Gong’s Amit Bendov: From Meeting Recordings to Revenue Intelligence

Contents

Amit Bendov: I get on a call with a customer, Gong already prepares me for the meeting. The way it used to work, you know, I’d get, like, five people from the account. We’ll schedule, like, a pre-meeting briefing. They prepare a document with all the questions, and it’s probably, like, five hours of some highly paid people. Now it’s 30 seconds, right? I just need to read. If I have a question, I ask. So it’s a huge time saver and, you know, we’re not even yet at, like, level five driving, so the potential is, like, way bigger. Remember, like, 75 percent of a seller’s time is not customer facing. That’s the data. Everything else is the opportunity size.

Sonya Huang: Hi and welcome to Training Data. Today we’re excited to welcome Amit Bendov, CEO and founder of Gong, which is one of the most beloved companies in the modern day sales world and also one of the very first AI native application companies. We interviewed Amit about Gong’s evolution from a wedge into a platform, specifically from a transcription tool into a broader revenue intelligence platform, and heard more from Amit on his prediction for what the sales team of the future might look like and Gong’s role in building that future. Enjoy the show.

Amit, thank you so much for joining us today. We are delighted to have you on the show. You are one of the OG AI applications, and absolutely beloved company in the sales world, and so looking forward to having you on Training Data.

Amit Bendov: I’m excited to be here.

What will AI take over in sales?

Sonya Huang: Let’s jump right in. I want to start with one of the hot topics in the AI sales world right now, which is do you believe that AI is going to take over the role of the SDR?

Amit Bendov: Completely? No, not in the near future, not with the current technology. I do think that a lot of the BDR work will be done by AI, and it’s a good thing. So it’s not binary, like, but short answer, not in the next few years. Definitely not if it’s a complex outbound SDR. AI is not going to be able to totally replace that.

Sonya Huang: Got it. Okay, follow up question. Do you think that CRM will exist in five years’ time? In a future where we have a lot of agents running around doing a lot of sales-related activity, what is the role of the CRM in that future?

Amit Bendov: Yeah, I’m sure CRM will exist in 20 years. Like, it’s not going away. There’s so much built in there. Just like, you know, mainframes are still there even though there’s, like, much better technology. I don’t believe that in managing customers CRM is going to be at the epicenter. We’re moving from a CRM-centric world to more like an AI-centric world. CRM manages customers, their data and a lot of other things, but it’s not managing the operations, the activities and how to engage customers. So that’s for sure—it’s still there. People tend to underestimate how much there is in CRM. There’s quite a bit, and it definitely will live for a while.

Pat Grady: Amit, in that AI-centric world, what is the role of the software? What is the role of the humans?

Amit Bendov: The role of the software, we’re starting to understand. The role of the human is actually less clear, and I think we’ll be surprised. It’s hard to predict what it will be. I’m sure it’ll change. There are roles to date, you know, prompt engineer is the obvious one that we couldn’t even imagine, like, three years ago. SDR did not exist. People ask—it did not exist 30 years ago. Like, this is like a modern invention, and it might go away. So it could be, like, different roles.

You know, I’d say in general, the current technology, anything that’s based on transformers is fit for certain types of work. It cannot replace humans whenever there’s, like, accountability or decision making or creativity. We’re not even close to that, right? So humans will still be in control, I believe, for a while, but AI can do a lot of the work.

So, you know, definitely I could do an amazing job reviewing a contract right now and redlining all the hot topics, even suggesting corrections, right? We would not let AI sign a contract or even send a contract or send a proposal, right? There’s always, like, a lawyer that’ll need to do that. So I think the roles will shift to humans that are augmented and using AI as a tool for, you know, quite a few tasks. You know, in our industry specific, there is this number that goes around that 75 percent of what sellers are doing is non-selling activity. So three out of four dollars that we’re paying them is to do admin and non-essential work. All of that could be replaced by AI. That’ll be pretty exciting.

The vision was never about transcription

Sonya Huang: Amit, take us back to 2015 when you founded Gong. Meeting transcription. Like why did you start with that? And was the vision always to build a meeting transcription tool, or to build something very different from that?

Amit Bendov: No. Actually, the vision was never about transcription. So when I started the company we were—like, at my previous company before starting Gong, we were recording calls, and I was using a transcription service, but the real reason was that I didn’t want to read transcripts. Like, there’s, like, there’s so many of them going on. Who has the time to do it? I have a little bit of an ADD as well, so I’m not the person to either listen at great lengths or read.

So I wanted something that would take all the information and translate it into structured data. And transcription is just a way and a process in the pipeline that you need to capture the audio and video, transcribe, then identify topics and themes and other things, and then use it in structured data. So that was the idea. We started with meetings because that was kind of the big black hole. We could kind of see other things that are happening and activities, but this is like a very rich data set that we knew nothing about, and nobody was doing anything. So that’s why we started with that.

