Gong's Amit Bendov on Powering Your Company Brain

Speaker A: I personally have not logged into a CRM like in years. All I need to do is like, uh, hey, what's the status of like zapier right now? And it tells me everything.

Speaker B: My guest today is Amit Bendav. He is the co founder and CEO of gong. Now when Amit started gong, he bet on an idea that a lot of people thought was backwards. He said, the truth about your deal is not in the CRM, it's in the actual conversation. And he has built uh, a billion dollar company proving this. Now GONG today is uh, one of the most AI native companies in the world. But uh, Amit is cautioned on the hype. There's a lot of power. You should use AI ton, but should you use it everywhere? Should you use AI SDRs? Should you cut headcount? Find out on the show. Uh, his whole argument is AI is making capacity cheap, but judgment, that's where the magic is. Amit, welcome to the show. One thing I am fascinated to start with is you have always said that the CRM is a lie. And I think that's uh, a lot of folks are starting to realize that. But you realize that in 2015.

Speaker A: Well, I didn't say it's a lie. That's a bit harsh. I said it's not the source of truth for like what's happening with customers. That's like, uh, so there are things that are true in CRM, like who bought from you or your customers are uh, what they're paying you. That is all true. So it's not a lie. But the interesting question, and I was asking like, well, why are we losing like so many deals? Like you know, every company's conversion is like 1 out of 5 deals or 1 out of 10, whatever it is, right? Uh, what happens with out of five? And uh, why are like, usually like half the salespeople don't make their numbers. Are they like, is it like them? Is it us? Our training? And uh, the answers were not. It is a CRM. So I said like, people think it is a source of truth. So it's uh, I think more accurately it's a source of um, a truth. But CRM depends on people telling it what happened. And they don't do it right because just there's not enough time and they don't always want to do it and everybody hates doing it. So the idea was, can we retrieve that information, uh, from elsewhere? Taking people out of the equation that seemed crazy. Like uh, when we announced gong in like 2016, I said this is like the biggest Invention since your introduction of CRM 20 years ago. And everybody said, like, oh, yeah, right. Like, there's another delusional founder. But now this doesn't seem crazy, right? People see that, uh, the majority of the information does not exist in a CRM.

Speaker B: Yeah. I mean, it's been fascinating to watch my own transformation in using these tools where, you know, I rely just as much, if not more on the GONG transcript than I do the CRM.

Speaker A: Yeah, I, uh, personally have not logged into a CRM, like, in years. All I need to do is like, uh, hey, what's the status of like, Zapier right now? And he tells me everything. Not to. Obviously you talk about the transcript, but the emails, all the interaction with the account, everything that's happening, like, um, uh, it's a much richer, um, data set now.

Speaker B: Yeah. I mean, you say, hey, I have not logged into the CRM. Same here. I would say my usage of the CRM has gone through the roof though, in the last, you know, 12 to 24 months. Like, I'm using it more than I ever have. And even though I've not actually touched it.

Speaker A: Right.

Speaker B: How, like, is that. Is that a trend you're seeing consistently across your customer base? I would have to think so.

Speaker A: Absolutely. Even. Even Salesforce, I mean, very smart. They embraced it rather than, uh, fight, uh, it. They said, okay, we're going like full headless, that everybody wants to use it with other systems, like, be my guest. And that's like a great opportunity for, uh, all the vendors. So this is still, uh, CRM is a good source of, uh, data and will be around for a. They're not going away, but the way the people use them is like, completely different and uh, and much, uh, more powerful.

Speaker B: Now. What are the modern, like, what are the workflows that you're seeing from your most progressive customer base? Like, what is the things that you want to shake all, like the long tail of folks and be like, you got to get on this. You have to do it this way.

