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James Roth, CRO at ZoomInfo, joins Toni to break down how AI is reshaping go-to-market. From the collapse of inbound demand to the rise of intelligent outbound, he explains how teams can stay efficient, use AI without the hype, and turn data into real impact.
We also talk about ZoomInfo’s $1.2B ARR growth, the myth of “AI-native” startups, and what go-to-market intelligence actually means in 2025.
Want to work with us? Learn more: revformula.io
- (00:00) - Introduction
- (01:38) - ZoomInfo's Growth and Public Perception
- (06:45) - AI's Role Today
- (10:04) - ZoomInfo's Approach to AI and Competition
- (15:35) - Go-to-Market Intelligence Explained
- (21:09) - Integration and Collaboration in the Industry
- (26:01) - SEO Challenges and Market Impact
- (28:45) - The Resurgence of Outbound Sales
- (33:27) - AI's Role in Sales Efficiency
- (39:46) - Leveraging AI for SMB Data
- (46:39) - The Drive for Efficiency with New Tools
- (53:10) - Next Week: $5M ARR per AE with AI
Creators and Guests
What is The Revenue Formula?
This podcast is about scaling tech startups.
Hosted by Toni Hohlbein & Raul Porojan, together they look at the full funnel.
With a combined 20 years of experience in B2B SaaS and 3 exits, they discuss growing pains, challenges and opportunities they’ve faced. Whether you're working in RevOps, sales, operations, finance or marketing - if you care about revenue, you'll care about this podcast.
If there’s one thing they hate, it’s talk. We know, it’s a bit of an oxymoron. But execution and focus is the key - that’s why each episode is designed to give 1-2 very concrete takeaways.
$1.2B ARR CRO on AI in GTM (w/ James Roth from ZoomInfo)
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[00:00:00]
Introduction
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Toni: Today I'm talking to James Roth, CRO at ZoomInfo. They're roughly running at 1.2 billion of a RR. We will talk about how AI is changing the game on a very tangible level, both for sales and marketing, and how ZoomInfo itself is evolving rapidly right now. And now. Without further ado, enjoy.
James: When you run any sort of AI workflow or any sort of AI automation that's primarily just over CRM data, it really shines a light on just the impact of that bad data foundation.
Irrespective of how cool or amazing the AI is, if it's running over 10 years of bad, manually inputted data in CRM, you're just gonna probably miss a lot more and a lot faster creating this dichotomy of AI native versus old dinosaurs. It really is just marketing buzz so that people, you know, it allows you to diminish, you know, certain companies or, or again, sort of increase your [00:01:00] sex appeal.
In the world of LinkedIn, AI native founders are just people that founded companies in a world of ai. And so maybe they've got a leg up, maybe, you know, we've got a, a product and engineering team of 1200. We've got the ability to go build out, spend the amount we spend in r and d, hundreds of millions of dollars if it's sitting on top of the same or similar AI foundation.
I would probably bet on the company that's got 1200 product and engineering people that spends hundreds of millions of dollars on data than the AI native four really smart guys in a basement somewhere thinking about AI because they're in an AI world.
ZoomInfo's Growth and Public Perception
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Toni: You know what struck me? So, and I asked a couple of people now and let's see if we keep this in, but I asked a couple of people now and I was say, Hey, how big is Zoom in for?
Tell me what, what do you think? How big is ZoomInfo? Um, and usually I get like a response back. Yeah, they're probably like a gong 200, 250, maybe 300 million a RR [00:02:00] and, and I was like, you know what? That's exactly what I thought. But then I looked it up and you guys are at 1.2 billion of a RR, so it's, it's a completely other wheelhouse than all the other brands that people are kind of having in their head in terms of go to market tech and all.
Does that. Am I an outlier here? The people that I talk to, an outlier. Does, does that happen to you a lot? That people realize, oh, wait a minute, you know, this guy is running a much bigger show and or ZoomInfo is much bigger than I thought.
James: You know, it's, uh, it's a great point. I think, um, being that we're public, anybody that wants to look, they can find it.
And that's, yeah, even in and of itself might be confusing to folks that don't follow public markets closely because they probably put us in. With all the other private companies. But yeah, we, we crossed over a billion dollars in revenue. Uh, we've got close to 40,000 customers. And when you look at the space, there's always this, how much noise are they making, you know, on LinkedIn or on social or whatever it may be, versus how [00:03:00] big actually are they?
And I think even if you look at. Some of those companies that don't always tout their a RR because they might not want to, um, until they hit a certain milestone. Or, you know, some companies in the space haven't touted anything because they hit a milestone and they may or may not be shrinking from it.
And so, you know, again, I think the perception of ZoomInfo is wild across the board in terms of folks that might think we're bigger than we are. But yeah, I think just given the space itself and given we're the only one that's public. It is tough, uh, for some folks to, to look at that, but I, I joke internally, if you took all of the a RR from the five biggest companies in the space we're bigger from an A RR perspective.
Toni: I was, I was about to make a similar point, uh, actually, so kind of good that you good that it took this already. I think another thing is also you guys have clearly escaped this echo chamber in this space, right? You are serving the enterprise folks. You're serving kind of the biggest companies [00:04:00] on the planet, um, and they chose you for probably many, many good reasons, and that's just not what LinkedIn is about.
I think LinkedIn is, is much more of a, you know. I don't wanna insult anyone, but it's, it's, it's more SMB, it's more mid-market, actually. And, and that's where some, sometimes some of the other players seem to be much bigger, more pronounced than, um, than what you guys already do. Right. Maybe taking this along here. When, when I, you know, I did quite a bunch of prep for this episode and I talked with some folks about ZoomInfo. Uh, I was like, Hey, what, what is, you know, explain to me what ZoomInfo is, right? And a lot of the times. I got something back. Oh, you know, it's this place where I go to look up, you know, a contact or an email or phone number.
