Crushing Rev Ops is All About the Data

There’s so much research and so much selling that goes on without the seller even knowing it. That knowing the right time to approach or knowing that someone is in cycle, now tailoring that message to be the right message to the right person at the right time from an effectiveness perspective, it goes through the roof. And so you get the benefit of efficiency, Gong’s platform helping you write tailored messages at scale, AI assistant doing a lot of that busy work for you. Now I can be super efficient at an effective approach. This is revenue makers, the podcast by six cents investigating successful revenue strategies that pushed companies ahead. I am so excited about this episode. My mind was blown. It happens every so often. It was blown. It actually happens a lot, but it was blown. Okay. So we’re talking to Brian Bayless from Gong. He is the VP of? Revenue center of excellence. Okay. Which when you have excellence in your title, like You’re winning. That says something like that. Right? And so he kind of does what we do at six cents where we run six cents for six Cents. He works on leveraging Gong and and really teaching rev ops teams how to make use of all the data that’s being generated through that conversational listening tool and how AI can help you scale in determining what the insights are and then what actions you should be taking. And this, of course, impacts not just sales and coaching and all of that, but also marketing and product marketing and even, you know, what content should be created or what objections are coming up and are being handled the right way or are not being handled the right way? Or where is there an upsell opportunity that the seller isn’t capitalizing on? I mean, it was super, super cool to hear how he’s using it. And it was really one, I think we both are like, we need to go back and take a look how we’re using our own instance, but also really, really actionable because I’m sure there’s so many folks out there, like, everyone’s recording calls now. It’s almost table stakes at this point, but they’re probably like, I spent seven hours listening to ten calls and, you know, and he’s really talking about gleaning insights at scale and really building a data layer that you can just go and execute all these different personas or use cases rather and really make excellent use of all the data. Because there’s you think about the amount infinitesimal amount of data you’re getting. Just amazing. Yep. Now you gotta do something with it. Absolutely. Let’s jump in. Let’s do it. But, Brian, thanks so much for joining us. Been looking forward to this chat a lot. So kinda wanna dive in because you’re at Gong. You know, Gong is so well known, sort of invented the concept of conversation intelligence. But can you talk a little bit about what you’re doing there? Because you’re and you’ve evolved. You’ve been there for quite some time. But can you talk about your role now? Because it’s really interesting what you’re doing for your customers and your prospects. Yeah. Happy to. Just to set where how I got here, I ran operations at Gong for about four years. We recently went through a CRO transition and, I approached the new CRO, Shane Evans, with an idea to be almost like an internal consultative group to rev ops organizations at our customers. Too often, I was getting into conversations about the power of Gong and what Gong could do with customers only to find out that they were mostly struggling with how to organize a rev ops team, how to set up commissions, how to think about territory carving, segmentation, partnerships, you know, just rev ops. Right. And so I really wanted to start a group to combine the power of Gong and what Gong can do for rev ops teams with some historical knowledge from large companies, small company, international, anything to help rev ops teams. Because when I joined Gong, I saw the power of Gong to really help rev ops, and that’s what I wanted to do. And I was blessed enough to be able to build rev ops at a company like Gong and help some customers along the way, and now I get to do it pretty much full time, which is amazing. It it’s very cool. It’s very similar to what we do because we run Six Cents for Six Cents. And so on the one hand, it’s amazing because you’re informing product road map. You are customer zero. You’re kind of showing the industry how to do it. On the other hand, all eyes are always on you. And you are doing the you know, you’re doing your day job, and then you’re also, like, my team specifically was on a thousand customer and prospect calls last year alone, speaking to customers about how we use it. And so it’s a fun place to be in, but it is almost like multiple jobs at once. If I had to ask you, Brian, what is, like, the lowest hanging fruit? Because Gong is so widely used. What do you find again and again that you just recommend off the bat that RevOps team should be doing? Typically, I’ll just ask how they’re using the data because I think it’s a nice jumping off point into all the possibilities. And to me, the thing that I would want to recommend