Speaker A: Well, the uh, what we're seeing, and that's a good thing, it's not a bad. But people look at the, uh, personal habits right now. Okay, we're going to automate, like meeting prep and like, here's my agenda. That's all good. But the powerful things, what. And this is what GONG has always been about, is to get, uh, the insights on a global scale. Right. To understand. Okay, what are we, uh, doing? Um, right. And what could we be doing better? Um, I'll give you an example. What uh, we're doing at GONG right now. Do you know that, uh, we actually don't have people writing battle cards and um, and like competitive information, even like product documentation. It's all done by gong and it's like better and faster. So if you think about it, right, you just like, uh, okay, create a battle card against Evil Corp, like whoever your Evil Corp is. And uh, before that it was a product marketing team or enablement team, spending like weeks speaking like one competitor and writing what they've heard. And usually those are like, okay at best. And then by the time they're out, nobody used them. They're in, um, some kind of a content management system now because they go and create a battle card. It'll sift through all the deals that we won. Not hypothetical, real stuff, all deals that we have lost. And it'll create like a three pager. Okay, here's who they are, here's their strengths, like truth, uh, here's their weaknesses, here's why we lost to them, here's why we won. Here are three customers that switched. Here's what they're saying that they're seeing different. Like, exactly the information that salespeople want to see. It is better, faster and cheaper. Right. So the ability to get content, uh, is insane. Where people creating marketing content from that, we have people that are, um, automating entire onboarding. So if you think all the information of the organization already exists, like in the collective brain, uh, and conversations, if you put it together, it's super powerful.

Speaker B: Yeah, I mean, spot on. Like we are. The nice thing too, about that use case you just described is that you said it's the faster part. I think that is so key because how fast the market is moving right now, if it's taking your product marketing team, you know, a quarter to sort of work through and get those battle cards out, like by the time your people are actually using them, they're out of date, they don't matter anymore. And so you already sound kind of silly, but if you're able to do it based on like what happened this week, you get real stuff and you're to your point. It is like the company brain is sort of housed in these transcripts and so you can deploy those in so many different ways. Like, yeah, we've seen customers that are taking them and kicking, uh, off, um, agents that go write code, you know, customers saying, I'm complaining about a bug or a feature request, Great, go, go kick a prototype and spin up an mister on that. You see, uh, you know, help Docs like, you know, a support person on the other side gives a really good answer and then it gets cross references to the help doc, like, oh, we don't have that answer on our site anywhere. Great, that should get, you know, published in a knowledge base. Uh, you hear a sales rep give like a really good answer, uh, to something, oh, that should be an FAQ on one of our marketing pages. Like, why isn't there? It's like all this information, you have it but you're not tapping into it to the fullest extent.

Speaker A: Exactly.

Speaker B: Um, and it was always there. It was just so hard to get access to it until you could use a tool like GONG to transcribe it, put an LLM in the loop to extract it, uh, and then figure out what to go do with it, uh, at the end of the day. And so it does feel like we're seeing more and more of these. Like some of the customers on the frontier are getting more and more leverage out of their call transcripts.

Speaker A: Right. The other is like uh, real intel, real time intel. So we launched like a couple of months, uh, three months ago, like we launched a new product called GONG Enable that uh, it's an agentic coach, it coaches people. Uh, it is like trending really well. If you look at the revenue numbers, they're great. It's our fastest growing product. So that's good signals. But I'm worried. How's the customer experience? Does it really work? Are the problems now? It takes time for people to deploy, so I wanted to see how are we doing like POCs, right? What's the experience? So I mean to put like an agent at gong, it says, okay, tell me every time, like every deal that we win, tell me like was there a poc and what was the experience? And I can see in real time before that I would have to go and start asking people and ask uh, them to write reports. And uh, it is so easy right now. It's amazing that a new product launch can be tracked in real time. And uh, if there are issues, like we can correct them like in real time.

Speaker B: Yeah, you mentioned this like company brain. Is this something you all are building out internally yourselves too? Like, yeah, this is a thing that, you know, I've gotten pretty, pretty obsessed about is like, how do you encode all your company's knowledge into sort of one repository?

Speaker A: Yeah, it's definitely something that uh, uh, we encode internally to capture the uh, organizational, uh, knowledge. Uh, but also something that we're building into the solution. Right. That uh, it is Shared with uh, customers. So uh, they could uh, get better and better over time.

Speaker B: Is it predominantly through gong, or are you like pulling in, you know like your code base, your, your help ticketing system, like all this other stuff. Like how, how expansive have you all gone with that?