Right. And I gotta, I have to admit, before I started doing some, some work on this, I kind of had the same image in my head. Am I, am I wrong about this? Where, where, where is Zoom ZoomInfo right now?
James: Yeah. It's a, it's a great point. You know, it's, [00:05:00] it's funny when you're known for one thing, there's a blessing and a curse to that.
Because everyone knows you for that one thing, which obviously helps getting to a certain size and scale. And in that particular area, you know, we are unequivocally the best just from a breadth and depth and reach and you know, all of the ways that we can bring data in. And it's such a valuable part of go to market.
So it's not like one of those legacy. Brand, you know, sort of anchors if you will, because it still does drive tremendous inbound and everyone knows us, and I think every sales person at some point, at some time has used it. Yeah. And so, you know, walking through an airport with a ZoomInfo logo on, you'll get high fives from salespeople saying, Hey, you helped me build my career.
And as somebody had started in door-to-door sales with no information. Uh, yeah, I mean, it was certainly like a, a huge moment for Argo to Market 15 years ago, and we implemented it, and so [00:06:00] I think there's the benefit of that where folks know us, folks typically have a, a, a good feeling about what we've done for them as sellers or marketers in the past.
But I think we have not done a great job of articulating. All of the additional stuff that we do. All of the, again, from an intelligence standpoint, yes, you've got contact data, that's a really important thing, but there's also a whole host of firmographic data and really signal data that we have built out over the last couple of years, which led us to the, again, the go-to-market intelligence platform, which is really, as we're.
I don't even wanna call it rebranding because we've always been a go-to-market intelligence platform, but I think it's not always obvious to our customers that we do so much more than just contact data.
AI's Role Today
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Toni: Given where we are right now, 2025, everything is ai, everything talks about agent and agent, everything.
Um, what's your position on this actually kind of is knowing, you know, or, or finding [00:07:00] data, finding information, getting insights. Is that enough in this current day and age or, or do you, do you see that this actually needs to go further than that?
James: It's a great question. You know, when you really think about the noise versus the reality in ai, there are some amazing outcomes.
There are some amazing tools that are helping people literally automate the things that they hate doing most, I think, unfortunately. A lot of it right now still noise because what folks are finding is that many of these tools are built primarily over either publicly available information that these things can scrape and or in go to market over CRM data.
And I think for the better part of the last decade, we've been shouting from the rooftops that your CRM data is trash. And you can't always, you can't really do much from CRM data because it gets outdated. The reps don't input it. And I give those companies a huge amount of credit from. The marketing standpoint of saying, well, that's [00:08:00] your problem.
Your team has bad hygiene. Your reps don't do what they need to do. And there's a, there's a whole variety of reasons that that CRM data becomes outdated and for us at ZoomInfo, again, you would have the more leaned in rev ops or the more leaned in CRO that says, yes, we have to fix our CRM data. Please come help us do that.
But then there was this large group of folks that was like, eh, it's just the way it's always been. I'll go yell at my sales team and hope that they, you know, have better hygiene. And I think in this AI transformation, people are now seeing at a scale like no one's ever seen before. When you run any sort of AI workflow or any sort of AI automation that's primarily just over CRM data, it really shines a light on just the impact of that bad data foundation, irrespective mm-hmm.
Of how cool or amazing the AI is. If it's running over 10 years of bad, manually inputted data in CRM, you're just gonna probably miss a lot more and a lot faster. [00:09:00]
Toni: You know, once, once you start thinking about ai, it's, it's really hard to. To not think about some of the, um, you know, newcomers in this data space that are basically kind of growing up and have been benefiting a lot from this AI wave.
Right. Um. I think number one, putting this into perspective, like everyone, um, you know, folks might have like a distorted understanding how far big they actually are. Right? Kind of, especially folks like Clay. Uh, you guys probably, you know, make this kind of revenue in a week or something like that, where they're currently at.
Right. It's a, it's, it's so far apart. It's, it's pretty insane actually. But. Um, there's not just clay, there's many of those. This is like a whole wave of basically folks, uh, trying to, to, you know, write on this right now. How, how do you as ZoomInfo deal with that onslaught of new AI incomings coming to the scene?
Which I think is not only a problem for ZoomInfo, it's a problem for a lot of people out there that have established [00:10:00] businesses, they're suddenly battling those new AI folks, uh, growing up.
ZoomInfo's Approach to AI and Competition
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James: So, Tony, I'm gonna, I'm gonna go off, off script here a bit because it's one of my favorite topics. I, I give marketing teams a lot of credit, the ability to turn companies into dinosaurs, if you will, just because they hit a certain size or a certain level of success.
Is, it's, it's brilliant. Especially, you know, you mentioned it, I didn't, the LinkedIn paradigm, we call it the LinkedIn Thunderdome of, you know, this ability to comment for reach and you got people starting fights just to get more comments and you know, knowing the algorithm of LinkedIn, it is a wonderful way for smaller businesses to get attention.
And you know, frankly I love it internally from a competitive standpoint. You know, if you look back. There was a time where we really didn't have any meaningful competitors. Uh, and that was a combination of m and a strategy and, you know, just a, a good market, if you [00:11:00] will. And while yes, some can say, oh, well, are you, do you really like competition?
I do because it drives innovation. It drives us showing up better for our customers. But more importantly, that concept of, you know, dinosaur, you know, we we're still the same company that our founder founded 17 years ago. The guy's 40 years old, like. Our executive team, they're not a bunch of old, you know, I, I don't know where the dinosaur thing comes from.
We were very early to start using ai. We acquired a company that was AI in firmographic data. The whole concept of, of native AI versus the quote unquote dinosaurs, I find it hilarious because everybody fundamentally is using the same ai. That the next person is they're, they're not building their own.
