The Exchanges

Q Um, so what, what, what was the, um, what was the sort of the why now moment, like back in 2015, um, as you were thinking about, okay, we're going to start a company. What, why that specifically at that moment?

A Um, I wasn't even thinking about starting a company. So, so when I was at Zycense, I mean, overall we're growing pretty well, but then, uh, then we had, uh, like a quarter from hell, right? Or is, is, I don't know if it's okay to say it like in this webinar, so like an oh shit quarter, right? Uh, it's like, everything's like going up, up, up, up, up, and then like, shoo, like one, one hell of a nose dive. And I, I had no idea like what's going on. Like, Marketing or pointing fingers in sales. Sales is pointing fingers in marketing. Everybody's like blaming the product and, you know, I'm kind of like the Switzerland in the middle. I'm trying to understand what's going on. Uh, so in my desperation, I had my, uh, my operations people start to like crunch the metrics. You know, we're getting like, you know, conversion rate. Do we have enough leads? Uh, we're making enough conversations. Everything looked fine, uh, which obviously didn't make sense. Uh, and I had, uh, my, Product manager is actually sift through Salesforce notes, and they'll dump everything in sale, and they start like reading, like, you know, go over like thousands of deals. They'll spend a couple weeks is like, there's nothing there. Like, we don't know what's going on. So, um, there's some, and then it dawned on me that this is, this is pretty crazy. Like, there are some fundamental questions that we don't Uh, th…

AI assessment note: “we had, uh, like a quarter from hell, right?”

Q Interesting. And how did that, um, translate in terms of teams? So for a company where AI is so central to the, to the product, uh, did you have, uh, like deep AI researchers like day one or you started bringing them in precisely when you started building your own? Product.

A When we started building our own. So the first is more an application that we, you know, can we create like a good enough experience? Something just, uh, I mean, use MVP. My partner Lonnie calls like MWP, like minimal wowable product that people says, oh wow. Right. So we had that and, and nobody complained about like the accuracy and all of that just, but then we have, we actually have, uh, we have a real, Research team. Like a lot of people like R&D means engineering. At Gong, no, we have like, Uh, about a dozen researcher. I mean, the entire R&D is, is a hundred people, right? So it's like, 10, 12%. It's a sufficient event. They work on real long-term research projects. Some of them, like, don't succeed, and that, that's okay. Uh, so we, we are taking risks, and they're, they're always thinking like a year or two ahead. Uh, so there is a real team. For speech alone, I think there's, it's outside of research, but we have, uh, four or five people working just on that.

AI assessment note: “When we started building our own.”

Q And you found that the engagement was, was strong. Like, how did you navigate the social dynamics of precisely the salespeople feeling like they may be listening to by some bot? And then what did you sell more to the decision makers or, or to the salespeople? How did you do that?

A We did both. So that was like, the people that had that concern, I mean, were pretty smart. It's a legitimate. So we built actually enough in it for the users themselves that they'll be able to at least go through the past hurdle. And what we've seen consistently is that like the first like there to may feel uncomfortable because now you're in this like big open space with everybody. But actually that's great. A very positive transformation, uh, within the company. If you'll say, okay, people now can help me. They could, they could watch my game. I can watch their games. Right. So just like, you know, LeBron watches game tape every day, it's working for him. Right. So, uh, so it, it is like, uh, plus now, uh, it makes their life a lot easier because They don't need the yellow pads, you know, to take all those, the details notes, and then put them in Salesforce. They can just focus on the conversation, so they're, they love going. Our Net Promoter Score, as of today, is 80, eight zero. Right. It's like higher than the iPhone in 2008. And most of those ratings are about, it's, it's insane for enterprise software. Right. So most of our ratings, um, is by the salespeople that absolutely love the product and can't imagine their lives without it. But it was, uh, we had to tweak the product to make it work for them.

AI assessment note: “We did both.”

Q And, uh, I, I, you, is a product structured in a way that, um, the AI learns across all customers? How do you, how do you think about that?

A Uh, yeah, some of it is across all customers, and some of it is customer specific. So what's unique about Gong is that, um, is our audience, right? They're not, they're not, uh, data scientists, right? These are like sales people or sales leaders. I mean, they love the insights, but they're not going to do anything. They're not going to punch numbers, most of them. So we couldn't rely on anything. That's why, uh, the learning is unsupervised. Right. It means that we were not asking people to label or train a system. You just, you turn it on and it's working. So everything that we do has to be like fully automated without human intervention. Um, so, so as you get into a new company, uh, Gong will start Uh, obviously first I can say the words, right? That gets better over time. So words like competitor names or product names, the system starts to learn, uh, if they seem repeated enough. Um, Fortunately, we have the emails as well. So that's a good training set because we know that some, some of the words are unique to that company, even a name like Sisens, right? It's hard, right? Or Gong could be like an object or a company, right? So that varies by company. So that's on the speech level. Then there's the topics, right?

AI assessment note: “yeah, some of it is across all customers, and some of it is customer specific.”

Q Yeah. Did you, how did you recruit them? Or is that, are you now able to recruit them? Because as you said, you're a hot company. It was a lot of traction and they're working on interesting problems.

