In this webinar, Jonathan (ZoomInfo) presents how a unified, AI‑ready data layer is essential for modern revenue teams. He explains that relying solely on first‑ or third‑party data is insufficient; instead, organizations must ingest data from data lakes, CRMs, and external vendors into a single pane of glass. Using ZoomInfo’s GTM Studio, teams can build custom audiences by combining ZoomInfo’s trusted third‑party data with a company’s own first‑party data, then enrich those audiences with AI‑derived attributes such as franchise status, menu‑item availability, job‑posting signals, and propensity scores. A restaurant‑franchise case study demonstrates how AI can automatically identify locations that serve French fries, enabling precise field‑rep targeting. Jonathan walks through a cross‑sell workflow, showing how account fit scores, revenue ranges, recent research activity, website visits, and competitive signals are surfaced, and how AI can generate account plans and email drafts. He then shows how GTM Workspace lets reps prompt the AI for a concise, actionable briefing on any account. The session concludes with a Q&A covering early‑stage company look‑alike list creation, list‑build time expectations, definition of marketing personas, and how CIOs can use the platform to identify addressable market (TAM/SAM/PAM).
Questions this video answers
Load existing customers into GTM Studio, match them to the ZoomInfo dataset, aggregate firmographic attributes, and use AI to generate a look‑alike list of similar companies to focus sales effort.
Depends on AI complexity and list size; for 2,000 companies, roughly 30 minutes.
Roles such as demand‑generation titles, CMO, marketing operations individuals—defined by their responsibilities, varying by organization.
Use GTM Studio (or services) to define TAM/SAM/PAM, pull relevant data sources, and then narrow down to the top ~5% of the market based on key attributes.
Chapters
Thank you for having me, Gerhard. I'm really excited to talk to everyone today. What I'm going to be covering on the ZoomInfo lens is, you know, the importance of having really strong data to fuel your AI initiatives within your organization. One thing that we always talk about with our customers and prospects is how you digest the data is going to be solely a decision that you make as the decision. I mean, as a business, but overall at the end of the day, the data that is fueling that AI initiative is actually gonna be the thing that drives the outcomes you're hoping to get to. So we are gonna talk a little bit about it from the ZoomInfo lens today. My goal is to walk you through a few slides, share a customer story with you, and then drive into the product a little bit for you to get a quick peek of how we help build audiences for our customers. The first part of this that I wanted to talk about is gonna be when you're going to market leveraging AI, many of our customers are thinking about the most common use cases within every business that helps drive revenue, right? Everyone's thinking about how do we drive new logo acquisition, account prioritization, upsell and cross-sell, churn risk detection, and then competitive displacement. And everybody is doing this in a different way today. And oftentimes it's a manual process that requires a lot of time from different teams. But they're thinking about what other things can we add into our audiences? What other attributes of our customers or companies that look just like the companies that we do business with today that are gonna allow us to create the best audience to maximize our advertising dollars, but also maximize our team's time as well. And then it all becomes about how do you execute on that data, right? As I mentioned just a little while ago, every company's gonna execute on that data in a different way, whether it's a homegrown system, whether it is something that you're leveraging with a UI-based product, like something like ZoomInfo has to offer, and it's gonna come from a variety of different places, right? But having that all in a single pane of glass in a single place where you can not only build the audience that you're looking for, leveraging the attributes that are important to your business, but then giving yourself the ability to go execute that across the different places that you have within your tech stack is going to be extremely important. Now, the data layer is going to be extremely important, but it's not simply— the days of just relying on third-party data or first-party alone are no longer going to be able to get the job done as efficiently or as powerful as you need it to be. So our take is, is that you need to be able to pull in the data sources from all of your different tools, whether it is your data lake, whether it's your CRM, whether it's the third-party vendors that you're looking for today, that you're working with today, or you have key attributes that you're looking to gather through AI, bringing all that information together to give the context to the AI layer opposed to just the data is gonna be extremely, extremely important to drive the most successful outcomes you're looking for. The old way required teams to come together and build these lists in silos, right? So because of that, it required marketing teams, revenue operations teams to sort of do their own due diligence, come back into a meeting and then talk about, hey, is this the exact audience that we're looking for? And if there isn't, if not everyone's in agreement, everyone has to break away, go build some more stuff, come back together and build those lists. And then go to market. That is a very time-consuming process for something that should be very, very simple because we typically know what our customers look like, we typically know what the prospects look like. Now it's taking all the data that we have in the different places that live in their own silos today, bringing them into a single place so that we can go execute those campaigns as efficiently as possible. This is just a quick overview of how you could think about leveraging GTM Studio to bring in all the different data sources that you're leveraging today and create an audience that's gonna allow you to build a narrative on who are the right people to talk to at the right time. But not only that, allow your team and give your team the best list that you have the best opportunity to create the most revenue with or win the most revenue with, but create the most opportunities with. Here's a quick example of a customer that works with franchises, and what they do is work specifically in the restaurant space. Historically, what they had to do is create manual lists, do a lot of manual lookup within restaurants, look at their menus, all that stuff to see, hey, do they