Pat Grady: Amit, I remember in those early days, there was this period of time where Gong was one of many. And then it felt—from the outside looking in, it felt almost overnight, all of a sudden Gong was one of one. What did you guys get so right in those early days?

Amit Bendov: I actually think we have, like, more competition right now. And I always tell the team, the more successful we are, we’re going to have more. So if you look at when we started, we thought that we were alone because there are other companies in sales—we didn’t know about it. Thank God we didn’t know. But we found that there are, like, two others. Now there are dozens of companies, and I hope to have, like, hundreds, like, in a few years.

Like, if you look at how many companies are in CRM, there are hundreds. So if the market grows, there’s an opportunity. But that’s a very important question. There’s never, like, a moment. There are always moments where people predicted our death or doom or whatever. So I think 2017 or something—so we didn’t know that we had competition. Like, I started Gong because I said, “Oh, like I have this problem. I’m scratching my own itch. Nothing exists. Maybe we should start a company.” And then I found there’s another company that was, like, better funded, like, a little bit ahead of us, you know, maybe, like, cooler technology.

And when I realized that—I still have the recording from our all-hands. We were like a very small company at the time. But so I’m like, by the end of this year, there’s only one goal that matters. We’re going to be number one. Or nothing else matters. Like, I’m not interested in this company if we’re not the number one clear leader. So like in SaaS, there is no second prize—at least nothing that I’m interested in. And we have to be. And we defined metrics first, how much we’re going to win. And second, it’s not us, we’re going to be the undisputed leader. So we even put metrics, like how much media share or LinkedIn or social media share. And we wanted to have 2x all the others combined. That was the goal, right? And we hit it.

And first, the gaps—first, it’s, like, very neck to neck. Then you get a little win. It’s very hard. And I think we started even a little behind, but the strong get stronger. Once you start opening a gap of, like, you know, let’s say, five, ten percent, it becomes easier. The salespeople become more confident, customers start to see, and then the gap widens. And then you get new competitors.

So we started, there was, like, Chorus and ExecVision. None of them is an independent company. Then people said, “Okay, like, Outreach and Salesloft are going to eat you.” Before we raised money, they said, “Google and Amazon are going to eat you.” So there’s always, like, competition, but you have—you absolutely have to win. It’s very hard at first, but once you start opening the gap, it gets easier. And then you get new competitors, so you’re never alone. If you’re alone, you’re in trouble. You’re on the wrong market.

Customer back, not technology out

Sonya Huang: I mean, my view as, you know, the person on the sidelines who is, you know, doing the investment memo work at the time was the thing that you all did that was really special was you won the hearts and minds of your customer, and you were really, really customer focused. And, you know, like, this is—at the time, meeting transcription was kind of newish. Like, a lot of the, you know, models weren’t that state of the art yet. And so a lot of the other companies were thinking technology out and you were really going customer back, and you knew how to win over those hearts and minds. And I think to this day, that is the thing that is so special about Gong. You go talk to any sales rep, sales team, it’s like, “Gong, Gong, Gong.” And they—you know, they get googly eyes when they think about you.

Amit Bendov: Absolutely. That’s a great point, Sonya. Thank you. Like, it’s not that—yeah, the fact that you want to win doesn’t win the battle, right? You have to do it the right way. And we’re, like, always looking at customer problems that we can solve better than anyone else, right? And always looking ahead. And our goal is always to be almost like every two years to be a new company, right?

I’m a big Beatles fan—sorry, that’s my age. And I told the team, I always tell them that I want to be like the Beatles. Like, every two years, it’s almost like a new band, totally different kind of music, and said, “If we don’t do it, we’re dead.” So if all we do is, like, meeting recording today, we’d be dead because, like, oh, like, everybody can do that. So we always have to reinvent, take great care of customers.

And people think the competition is like a zero sum game, almost like football, like, you know, like ball possession and all of that. It’s more like an Easter egg hunt, right? If you see—you don’t know where all the other kids are running, just find the ones that are your own that nobody’s seeing and get as many of them as you can.

Sonya Huang: I just watched my toddler try to do his first Easter egg hunt. He did not find very many of those.

Amit Bendov: [laughs]

Sonya Huang: So when you started the company, you know, this is a pre-OpenAI or pre-ChatGPT era at least, and there weren’t really great foundation models to build upon. And so I remember back when we invested, you know, you had a very state of the art kind of model research lab in Israel that was doing a lot of, you know, speech to text and model technology. To what extent was that a source of competitive advantage for you then, and is it still a source of competitive advantage for you today?

Amit Bendov: Great question. So we went back and forth on these, I think, like, two or three times, and I’m still not sure we’ve seen the last chapter in this. So when we started, we did not have our transcription engine. We’re using just like a web API. I was of the opinion that we should have one; it’s so core to what we do. But Eilon, my co-founder, the smarter half, said “No, we only have $6 million. I don’t want to invest in something, like, unless it’s three percent more accuracy. Let’s see what people want to buy first, develop the app and then once we raise more money, we develop.”

