How ZoomInfo’s RevOps Team Uses AI to Drive Efficiency and Accountability

James Geyer: And we’re back for our latest episode of boardroom RevOps, where we’re bringing you valuable tips from RevOps experts so you can make to the C-Suite. I’m James, the co-founder of AccountAim, the RevOps BI platform. I’m joined by Courtney Coleman, a director of RevOps at ZoomInfo. Courtney, good to have you on.

Courtney Coleman: Yeah, thank you so much, James. Excited to be here.

James Geyer: So much talk about AI and tech right now, um, in the, the sales tech landscape. So who better to talk about the future of AI in RevOps than someone doing RevOps at perhaps the leading go-to market tech company. Um, so I’m super excited to have you, Courtney.

Um, before we dive right in, like do you wanna share your background for folks?

Courtney Coleman: Absolutely, absolutely. So I’m a director of RevOps at ZoomInfo like you said. I oversee our center of excellence function. Which is comprised of all things intake, standardization, prioritization for our internal RevOps team, as well as more of that go to market lens, which is our business partners and business process analysts.

So a lot of great things. Uh, my background is in project management and consulting as well as the better half of my career spent in operations. So I love taking all of those things I’ve done in the past and bringing them to this role today. So, yeah.

James Geyer: I am curious, this is a, a little different than our, um, agenda, but can you share a little bit more about the center of Excellence?

It’s something that I only hear about from like larger companies and I think a lot of listeners might actually won’t fully understand it. So like how does that sit relative to like the broader RevOps org one exists and how does that work?

Courtney Coleman: Yeah, so transparently, when I joined ZoomInfo about three and a half years ago, I started in RevOps.

It was one big org and, and we were all doing kind of a, a myriad of things. We were all doing a little bit of everything, and it wasn’t super specialized, I’ll say. So in the past couple years, um, we’ve, we’ve bifurcated a bit where we have a center of excellence, which like I said, is more focused on that internal operations.

How can we ensure that our RevOps team, as it’s scaled and grown over the past few years is operating as effectively as possible, but also that strategic lens within RevOps, like the business partners. Like I said, the other couple functions we have within RevOps are business process owners. So I think of them as pseudo product managers.

They work a lot on our CRM and other systems as, as, again, like those pseudo product managers. And then we have another team, which is revenue technology. They oversee all of our, we call it tier two tech, so not Salesforce, but other systems that we use within RevOps.

James Geyer: Got it. Super helpful. Really, really good.

Uh, layer of the land. Let’s chat AI then, uh, let’s start at the highest level possible. How is ZoomInfo thinking about using AI internally in their go to market efforts?

Courtney Coleman: Yeah, so when I think of how we’re using AI here at ZoomInfo, and you touched on it a little, is I think of it in two lens. And I think when we jumped in and AI is the bright shiny object, right?

It’s super exciting. We focused a lot on how can we make go-to market teams better? What can we do to optimize their performance? And let’s, let’s look at all of the processes that we’ve built and where can we leverage AI and all of those things. And that was really exciting. And we moved really fast.

Then we kind of had this aha moment of what about us? What can we do as RevOps professionals to better leverage AI and automation and make us operate better? So when I think of specifically, how is RevOps at ZoomInfo thinking of ai, it’s really in those two big buckets. What can you do to ensure that your go-to market teams are leveraging it and operating effectively?

But what about the internal RevOps teams and how can we ensure we’re operating better? So one of the things we’ve done that I think has been incredibly instrumental and helpful to anchor us, because otherwise we’d all just be running at a bunch of stuff. We built both an internal facing roadmap. What are all the processes and things that we do within RevOps?

Can it be automated? Can we leverage ai? And then we also have a separate roadmap of what about all the go-to-market functions? What can we leverage AI or automation for? We come together as a group once, twice a week to review this roadmap, talk about progress, what new needs to be added, but really taking that lens of not just supporting your go-to market teams.

We always think of others in RevOps, right? Mm-hmm. What can we do to make others better? But also having the lens of internally, what can we use AI or automation for more effectively? That’s been huge.

James Geyer: That’s great. That’s great. So I hear two things. Um, two buckets. Rep facing initiatives, RevOps owned initiatives to make you guys more efficient.

And then from a process standpoint, you basically mapped out. Basically everything you guys are doing to understand like where there’s opportunity. Is that the right summary?