They're either putting it in anthropic, they're putting it in open ai. It's the same underlying AI and the same underlying data centers. The fact that they started the business a year ago versus starting it 10 years ago or 15 years ago, where they can say, we're AI native. [00:12:00] The amount of AI native demos I've had, again, outside of our business, it is literally the same wrapper.
To accomplish whatever goal that they're trying to break into. And so again, kudos to them saying, Hey, we're AI native that makes us better. I don't necessarily disagree, and that doesn't mean that it's because I'm a dinosaur. It just means because I know the underlying tech. And so it's basically like, what is your core value proposition?
Whether that's in, you know, I was just at the seismic shift conference, whether your core value proposition is, is enablement. Whether your core value proposition is go to market intelligence, whether it's, you know, spreadsheets, whatever it may be, irrespective of how long you've been doing it or how big the company's gotten.
They're all using the same underlying AI to make their products better. And so creating this dichotomy of AI native versus old dinosaurs, it really is just marketing buzz. So that people, you know, it allows you to diminish, you know, certain [00:13:00] companies or, or again, sort of increase your sex appeal in the world of LinkedIn, because I feel like, and a AI native founders are just people that founded companies in a world of ai, and so maybe they've got a leg up, maybe.
But I think personally, you know, we've got a, a product and engineering team of 1200. We've got the ability to go build out, spend the amount we spend in r and d, hundreds of millions of dollars. If it's sitting on top of the same or similar AI foundation, I would probably bet on the company that's got 1200 product and engineering people that spends hundreds of millions of dollars on data.
Then the AI native four really smart guys in a basement somewhere thinking about AI because they're in an AI world.
Toni: Yeah. I'm also one of those AI native founders, by the way. But you know, no, no offense. No offense taken. There
James: shouldn't be offense. And just real quick, there shouldn't be offense on either side.
You know, basically if I founded [00:14:00] a company in 1988, I shouldn't be diminished because I was a pre-internet founder in the same way that if I graduated college or dropped outta college or whatever, in the internet world. There. I don't think there should be this, like you get diminished or the dinosaurs get diminished.
It's basically like who has the best tech and what drives the best outcome for my business. Yeah, and I think to create that noise, if you will, to get eyeballs or clicks or start fights on LinkedIn or whatever it may be, it's fine. It's noisy, but if you are an AI native founder and you have an amazing product that's gonna drive amazing outcomes for my business, I'm not gonna say it's better because he is an AI native founder, or it's worse because he's not.
I'm just gonna look at the underlying tech, the underlying outcomes. Better or worse, there are amazing. Look at Microsoft. There are amazing non-AI native companies doing amazing things with ai, and there are amazing AI native companies doing amazing things with ai. Those, [00:15:00] those things are not mutually exclusive.
I, it's just, I feel like it's just. Noise and fight starting on LinkedIn.
Toni: I think it's, it's a more sophisticated version of name calling, right? Kind of. That's kind of what it is. And, and then I think it works, you know, I mean when, when someone doesn't have 1200, you know, engineers working for him or her.
You, you gotta find another way in. Right. And I think that's what it is. Um, but ultimately, and this is I think to your point, uh, the, the customer needs to make the decision. What is better for them and how much does the name calling then still carry when it gets to that point. Right.
Go-to-Market Intelligence Explained
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Toni: And, and trying to double click a little bit, um, you mentioned go to Market Intelligence, GTM Intelligence, um, can we go just one or two steps deeper into that?
Because I think it's a, it's a very big. Phrase. A lot of things fall under that. A lot of people are talking about GTM Intelligence, right? It can. It can mean so many things. What does it mean for ZoomInfo?
James: So go-to-market Intelligence. For [00:16:00] us, if I think back just a couple years, everyone was trying to get to the same outcome, which was one platform for go to market that everybody's gonna use and see.
Clary a great forecasting tool that then bought a conversational intelligence tool and then they bought, uh, groove and so they wanted to get into sequencing and, you know, six Sense Great a BM tool that then bought lintel to try to get into the, the data business. Everyone was trying to become this one size fits all platform.
We did it too, obviously we bought a lot of companies. Everyone was trying to go for that same approach. You think about 20 20, 20 21, 20 22. The getting was great. If you could be that one sole provider in a growth world, it was amazing. I think what we learned the hard way, and a lot of other companies learned and are learning the hard way, is that, you know. Revenue go to market wants best in breed. And so if you're the best in breed forecasting tool, that doesn't necessarily mean you're gonna have the best in breed sequencing tool. [00:17:00] And we did the same thing where we went to market and we said, Hey, you don't need this anymore. You don't need that anymore.
And we built out these things that were kind of far off our core competency. And so the go-to-market intelligence, especially in this AI world, the way I think about it is you've got amazing tools. You've got amazing products that sit in your go to market, and all of them require intelligence. Whether that's firmographic, whether that's signal, whether that's psychographic, whether that's demographic.
Each one of those tools to get to that better outcome. We discussed CRM earlier, if you're just running some of these tools over CRM or just over, you know, first party conversations, there's a whole 360 of, of kind of data that you're missing. That will inform better actions. It'll inform better forecasting.
It'll inform better sequencing. It'll inform better signal to action. And we've taken this approach to say, we don't need to go out and say, you know, chorus is better than gong. If a customer loves gong. We want to integrate to bring that first [00:18:00] party data, to bring that rich first party data into an overall first, second, third party data ecosystem that's actually working together that's actually orchestrated so that you can go drive that better outcome, irrespective of who's gathering it.
So I think that was a big shift for us. You know, there was a period in time, Hey, should we get into forecasting? Hey, we could probably build a less good forecasting tool. And I still see companies doing that and I try to give them the cautionary tale of, you can take a very happy half million dollar customer, tell 'em that they don't need SalesLoft or Outreach or one of these other tools, use ours and it might not be as good.