to them is to use the data or harness the power of the platform in a way that helps them with their number one, number two, number three priorities. Right? And that’s different for any company. Depends on the time, depends on how they’ve done an acquisition recently. Are they rolling out a methodology? Are they onboarding a bunch of reps now and they didn’t before? Are they building a CS team? Are they splitting do like, I mean, anything and everything. And I think that’s where sometimes folks without a rev ops background can get lost is how to prioritize all of those different things, like you said, that Gong can help with. And so typically for me, the starting point is the data. Because once you understand the data that Gong is providing, then you can start to understand how to leverage that into your use use case. It irked me. Right? It bugged me as a rev ops leader when I would get pitched a product. As an example, something to, let’s say, a forecasting solution. Right? If it was, hey. We can help you be more accurate of forecasting. If my response was, no. No. Accuracy is not my problem. If the next solution out of your mouth is no, but let me tell you how we can make you more accurate, that’s not my problem of the day. Right? That’s not what I’m trying to solve. I need partners that are gonna help me solve whatever my my current challenges. And so that’s usually where I’ll start is how they’re leveraging the data in order to do that. So when you think about I mean, again, like, there’s so many solutions now. Right? I mean, obviously, you guys are the the innovators, the creators of this thing. But it almost feels like in some form or fashion, most teams are doing call recording to some extent. Right? Or if they’re not, they’re getting ready to do it. And I’m sure, like, especially the smaller orgs are like, there’s so much data. What do I do? Or they have very specific use cases in mind. But how do you advise somebody, say, okay. Now I have this data. Yeah. I can go in. I can listen to a call here. I can listen to a call there. I can gain insights. And I’ve done this myself. Right? Because trying to understand what are customers talking about messaging. We could talk about marketing UCS’s later. But how do you leverage it at scale? Because I think that’s the the challenge because the number of data points is infinitesimal at this point. Like, how do you start to think about a data strategy for these recordings? It’s a good question. I think the data strategy comes back to the starting with the what. Like, what are you trying to solve? What outcome are you trying to drive? If you start it, how do I organize all this data? I think you will end up getting lost in the millions or trillions of possibilities around what you can do with the data. I’ve been attached to many data projects that end up dying on the vine because of that. You just kind of spin and never solve. And with today’s AI going beyond keywords, right? Going beyond, I want to track this phrase or this word to concepts. Right? I wanna understand, is someone doing good discovery? I wanna understand, is someone handling objections correctly? If you have some hypotheses or some inkling of where to start with that, now set up your platform to inform that as scale. Right? So if you think about me, the old days of walking the sales floor, you know, with the cord and the headphones, right? You plug into the system and you listen to a little bit. The right AI in the right platform effectively gives you an infinite number of plugins at exactly the right minute or exactly the right second. When that thing happened, that was always the challenge with ride alongs or with plugins. I mean, you didn’t know exactly what it was going to happen and systems evolved, right? Where all of a sudden a keyword would trigger and you’d be like, oh, I need to go listen to this. Right? But you still had to go listen. The way that the systems are evolving now in order to do that at scale is it’s listening for you and using context based approaches. Now you can do that at scale because now I can answer questions like, so we recently rolled out a new methodology, right, a sales methodology. And step one, we just wanted to know, are the reps even asking the questions that they should be asking? That’s easy. Because that’s for the most part, it’s keyword, and you don’t need a ton of context for that. But you get into some of the more complicated things associated with with a methodology, and you wanna know are they doing it right, And are they doing it at the right time? Now you’re getting into some more contextual things and using a platform like Gong that has evolved the AI to that point, you can get served up which teams, where, what individuals, in what context, in what forum, with what personas, in what types of accounts, and what types of sales opportunities is it working, is it not working. Now suddenly at scale, I’m gonna go and I’m gonna hone in on that dataset. That’s where I’m gonna focus the data. That’s where I’m gonna focus my reports. That’s where I’m gonna focus to ask me anything, you know, with my