Speaker A: Well, each team, each team did their own. So definitely everything, revenue and product is from gong. But we also have uh, other system. We use it like in legal, we use it like in uh, in engineering. Obviously you build skills that have like the uh, the coding conventions and the uh, uh, the practices so that, that uh, builds the organizational brain.

Speaker B: Yeah, makes sense. Um, one of the things that I think is interesting about you is you know, you yourself are like pretty progressive as um, you know, an AI native company like, or you've built a lot through AI, but you have been pretty public about saying, hey, maybe don't use AI so much. Talk a little bit about that.

Speaker A: Oh no, well that's the way understood it. That's a problem. I uh, was understood no use AI like a lot, right? I was like, uh, there's a lot of hype that people don't understand. Like every day there's like, oh, I just like uh, vibe coded Monday.com as a weekend project. Right? Uh, uh, this is BS, right? Uh, so, or like even a year ago when people say uh, started like um, hire our SDR and even had like a person name like Fire SDR team and said this is, this is bs, right? We knew it's not gonna work. Like uh, and, and sure enough, like it doesn't work. So they're, they're.

Speaker B: But a lot of folks have tried to like deploy the AI sdr. Like, I mean, gosh, my inbox is like you know, an example of like how many people are doing this.

Speaker A: That's, that's exactly the problem. That's what we knew. I can tell you how we like Elon and I discussed, well this is like should we be in this? And we thought about saying, oh, this is not going to work, uh, at least for now, right? It might, might, might work in the future. But we always tried at gong. When Elon and I started thinking about the company, it was an AI vision. We wanted to be like an autonomous revenue management system. This is like a self driving Tesla, right? Level five. Right. But we also wanted to know when we interviewed a lot of people from the industry to understand why what works today, right. We wanted the state of the art, but not a vision or a science fiction. Right? We wanted to go something that people can use today so We've always been on this edge, uh, or a frontier if you'd like for something that actually works well today and can create value versus something that it's going to be like three years out there that maybe uh, would work one day. So we always try to ship something that uh, uh, people can really uh, really use. And uh, now there's this expectation. So that's the uh, some you know, there's hype. You know, I've just vibe coded something right. Like a workday. And uh, you. So this like CEO like a couple years ago said oh I dumped my CRM and we're going to develop it. Which turned out not to be true.

Speaker B: You know it sounds like you do a good job of like balancing you know, uh, sort of being on the frontier with sort of pragmatism. Like hey, this is the stuff that actually works. How do you actually operationalize that internally? Is there like you know, is this like a centralized thing where you've got like a team that's sort of always testing the boundaries? Have you you know, uh, you know, encouraged everyone to sort of be like building like what, what does it look like practically?

Speaker A: Well it's not centralized. We actually like instilled it in the culture and the work practices. So like it's kind of, it's built by, by design of the company. So there, there are two things. First we have, they're really thinking uh, ahead but it'll never be like uh, foundation level, like uh, quantum physics that might work on a quantum computer. We don't do that. We're not IBM or uh. There's nothing wrong with that. It's just not us. So where's. Think of things that um, might not work, but if they do work, they could enter a tremendous value to our solution. So we have a research team, that's what they do, they test concept. But it's not, not a free check. Right. Or a free license to experiment with anything. Right. So mhm. Uh, these are things that we have a hunch that might work and they're hard and they might fail. Right. So that's one. The other is we always like testing with the customers like very early. So it could be there is a concept. Our product managers will talk with customers and CEO. We're thinking about these and show mocks as it nothing really works. But first to see is there value assuming that this work is even remotely interesting. Then they would try to put uh, some data. So when we get some and sometimes we decide to kill a project or change direction or uh, what we thought is interesting, uh, is actually not so interesting. That's the hard part. To know what matters to customers and what can uh, actually work. And then when we ship something, we try to see like okay, what actually works. And we know that there is a cycle that uh, we think about it. Customers see the value, customer tell you that it's great. But then until they see it on their own data say oh, like why did you choose like this deal? That doesn't make sense. Right. Or this is like a bad data. That's the time that you know. So we take those like um, uh, small steps that we can iterate really quickly and understand like ah, what actually works.

Speaker B: Yeah. Makes uh, sense. Um, so tell me. So another thing I've heard you talk about recently is um, you know, a lot of these CEOs are citing you know, AI as a reason for, for headcount, uh, reductions. And you've been pretty outspoken and say hey, that's not the right approach. What do you think is the right approach?