Courtney Coleman: Yeah, and I think especially on the RevOps side, it’s, you know, what are all the processes that we’re doing? I always think of this, if someone on the team left tomorrow, do we know.

How to do the process that they’re doing. You know, do we have that documented? Is that stored anywhere? And what are some of the other things that we’re doing today? So really from an internal perspective, um, what we, what we are looking at is low hanging fruit. What can we automate really quickly as opposed to before we jump straight into automation or leveraging ai, does that process need to be cleaned up?

You know, when, when you introduce automation, I think I’m a bit of a skeptic sometimes when you introduce automation or just jump straight into automating a process, you naturally lose some visibility into it. Yeah. And some control over it. So one of the things we’ve been really conscious of, and you know, someone, um, someone on my team that leads more of that internal focus is before we jump straight into automation, are we confident in this process?

Yeah. Do we wanna automate this? What needs to be cleaned up first? So it may seem like we’re taking a bit more time, but it’s gonna pay off in the long run so we don’t automate a chaotic process.

James Geyer: I think that’s so important. And I think, uh, ZoomInfo is certainly more buttoned up than some like earlier stage companies, which is, which is natural.

But I think so many folks want to throw an AI tool at a problem when like they don’t even know what they’re trying to solve for. And so I think exactly, such a good point. You need the foundation, you need quality data. You need to know what you’re solving for, you need the process. And then you guys are even a level above that.

Like how do we actually make sure the process is. Streamlined or simple enough that AI can be successful and we actually know what’s going on.

Courtney Coleman: Yes, exactly.

James Geyer: I know this is probably a murky question. How do you think about that? Like how do you assess the current process and if it’s ready for ai?

Courtney Coleman: I can use actually a real time example of something I’m doing with my team today.

So the business process analyst function that I alluded to earlier, they do a lot of process monitoring. So one of the things that we’re really conscious of in RevOps is as we change or optimize a process, is it effective? So there’s a lot of monitoring that we’ll do where we’ll do Salesforce reporting or use our own internal products or our forecasting tool.

And we’re doing a lot of monitoring and effectiveness of these processes. It is so manual today and one of the biggest pain points we hear from our go-to-market teams, because we’re doing this monitoring and then sending out communications to a bunch of leaders, like, here’s one of the biggest pain points I hear.

I have to check 15 different Slack channels to get these updates. ’cause they’re going to so many different places. We’re manually doing some of the monitoring and then it’s going into these different communication, right? So what we’re doing today is we’re going through creating that repository of all the monitoring that we have.

Mm, we are determining is it effective? Do we still need to be doing this? What type of monitoring is it? Is it informative? Is it investigative? What’s the threshold? What’s the trigger for it to become investigative? Where are you communicating this out? Why is it in a separate channel than this other thing?

Right? So we’re really spending the time to do that, especially for those things, like I said, on that roadmap that are more external facing and going to our stakeholders. Take the time before you automate it. That would be my advice to everybody, take the time. Especially if it’s going to executive stakeholders, which a lot of our comms are.

And then, like I said, what we’re doing is we’re aggregating all of that, making the decision, do we even need this monitoring anymore? Mm-hmm. Before we go ahead and just automate it. Um, and then is there opportunity to consolidate, especially on the communication side. So there’s a lot that we’re, like I said, we are making sure that we take the time to evaluate the effectiveness of what we have today before we just jump straight into that automation, which

James Geyer: I think, I think is a super helpful example.

Yeah. Really smart too. It kind of reminds me of just building like, like a, if you wanna talk like. Product like building a POC before you build the whole thing. Or even if you wanna talk to RevOps, like doing an analysis in Excel before you go buy a tool or before you automate the analysis too. It makes total sense.

Courtney Coleman: Exactly. And there’s definitely, you know, there’s some folks that could say, do you really have to take that much time upfront? But I, I do really believe this will pay off in the long run and not just create more noise. AI’s really exciting, but when everyone’s doing it, it can become noise. Right. So we really wanna be sure that what we’re automating or implementing AI with is clean, and we’re not just automating chaos.

That’s so important.

James Geyer: Yeah. Great. So that, that’s kind of the foundation. Let’s maybe move into like some of the specific areas that you guys are exploring on, like the, the use case side. Maybe let’s start with like the rep facing angle, if that works. Like what are some of the areas there that you guys are prioritizing on the rep side of things?