A We were able to recruit them before we were, um, hot. Uh, I think that one of the things when Ilona and I started, remember we did, we did a survey of both like the market with people buy, but also the technology. And we interviewed a lot of people, right? Pretty much. So we started a company in Israel and I don't know if everybody knows, but, uh, the, the R&D is based in Israel and, uh, and we pretty much went to companies who did like similar speech technology in the past for different applications. So we kind of like map everybody in the market, and we started like knowing like who's good, and, and once, ah, these people kind of know each other, so it's a network, so once you hire like one or two, odds are that they can bring their, their friends, and that's how we started building. So the team was built, um, organically, but we made it a point to really know everybody in that kind of like narrow community.

AI assessment note: “We were able to recruit them before we were, um, hot.”

Q And then what did you do next? I always find those entrepreneurial paths to be fascinating. Like, how did you, uh, how did you get started building a prototype and all those things? How long did that take? How much sort of technical sort of product building was there to do before you had an MVP?

A Uh, it worked like, it worked pretty fast. I wouldn't say it was super smooth, but, uh, uh, so first we did two things. First, I, I found like a great co-founder, uh, Ilan, who was my CTO, and when I was at Sciences, at Sisense, I was interviewing for a VP of engineering, and as soon as I left, I was like, hey, I've got this like little startup for you, so we were like meeting at a coffee shop like once a week and, uh, trying to kind of think about the idea, and we, Uh, we did two things. First, we, um, we did a market validation, you know, something often like a common mistake for founders if they think that something is a great idea that they would love to buy, right? They think that the entire world is willing to, and that's not the case. So, uh, we interviewed about 50 potential buyers and asked them, hey, we're looking at something that will automatically glean insights from conversations. What do you think? Uh, will you buy? How much will you be willing to pay? And the feedback was pretty positive across the board.

AI assessment note: “we interviewed about 50 potential buyers and asked them, hey, we're looking at something”

Q Like, so who's performing better or who's, uh, how do you, how do you get it?

A Well, you kind of know who's performing better, right? What you don't know that we knew that even in sizes, right? We just don't know why, right? So what are the difference in behaviors that might explain some of those differences, right? And what are the best practices? Uh, deal intelligence. Look at all of your pipeline and tells like which customers and deals are likely to close, which one are progressing according to Gong. Uh, for example, if the deal is like 30 days from closing, Right. But still there was no discussion of pricing like whatsoever on any of the channels like on, on emails or in one of the calls that deals is a high risk. Right. Or, um, if they're not talking like a high enough in your organization, so going tracks with email, who are you talking to? How many people are engaged? How, how responses is the customers? All those signals. So it does measure your pipeline better than any traditional pipeline management. And the third is marketing intelligence gives you a kind of higher order. You know, how much are you losing to competitors? What do people like about your, um, solution? How did it respond to new pricing? All those things. Very popular, but not just by sales team, but also with product and marketing team gives him like great input about the, uh, the product.

AI assessment note: “you kind of know who's performing better, right? What you don't know”

Q And in terms of sort of like concrete steps around that, like what do you do? You create a conference around it, you create a content like a podcast, um, or you, how do you, how do you just say, okay, this is our category?

A Um, I think that first you, you can't really create a category category, right? Just technically you can, you can help it happen, right? It's gotta be genuine. It's gotta be, uh, it's the fundamental. There are a few companies that have done it. You gotta create like a great product that get people like Passionate about it and start with a small circle of people that would, um, advocate for your product, right? That's like the core. Without it, nothing happens, right? Just, and, and start growing. It's kind of like a fire. Uh, yeah, conference can help, but if, if I just do a conference, like, uh, that doesn't, uh, doesn't do it. It's one of those things. If it needs to be like the full story, a product that solves a problem, People that are super excited. It might be a small group initially, that's fine, right? You don't need the entire world. Just, just, um, um, just preach the Congress, right? Not the Yankees, right? And, and, uh, and grow it over time. You need to, to have like a story. I need to understand people why this is like a big deal. Um, it's important both for investors and the, the buyer, uh, community. Uh, there's actually a pretty good book, uh, by, uh, Anthony Cannata. He was, uh, he was the, uh, PPO marketing at Gainsight that have done, like, a pretty good job, so I think he explains it way better than I am, but, uh, I mean, those are, like, techniques that …

AI assessment note: “You gotta create like a great product that get people like Passionate about it”

Q Those buyers were VP of sales types, or VP of sales ops, or?

A Yeah, both. Like at that time, we didn't know the difference, like, so we, we kind of, we did a pretty broad spectrum. And again, this doesn't tell you, I mean, because again, it's my fourth company, I know that they can say yes, when it times to actually buying, they may still say no. It doesn't, but if everybody said no, that's a stupid idea, then Uh, probably, you know, we would have been in the idea. The other things we kind of like try to understand, uh, the state of the art of the technology that's available, especially like in natural language understanding, uh, speech, video. Uh, we didn't want to like spend like three years in development. We want to know what's available right now. How good is it, um, is it, and can we deliver something today? So, Fortunately, we started in 2015 where, um, both like deep learning and, um, natural language understanding just Made a leap that allows to be successful. I think if we started a company two years before, I'm not sure that it would have been successful. So with that, we said, okay, that's a, that's a, that's an amazing idea. Let's go and raise money. It wasn't a walk in a park. I mean, today Gong is a super hot company, but at that time, like, We got a lot of no's, uh, but not stupid people. Uh, there are a lot of objections like, uh, salespeople are going to hate it as, as a big brother. Um, and Google and Amazon will compet…

AI assessment note: “Yeah, both. Like at that time, we didn't know the difference”