systems is to understand whether or not that initiative I just spent millions of dollars to create rollout is having the success that I envisioned. I was talking about it recently with someone else, but it opens up this idea of, like, rapid iteration because I think revenue teams are always looking to evolve. I don’t think any CRO or head of rev ops gets in seat and goes, okay. Good news, everybody. We’ll get this methodology in place with this messaging, and we’re done for, like, three year. You’re right. It doesn’t happen. And so you want to intelligently evolve that over time and having something at scale that is always listening for the right moment with the right people, with the right customers, the right personas, it can do that for you. Right? It can tell you, hey, we need to tweak this. We need to tweak that. And you do it in a way that you have a little bit more confidence that it’s driving success as opposed to just throwing darts using the old playbooks. So It’s fascinating, and I almost wanna get some time with you after this podcast recording and, like, learn more about what we could and should be doing. But I guess a question for you around ownership, because there’s a lot of data and there’s probably a lot of customers internally of that data. Right? There’s the product marketing team. There’s the enablement team. There’s obviously rev ops, and then there’s sales leaders. How do you recommend teams start to drive ownership and then usage of the data so that it isn’t, like, one off or ad hoc, but there’s this kind of broad strategy as to how we’re gonna leverage the intelligence that a platform like Gong is giving? That’s a good question. I think with any data, there’s different modes of consumption like the old days. Right? I download a CSV. Now I have a data dump. Right? I’m not really consuming anyway, but I have it. Salesforce reports. Right? I can consume the data, but it’s a nice to look out form. Inside of Gong, we have reporting and analytics engines. Inside of we can port that data to Tableau or Power BI or any kind of system you want to visualize data. I think the right approach is understanding the use case by persona for why they need access to that data or why they need to to getting their reports in Salesforce, the beauty of a platform like Gong and hopefully most platforms now, you can consume that in Salesforce. Right? You can set it up to consume there. If you’ve got a team that’s just used to getting their reports in a Tableau or a Power BI, you can set it up to consume there. The thing that I always found that adoption falls flat when you try to force somebody into a platform to do something they were already doing somewhere else with success. Don’t change for the sake of change. Never gonna happen. It’s never gonna happen. And I think most successful platforms understand that now. Right? Let’s meet people where they work. Let’s not force them into something that doesn’t feel natural. But I think as companies evolve, you want to set up a center of excellence for that, where you understand the personas and the defined use cases. And so you start to recommend ways to consume that data. You don’t want it to be the wild, wild west where inside of forty sales managers, as an example, half are in Salesforce, a third are in Gong. You know, like, you wanna try and make that as uniform as possible so that you can create that experience for the different personas in your organization. And I think that starts with for us, it started with a center of excellence. Right? It was a small team helping define how you consume that data, how you get access to that data. In some of our more complex customers organizations, the IT team is involved. And so the team’s responsible for either designing BI or designing the data structures or the data access. They get involved in a central manner. So I think it depends on how big you are and how complicated you wanna make it, but I’d say as you start to evolve, a revenue center of excellence is a great approach to start with. It makes a ton of sense. We have our data layer. We’ve thought about what we’re gonna do. Let’s go do it. So we think about use cases. Right? And I think some of them are super obvious. Right? There’s the sales coaching use case. And we have an audience of marketers and sellers, so I’d kinda like to maybe just dig in on the marketing side first. So there’s product marketing. There’s brand level messaging. There’s also what are some of the most prevalent or the strongest marketing use cases that you’re seeing that are resulting in, like, really, really strong outcomes or really strong data that marketers are acting on? So we recently had one where product marketing team wanted to understand when customers were asking about certain features and capabilities that the reps were not qualified to respond to. They knew the demand was there, and they had a suspicion that the selling team was not properly equipped to address. And so they built a smart tracker to effectively listen for that so that they could go to the selling team with a business case that said, look, we’re leaving