Courtney Coleman: Yeah, so I think on the rep side of things, there’s, there’s a lot to be honest. So we have, um, an internal chat bot that we have here at ZoomInfo, which is super, super exciting. And one of the ways that we’re using it is you can use it to create an agent to coach your calls. Evaluating the effectiveness of your calls, are you effectively prepared?

And all of those things. One thing we’re, um, actually actively working on, so I can’t go into a ton of detail, but I think within RevOps, a lot of what we try and do is optimize the sales process, right? And I think of like sales methodology, think MEDDIC, MEDDPICC, all of those things, right? So we are asking reps, Hey, after you have a call, go into our CRM, enter your metrics, enter the pain.

That’s manual, right? No one wants to do data entry. That is really time consuming. So we’re actually exploring how we can leverage our own internal tools to automate that capture. So an example being, you know, again, I always think RevOps is associated with the efficiency. And that’s really important. But I love the possibility of using AI to drive accountability.

So if we can use our own internal tools to actually, again, not just create efficiency, to say, Hey, you no longer have to manually enter information into our CRM, but use Chorus. Use our conversational intelligence. Use all the data that ZoomInfo has to actually populate some of these critical fields, like metrics, like your economic buyer, like your paying.

It’s not just, again, going to create efficiency, but it’s actually going to ensure we have the most up-to-date accurate information in our CRM. So if I’m a sales manager, I no longer look and say, alright James, let’s open up your pipeline here. Let’s look at your opportunities. I see in metrics, you put A, B, C, D, E ’cause you just wanted to bypass entering the information.

Right. That happens. Unfortunately, it happens with doing something like this. Like I said, we’re exploring it right now with. Automating that information from our own product, it’s huge. It doesn’t just ensure that we’re more efficient, it ensures that we’re more accurate and we can hold our reps more accountable, which is super exciting.

James Geyer: Yeah, that’s great. How do you think about like the, the business impact of that use case?

Courtney Coleman: Yeah, so I think like I, I touched on a little bit. It’s not just efficiency, right? That’s huge. It is gonna save time. It’s gonna save time, not just for reps, but it is also gonna save time for our managers. From a review perspective, again, opening up our pipeline, it’s less a conversation of why didn’t you accurately.

Update this. Why are these fields blank? But I’m gonna feel that much more confident of what is in our CRM because it’s coming from our own data. So I think it helps there. It ensures we have a healthier pipeline. I can feel more confident in it. It helps from a forecasting perspective. It also just, again, coming back to that accountability piece, it helps me if I’m a sales manager to say, why is this deal in stage three if we haven’t identified the pain yet?

Right. Yeah. As a very tactical example. But then I also can ensure, hey, I know that you spoke about this on our most recent demo or conversation, boom, that information is populated and I know it’s, I know it’s not, oh, you had the conversation or demo, and then a day later entered it in the CRM and it’s not super accurate.

So I do think just from an accuracy and pipeline rigor perspective, it’s, it’s huge.

James Geyer: Yeah. That’s great. I feel like when you have more time to analyze what you trust in terms of pipeline metrics, you have more time to then go figure out shortfalls or, you know, get things out of there that you don’t want to forecast in, which is really good.

Courtney Coleman: Exactly. And selfishly, I think, you know, obviously this, this is geared toward RevOps, right? It’s, it’s hard when we make changes or try and optimize process and, and the conversation is. We’re gonna make this change, but it’s gonna make your life harder. Yeah. We’re gonna ask you to populate more fields because all they hear, or one of the big things I think they hear is, you’re slowing me down.

Yeah. But if I can go to them and say, we’re gonna optimize this process and we’re gonna change our sales process a little bit, but guess what? We’re gonna use AI and automation and do it. That’s a whole other conversation. Yeah. So it’s, it’s made. Selfishly my life a lot easier.

James Geyer: That’s great.

Courtney Coleman: But it’s, it’s huge, right?

Like it is really exciting. And again, we just feel that much more confident in, in what lives in our CRM and in our tools.

James Geyer: How has rollout gone in this example? Any unexpected challenges? How do you Quality control,

Courtney Coleman: like I said, we’re actively working on this, so it, it hasn’t been formally implemented just yet.

I would say one of the biggest things that’s been successful with this initiative in general and just the talks of AI and automation embedding it more, is getting the sales team involved. If I go to them after, like right before this is ready to go and let them know what we’re optimizing and what we’re changing.