Speaker A: Um, well, it could be the right approach. What I said it's not all things that uh, are saying, oh, we're gonna lay off like half the company because of AI. That might not be. That might be the truth, but maybe not the whole truth. Uh, the truth is like a lot of companies over hired and sometimes find themselves with bloat. Right. Uh, and pardon uh, me for using that term for like, you know, we're really dealing with people, um, and they want to like streamline the organization. Right. Uh, and adjust it to reality. It allows more agility. I think there is a real opportunity to rethin org structures uh, with AI. Maybe like better uh, spin of control for managers, maybe less uh, specialization. So instead of like uh, five people like each one doing a step of the process, we could blend uh, it all together. Everybody's doing like everything right with the. If AI provides the skills and the knowledge and people uh, have like um, more um, opportunities to do like more things. So there is an opportunity to rethink like structures and uh, and become more efficient. But a lot of these layoffs, uh, they have to do I think more with. Well it could be because of AI because uh, we need more budget for AI so we're cutting like elsewhere and we're gonna redeploy uh, that capital. Right? But it's not necessarily that AI has already replaced half of my jobs and uh, I'm replacing people.

Speaker B: Yeah, it's an easy scapegoat. Uh, right now in Trinity, say more about like how you see the or getting redesigned maybe specific to like, you know, a revenue org. Like revenue orgs tend to have, you know, lots of these specialized roles. You have like an sdr, a CSM and ae, an fde. Like, you know, there's so many of these different roles that can exist. Um, you know, what does it look like in the future?

Speaker A: Well, I think we're gonna uh, we're gonna see people that are more um, multidiscipline. Right? They can help more. I think that uh, there was a time where they're like only salespeople or account manager. This was like the two roles that you had maybe like one or two. Right? And then like uh, 20 years ago or so started the whole idea of like hyper growth companies. And now the business was growing so fast you just couldn't hire fast enough. So we said, okay, we can't train like a person and everything, right? Uh, so let's try to build almost like an assembly line. You know, one person like uh, taking the inbound, the other one like doing the initial meeting, the other one like deploying, which created like a reasonable fast growth model. But the problem that um, it creates, uh, it's a fragmented buyer experience. People don't like, oh, I just told you what I bought, why I'm buying. And now I'm getting like a different person. Like I want that, uh, especially like in enterprise, you want to trust, right? Someone that uh, has a relationship. It doesn't feel good that you switch, uh, people, uh, and second, uh, siloed flow, uh, of information. Uh, but now, uh, with AI, you uh, could have like one person do more things because the skills are now, uh, encoded, uh, in the system and it can walk someone with a brain and a desire and passion, uh, to do incredible things. So I do see that the roles, uh, um, start to merge back, uh, and it creates a better buyer experience and uh, more flexibility for the company. Also when you create silos, it's very hard to balance something. You have like too much of these and too little of that. There's always these like mismatches. So I think it creates like a better, better model for companies unified.

Speaker B: Why, why do you think we got away from that in the first place? You know, you mentioned 20 years ago there just used to be, you know, a salesman or uh, a sales rep. And then we sort of added all this specialization. And so clearly pre AI, we could have done it with just one role. Why does it take AI to sort of swing us back the pendulum back the other way?

Speaker A: Well, I think there's like uh, there, it's complex. There are multiple reasons. First like uh, salespeople don't like to uh, do prospecting. That's a, that's a stereotype. But if they're right, they like to get the deals right. Okay, give me the qualified ones. Right. Uh, and who likes to pester people like over cold calling. Right. Some do. Right. But uh, uh, it's something that uh, it requires discipline. And I know that there, there are lots of solutions. Right. Uh, people are like focusing on current pipeline versus like developing pipeline. And companies got like you know like uh, lead generation Tuesday. Right? On Tuesday you only do this so said okay, let's hire some junior uh, people who could hammer the phone all day and uh, and do that. That started like the compartmentalization, uh, uh process and it is easier, right. Uh to train ramp time for a salesperson to do the whole thing. Right. Cradle to grave as they call it could take like six to 12 months. Right. But to train SDR could be like uh, six weeks. So it allowed like for better uh, scaling and faster scaling of companies. But now when companies uh, might not be growing so Fast, uh, and AIs present, uh, the possibility so you can have like people doing like more things.

