GTM's AI Revolution: How a $200M R&D Bet is Reshaping Go-to-Market
ZoomInfo x The Signal
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Hey y’all!
This is a unique deep dive post for several reasons.
First of all, I typically write about early-stage companies building at the frontier of technology (these days, namely, in AI). However, today’s post is about a company that's been around for 18 years. Most readers of The Signal probably already know this company. They’ve been publicly traded for 5 years, and they clearly have product-market fit (spoiler: they do over $1B of revenue).
For all intents and purposes, they are “the incumbent” being ”disrupted” by all these new up-and-coming AI-native startups.
But I'm here to argue today that I've seen firsthand that ZoomInfo, recently rebranded under the ticker $GTM, led by the savage Henry Schuck, is here to reinvent itself and stay competitive. I'm betting that if anyone can, it's ZoomInfo.
Today I’ll outline the bull case for the “Go‑To‑Market Intelligence Platform” they’re building.
I convinced Henry to talk with me directly about their progress and how they're thinking about the space. He was also generous to include his Chief Product Officer, Dominik, whom I've known for a few years now and also “gets it.” Henry has been a supporter of my career over the years, and was an angel investor in my last company, Groundswell. I also respect his ability to get in the weeds, respond to customers directly on LinkedIn, message with me about random questions, all while running a publicly traded company. Impressive, to say the least.
Usually, companies get to a certain size and slowly decline and don't worry about trying to reinvent themselves. Maybe they do an acquisition here or there, or maybe they try to bolt on a new feature (yes, I'm looking at you, Salesforce). Not ZoomInfo.
ZoomInfo has hit that inflection point where, as Alex Rampell famously put it:
“The battle between every startup and the incumbent comes down to whether the startup gets distribution before the incumbent gets innovation.”
— Alex Rampell, Distribution vs. Innovation, Andreessen Horowitz blog (Nov 5 2015)
I’m excited to be on the front row watching it all unfold.
That’s why I’m excited (and honored) to give a peek behind the $GTM curtain and outline the bull case for the “Go‑To‑Market Intelligence Platform” they’re building, in today’s deep dive post on ZoomInfo:
Here’s what we cover in today’s post:
The Data Foundation That Everyone Assumes Exists (But Doesn't)
Why Perfect Emails Are a Red Herring (And What Actually Drives Revenue)
The Custom Data Arms Race is Just Beginning
The Go-to-Market Engineer Debate: Who Should Own Revenue Innovation?
The Unified Data Layer That Makes It All Possible
The Long Game: From Data Provider to GTM Intelligence Platform
One caveat before we jump in: having been a founder and worked at startups, ZoomInfo is probably not the tool that you want to be looking at if you're a small startup (eg: <10 employees). They’re purpose-built for the mid-market and enterprise. So, that’s the lens in which I wrote this piece.
Alright, let’s get into it.
GTM’s AI Revolution: How a $200M R&D Bet is Reshaping Go-to-Market
You probably know ZoomInfo as the classic database. People bicker about whose data is better — commoditized data points like email addresses and phone numbers. That's a pretty boring debate at this point. Anyone reading The Signal is past trying to determine which email provider is going to give the best email. Frankly, you should just waterfall several. Of course, these data points matter, but there are way more interesting data points to use in today's modern and nuanced go-to-market motions (especially when you’re layering in automation, AI, and agents on top of your foundational datasets).
In the age of AI, data is no longer a commodity as much as it is the oil that runs a modern go-to-market engine. And ZoomInfo is building what I think is one of, if not the, most comprehensive platforms of GTM data in existence. They have a massive, high-quality dataset. People seem to realize this, but they don't fully comprehend how necessary it is to have great data to build AI workflows.
AI does exactly what you tell it to do based on the data set that it has access to. Especially if it's a workflow that has no human in the loop, the workflow will only be as good as the dataset. ZoomInfo has a massive, third-party dataset and can combine (via native connectors) into first-party data, like CRM, marketing automation, or data warehouse, which allows you to activate all kinds of otherwise overlooked/dormant data.
At a time when every SaaS company claims to be "AI-first," Henry’s team has quietly assembled what might be the most sophisticated data foundation in B2B—and they're shipping production-grade go-to-market agents to enterprise customers to solve go-to-market problems that most companies don't even realize they have yet.