That’s not ideal. Yeah, so bringing them along for the ride and helping them co-create and design this with us as much as possible has been massively instrumental in this effort. I think for something like this, on the more technical side is there’s a lot of, like I said, just on the technical side, is how does our product speak to our CRM and when do you, for this information I gave of the MEDDPICC automation and looking into some of these things, how frequently do you automate it?

And is that the same up market versus down market? And is that the same when it’s a renewal versus an upsell? So there’s a lot of things we haven’t had to think of before by implementing some of this automation and ai, which we’re having to take a different lens. And I think one thing I especially love about ZoomInfo and just the culture we built is try it and break it and like, let’s learn fast, like we do move really fast.

So I think one of the things we’re doing is. Consistently just iterating, building, and we’re gonna pilot this. But that’s, I wouldn’t necessarily say it’s been a challenge, it’s just a new thing for us to think of is the triggers for this. Especially something that is so embedded in all of our go-to-market teams day to day.

You know, we’re gonna change how they operate. So that’s, yeah.

James Geyer: Back to the process side too. What are we really trying to solve for and what, what are the needs

Courtney Coleman: exactly.

James Geyer: Important to be thoughtful. Exactly. Let’s, uh, let’s switch over to like the RevOps side of things. Um, you mentioned that that was another bucket and maybe one that’s even more exciting for you.

How is your RevOps team Yeah. Looking at AI use cases to make you guys more efficient or, or maybe there’s other benefits beyond efficiency?

Courtney Coleman: Yeah, yeah. I think, you know, there’s a few, a few different things we have in the works right now and we’re actively using. So on the RevOps side, like I said, we’re focusing on how can we operate not only more efficiently, but I think one of the things we’re also trying to do is remove some of the bias where we can.

So I’ll give an example. Like I said, we have this internal chat bot that we use here at ZoomInfo, and we’re building several different agents. For RevOps, and one of those is an intake bot and prioritization. So today, I’ll give you a little background if that’s okay on how things work today. Mm-hmm. So if I’m gonna go to market team and I wanna make a request to how Salesforce works, or I wanna ask for a change in our forecasting system, whatever it may be, if I have a request of RevOps, I would go into a centralized intake form.

That form gets routed into Jira. We review it, and we as RevOps assign a priority. Now we have a framework for how prioritization works, but as we all know, unfortunately, you can interpret that maybe a little bit differently than I do. So what I deem a P one, you might deem a P two, right? That naturally is going to happen.

So what we’ve done is we’ve actually, by leveraging ai, we’ve built a prioritization bot and an intake bot that actually reduces some of the back and forth between RevOps and our go-to-market teams, where instead of just going to a form. And answering, unfortunately a lot of questions. We now have a bot that interacts directly with our go to market teams.

So when they submit a request, it takes on the persona of RevOps and we go back and ask it some questions to clarify and better understand the request that it has or that that person is asking for. So it kind of does a little discovery for us. So then by the time the request comes into us, we then have another layer that evaluates that request based on some of the questions we’ve asked and other criteria.

And automatically assigns a priority for it. So again, it’s taking away some of that guesswork and reducing a lot of the back and forth on evaluating those things and doing the discovery. It doesn’t remove the human element. You still need to talk to your stakeholders. Mm-hmm. You still might have to go to them and ask questions, but this just creates that efficiency for us and remove some of the bias on how we’re prioritizing our work, which is super exciting.

James Geyer: That’s great. What have you felt, I know it might still be early too, like how are you feeling like your day-to-day change as a result of this?

Courtney Coleman: Massively, I’m not gonna lie, it does make some conversations easier with stakeholders because they know we’re doing this. So it kind of removes that bias of, well, why is this person’s work getting prioritized and not mine?

We’ve told you how this works. Like we have this prioritization framework and we’ve communicated that we’re very open and public about how it works. I think the. I don’t wanna necessarily say challenge, but there is still a human element, right? So again, someone can still within RevOps look at that ticket or look at that piece of work and say, Hmm, should that be a P two, or there’s still an element and accountability on us in RevOps to ensure that we are adhering.

To this framework. Mm-hmm. So I do envision, you know, again, there’s a lot of excitement about AI and automation. It’s still on us as RevOps professionals and really anyone else to uphold to it. Otherwise, we’re putting in all this work and all this automation and. Actually adopting it. So we still need to ensure our teams are adhering to all of these frameworks and things that we’ve built.