And then you ruin the NPS of a very happy customer, giving them. A less great product. I try to tell other CROs and other folks that are in the midst of that transition. If we were to come out with a less good forecasting tool, great. Maybe some SMBs would want to, you know, just have a one size fits all and it would probably [00:19:00] be okay there.
However, we see the world as there are products and tools out there that are amazing. And customers love them and they are driving the outcomes that those customers want. But they could be better if they had the right intelligence at the right time. And so marrying that first party, second party, third party data into go inform, you know, your next outreach, your account plan, your, you know, forecast, whatever it may be.
And just to really drive the point home, if you think about a forecast that's sitting on top of CRM and in some cases conversation data. That's great, but do you have the full buying committee? Your c m's not gonna tell you if you have the full buying committee, your c m's gonna tell you who you've talked with and what the rep has put in as the buying committee, but you don't have that full picture.
There's so much context, you know, that's, uh, unless there's a mention on a conversation or unless the rep hears it and puts it into CRM, if they raise funding, if they lay off 20% of people, if they have a key job change, if they get a new CFO. In the [00:20:00] world of just first party data and CRM in forecasting, you're gonna miss so many critical things.
And so, again, not to belabor the point, but that to us is go to market intelligence, where within go to market, across marketing, across sales, across data science, across signal to action, all of these areas that go-to-market practitioners should be focused on. They all require. Data. They all require intelligence.
And I think what's interesting, you made the comment early on, you know, yes, we've got SMB customers, we've got mid-market customers, we've got large enterprise customers. We serve the whole market, and as you know, you're further down market, they're typically buying off the shelf and we can go full end to end.
And then as you move up market, it's really more of the journey of, okay, what do you have in place? What is built? What are you building internally from an AI chatbot standpoint? What are you doing and where can we sort of pipe in this key intelligence to help whatever you already have built [00:21:00] versus going into that enterprise saying everything you have stinks.
Everything you built stinks. We're all you need. And I think that's a key transition into this go-to-market intelligence platform.
Integration and Collaboration in the Industry
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Toni: You know, you, you almost went into the next question I had, which, which really was about, um, you mentioned best of breed four years ago. That was not the line that people were hearing from the claris, from the gongs, from the outreaches and the SalesLoft.
Now some of those companies are basically the same now. Right. Do you have, what's, what's your take on the whole SalesLoft Clari Drift? Thing that happened under that lens. I'm not sure if you have something or if you, if you are kind of open to share your thoughts on that, but, but would be really keen to hear that.
James: Yeah, listen, I think in the space, like I said, there are times that I wish more of them were public, so we actually had compare points when we have to go talk to the world every quarter. Um, you know, it's, it's been a challenging couple years I think for the overall space. Just because you think about the, hey, you know, tech layoffs in [00:22:00] 2023 and salespeople are going away because of AI and all this noise.
You know, if you look at 2019 through 2021, it was arguably the best place to be, which is why a lot of those, you know, Vista paid 2.2 billion for sales law. There was a lot of money coming into the space we iPod and now you look at today where there's this, are we gonna hire more salespeople? Are we gonna spend more in this space?
Or can AI do it for us? So. I think they're all great companies and I think, you know, frankly, we partner with all of them to drive great outcomes for our customers. There's my political answer. Um, you know, my non-political answer would be more so along the lines of, you know, they're kind of taking on that similar approach to say, okay, if someone loves SalesLoft and someone loves Clary and they're all in the stack.
Let's bring it home together. But they have to be well integrated. Obviously that was announced a couple weeks ago as a cashless merger. You know, their ability to integrate those things. I think that will [00:23:00] be the key determining factor of how successful they will be. Um, you know, in gong kind of building out sequencing and building out forecasting internally, they're both great products.
And if SalesLoft and Clary and Groove and Drift can integrate, I mean that's ultimately what it comes down to. Having the different names on your shirt and bringing them together, it's gonna be the same as it was before if they don't integrate them well. And I think the key in this space, which is why we pivoted so aggressively to go to Market Intelligence, is if Gong wins that and Gong has the best sequencing and the best forecasting and the best, uh, conversational intelligence.
We want to provide intelligence there to drive those particular outcomes. I'm a huge Clary fan. I'm a huge SalesLoft fan. I'm a huge Drift fan. If they integrate really well, it's, look at any industry, it is fine to have two great players. Again, to the competition point. It'll [00:24:00] keep them innovative, it'll keep them listening to their customers.
And so for us, whether you use that stack of groove, clarity's, uh, you know, sales loft, whatever it may be, what it ends up after they integrate it and close the deal, et cetera. Yeah, if their customers love it, we want it to have great data. We want it to have great intelligence, and we want to have that golden tech stack for that customer for what they're trying to accomplish.
Same thing goes for Agent Force. You know, all of these companies that are getting into this space. I think one of the benefits of, of being ZoomInfo is to that earlier point, we have the size and scale to make sure that the data that we're providing, the intelligence that we're providing is second to none.
And that's not because of AI native or non-AI native. It's because back to those 1200 people, you know, we've got half a billion dollars in free cash flow and we've got a lot of people that make sure that data and data's very, very hard. To get right is a lot of those companies that you didn't mention but probably wanted to mention it started getting [00:25:00] into the actual data space.
You know, not as much the clay, which is more waterfall enrichment and bringing different data sources in, but the folks that really focus. On the data itself, they realize it's really expensive. It's really hard, and keeping it clean and up to date and correct is also very hard. And so that being our core competency with the ability to wrap the AI layer around it to get first party, second party, third party.
Bringing those data points together. It used to be too hard. They were siloed, they were sitting in other areas. You had to have CIO go get snowflake information. Then you had to have, you know, your rev ops person bring CRM information in. I think the biggest unlock in our space is the ability now to break those silos down, bring huge amounts of data together, both internal data, first party, third party, and actually make heads or tails of it.