money on the table. And they were able to do that with data that said, right, here’s the demand. We can see it. We can hear it. We can touch it. Right. And we’re not responding in an effective way. That’s a very different message than a product marketing team going to a CRO and saying, your salespeople aren’t very good, or I don’t think your sellers are selling well. So So it enables that. It enables a real database conversation that orients around everybody’s common goal, which is make more money. And so it changes the way that a product marketing team can address that gap. We had a customer who automatically created leads, effectively cross sell leads, right, based on conversations. They had a specialist sales team. So they had kind of a core group of sellers that were selling the platform, and then they had specialist sales teams that would blade in. And so what they did is instead of relying on the seller to listen for the cues, go create something in Salesforce and send to or invite the specialist team, they just automated that. So Gong listened for it. Gong created the workflow that then invited the specialist sales team into a sales cycle via an opportunity in the CRM. I loved that use case. I thought that was an awesome use case. I would have killed for that use case back in the day. I mean, I had fifty product marketers that were all trying to say that their product was the best thing ever. And they’re, like, if we could have just automated what the listening part, what are the customer’s needs? Because ultimately, if you focus on that, you’ll win, I would hope. So those use cases are pretty cool. The one that I thought of, because you mentioned branding, the one that I thought of when I saw Gong, because I was at McAfee for almost twenty years, we went through a period where we had multiple names. We were McAfee, we were McAfee security, we were Intel, we were Intel security, we were back to McAfee, we had products called it was very confusing. It would have been so valuable to know what were our customer facing teams calling themselves, Just that. And how was the market responding? We never knew. We hoped. And we got feedback from the sales teams like this does not go well when we say we’re Intel security. People ask, what does that mean? And so I I think there’s a lot of interesting use cases there for the marketing teams to just hear what’s happening and then sometimes to action that whether it’s with opportunities or, like, asset creation is an interesting one. You know, you spend a lot of time and energy on creating an asset for sales to use. Are they using it? Are they using it effectively? Are they using it at the right time? When they are saying those words, is the right slide up on the page? Did they modify the slide? I always thought one of my learning use cases that I wanted as a rev ops leader was I wanted to learn from my best reps. What did they do with those materials once they got them? You know, they changed them. The best ones always figure out what is going to work first. And so having a platform that actually teaches back, I think this is the right message. This is the message that’s actually being said and it’s working. Wow. That unlocks some possibilities. So those are a few that come to mind. Super, super interesting. And, again, just talking about scale. Right? To not have to go in and listen to every call, but have the insights given up and bubbled up to you. Any interesting sales use cases maybe from a coaching perspective, maybe from a, you know, sales leadership perspective that are worth calling out here? Yeah. One, we launched today a couple of new capabilities. One of them is AI driven scorecards. I think scorecards and scoring, it’s seen as busy work a lot of times. Right? Like I have to go listen to this fake pitch, and I’ve got to score you, and, you know, it’s manager and rep, and it takes time time away from being with customers. It takes time away from other coaching. It takes time, but it is needed. There are stats out there that say that roughly forty percent of reps think they’re getting enough coaching. Right? So sixty percent aren’t. And so having an AI assistant be able to listen to all the live interactions that you’re having and create effectively custom coaching recommendations for you based on a set of criteria that we know will lead to successful outcomes, I’m crazy excited for that one. You know, you just think about the number of hours that managers spend listening to pitches and doing certifications and filling out scorecard data. Like having an assistant do that, I think is gonna be huge. The other one that we’ve been using internally now for quite a few months, because we recently rolled out a methodology and so we built this to help us roll out the methodology is the playbooks. So if you have a methodology, we now have the ability to inside of your deal boards or inside of your how you’re looking at that data to automatically surface whether or not the reps are ticking the boxes on, like, a medic or a value selling or or something like that. And so it takes the adversarial approach out of it, of