ZoomInfo Demo

Julia Nimchinski:
And… demo time! Welcome to the show, Steve Kerr!
Steve Kerr:
What’s the latest and greatest with ZoomInfo? Yeah. Well, first of all, shout out to the HSC team for having me here. I’m really excited to be here and show you guys what we’re now working on with ZoomInfo. We recently just released a new product to the marketplace called GoToMarket Studio. And to kind of frame us up and set the stage here, what we’ve built with GoToMarket Studio is effectively a centralized command center, if you will, for folks behind the scenes in operation-based roles. to aggregate data at scale, regardless of where that data’s sitting across your infrastructure. You may have some data sitting in a CRM, some in a data lake, some in a MDM warehouse, some may be in a marketing automation platform. So we’ll allow our customers now to tap into all those varying different resources, ingest that data under one roof. So you can truly paint a holistic picture in regards to how you want to go to market.
Julia Nimchinski:
Love it. What’s your prediction for AI and GTM for 2026, Steve?
Steve Kerr:
I think probably, just the increased level of agentic workflows that we’re seeing today across the market, and having AI being able to really automate a lot of the day-to-day tasks that we do kind of on a more manual basis today.
Julia Nimchinski:
Cool! Well, let’s see it in action.

Steve Kerr:
Awesome. Yeah, so to hop into the tool here, I’m just gonna go ahead and share my screen.
Julia Nimchinski:
Yep.
Steve Kerr:
Women here. Okay. Fantastic. So, ZoomInfo’s go-to-market studio here will all be found, for one, in the ZoomInfo admin portal, specifically through a module here called Audiences, and it’s within Audiences is where we build what we call workbooks. And this is, again, where we give our customers now the ability to aggregate data at scale, regardless of where that data’s sitting across your infrastructure. And we’re really taking an agnostic approach towards data and allowing our customers now to bring their own data into the ZoomInfo ecosystem. So for this workbook that I’ve created here in GoToMarket Studio, just brought in 24 records directly from ZoomInfo. These are some of our Topics customers, brought in some baseline firmographics as well, some, you know, what their revenue range is, total employee count, where they’re located. But then, in the spirit of tapping into alternative data sources, I then went and pulled from our Salesforce instance. Who currently owns these accounts, their annual spend with us, their overall health score, and then when they’re renewing with us as well. Then took it a step further and did what we call intent-based signal stacking, where I brought in ZoomInfo signal data to see if we ideally can identify some trends that are taking place across these businesses. You know, do they have hiring plans? You know, are there changes happening across given buying groups? Were they part of a ZoomInfo marketing campaign recently? Additionally, I went back to ZoomInfo to pull in some baseline technographic data, specifically what these customers’ CRM and marketing automation platforms are. And then again, in the spirit of tapping into alternative data resources, went to our Snowflake instance to pull in some propensity model scores, as well as some NPS scores, net promoter scores, right? And then, like most tools today, I now have the ability to query AI to answer questions about these larger-scale data models. Things like, have we discussed our enterprise platform bundle, for example? Or, what are their RevOp pain points? What are their marketing pain points, for example? And this data specifically is all being fed through our conversational intelligence tool called Chorus. We have an integration with them, naturally, and so having the AI, having the ability to reference what was discussed on calls helps further fuel, further go-to-market motions when engaging this customer base. Now, in terms of how I ingested all this data into this workbook within GoToMarket Studio, it’s all going to be leveraged here through our enrichment option in the upper right. Just click on Add Enrichment. Here’s where we have the ability to query the AI data agent to either do deep-level web research for us, or reference maybe first- or third-party data that exists across the infrastructure, have it build out things like account plans, reference those historical call summaries, to draft, you know, really actionable either account briefs, account plans, or again, to have it do that deep-level web research for you. Here, we also have the ability to pull in Zoom info data, whether it’s company firmographics, location-based details, corporate hierarchy data. Naturally, we can find contacts at these accounts as well, pulling in contacts, we can do waterfall-based enrichment as well. If a contact was mentioned on a podcast, we’d oddly have that data as well, or if they were announced in the news. Here again, we have the ability to pull data directly from the CRM, all into GoToMarket Studio. You can see here I have my Salesforce, HubSpot, and Dynamics instances, all interconnected and integrated. I can pull in things like accounts, contacts, leads, opportunities. Actually, one play I can tell you guys that we run internally at ZoomInfo with GoToMarket Studio specifically, is