That is where we're seeing the biggest success, irrespective of kind of who wins the, you know, that last mile sequence or [00:26:00] forecast or whatever it may be.
SEO Challenges and Market Impact
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Toni: We've talked about, um, sales of clarity. Um, there was another piece of news that I wanted to get your take on, which was really. Uh, monday.com. You've probably seen it on, uh, on, uh, you know, LinkedIn.
These guys are also public. They talk to the world in one of their quarterlies, and they talked about, you know, oops. Our SEO our organic traffic is, is taking a large hit. Um, and I think they lost something in the, in the, in the realms of like 30, 40% in market, uh, cap basically in, in, in one day after that call.
What's your, what's your learning from that and, and, and so to speak, what, what is it that you as a CEO, I mean, you guys could get hit by the same thing, I guess, right? So that there must be some thought that goes through your mind of like, oh, I really wanna avoid that. But also maybe is there some learning here from folks, other folks that are listening that, that maybe haven't.
Fully, you know, uh, gone through that problem in their heads yet.
James: Yep. [00:27:00] So first and foremost, Monday is an amazing company. I mean, if you look at what they've done over the years, it's an amazing company. I think the A IO AI in search has hit them and everybody else. I don't think there is anyone that's impervious to that particular paradigm shift. I mean, think about the last time that you just went to Google normally. And search something, you're going to chat GPT. Or even if you do go to Google, you're typically just reading the AI summary and that whole structure that's been in place for two decades that gets you to click through and click to the right page and search engine optimization.
It's changing. And so I think there's a couple things there. I think Monday will absolutely solve for it. They're a great company. I think, you know, for ZoomInfo specifically, two things. The first one is Monday's heavy PLG. So that affects certain companies that are heavy PLG, more than companies that are sales led.
And so it's funny because [00:28:00] we used to get hammered for being too sales led for too long and we need to move into PLG and you have to do more with PLG. Efficiency, efficiency, efficiency. And you have these folks that you know have been all PLG and when that top of funnel inbound that has literally created so many of these companies for the last couple of years.
Starts, you know, in some cases down 25%, in some cases, down 50%, in some cases, down 75%, you have to pivot very, very quickly. So we were well positioned in the sense, again, poorly positioned, if you wanna look at nine months ago, and we were getting hammered for not having more PLG. But now that we've got this team in place, we can pivot quickly.
Because we don't need to go hire folks. We have them in-house.
The Resurgence of Outbound Sales
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James: And so, you know, to that point, the paradigm shift that I find really funny is that 18 months ago, everybody talking about AI was that it's gonna replace salespeople. AI is gonna take over salespeople. You're not gonna need salespeople anymore.
What AI really has done [00:29:00] is crush inbound demand because of SEO. And so what people are doing is they're hiring more outbound, they're literally hiring more salespeople. To go outbound because of ai. And so there's this resurgence of outbound, but I think intelligent outbound, and that's not like a tagline or a play on go to market intelligence.
I started my career, like I said, in the most unintelligent outbound, which is knocking on cold doors. But that shift, you know, Monday is hiring outbound people. A lot of companies are making their AEs that used to live this great life where I don't have to do any prospecting, this motion. My SDR motion.
The inbound motion, I'm gonna have two to three demos a day, and I don't need to ever pick up the phone to go outbound. Those days are ending and it's, I think, only gonna get worse. And there's all kinds. I've sat in every round table, every consulting firm, to try to figure out, okay, what can we do to optimize for AI search?
Oh, go Reddit. Go to [00:30:00] YouTube. You gotta pump out all this content and you gotta be clear on this. They're all saying the same things and it's not necessarily having the impact. 'cause while you might move up a little bit, you know, and again, to your point on the size and scale, like ZoomInfo always comes up in these, you know, searches, but the ability to take that showing up and then tracking them to your actual company webpage and tracking that inbound, it's gonna be hard for a while irrespective of how good you get your Reddit page. And so I think companies have to move into more outbound. And they're scrambling. Yeah, and I think some companies, I look back at us, we started seeing it in Q4 of last year, and of course it's like, oh, is this seasonality typically November, December? Mm-hmm. We see it found down because it's seasonal. Then Q1 happens and we're like, oh, is it tariff related?
Is it macro related? But you know, basically you can see quarter over quarter, month over month as pe more people like yourself, myself, and everybody else out there start doing their searches in Claude or in chatt. [00:31:00] You start to see that go down. And so yes, I would love to be in a world where I can sit back and say, yep, hey, marketing, go fix that.
Let's get top of the funnel back. Go make sure Reddit's saying nice things about us. Or we could just go deliver. Pick up outbound. And so what's been nice, you know, from a, again, just a inside baseball standpoint, we've got a large inbound team. You know, we, despite all the noise on LinkedIn, to your point, we still had a huge amount of inbound.
And so we had a large inbound SDR team that was handling all of that inbound traffic. The opportunity for them is to shift to outbound and then we can actually have AI supplement some of the things that those inbound SDRs were doing. Or if you really break it down, inbound SDR first job, you know, it's usually our lowest level of the totem pole.
Everybody has to start somewhere and something comes inbound. They do a quick discovery, they set up the meeting for the ae. Talk about something that AI actually [00:32:00] can help augment or automate in some cases. That's not some cautionary tale for any inbound. SDR listening. The ability to get to outbound faster is a faster promotion.
You know, those guys typically have to fight in inbound for six months, nine months, 12 months, get to the top, and then they move into outbound. And then from outbound you go up to ae. It's an opportunity for folks to jump faster because of necessity. And so again, it's a long answer to the Monday question, but mm-hmm.
We are seeing the same. I think everyone is seeing the same. I don't think there's any company out there because these AI search engines have not monetized SEO yet. I don't know if they will, there's talks that perplexity might, they might be the first to do it, but I also think they have their sites set on even bigger things.