Speaker B: Yeah, it makes sense. So you, you basically can use AI to speed up the onboarding process, have like just in time learning and get closer to some of the things that maybe you had in the past but without the upfront investment that was required to give you a, you know, an into, you know, full, a full cycle, you know, sales, uh, rep or something like that.

Speaker A: Imagine like ah, like an assistant that always like uh, whispers in your coaches like here's the next step, next step. And you need to apply uh, uh what you know the term today is like uh, judgment and taste. Right. And then accountability. Right. You have a person in choice almost like an autopilot. Right. And uh, you just need someone with the right brains and common uh, sense. So you could hire like people out of college. Right. Uh, that will do that. Right. They share those traits if they're smart and hungry, like uh, why not? And the system kind of knows what's going on. Uh, so definitely like uh, exciting possibilities.

Speaker B: Yeah. You know, shifting topics a little bit. So similar to Zapper. You all were founded well before, you know, LLMs, ChatGPT, things like that. And so you came of age kind of in this hyper growth era that we did. And I imagined, um, you all have gone through your own transformation and like changing how you all operate internally. What has been like the best tactics that have enabled you all to make that shift. What has worked m most uh, effectively for you that you think others should steal?

Speaker A: Fortunately for us. So first we're like deemed dead. Like in 2023, uh, people said like gong is dead, right? We're now like uh, one of the fastest growing uh, companies at our scale, right?

Speaker B: What, what killed you in 2023?

Speaker A: Oh, first, like it was a, it was a rough year, right? Uh, you might remember that where post uh, post zer hangover, right? So our gross definitely slowed significantly.

Speaker B: We're uh, no more seats, everyone's not hiring, so no seats.

Speaker A: Everyone's firing right now. So uh, that was like a tough period. And then like uh, chatgpt, uh, came out, right? And um, and everybody said like, oh, now I can take the transcript and load in ChatGPT and tell me how to win the deal, right? Uh, we've, we, and we've been accelerating every quarter now for like uh, the last 10 quarters since that moment. So uh, it created like a huge tailwind for us. Now everybody, every company needs AI, um, so they're calling us, uh, second, it made the product better. Things that we can only dream. Like in 2016 when we launched Gone, we said one day it's going to do all of these things. Now they're a possibility, right? It's telling me how my product is uh, progressing in a market, right? This is like unthinkable like uh, ten, uh, years ago. So we built the infrastructure both in terms of the company and the product. We always envision a system that has situational awareness, like what's going on, the context today. Second, the insights layer and three, the application or the user interface. And we're just able to bolt on um, the new technology. We had machine learning. We had like small language models before that. This is not new. A large language model is the new exciting things that actually like enables a lot of the uh, growth right now. But so what we have, what we have done, right? And not necessarily just because of AI. Just learned that um, to focus on customer outcomes, right? That's like uh, because as we grow, obviously we're not uh, we're not the only one in the field. And uh, you know, we had like one competitors or two competitors or three and now probably like a hundred, right? And I'm sure like in three years there'll be like a thousand, right? Which is like everybody hates, I love, right? Uh, as long as we lead. So we need to like always be ahead. But you can't get into like, all these, like, features. Uh, right. He did this and he did that. You just said, okay, there's one thing like gong, we drive sales productivity, right? Which means that we help you, like, uh, win more deals and do less work. It's like, very simple. That's the best record and we try to be the best version of that for our customers. Uh, technology is a mean to an end, but also the way that we, uh, deploy it, support it, uh, and uh, partner with a customer, uh, is the key. Right. And uh, in the early days, we just, you know, throw Gong and you know, people will figure it out. Right. Which works to a certain extent. But to get it next level, you really need to, uh, do a lot more M. Mm.

Speaker B: You. You mentioned, you know, in the early days there wasn't much competition. Now there's more and more and more. Um, I mean, I could vouch for that. There feels like there's like a million and one, you know, call recorders. Of course, call recording isn't the only thing that Gong does, but that's what Gong sort of like, I think kind of was known for it. Um, and yet when I talk to company after company, everyone uses Gong. There is but one. Like, what do you think creates that differentiation when, you know, ostensibly you could choose from many hundred of tools that could replicate at least a chunk of what Gong could do. Um, probably not all, but like, you know, portion.

