration of production that becomes incredibly interesting and nowadays more faster than ever.
[ 10m49s923ms ] Greg Kihlstrom: Yeah, yeah. Well, yeah, and I mean the the to your point, the the volume of the data in in many cases is is so much that human teams, you know, they could do their best to to try to make sense of it, but, you know, this this is one of the areas where I’ve seen AI be incredibly helpful. For all the like press that the, you know, content generation part of things gets, I would say from the AI perspective, I think crunching the numbers and just making sense of large volumes of data can be incredibly helpful.
[ 11m19s393ms ] Marcio Arnecke: Yeah, and you see nowadays, you know, uh, that your analyst teams, you know, are much more leaner in a sense, they’re much more strategic, you know, they they can do some very interesting work and, you know, back in the days, not too for far back, actually, you needed quite a larger organization to be able to digest amount of data that was available to you. So I I believe this is one of the fundamental changes, you know, that everyone should be using and applying in their organizations is how to to be able to do better analysis in a much faster pace.
[ 11m52s333ms ] Greg Kihlstrom: Yeah, yeah. So then building on on all of this, everything from from the, you know, the speed and the efficiency gains, better insights, quicker insights, all all of the above really. How do you see the relationship between sales and marketing evolving, you know, in this world where AI agents are are, you know, doing doing a lot of the the the heavy lifting? [ 12m18s249ms ]
Marcio Arnecke: The line between sales and marketing blurs. Uh, AI can manage large parts of the top of funnel, targeting, engagement, qualification, while human focus on complex conversations, value creation and closing. Marketing becomes less about volume, as you know, you know, marketing has always been about driving massive volume, right? And sales becomes about less about admin work. So both align really around growth outcomes. So the line definitely becomes a little more blurry over time. [ 12m48s369ms ]
Greg Kihlstrom: Yeah, and I mean that that’s a pretty fundamental shift of, you know, I know I’ve done a bit of sales in in my life but a little more marketing, but it’s often referred to as a numbers game, right? Which literally means let’s throw a bunch of stuff out there and see what sticks, right? So what you’re saying is and what I hope is is true as well is that yes, we’re reaching out in compelling ways, but not to so many people who are not either receiving or wanting to receive the message, right? Is that is that kind of what you’re saying? [ 13m20s229ms ]
Marcio Arnecke: Yes, you can be more targeted, you can be more personalized, uh, you can be more efficient in your campaigns. You can go a little deeper to find that buyer, you know, in a way that you haven’t been able to do before. Yeah. Based, you know, the agentic approach that you have in marketing, right? And the sales organizations who are normally buried in tasks and admin work can really focus on the conversations, especially high value MQLs or customers and prospects at that stage. That’s a fundamental change that is moving really fast. [ 13m53s389ms ]
Greg Kihlstrom: Yeah, yeah. Uh so for those leaders out there listening and certainly all of this makes a lot of sense and and is the the direction to to move in. What’s a maybe first or practical step that they can take to to move things forward to to adopt agentic, you know, sales and marketing? [ 14m15s159ms ]
Marcio Arnecke: I see a lot of friends getting lost, you know, in this AI agentic, you know, and trying to to push, you know, what’s best in class, you know, in their organizations. And I I tell my friends like, listen, start by simplifying. Don’t try to boil the ocean or move too fast here, you know, from a 1.0 to a 3.0. Yeah. Take take the right steps, you know, forward. Pick one motion, for example. Let’s say inbound qualification or outbound targeting. And let AI on end to end. Really get good at it, right? At the same time, invest in change management. Help your teams understand why this shift matters and why high value work really is going to uh, help them move, you know, forward uh, together as an organization. Do we need those two things is I think where leaders, especially in larger organizations, will help them to truly make changes, you know, and how they think or apply AI. [ 15m11s959ms ]
Greg Kihlstrom: Yeah, yeah, love it. Well, Marcio, thanks so much for joining today. I’ve got two last questions for you before we wrap up here. The first one, if we were having this interview one year from today, what is one thing that we would definitely be talking about? [ 15m26s691ms ]
Marcio Arnecke: I think, uh, now we’re still talking a little bit about AI features, to be honest. And, you know, a year from now, we should be talking about AI operating models. Companies won’t be asking if you use AI and go to market, but uh, we’d be asking how agentic your full system really is at that stage.
[ 15m45s841ms ] Greg Kihlstrom: Yeah, nice, nice, love it. Well, we’ll have to talk about that in a year then. That’s that’s great. Well, and again, thanks so much for joining today. Last question for you. What do you do to stay agile in your role and how do you find a way to do it consistently? [ 16m0s111ms ]
Marcio Arnecke: There’s three things that are really important for me, to stay close to customers, to the product and to the team. And I listen constantly, I test ideas very quickly, I fail very quickly and succeed, you know, quick as well. And I try to stay curious. I don’t think agility is about speed alone, to be honest. Is about being willing to change your mind as new information shows up, uh, uh, very quickly.