Yeah. So they're probably gonna keep taking over the world the way that they are before going and focusing on search engine optimization and pay for clicks, et cetera. And so that isn't gonna change. And [00:33:00] I think the only thing that people can control right now is I need to go outbound and I need to go outbound more intelligently.
So how can I bring on kind of a new class of outbound folks that are not just calling a hundred dials a day and you know, it's an activity game. How can we leverage all of this ai, all of this context, all of this data, all of these things that are out there. How can I go outbound more intelligently to offset what this gap is in inbound from AI search?
AI's Role in Sales Efficiency
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Toni: So you touched on a bunch of things, obviously. Uh, one, one thing I wanted to double click on, so we talked about the negative impact of AI to the top funnel, basically, right? You already mentioned a little bit, Hey, we are maybe shifting the roles around a little bit, some of the inbound stuff. Maybe I can help that a little bit more.
Some of the outbound stuff, maybe AI can't, and uh, and that's where we are shifting our talent. Do we have a couple of other, um, you know, I don't wanna say tips, but, but other thoughts on your head where you think AI in the go-to market under your purview? Where, [00:34:00] where you actually see use cases that work either for you, ZoomInfo or for your customers, uh, or for other folks that you're talking with.
Where are those use cases that that help companies? It's not about cost cutting, by the way, but, you know, be more efficient and then potentially allow them to redistribute some of their budget to adjust for what's happening right now.
James: Yeah, so I, I fully agree on the redistribution. I mean. You talk about inbound SDRs moving to outbound, or you talk about SMB folks that are moving into up market.
I don't think it's a cost cutting game. It is a reallocation of where you need bodies. I think to answer your question super specifically on what we are seeing, especially mid funnel, down funnel and across the board with ai, you know. There's a handful of things and anyone who's ever run, go to market or a sales team or even been in sales, there's a handful of things that your best five to 10 people do.
You know, they do the research, they have a point of view, they know that vertical, [00:35:00] they know that sub-vertical, they know the size, and most importantly, they have a point of view. I think of all the things that make me cringe the most after having run sales for a lot of years. Is when a sales person shows up without a point of view.
Mm-hmm. And I think one of the things we're seeing the most success with both internally products that we're selling, it's not a shameless plug, but. The ability to get kind of a point of view in a box now in one click where you can take, again, if you're selling to me in an instant, you can get the 10 K recapped, you can get our last earnings call recapped.
You can get all of the key, you know, we just promoted an interim CFO to a full-time CFO. You know, we j there's so many data points out there that I would've, as a great rep 10 years ago, had to do just a huge amount of research. Yeah. Somebody would've said, oh, why is Roth so good at sales? Because I do that and so many people don't.
The level of organization going through all of these different channels to find out what am I gonna say when I talk to Tony? And I [00:36:00] think that from a mid and a bottom of funnel standpoint that we're seeing is the ability to say, you don't need to be an industry vertical rep. Like you look at companies that were great 10 years ago, they would go hire somebody that had been in the retail business for 20 years and they were the retail vertical rep.
Mm-hmm. You can become. You know, a retail vertical rep so much faster knowing their acronyms, knowing you know, what's important to them, who their competitors are. That used to take somebody that had built that muscle up and now you've got this democratization or this equalizer where I can be an expert in retail and know exactly what I should be saying based on all of this first, second, third party data that exists.
So I would say, I mean, that's a huge driver. I think one of the additional areas, again, to the data silos. You know, we've built this internal chatbot and then externally we call it go to Market Studio, which is, if I think about even two years ago, if I said, Tony, you're my leader of Rev ops. I want to go run a really aggressive campaign against anybody that went [00:37:00] with Six Senses data, because I know they're probably coming up in contract and I also know how hard data is.
We'll leave it at that. You would as the Rev ops leader. Have to go to, again, CIO, you'd have to go pull Snowflake tables. You'd have to see conversations. You'd have to go into CRM. It would take you weeks. And then you would probably say, Hey, the C i's busy. They don't want to get me all this data. Or the CDOs busy, they don't wanna get me this data.
Can you slack 'em when Nasty Graham and prioritize it? I think every CRO has been in that position and here I am thinking I'm brilliant. 'cause in the shower I was like, we should go run a competitive campaign. And then I find four weeks later, I gotta go horse trade with our CIO and say, please. Get this data over to Tony 'cause I'm trying to run this campaign and then we're a month late.
And so I think the most impactful AI that we are both using internally and soon to be putting out there in the world is this ability on top of our data and intelligence foundation to start breaking [00:38:00] down those silos and plugging in again, 10, 15, 20, 30 different data sources, most of which aren't ours.
By the way, this is not like a ZoomInfo data. It's all you need. It's more of a. The amount of context that lives in calendars and emails, in calls and conversations in CRM in third party. In second party, it used to just be too much reps would've to go back and forth between 12 different screens to get that information.
And again, now with AI built into that data foundation, you can plug those things in and build a query like you would in chat GPT, asking how many times to mow your lawn after you put new sod down or whatever you might ask it. Now you can do that from a go-to market perspective, and it's never really been available like that before.
Toni: There were a couple of different efficiency use cases or angles or place rather than you just mentioned, right? The first one was really about, um, Hey, you don't need to be an industry expert anymore, you. You know, what does that mean for your, for your organization? Well, you don't have [00:39:00] to, um, you don't have to be too rigid with your, with your, with your chess board, basically.
Right? People can move around more freely. That gives you flexibility. If a rep leaves, kind of, it's very easy to backfill that, right? It's number one. Number two, um, hey, you know, we can cut down the research. That's, that's another piece, right? Which. Speaks into this RGA revenue generating activity, trying to get that up.
Right. And then I think the last thing you mentioned here, just to kind of repeat that back, was almost the, I don't need to wait for some data person to help me with my problem. I can just be creative, think this up, whatever I want to do, and go execute this. Right? All of these things are really cool. What, what I wanted to kind of double click on is really here on the, uh, on the obligation of that is.