Speaker A: Yeah. Uh, well, first, if you want to record calls, you don't need Gong. Like, if that's all you want to do, you certainly don't. You could get it for free, like on most videos. And we knew it. When we started a company, like, yeah, we didn't even like, plan to record anything. We saw ourselves as like, dealing with the data that recordings provide. Uh, but because people didn't have anything. So that's why Ilona said, okay, we need to develop it, or OGA will never take off. But said one day it goes away, that's fine. But, uh, um, the reason, uh, is that first, like calls alone are not enough. So we want to capture, we capture what's happening in an account or an opportunity. And most of our customers, like in B2B. So it could be like 10 people have gone talking to like 10, uh, people, let's say Amazon or something. Right? And it's a bunch of like email, in person, meeting calls. Everything needs to be associated with the right account and into create a complete picture. So, uh, emails contain about 40% of the signal. Right. If you, if you just listen like uh in second you need to look at the whole thing. So that's uh, one you need to capture like everything, ideally everything like, like uh, fanatically like everything that happens with the account. Because otherwise the one thing that you miss that could have an email saying that uh, oh, our CFO just putting the budget on hold, right. All your calls aren't going to help you. So you need to capture everything. And that's like a constant um, evolution for us as we add more and more signals. Second is to do it uh, it's one thing to capture my own meeting. You could use like a granola or something. Uh uh, but to do it in an enterprise or even like a mid sized market our size, you need compliance. Right? It's this thing that I tell you like well hey, like uh, why is my call recorded? I did not consent to that. Gonk and go and prove back you need like access control, data retention policies, uh uh, for organization access control is massive. Privacy is a massive uh issue. For example like if I send like an email as a CEO to one of my board members who's also on ServiceNow as a customer and GONG captures that email and that email says oh I'm looking to replace one of my executives. Like can you imagine the disaster? GONG is like fine tuning of access of who can see what. Right. Uh, and uh, that's the hard part. Like capturing a meeting is like super easy today. Capturing like all of the organization in ways it's compliant and can uh, actually work and not miss a bit and not miss my most important call, uh, and run at high availability security compliance. That's incredibly hard. Uh, we call it the revenue graph that associate the right opportunity with the right activities. That is the way it is controlled with workspaces. And uh, yeah it's like to play

Speaker B: that back it's like you know you all have gone so deep on this one specific part of the org which is selling and revenue and like how do you go do that? Well and there's all these workflows that have to be accounted for every step of the way. And so on the surface yeah it might just look like oh you're doing call recording but it's so much, the depth is so much more there that you know your customers no way the, that they're going to replace that with just any uh, any sort of random tool.

Speaker A: It's, it's very hard to run like any organization of like uh, you know, beyond like five people to do it in a way is like a legal secure that works Right. Uh, not to mention scale and availability is like challenges. Ah, data. Um, and uh, that's uh, that's why we're doing well.

Speaker B: Yeah. I think this is like, you know, for other people who are struggling with this, I think this is where it is really useful to think through. Like, what are those use cases? What are the hard things that your customers are struggling with? Like the real hard stuff that no one else is going to do the last mile work on and be like, oh, that's where we're going to put all of our source of differentiation. And then that's what makes them sticky customers at the end of the day. Because you've solved something that is like really, really challenging that you can't just kind of duct tape together at the end of the day.

Speaker A: Absolutely. And uh, there's like, um, there's so much nuance, uh, because we have so much scar tissue and real customers or like thousands of customers, like across like all sorts of industries to nail it is, uh. I, um, don't even know as the founder of the company, like, all the details that go into that now. There's so much, right. That uh, you know, I used to know like every nook and cranny in a product and now it's just impossible for like any one person. And uh, you can't vibe code that. Right. Because you don't even know what the spec is. You don't even know what to ask the system for. Right. That's. Yeah, that's the hard part.

Speaker B: Um, shifting topics again. You know, one thing I've heard you, uh, say is, you know, Cloud was uh, an IT revolution and AI is much more of a work revolution. What do you mean by that?