In a world where everyone can build signal-based selling workflows, the real competitive advantage lies in the unsexy work of identity resolution and data unification. While competitors are still trying to connect their CRM to their marketing automation platform, ZoomInfo has built what Henry describes as "an MDM deployment that's 50 times the size of the largest Informatica MDM deployment"—and they're making it available to their customers through GTM Studio.
This isn't your typical "we added ChatGPT to our product" AI story. This is about a company that saw the go-to-market transformation coming and spent $200 million to position themselves at the center of it.
The Data Foundation That Everyone Assumes Exists (But Doesn't)
Here's a problem that sounds mundane until you try to solve it: most mid-market and enterprise companies have 8-10 versions of Cisco in their CRM systems. One is a free trial, another is a prospect, one is an open Opportunity, etc. When you're trying to route an important signal about what's happening at Cisco, you simply can't do it effectively when there are 10 different Cisco records scattered across your systems. ZoomInfo is able to bring that all together into one view.
"This feels like a small problem," Henry told me, "but when you're trying to build go-to-market AI and go-to-market agents, it's a massive problem." I couldn’t agree more (and I’ve seen this first-hand).
ZoomInfo saw this data chaos coming more than a year ago. Their response wasn't to build another integration or dashboard—it was to acquire SetSail, a company that had raised $40 million specifically to solve enterprise data unification problems. Companies like Snowflake and Shopify were already using SetSail’s technology to fix this exact issue.
And they didn't just bolt SetSail onto their existing product. They integrated the same master data management technology that ZoomInfo uses internally—the system that takes data from hundreds of thousands of email signatures, tens of thousands of SMB CRM integrations, thousands of web crawlers, and a DSP pulling contextual data from ad placements—and brought it directly into GTM Studio.
The result is what Dominik (CPO) calls "a virtual CRM layer of a perfected unified profile." It's not just your CRM data anymore—it's your first-party data, product usage data from Snowflake, marketing automation data, recorded calls, meeting transcripts, all married to ZoomInfo's third-party data, and presented as a single, queryable source of truth. A hairy problem that, if goes unsolved, compounds in the AI era.
Why Perfect Emails Are a Red Herring (And What Actually Drives Revenue)
If you've spent any time in sales enablement circles lately, you've probably heard someone obsessing over the "perfect email." The logic makes sense: use AI to “hyper-personalize” emails by incorporating signals and insights to craft the ideal message that will get a reply.
Henry has a contrarian take: "a perfect email doesn't really matter that much." Spicy take, and I agree.
It's not that personalization and signal-based selling aren't valuable—they absolutely are. The issue is that everyone stops at the email. "You only get 5% to 10% of the way with a really great email," Henry explained to me. "There's all of this downstream stuff that you have to do to turn that perfect email into revenue. You have to have an AE engage. You have to have an SDR call. You have to have marketing invite them to events."
ZoomInfo is one of the only providers that can be the best at both critical components of a system of intelligence: the data foundation (they own it) *and* the revenue orchestration to take action.
This insight led to what might be GTM Studio's most important feature: an interface where Account Executives and Account Managers can take one-click action on their top prospects, complete with the signals explaining why they should be engaging with them right now.
At the end of the day, the customer still needs a place for the AE’s to go execute on whatever that perfect audience is. And, imho, trying to do that in Salesforce is not the answer (I’ve seen this fall flat time and time again). Salesforce should be the source of truth, yes; but not the system of action.
Timing beats message quality every time. If someone is in the market for what you're selling, a mediocre email will get a response. If they're not in market, the perfect won't move the needle. I will die on this hill. And ZoomInfo is leveraging AI to productize this thesis.
The Custom Data Arms Race is Just Beginning
While most companies are still figuring out basic signal-based selling, the most sophisticated revenue teams are already moving to custom data enrichment. They're building agents that can answer questions like: "Is this company B2B, B2C, or B2SMB?" where B2B2C is defined as "their customer sells to somebody for $100 or less." Or “Show me companies who have expanded to Europe in the last 3 months.” Or “Show me any B2B SaaS company who become SOC 2 compliant in the last month.” Or “show me yelp reviews with negative sentiment for restaurants in Toronto.”
How do you figure out these “rich” data points? Custom AI workflows or agents.
ZoomInfo is building exactly this capability into GTM Studio. Henry confirmed they can already handle many of these custom jobs. And for the most commonly requested data points, ZoomInfo plans to pre-index all of that information so it's instantly available without waiting for real-time scraping.