Leveraging AI for SMB Data
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Toni: Do you also see this as, um. A lever to have reps be able to sell more, because at the end of the day, right, we can talk about all of these different ways of finding efficiencies. [00:40:00] Um, a hardnosed, uh, COO not necessarily unlike yourself would be like, Hey, you know, where, where, where's the money in the end?
Right? Can I, can I increase quota? Can I, uh, can I have fewer reps? Can I relocate some resources? Do you, do you think that, um, these things are, uh, gonna enable teams? To really make those efficiency plays come through in their, you know, in their p and l, in their CAC and their CAC payback and all of these different, uh, metrics.
James: Yeah. So I'll use a quick example that I should articulate. I think pretty well what the ultimate outcome is. So we just, uh, came to market with a new data set for those in the data business or those in go to market. You know, SMB data is very challenging. There's not a lot of public information on them.
Companies, believe it or not, are still sending people out to the mean streets to go knock on doors to find information out about them. And there are a host of companies that are very large, that still have huge SMB sales, if you [00:41:00] will. Mm-hmm. So we had this problem and we said, okay, we've got the resources.
How do we go solve this SMB data problem? Mm-hmm. We basically went Secretary of State. We went state by state Freedom of Information Act, and you can see every week basically new business formation. So, you know, James and Tony decided to go open a coffee shop. We have to go file. We're a new business now.
You got James, you got Tony, and you have that information. It's all publicly available, but it's hard and it takes a lot of work to get to, but it's an incredibly important data set if you're toast and you're trying to find new restaurants every week. Um. The reason I bring this up from an AI perspective, so that's like the ground and pound.
Let's go get that data because it's gonna be really important to anybody who's selling to SMB. Now, for anybody in revenue leadership a couple years ago, here's what would happen. Hey, everybody, you know, 2000 salespeople, we've got this new data set go [00:42:00] and they would go show up to Zscaler that's got 7,000 enterprise customers and never sells a thing to the SMB.
They show up, they waste a call, they waste a relationship, and it's like, Tony, why would you try to sell me this data? I don't care about SMB. We sell to the enterprise. And then you'd get mad at the sales rep being like, how'd you not figure that out? And they're like, well, you told me to go sell this and I got 50 other accounts. I think every revenue leader has been, in that case, what we've been able to do is we could go in to go to Market Studio and basically say, in my territory, in my patch in North America, wherever. Show me all companies that are customers of ours that have either on a chorus call or on conversational intelligence complained about our SMB data or in earnings or public filings.
They sell to the SMB. We had all these different proxies for fit for companies that would sell to the SMB and it even in our enterprise segment alone, we were able to shrink that ecosystem down to 1500 customers that we knew. Cared about the SMB, whether they told us to be a first [00:43:00] party, whether they said it publicly, whether, you know, they went on their earnings call and said, we're gonna go to the SMB now, all of those things, it would've been an impossible data exercise prior to a go-to-market studio.
And so now I can say, here's this data set that is unbelievably relevant to these 1500 customers in the enterprise. Here's really tailored messaging to each of them, because it's not just getting the list. There's a lot of cool AI companies that can build you a list based on scraping public information or whatever it may be.
It's getting that list of, here's the 1500, here's why we know unequivocally that they sell to the SMB and care about the SMB, whether they told us directly or we found it XYZ 1 23. And then most importantly, here's all the context from. Their account relationship with us, their growth with us, their downsell with us, all the conversations that we've had.
Here's a point of view, so me as a seller, the click of a button, I can say my territory of 50 enterprise accounts. I've got [00:44:00] six that care about this SMB data, and I've got a point of view, account plan, account brief for each of them that allows me to go into them. Vertical specific, sub-vertical specific, first party context specific.
If you think about the amount of waste, and I think, you know, some people could listen to that and be skeptical, oh, I can get an account plan AI from such and such tool, and I can build a list from AI such and such tool in their AI native. The ability to do that end to end, I had to say it. The ability, yeah, I know the ability to do that end to end and more importantly, end-to-end to the actual outcome, to the actual action that you're taking, and then put it into a sequence and then get marketing around it.
That doesn't exist. And I think more importantly, the amount of time that goes into that, if the old James Roth at 10 years ago is that good rep doing all that research and all that organization, think about the waste that I'm not in front of those customers. And so we have this, we, again, we are a [00:45:00] heavy data tracking company as I'm sure most could imagine.
The thing that we cannot do is spend a bunch of money on ai. And then not get the outcome from it. So we pull each of our enterprise reps and we look at time spent, another easy thing to get. And so we have a rep, his name's Josh Enterprise guy. He is got 20 accounts and he is got a large expansion opportunity with a big cybersecurity firm.
And we basically said, went into the chatbot and we said, show me how Josh has spent his time on this account. 35 hours in meetings. That's good. 35 hours in meetings is great. 85 hours. Doing prep account planning docs. 'cause again, we see all the Google Docs. All the Google sheets. We see that 85 hours for 35 hours of meetings.
And so the ability to take the 85 hours down to 10 hours, and this is not anything revolutionary in AI land. It's the number one use case of like, oh, more efficiencies, save time. Mm-hmm. But taking it a step further to say, if Josh saves 75 hours on [00:46:00] this one account, then I'm gonna look at Josh's calls.
I'm gonna look at Josh's meetings. There should be an increase somewhere else. And so that is just the basic time back. Josh should go from 35 hours of meetings. To 45 hours of meetings and cut that, you know, and that's just in one account. And so we track that maniacally to make sure that this isn't just some, Hey, Josh has got a better life now.
He's gonna go walk his dog more. Work life balance is a great thing. Disclaimer, cut that if you want to. Um, but like making sure that it leads to that better outcome in terms of more meeting coverage and conversion rates, close rates, all the above.