serve fries? Are they part of a franchise? There was all these interesting pieces of information that were really important for them to detect who is it that they should be talking to, and can they support them at a large scale? What they came to ZoomInfo, that was the problem statement they came to ZoomInfo with. What we were able to do within GTM Studio is leverage AI to be able to identify all the companies or all the restaurants have more, you know, have multiple locations or are part of a franchise or not part of a franchise. And then we're able to use AI to layer that on top of it to figure out on their menu, do they sell french fries or do they not? This customer only cared about talking to the companies that have french fries on the menu so that they can tell their reps in the field which, which restaurants to focus their time and attention on and then be able to prioritize that based off of locations and other pieces of information to allow their team to spend their time in the right places and not waste time driving around talking to restaurants that are not a good fit for their product. Here's just another quick example of what that looks like, right? You build it based off of, are they part of, are they a franchisee or not? Are french fries available on the menu? Do they have a menu that's online that we can go and search for? Are they part of a parent organization or not? Like, who would be making the decisions within these individual restaurants, or do we need to be talking to a larger parent who would ultimately make the bigger decision on where they consume or where they, they purchase their french fries from. If you are interested in learning some more about how GTM Studio could help your business, before I transfer over and show you guys a quick walkthrough of the product, you do have the ability to scan this QR code, which we can share with you again after this. So if you would like to learn more, we can have a bigger conversation about that and how it could impact your business specifically. I'm going to just quickly make my screen here a little bit bigger. So what I did today is actually put together an audience. This is for cross-sell specifically. So this is one of the few plays that we talked about, or which are a main focus of every organization, and how we do it here at ZoomInfo is we take our third party, which we talked about, the ZoomInfo data. That's the most trusted data in the industry today. And then we start to layer it in on top of our first party data. So anything you see on your screen that has the ZoomInfo logo next to it is coming directly from the ZoomInfo dataset. Anything with the CRM or this little sort of like hamburger picture next to it is coming directly through our first party data, which is coming through our CRM. And what you're noticing is we're saying, okay, great, we have the company name, we know how it looks within our CRM, we can see are they a customer, are they a former customer, how would we go about having the conversations with them if we're looking to win back their business or if we're looking to expand within the current customer portfolio. We can also see what their revenue range is. So how do they fit within the ZoomInfo umbrella? Like, are they an ideal size organization for what we're looking to sell them? Then we start to understand a little bit more about them, the industries they're in. Have they been doing research, right? And is there certain information based on the conversations we've had with them over the past 90 days that we can bring to the forefront for our sellers, or we can leverage as context to be able to build AI emails to be able to push out information that's relevant to these customers about how we could support them within a different initiative. We can see the products that they're on. We can see the account fit score, which is gonna outline based off of, you know, the size of the organization, the industry they're in, things of that nature, the attributes that we know tend to be a good fit for ZoomInfo customers. And then we can now start to build our list based off of who is the right fit and the best fit for the thing that we were looking to go sell them. We then can pull forward directly out of the ZoomInfo database signals that show their propensity to be looking at things like competitive products, or are they doing research on certain types of topics, right? Like maybe they're looking at ABM solutions, and because of that, we can pull that into a summary and we can summarize exactly what they've been doing over the past 90 days. We can also take other insights from the ZoomInfo platform and we can see have they been on our website over the past 30 days. If so, we flag that for you so we can then add that into the, the, the Account Fit Score to make sure we're prioritizing the companies are spending time there. We then can go, give me one second, I'm just gonna just change the view real quick just to give you guys a little bit better view of how this can lay out. And what you're seeing is we can start to pull in where there's good fits based off of the, the scope that we're telling AI. So we start to bring in AI into the solution and it tells us, hey, this company here has a high probability for purchasing additional products within the AI scope based off of other things we know about that organization. We can then pull in any specific signals around this company, and we can start to build out a template based off of that. And then we have an account plan that we can help drive forward as well. And that also can give the context to the AI emailer. So we want to push these emails across the board, we can. And then on top of that piece, right, we can say, great, are they looking, or do they currently have a competitive product of ours? And if so, how do we change the conversation from our SDR team or AM team about how we can go and have, how we can disrupt that product within their landscape? That being said, on top of that, we also can go and say, great, how many personas do they have within their marketing organization? And the larger we see on the persona count, the higher likelihood they have a strategy in mind when it comes to ABM or a more complex strategy in place. We can then layer that on top of their, their estimated marketing budget to then say, great, based off of that, what is the likelihood that they would, they would be purchasing a product like this? The one thing that I love the most and I leverage all the time with my teams is going to be looking at job postings. So we can search the web and we can look at this in a variety of different ways. If you want to understand based off a job description, Do they mention something specific in that job description that's important to