the, you know, I’m gonna get on a forecast call. I’m going to ask you if you did these things instead of focusing on what we need to do in order to drive something forward. You get the busy work stuff out of the way. Those are a couple that I think as far as time savings for reps and managers are gonna be huge. What is the wildest use case that you never thought of that you’ve come across? As I’m sure there’s something just completely out there. You’re like, wow. That was not what we thought of, but that’s really interesting. Commissions was one. I have a commissions history. History. So I was one of the people that they called in to solve challenges at McAfee and commissions was one of them for quite a while. And I don’t love that space, but I love talking about that space. And so I was surprised that I didn’t see the commissions use case when I first saw Gong. But we have a client who they sell a lot of products and they wanna make sure that the reps aren’t getting paid on what they would call an organic sale. That’s where the customer is just like, oh, I know I need that and I bought it. And so the rep has to actually talk about it in order to get paid. And we’re it was super interesting because I’m like, well, wouldn’t they just get on a call then it’d be like, just say all the words and no, that’s not what’s happening. Right? Because that would sound really weird. But they’re actually using it to validate whether or not commissions are earned, which I found I don’t know. For whatever reason, I found that pretty fascinating. I wasn’t expecting that. Super smart. So listen, Brian. Six SENSE and Gong have a really interesting integration. I think there’s something to be said about putting what is intense data that Sixth Sense is surfacing in terms of what accounts care about, what stage they are in their journey, and then marrying that with so much of the intelligence that comes out of Gong and just that conversational listening. Can you talk a little bit about how IntenseData is really augmenting what you’re doing? I think everybody in a customer facing role has a lot to do. There’s so many things that are pulling your attention, right? Whether that’s follow-up or creating outreach or setting meetings or learning or forecast calls, So many things pulling you in different directions. Where I see a lot of value coming from this partnership is helping the teams prioritize their time when they’re focused on customer engagement. If you have a list of fifty things to go do in a week, it would be great if you knew the ten or the five that were going to drive the most for you. And so in terms of prioritizing your time, I think that intent data as an interaction signal is critical. There’s so much research and so much selling that goes on without the seller even knowing it. That knowing the right time to approach or knowing that someone is in cycle, knowing that a company is a prioritized account, I think is gonna save the teams a ton of time. I also think that the right messaging element of it, when you know that an account is in a cycle or you know that an account is showing intent and you know who the right persona is because that’s another element of the integration. Right? Now tailoring that message to be the right message to the right person at the right time from an effectiveness perspective that goes through the roof. And so you get the benefit of efficiency, Gong’s platform helping you write tailored messages at scale, AI assistant doing a lot of that busy work for you, the intent data coming in, the who to contact. Now I can be super efficient at an effective approach, which I think a lot of solutions without the intelligent approach to it, you can get really efficient at a bad approach, which is, like, infinitely bad. You’re doing the wrong thing over and over again really fast. And so I feel like this integration gives our customers, especially the joint customers, the opportunity to do the right thing really fast and be able to do that at scale. So I’m excited for it. We were looking at this close to a year ago now, I think, is when we at least I first got involved in talking about this and figuring out what this was gonna look like. So super exciting, and I’m really anxious to see some of the use cases and stories that come out of our customers. So Yeah. So given, you know, you’re obviously at the forefront of AI, and we there’s probably not an episode that goes by. We’re not talking about AI. But what do you think is next? From a feature set, I mean, Gong is constantly innovating. There’s new features. The road map, I’m sure, is incredibly robust. But if you look beyond and say, okay. Like, in your mind, being able to glean insights through AI, is there something that you think that it doesn’t exist yet? The technology is not there. AI is not there that you think should come or could come, or if you could snap your fingers and magically make happen. You have the power, Brian. Snap your fingers. What would Brian’s magic bring for the next wave on this tech? I think there’s so much opportunity in action, in the actual doing things. I think