we’ll pull in recent close-one opportunities. Do some intent-based signal stacking against those close one opportunities to, again, ideally see if we can identify some trends in regards to what led to those deals closing, whether it was the products that we were pitching or the personas that we were chatting with. Then once we’ve identified those close one trends, we’ll then inversely pull in closed-lost opportunities to then see if we can apply those close one trends to those closed lost deals for either win-back plays. Mitigation against downsell, or ideally identifying potential upsell opportunities there. Here as well, we can pull in ZoomInfo signal data, whether it’s our intent data, who’s coming to your website, technographic data, job postings, if organizations just got funding, if they’re launching new products, if awards are being granted, if M&A activity is persisting, if IPOs are being announced. There’s really so many other additional signals that Zuminto has on file that, in full transparency, a lot of our customers aren’t even aware that we have a lot of this data. So just know that we have all these additional data assets to really help our customer base be informed in regards to what’s happening across their adjustable market. And then lastly here, in the spirit of, again, really being agnostic towards our customers’ data. We’ve built out third-party API connectors, so again, if you guys have data sitting in Snowflake, or maybe Bombora is your intent provider, maybe you happen to be mutual customers of Dun & Bradstreet or alternative third-party data vendors, maybe some data sitting in Google BigQuery or Amazon Redshift, S3 buckets, maybe Azure is your data lake, or Databricks, potentially. Even if you just have data sitting in a Google Sheet, we’ll allow you to tap into all these varying different resources so that you can marry and pair all these data assets together. Again. Through a single pane of glass here. And then the nice thing here is that once we’ve compiled all this data, we then have an activation layer. We can push this downstream to end ZoomInfo users through what’s called GTM Workspace, or alternatively, we have the ability to push it directly back into a CRM, marketing automation platform, or your data lake. Naturally, for this workbook here that we’ve been referencing, this has been mainly for account-based targeting, but know that we certainly have the ability as well to now, once we’ve identified the accounts that we want to start engaging, find contacts at these accounts. So if we click on Find Contacts here. This basically just launches a microservice of our advanced search, where we can come and specify specific job titles, departments, management levels across varying locations and industries. And then once you process this request for the contacts that are of interest, we then have the ability to compartmentalize the contacts into a new workbook here at the bottom. Very similar to what a Google Sheet would offer. And this now will pull in all those contacts that we just requested. So just take a moment to load here.

And now, once I’ve identified all these contacts, probably would be best to go back to our AI data agent to maybe say something to the effect of… You know, draft me introductory emails to all these contacts. quite nice here is that once I hit next, I now have the ability to customize our AI data agent. It does default to web research, but for the purposes of drafting introductory emails, we probably don’t want the AI doing high-level web research to draft an intro email. So what I’m going to do here is add an alternative source. And pointed out what’s called ZoomInfo’s Knowledge Graph, where we can reference things like maybe an account summary, important contacts that we’ve had conversations with, recent conversations we’ve had, maybe pain points that have been expressed here. Maybe even a brief of the data as well, and since we’re drafting introductory emails, probably healthy to reference the contact’s first and last name. So now if I hit save here, and I’m just gonna do a preview… This now will create a new column within this workbook to then have the AI draft those custom-tailored introductory emails, leveraging all that internal first-party data. One other play that we run internally at ZoomInfo as well, if I was, say, a sales manager, I could come into GoToMarket Studio, compile a rep’s given book of business. Build out account plans for all those accounts, and then push all those account plans downstream to that end seller, creating effectively more cohesion between that sales manager and that end seller, so that they’re more aligned for how they want to go to market to, naturally their customer base. If we drill into the email that was generated here, here we can see, looks like it’s addressing Yuri here. Hope this email finds you well. We can see that it’s actually, generating emails for all the contacts that I requested here. So it looks like I specified it to pull in at least a minimum of two contacts per company, so it’s writing emails, actually, for both of those contacts that are affiliated with that company. Or actually, it looks like it’s 3. Agreed. No, I just threw a lot at everybody. Julie, I don’t know if we’re pausing for questions, or if, Is any… Additional things that we want to walk through.