your business or competitive product that you want to go disrupt? If it's in the job description, it's likely that they want somebody to have that experience when they join the company, which automatically tells you that is a product they are using or they're considering using. Or you could do it more generalized within a certain, um, within a certain department or whatever the case may be. But you have the ability to be able to tell the AI where to go identify the thing that's important for you from a job opening perspective so that you can get in front of the right people and start to build your point of view. And you can be the first one in place, right, to start to create the deal cycle and what's required within that deal itself. Now what I'm going to do is quickly shift this over from what we refer to as the centralized motion, right? Marketing operations, revenue operations, they're gonna live in a tool like GTM Studio to build these custom audiences that they can push into different directions, whether it is from a marketing advertising perspective and hitting on the different channels that you hit on today and making sure that you're getting in front of people where they tend to live to get your brand out there, or it's getting the right list in front of your Sales 3.0 team to be able to go and then attack that list and where you're most likely gonna get the most bang for your buck or the most efficiency from your team. But let's say you get this list over to your team and your SDR books a call with your account manager, and now your account manager wants to go and leverage AI to prep for the conversation they're about to have with a customer. They can go into GTM Workspace and they can give GTM Workspace a simple prompt and say, tell me everything about this company, this customer, and how I could support them with an action plan. By leveraging the AI, what we're able to do is take, again, the first-party data that lives in our CRM, all the context from our conversations that we've had historically with this customer. We can take information we know about them in third-party sense, the types of research they're doing, what's important to them, pain points that they likely have, And then we can start to build a point of view so that we know how to, one, support that customer, how we can identify pain where we can help drive further sale for them, and then we can leverage that information to have the most productive conversations possible with this customer. So what you can see here is it starts with immediate actions in the next 30 days. How do we help them get the most out of the platform that they have today? By training their team how to maximize the solution that's currently in front of them. Then understand, based off of what they have from a strategic CRM enhancement initiative, how ZoomInfo can support that project to ensure that they have information across their CRM that is in a digestible manner. So when they go to leverage it across different tools, they're all leveraging a single source truth piece of data. Then it will drive in to understand, great, what we've done from research on them, we understand that they have $50,000 in monthly advertising spend. So what about the ZoomInfo company or a product set can we help them optimize that information? We can go in and we can do some great targeted plays, but we can create a point of view, show up to that conversation, knowing a lot about this customer prior to us even having to ask a lot of discovery questions, and we can help drive forward a point of view to help try to initiate a conversation and understand the pain points and drive a conversation forward. I will quickly scroll through the rest of this because there is also some other pieces I think are really important about how we integrate it within to help them find success, things like that. But overall, I know that I am at time, so I'm going to stop here. And obviously, if there's any questions, happy to take them.
Thank you, Jonathan. Excellent presentation. There's one quick question. Somebody is asking, how can this help early stage and scaling companies, AI and HTEC, to target their ideal client profiles?
It's a great question. So one thing I always talk to customers about that are trying to either understand who's the best fit for their, their, who they're targeting is take your existing customers that you've closed one business with, you load it into the GTM Studio platform, you match it to the ZoomInfo dataset, and then you start to aggregate all of the firmographic data and the attributes that you have on that company. And then you ask it to go use the AI to go build you a lookalike list for all the other companies that look exactly like this one. So then you can identify exactly where to go focus your team's time by saying, hey, we've done business with a lot of companies that look just like you. And it makes that transition, that conversation a lot easier.
How long does it take to build that list?
It's not extremely long. It depends on the complexity of the AI that you're using and the size of the list. But I mean, if you had a list of 2,000 companies, you could build this in probably 30 minutes.
Wow.
Impressive. Hey, would you do me a favor and define what you mean by marketing personas? That's not a term that I typically use. Absolutely. So it would be maybe like a demand generation title. It could be a CMO. It could be a marketing operations individual. A lot of it would be defined based off of in most cases by the description of what they're responsible for. And that changes slightly depending on the organization. But that being said, that's typically what we're, we're talking about. Understood. Thank you. Very good.
Final question. How can your solution help CIOs identify the addressable market for their company?
So I think there's a few different ways we could do it. One, we could look, we could take it, meet with you, understand, you know, exactly what you look for in a company. We could then pull down the data source so we can go use it, either use our services or we could use something like GTM Studio to build that list. So we have an identity, identify your TAM, SAM, PAM, whatever it is that you're looking for. And then from there, be able to then boil it down based off of other attributes that would be really important for like the now conversation, because usually at any time it's about 5% of your total addressable markets in, in market, right? So it's trying to identify which 5% you should be focusing your time and attention on.
That's awesome. We are running out of time. Jonathan, thank you so much for enlightening us. It is to me The AI augmented sales team begins on a foundation of solid data, and you can get this from zoominfo.com.