right now we’re just scratching the surface on like kicking off or close, understanding the next best action, the thing that should take place, but it doesn’t without someone doing it still. And I think that this going from recommendation to action and doing it in an assisted way, like a slick way where you’re not taking the power away from the seller or from the customer service agent or from the customer success manager, you’re augmenting that power. There’s always a set of routine tasks that have to be done, getting them done in the right order, in the right way, with the right content, the right messaging, the right approach. If I could sound my fingers and have something working right now, I mean, that’s what I would hope for. I just I think we’re barely scratching the surface with it. And I I think everybody’s not necessarily struggling, but he’s working towards that spot where it really becomes assisted selling. Right now it’s recommended selling, right? It’s like, I’m going to coach you a little bit. I’m going to show you something you can do differently. Maybe that’s as visionary as I can get because I’m an operator. You know, this is why this is why I haven’t gone and started a company yet because I can’t think that far outside the box. And I think that’s one of the challenges with an operator is I get into the weeds so often it’s so hard to come out and go, well, what is the art of the possible? And to your question, it resonates with me because now I’ll go ask myself, like, I’ll actually set some time and go, like, if I really wanted to stretch the art of the possible, where would I go? For now, I would snap my fingers and I would have AI start doing the routine tasks for me in the right order at the right time with the right customers and the right approach. And I would have routine tasks for me in the right order at the right time with the right customers and the right approach and make me, like, almost make me superhuman. Yeah. I love that answer because it is rooted in reality of what can we solve today, but, obviously, needing to challenge ourselves to think even can we solve today, but, obviously, needing to challenge ourselves to think even bigger. Six months ago, what we thought AI would be doing versus now what we know it can be doing. I mean, we’ve evolved so quickly at this point. You know? And so I think, you know, where we’re gonna be going, it’s hard to even predict. But I agree in terms of scaling the repeatable stuff, the stuff that falls through the crack. Let’s just address those leakages. Let’s automate workflows where it’s possible, and then we’ll go dream out some bigger dreams. We have a question that we ask to all of our guests. We’d like to have a little fun here at the end, and it’s what is the most ridiculous thing you’ve ever been asked to do in your career? It could be ridiculous bad or it could be ridiculous good. And we’ve gotten some answers on very much on both sides of the spectrum. I have to choose my answer carefully here. We are a family show. Actually, no. You can go a little ways. I’ve been asked to do some fairly ridiculous things. One that I actually just shared because a friend of mine was looking at getting an an internship at a consulting firm. So I shared the story of my first I was so excited. You know, I get invited into one of the big five consulting firms and, you know, I got a coveted spot and I get there. I don’t know anything. Right. I think I’m going to be handed some awesome project or something to work on. And I get introduced into this little conference room that’s full of reams of paper, probably four feet high. There’s just stacks of paper. And that side of the room needed to be photocopied exactly and put on the other side of the room. And when I say exactly, every couple of pages had like a blue sheet and then a yellow sheet and then a pink sheet and then a green sheet. These are files. These are client files. Right? That was like two months of just photocopying. It was awful. But on the resume, it looks great. I had an internship at a big five consulting firm. I’ve been asked to do some pretty crazy stuff. We used to do a lot of our big events in Vegas. And in Vegas, when people start getting creative with their ideas of what they can do to push the envelope, you get asked some pretty ridiculous things. So with that, if we follow-up on outside of this, I can share some of those stories. So Well, listen, Brian, you are amazing. I’m so wanna pick your brain on some things that we could be doing to better leverage our integration with Gong and and our use of the data, but thank you so much. Lots of really tangible takeaways here for for the listeners. I appreciate the invite. I always like talking about this stuff. It fascinates me, and I really do enjoy it. So I appreciate the opportunity. Revenue Makers. Do you have a revenue project you were asked to execute that had wild success? Share your story with us at six cents dot com slash revenue, and we might just ask you to come on the show. And if you don’t wanna miss the next episode, be sure to follow along on your favorite podcast app.