The Drive for Efficiency with New Tools
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Toni: I think you're touching on a point that I really, really wanted to get to.
So I'm really happy about that. And it's all the AI tools from all the AI native founders, it's all the tools that have been around and are plus a billion dollars. Um, if you as a leader at the end of the day, you know, you implemented all of that stuff and now suddenly the workload of your team goes down, which is fantastic.
That's what [00:47:00] those tools are there for. If you are as a leader, unable to take that gain and convert that into. More valuable work, or I might say fewer folks doing that work or other ways of finding actual efficiencies in the end. Then I think you still have failed in the idea of implementing those tools, right?
Kind of. Uh, I, I think what, what is really important, especially with this, I feel this new drive for efficiency because there is so much pressure right now that that's really what I feel and what a bunch of other people are also feeling is no one know a new tool will probably not solve that. It will be the key to unlock it, but you as a leader still need to go through the uncomfortable job of.
Actually, you know what, Josh, um, your target could go up now, or you know, Josh, you know, you can, you can cover more than 20 accounts now, right? Is what do you, what, what's your, what's your position and your perspective on that? Actually, kind of, because that last mile in order to really unlock the gain [00:48:00] that is also really the difficult part, isn't it?
James: I've been on this mission since I started at ZoomInfo. We used to have enterprise reps that had account loads in the thirties and forties and the way we used to go to market with a super fast lane and expand. You know, we had one Fortune 50 company that had 42 active agreements with us. So that account manager had 42 agreements to renew with one of her 30 companies.
Mm-hmm. So we went on this mission, lower account loads, hire more people, go external, hire people, lower account loads. You hit the nail on the head now, rather than saying, Josh, you have 20 accounts and we've been fighting for investment to get you down to seven. And we're gonna get that from all these other areas because we're moving up market now I can say, Josh, you're gonna keep 20.
But you're gonna show up to those 20 as if you only had seven, because you're going to be prepared like you've never been before. And so that just real-time use case is exactly what we're doing. And then I think just one step further, in that example, if you think about that rep, most of these companies, you have [00:49:00] multi-product.
You have multi vertical. Keeping that in their head to know what to say, how to say it, who to say it to is damn near impossible. Yeah. And so if I can feel confident that Josh is gonna show up, especially with these point and shoot solutions, where it's like, I have this data set. I know you want this data set because of these three things that you've said publicly or you've said to us, and here is this data set, go try it out.
Versus old days. You throw that to marketing, they go blast a whole bunch. You know, they're sending that to Zscaler, they're sending it to everybody, and you just spam at a higher rate with these AI sequences versus, I know exactly what you want. I've got this particular product. We've got the same thing with franchise data.
Really hard to get franchise data. A lot of people really care about franchise data. We went out, we got franchise data, and now we can go to companies that we know unequivocally care about that data, again, for a variety of different reasons, and say, we have this data now. And so I think it's the [00:50:00] efficiency, it's the headcount, it's the account loads, but it's also it again, just from a conversion rate, from a sentiment.
It allows you to really make salespeople into your best salespeople. And that's such a cheesy tagline. I get it. But when you think about the things that make your greatest salespeople the greatest, we now can automate a bunch of those. Now, the things that you can't automate are the ability to build that relationship. When we talk about the retail vertical person, the relationships, the network that they have to say, oh, you, you worked with Tony over at uh, JC Penny. Those things still exist and they're incredibly important in sales, don't get me wrong, but a lot of people, and I think will understand this, typically, there was a trade off the person that was great at relationships, that was great at golf, that was great at going and howling at the moon that had those relationships.
Not always the best seller, the best technical seller, the best acumen. They were great at building the relationships and you always had to make this trade off. You have skill, you have will, you have the person [00:51:00] who's gonna make a thousand phone calls, but every time somebody answers you cringe when they talk.
You don't have to make those trade-offs anymore because I think there is this better equalizer where you can start hiring in a different way. You don't have to have that, Hey, you're gonna make a thousand calls, you're gonna make a hundred much better calls. And so you start to get a different hiring profile.
So again, I could go on and on on that topic, but I did just wanna make sure it's not just an efficiency. It's not just a headcount thing, it is also making sure that you are showing up better to your customers with a point of view, understanding their industry Last cringe-worthy moment. I remember when I first started ZoomInfo, 50% of our revenue was growth tech, and I would see senior people show up in the commercial real estate business, customers of ours.
Talking about SDRs, I'm talking about rev ops. I don't think that's ever existed in commercial real estate. They're a fundamentally different vertical. And watching those folks, great salespeople show up to a vertical or in, in [00:52:00] insurance, you know, they call 'em producers. They don't call 'em salespeople. All of this nuance.
You used to have somebody that would live there, and I, I couldn't even imagine being on the other end, being somebody in commercial real estate being like this effing guy, like talking about, you know, growth tech BDRs like we're CBRE. And so I think those things will drive outcomes, and I think the key is measuring those outcomes versus the great AI proliferation where you got 60 different tools that are all kind of hanging around the hoop on similar use cases, and you can't track when that same board that says, Tony, do more with ai, and you're like, Hey guys, I did a ton with ai, then your margin is crushed, your expenses go up, and you cannot point to anything that has led to a different outcome.
You're just spending a lot more money.
Toni: James, I would love to keep on going here. Uh, I think we're on a roll, uh, but unfortunately time is up. Uh, thank you so much for your insights. This was, this was really fun for me and I'm sure it's really fun for everyone else to listen to. And I think there are a couple of [00:53:00] pieces everyone is gonna take away and, and start thinking about with their business.
James, thanks. Thank you Toni. Thanks for having me
On
Next Week: $5M ARR per AE with AI
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Toni: next week, I have Raul back on the show and we are discussing how we believe the $5 million a RR per year AE can be achieved with ai. If you don't want to miss this, then hit subscribe and see you next week.