James Geyer: Yeah. I don’t know if you were privy to this, but I’m curious if you have any insight into like the tech of the chat bot. Is that like an internal ZoomInfo proprietary build? Is this a third party company?

Courtney Coleman: No, it’s something we built internally actually.

James Geyer: Cool.

Courtney Coleman: Yeah, it’s really, really cool. It’s really cool.

James Geyer: That is cool. And then training it. So it sounds like the prioritization framework that already existed, was that kind of like the main. Input to the bottom, like how did you guys think about training it up to ask the right questions?

Courtney Coleman: You know, it’s, it’s funny you asked that because that’s, so, again, I had mentioned there’s an individual in my team who’s built, um, a lot of these agents and, and we had a prioritization framework.

We’ve established it. Again, was it always adhered to? Nope. It’s not, it’s not always easy to, to adhere to those things. So this is another example of, instead of just taking that prioritization framework that we last refined maybe a year ago. We said, Hey, hold on a minute. Is this still the right way to think of things?

Mm-hmm. So again, we reevaluated how we’re prioritizing our work, and that’s what we have fed into it. But again, it was an element of we agree, and it wasn’t just, again, me or anyone on my team defining that. It was across the RevOps org and other stakeholders. Are we in alignment on how we plan to prioritize our work because we’re supporting.

All of our go-to market teams, so we need to ensure there’s alignment on, on how we’re actually approaching that. Another interesting one that I think is just really cool and makes me excited is obviously within RevOps, a big part of what we’re doing is writing requirements, right? And we’re handing it over to developers to then go build different systems and whatever it may be.

It’s hard to refine requirements if you’re relatively new to RevOps or if it’s not something you’re doing all the time. So we also actually have an agent that helps you refine your requirements. Hmm. So let’s say I draft requirements and I, I can plug that ticket into Jira, um, and I can have the bot help me better understand, is there something I’m missing?

Is there a better way that I could have written these? So it also just helps to uplevel individuals within our team. Maybe there’s someone really strong at writing requirements, go find out what they do. And then us as experts, again, my team more focused on how do we operate most effectively, how can we take that plus what other really strong folks within RevOps are doing and incorporate that into the agent.

And then that just helps uplevel the whole org, which is exciting.

James Geyer: Yeah, I think this is a great example too where someone in the center company doesn’t have the resources of ZoomInfo could probably also do a version of this as well. Even with like a pro subscription of chat GPT. It’s like, let me go find a great example of this online, feed it in as like the standard and then going forward I can just.

Put this in all the time and be more efficient.

Courtney Coleman: I, I think one of the, you know, even when I use chat GPT today, I love just asking chat, GPT, how can I better use chat GPT? Yeah. And I ask it for feedback. You know, you, it knows my persona, it knows what I do. It knows I’m a director of RevOps. It knows a lot of the initiatives I’m maybe working on.

Is there something that I could be, you know, leveraging even AI better for that I’m not today. And it, it’s a good tool to even just ask, how can I better perform?

James Geyer: Yeah.

Courtney Coleman: I love that lens of it. Yeah,

James Geyer: for sure. Anything else to cover about ZoomInfo and ai? I know we, we covered this a little bit, like throughout, like maybe how you’re using ZoomInfo tooling for this.

Uh, what else you think is missing in AI for res posts generally beyond ZoomInfo? Like anything we missed that I should have asked?

Courtney Coleman: I really think so. I think, you know, like I said in the beginning, I think some of the, the key points I just think are so critical is. Ensuring that you’re not just automating chaos.

I think there’s so much pressure, like I said, on us in RevOps to move quickly and use AI and do this and this, this exciting thing. And I think just really ensuring that you’re confident in the process or whatever it may be that you’re looking to automate or leverage AI for. And another thing I, I think I touched on this too, is I love the possibility of leveraging AI and even different, different variables of automation to not just drive efficiency, but drive accountability.

So like that MEDDPICC example I gave of, sure that’s gonna drive efficiency, but there’s a whole other level of accountability that comes with those kinds of things. So I think just again, when I think of how, how those of us in RevOps are thinking of it, that’s, that’s some of the bigger pieces for me.

James Geyer: That’s great. Well, sadly, we’re at timing. That’s a great place to cap it. Courtney, thanks so much for coming on. This was really awesome to hear how you and the team at ZoomInfo are thinking through this.

Courtney Coleman: Awesome. Thanks so much, James. I really appreciate it.

James Geyer: Of course.

Courtney Coleman: Alrighty.