Speaker A: Well, we always, uh, people always ask us in the early days, oh, like, wait a minute, like, why do I need my CRM? Like, when are you gonna kill CRM, right? And uh, I said, uh, we're probably not like, uh, first, like, it's hard, right? People thought because it's very easy to put the front end, but there's a lot of like, plumbing and uh, messy stuff just like gong, right. Uh, it goes like behind the scene. Second, it's not very attractive, right. Uh, it's not very lucrative because it, you know, Cloud was an it revolution, right. Instead of like using Siebel, I used Salesforce, right. So now I don't have like the version control and uh, worry uh, about like installing an infrastructure. That's all true, but it is 6% of an orgy's budget, right. Uh, payroll for Most companies is the larger thing. Right. And uh, our enemy is not the CRM. Our enemies like drudgery and ignorance. Drudgery is the amount of work that people, uh, are doing. So 75% of a salesperson time is not selling. If you measure, try it like with your team. I don't know how efficient are you? Look at their calendar and see how many customer meetings they have. So that might give you like 10, uh, hours. Right. And let's say they have like 45 hours a week. It shows you their productivity. So a lot of it goes on, like meetings, uh, internal meetings, uh, updating systems, researching. Whatever they do, it's not customers. So 75, uh, percent and second half of them don't hit their numbers. If you look at the, uh, the market size, There are roughly 10 million B2B sellers out there worldwide. So let's say they're costing like $250,000 a year, selling 600,000 at uh, quota. Uh, right. That's 6 trillion revenue, 2.5 trillion in potential. 75% of it goes to waste. Why would I try, like replace a CRM that is like hard or like the bpo. So we outsource the drudgery, the work that they don't like doing, and the ignorance, like why they're losing deals. So uh, that's a way, uh, bigger opportunity. And now the world see like uh, we said it like ten years ago, this will be bigger. And now the world recognizes. Not such a crazy idea. People talk about like service companies. This is like, this is it.

Speaker B: Yeah, I want to follow up on that thing about, you know, how much percentage of time is someone actually spent selling? You know, uh, we look around and everyone can look inside their organization and find, you know, individuals that have like 10x their productivity. You probably have engineers that are like shipping so much more code things like, like that. But it's a lot harder to look around and find the companies that are, you know, 10xing actually like, you know, uh, operationally more effective. And you'll partly. When I think about why, you know, I back up and say, well, you know, 10xing, an individual looks a lot different than 10x in the company. If you want to 10x a company, you have to step back and say, well, what's the point of a company? And the point of a company is get a customer. And so, okay, well if your job is to get a customer, how do you get a customer? It's like, well, you either got to build new stuff that they really, really want, or you Got to sell the new new customers. And so if you can deploy AI to increase the percentage of you know, time, energy, people etc that are doing those activities, you stand to gain quite a bit. And so I'm curious like when you, when you look at like the, the productivity gains of a sales rep, um, you know, when folks deploy gong and uh, you know, where do you see the like the biggest gaps like or like the biggest opportunities? Uh, I think I'd read somewhere where you know one had gone from you know, spending like five hours on call up to like 30 seconds and ended up getting like 60% more like selling opportunity. Is that normal?

Speaker A: Absolutely. Yeah. So there, there are certain tasks and again I don't think we could like 10x like human productivity. I mean there are areas where we could. Right. Depends on the nature of the task. Even we see it though with our engineering there, there's some tasks that are. You see very little. You might see like a 10% improvement, right?

Speaker B: Yeah.