Julia Nimchinski:
Yes, for sure.
Steve Kerr:
Duh.
Julia Nimchinski:
Yeah, so one of the questions is, what do signal types matter most going into 2026, Steve?
Steve Kerr:
Yeah, great question. So, I think, for one thing, actually, I’ll call it that ZoomInfo not only has the ability to surface which organizations are visiting your website, but we now actually have the capacity to surface which individuals are visiting your site. Which, that, in my eyes, acts as a fantastic buying signal. If I know a certain individual’s on our website, and they’re looking at certain products and services, that is a fantastic, you know, first-party signal that I can then start engaging off of, and maybe reach out to that contact to ideally generate some business.
Julia Nimchinski:
Love it. And then people are asking about personalization of outreach, and ZoomInfo do it automatically at persona-level depth.
Steve Kerr:
So, like, for the emails that are being generated, like, would those go out automatically? Yeah, great question. So, today, they would be just generated in GoToMarket Studio, and then it’s through our activation layers where we can push those emails downstream to end sellers, who then would have the capacity to fire up those emails on a cadence of their choosing.
Julia Nimchinski:
Another one here, about routing accuracy, how does it work in complex pipelines?
Steve Kerr:
Yeah, great question. So, if I come back to our enrichment option here, I will call out that we do have routing capabilities within the tool itself. Where we can dictate owner assignments. I will preface that this product literally just came out about a month ago, so it is on the roadmap to develop more kind of agentic routing-based workflows into the tool, but here, it would just be kind of dictating those assignments manually from a route perspective.
Julia Nimchinski:
I don’t know if you can share this, but people are asking, specifically about the mechanism of detecting and scoring bike signals at scale, like, how does it work?
Steve Kerr:
Yeah, so… For one, I’ll say that ZoomInfo naturally has our own kind of buying signals through our intent data or our scoop data. We collect a lot of additional, kind of third-party signals to help our customer base be informed of their addressable market. But naturally, we’ll allow our customers as well to ingest their own signals that they’ve captured. And it’s then going to be through… our formula field here is where you can say, you know, based on the varying different data attributes or signals that are being brought in, generate a score based off of, say, maybe annual revenue, or website visits, or varying different engagement signals that have been captured. And then we can then leverage the formulas here to then generate additional scores.
Julia Nimchinski:
What’s your favorite use case so far, Steve?
Steve Kerr:
That’s a great question. it’s more of a high-level use case, but I really like the use case of creating that kind of lockstep, if you will, between a sales manager and an end seller, having the ability for a sales manager to come in here, again, compile a rep’s given book of business. draft those introductory emails or build out account plans, meeting briefs, creating, maybe, artifacts or additional collateral via the AI for that rep to then use within their communications with their customer base.
Julia Nimchinski:
Just transitioning to 2026, what can you share about your product? just, I don’t know, like, little highlights or anything you’re allowed to share?
Steve Kerr:
Yeah, so some of the… kind of the next phase that we’re going to be taking for GoToMarket Studio is really activating agentic-based workflows within GoToMarket Studio. So having the ability to go into the AI, say, you know, find me contacts across these accounts. have them immediately created in the CRM, all through natural language processing. Today, you can do that through compiling all the data here within GoToMarket Studio, but adding that additional layer of having the natural language processing to compile all this data for you, and then have it automatically sequenced into your CRM, I think is going to be exceptionally powerful for our customers.
Julia Nimchinski:
Love it. Steve, what’s the best next step to engage with you? Linkedin, email, or should our people go?
Steve Kerr:
Yeah, fantastic question. So, if this piqued any interest for anyone who observed this today, please feel free to either reach out to your ZoomInfo account manager, you guys can hit me up on LinkedIn as well, and I can connect you with the proper folks. trying to think… if you guys are familiar with who your customer success managers are as well, feel free to reach out to them. If you’re currently not a ZoomInfo customer, you can just go to our website and then file an inquiry there, and we’ll certainly be in touch to continue the conversation.
Julia Nimchinski:
Awesome. Thank you so much again.
Steve Kerr:
Yeah.
Julia Nimchinski:
Thank you so much, Tim.
Steve Kerr:
Oh yeah, oh, please go ahead.