This is where the next competitive moat will be built. When basic signal-based selling becomes commoditized (and it will, faster than most people think), the alpha will come from these highly custom data points that are only relevant to your specific business.
The Go-to-Market Engineer Debate: Who Should Own Revenue Innovation?
There's been growing discussion about "GTM Engineers". I first wrote about the role back in November. Henry thinks this trend is fundamentally misguided.
"Where do the best ideas for a go-to-market play come from?" he asked me. My immediate answer was: "They come from great sales reps and great sales managers who are thinking a lot about the accounts in their book of business.” “Exactly!” Henry said back to me. “And, why would that person then have to go stand in a line with a GTM Engineer to get that idea to reality?"
Here’s a simple but common scenario: a sales manager wants to run a competitive displacement campaign. Today, that manager has to hunt down competitor mentions across CRM notes, call recordings, technographic data from various tools, and maybe email mentions that aren't even accessible. Then they have to somehow bring all these siloed datasets together before they can even start their campaign.
"That's an insane thing that we would need a GTM Engineer to do," Henry argued. "We need to have a platform where great sales leaders, when they have an idea, can execute on it without going through another engineering layer."
The problem isn't that GTM Engineers aren't valuable—it's that they're a symptom of inadequate tooling. In a world where all your calls, emails, CRM data, and third-party data live in one unified, queryable system, any sales leader should be able to say, "Find me all the companies that use 6Sense and all the companies who mentioned 6Sense on calls, give me that list and I'll go execute against it."
That's the vision ZoomInfo is building toward: putting the power back in the hands of GTM practitioners, not creating another technical bottleneck they have to navigate. I’m excited to see how ZoomInfo races towards building a platform that can achieve both power and ease-of-use.
The Unified Data Layer That Makes It All Possible
Everything ZoomInfo is building—the custom agents, the one-click execution, the elimination of go-to-market engineering bottlenecks—depends on having all your data in one place and making it queryable through natural language.
When I saw GTM Studio, I could see this vision coming together. For any account, we could pull up a unified view that included everything happening in Salesforce, product usage data, recent conversations with links to call recordings, pain points and use cases extracted from conversations, pricing and competitive discussions, and real-time third-party intelligence.
But the interface goes beyond just displaying information. You can ask questions like "Who owns this account?" or "How many salespeople does this company have?" and get answers that draw from both first-party and third-party data sources.
Once you have that unified data layer, the next step is to build agents on top of that unified data.
This is what Dominik calls the two-step process: first, data processing (having all the signals, conversations, emails, and context about an account), and second, asset creation (turning that data into decks, email sequences, call scripts, or account plans tailored to specific prospects).
The customization happens at both levels. Admins can define what data points matter for their business. Sales reps can create their own templates and workflows that operate on top of the unified data pipeline.
The Long Game: From Data Provider to GTM Intelligence Platform
What's happening at ZoomInfo represents more than just product evolution—it's a fundamental shift from being a data provider to becoming the GTM Intelligence Platform. The company that once sold you lists of contacts is now positioning itself as the platform where all your go-to-market execution happens.
This transformation required massive investment ($200M annually in R&D) and strategic acquisitions (the $40M SetSail deal), but it also required a recognition that the B2B landscape was changing faster than most incumbents were prepared for. While competitors focused on adding AI features to existing products, ZoomInfo rebuilt their entire approach around the assumption that data unification and intelligent workflow automation would become table stakes.
The timing is crucial. We're at a moment where signal-based selling is moving from competitive advantage to basic expectation, where first-party data integration is shifting from nice-to-have to necessity, and where the companies that can operationalize these capabilities at scale will pull away from those still trying to piece together point solutions.
Henry saw that this was going to be a big deal more than a year ago. That foresight, combined with the resources to act on it, has positioned ZoomInfo to be not just a participant in the AI-driven go-to-market transformation, but potentially its primary infrastructure provider.
The future belongs to GTM teams who can unify their data, automate their workflows, and execute at scale. And I’m excited to see Henry and the team continue to innovate, which continues to impress me, especially given their size and scale.
If you want to explore how ZoomInfo’s GTM Intelligence Platform can help your team, reach out and let them know The Signal sent you.
PS: They'll have hands-on demos at Dreamforce this year where you can see this come to life with your own data!
Thank you for your continued attention and trust—I do not take it for granted.
See you next time,
Brendan 🫡