Speaker A: Uh, because just the cognitive load on people versus stuff that are mundane. Right. You know, update these like uh, import export script that is very repeatable that there you can see like 10x uh uh improvement. But if you look at the, the mix like it's definitely, you know, it's hardly 10x uh in salespeople, uh, they're like researching for meeting. Like so sometimes I get pulled into like a customer conversation, right. And it used to be hours spent like the team writing a brief for me, uh, probably having like another session with me, uh to go over it and uh prepare and I can ask some clarifying question and then they have the customer meeting versus like all of that is gone. Right? This is like so five or six hours of like very expensive of people went down to zero. Right. For reps definitely like uh, meeting preps, writing emails like gong crafts, all my customer emails, like I don't even like uh, bother to correct them. They're not a hundred percent what I would write, but it's not the correction are not worth the effort of like editing. Right. So I just like yeah, good enough sin right. Uh, this is like uh. So there's like uh, this. I don't think that uh. So if you look at like the 75% again measure like how much customer time you have for your own salespeople, like you'll be shocked. Right. But most companies know it's like very little and if you could cut it, I don't think you can reduce that thing by 100%. There's a limit to how much people can absorb. Just thought if you could make like cut it by half, that's more massive for companies, right? Uh, and uh, if you can increase win rate by 5, 10%, that's massive. Just think about it. It's like you're talking like massive ROI on a very small investment. Uh, and you could do more than that. So there are two, two levers for sales, right, for co. For engineers. Like how much, how quickly you run code. How much code. Right. Uh, again it's a bit of a novelty metric but there are many PRs. But let's say that you look at that for sales, there's how much customer time and then the customer time did you have? Are you being effective? Are you saying the right things and driving the right behavior to win more deals? So these are the two levers and you put them together. It's, it's very substantial.

Speaker B: Are you. Do you let the gong like auto send those emails or do you still review them and press manual press.

Speaker A: I, I always like, uh, I always review them. I always review them. But again it takes like a second. Right. It's a quick read and good. Yeah, uh, uh, I don't think AI, uh is at a place where it could fully be trusted. Like uh, even like as uh.

Speaker B: Yeah, I still, I still uh, you know, a big part of like the workflows I set up finish with a draft email and then.

Speaker A: Yeah, because it only takes like one crazy email that'll like uh, drive the wrong. They have like really negative impact. So I think it's a good uh, habit. And again it's not nothing negative in AI. It does an amazing work. But you should be reviewing that. I wouldn't let it send a proposal.

Speaker B: Yeah, uh, I love it. Before we wrap, quick hitters, what's your favorite tool in your stack that's not gone in your personal stack?

Speaker A: Um, Well, I like LinkedIn. Uh, uh, I use it a lot to uh, get up to speed. Obviously use uh. I don't want to say which one because I'm gonna get in trouble with either one of them. But obviously I use the uh, the chat chat applications.

Speaker B: Well I feel like you have to use all of them now.

Speaker A: Well they all uh, they all use gong, right? So if whatever I say is like uh. But I do use sometimes um, I do switch between them. So let's say I run like a thread, like a dialogue with one of them now I want to get like an independent opinion not being aware of my context, like ignoring. And I want to get like a truly independent so I Do use them both, right? And, uh, it's great.

Speaker B: I feel like that's what you kind of have to do. You get so much better outputs when you. You use them in sort of concert with each other, right?

Speaker A: So, you know, the beautiful thing about them that they have memory, so they might remember something. And I said like, three months ago, and, uh, uh, it is context for, like, anything that we discuss. But sometimes I just want, like, a fresh mind, right? So I use them for, like, different things. And sometimes on a project, I would, uh, uh, switch between them.

Speaker B: It makes sense. Like, we've. I've started, uh, building out like a, you know, a whole bunch of, like, my memory is just like a bunch of markdown files. And then I have a harness that I can use. Sort of do a model picker and like, point them all at the same context, the same stuff, the same prompt. And then you can kind of, you know, uh, help get that sort of similar experience. I find that's pretty powerful. Um, awesome. Me. Well, hey, I appreciate you coming on the POD today. Uh, thanks for, uh, having, uh. Thanks for taking some time. Any, Any last things you want to share with the audience?

Speaker A: Well, it was. It was a fun convo and, uh, congrats on a success and, uh, growth. Wade, uh, you're building an inspirational company.

Speaker B: Alrighty, folks. That was Manit Bindav, the CEO of Gong Amit. He's built one of the most AI native companies out there, and he's teaching you how to use AI. Great. You got to use it a lot, but you got to be careful about the hype. Make, uh, sure to get your calls recorded, but it's not just recording your calls. Uh, use AI to help you drive your entire business. And he shares a lot about how the best revenue teams are doing that. So thank you, Amit, for the time. Thanks to everyone who is listening. We'll catch you next time.