So we start with something that’s really not—it was an okay service, just duct tape it to—and got to the application and got the first thing that actually works. And we saw what was important. Our competitors were investing a lot in, like, real-time transcription and all the cool technology that never made, like, a real difference for customers. So I’m glad in hindsight that I listened to Eilon and we didn’t burn our Series A money on a transcription engine.

But then once we started, you’re right, at that time we had to rely on things like nuance, right? Which was, like, very expensive, and people don’t even know what it is today. And not great. So we decided now we can invest. We started our own team. We hired some of the best speech people, like, in Israel—and there are quite a few of them—and develop our own. And it was, like, better quality and a lot cheaper. So that was a competitive advantage.

And now we use anything from some of the Amazon services and Whisper for some of the things. We still have our own models for some languages where the others don’t do a good enough job, but if they do, we’ll be happy to switch to service. Like, our transcription is not our core competency. We’re very good at this, but we are at the AI application layer. This is very low level that we do it. It’s like a car battery, right? If we can’t find something, we’ll develop it, but if we can find something better and cheaper, we’ll use it.

Sonya Huang: I’m glad you brought up real-time transcription because that was one of those—I remember from the technology out, that was one of those, like, of course Gong should go in that direction. And I think you stuck to your conviction on that’s not what our customer wants. And so even though that may be the cooler technology, like, what our customer wants is, you know, actually coaching workflows, and the ability to, you know, analyze competitor mentions after the fact. And so, like, that I think is a great example of thinking customer back versus technology out.

Amit Bendov: Yes. Yes, absolutely. Since we started, every time we’re always asked about real time, which is like, you know, it makes total sense, right? Except that the technology doesn’t really work to this day and the value is questionable, right? So we still have not seen it, like, in action, like, in a great way.

The tailwinds of generative AI

Sonya Huang: I want to talk about generative AI. And so you started this company back in the days of what I would call predictive or analytical AI. And a lot of the value is in that, you know, how many times are your competitors being mentioned? You know, if you talk about this feature first, do your win rates go up? And I think a lot of the value is in that. Tell me about what you see as, you know, the opportunity for Gong in a kind of generative AI technology era.

Amit Bendov: Well, I mean, these are exciting days. And when we started the company 2016, even 2015, we were starting to think about it, the model that we used is a self-driving car, right? Autonomous system and self-driving car of, like, five levels. Level five being, like, fully self driving and level one is kind of like alerts of sorts, right?

And we envisioned an autonomous application that runs a revenue organization that you tell what my revenue goals is, and then it understands how to break it down to goals, and how to help from the leaders to the individual sellers, how to run the things. That was like total science fiction. The technology didn’t exist back then. It still doesn’t fully exist. There are still components that are missing. But every time we assess what’s real today, what’s available, what’s the state of the art—not the hype, what can really do reliably and create a great customer experience that we can stand behind and integrate into our solution.

And generative AI was a game changer. You know, things like summarizing calls is something that we wanted to do in 2016. I actually hired a news editor, a TV news editor, and I wanted to see—because we wanted to take—okay, take, like, 60 Minutes and create, like, a 30-second newsreel like you do on TV or sports, right? And I paid someone. I gave a report and said, “Okay, why don’t you create something for me?” And we did probably, like, 20 attempts, and I gave up because they’re not good.

And you understand that actually summarizing, it’s already biased in some way. So now you could do it, like, super easy. So it creates, like, a ton of value. Some of the holy grail apps that people ask for, you know, “Tell me what’s going on with these accounts.” And I could just ask, like, we’re at the end of our quarter right now, so I could log in and just say, “Hey, how is this deal progressing? What could make it go wrong? Can I help with anything?” It’ll tell you, it’s pretty amazing.

On the market side, it provided, like, a huge tailwind for us. So we’re grateful not just for the technology, but what it did in market awareness. So when we started—Gong is an AI company, or an AI application company more precisely, but we never spoke about it. Like, it was like third-level messaging, that this is, like, AI technology because it would scare the heck out of people. So especially, we sell to non-technical people. We sell to CROs and business users that aren’t super technical. So if you talk about AI, that seems, like, scary and science fiction. So it was like third-level messaging. You had to double click, like, at least a couple of times. But now we got a lot of people calling us, “Hey, my CEO was asked on an earning call if they plan to increase, or how are they going to plan to increase sales productivity with AI? Do you have something with AI?” So the openness and the excitement, and ChatGPT made it so accessible at a consumer level that that’s super exciting.

Sonya Huang: On that note, I think a lot of companies, boards are focused top down on how AI is changing productivity metrics. And I think in coding, for example, it’s been pretty exciting to see a lot of companies are now reporting, you know, 20 to 30 percent increases in engineering velocity and metrics like that. What have you seen on the sales side? What has been the impact of using AI for your customers in the revenue orgs?

Amit Bendov: We’ve seen dramatic changes. So some of our customers have seen as much as, like, 60 percent more sales capacity. You know, you can measure it, like, lots of different ways. Let’s say you know a person can handle, like, 50 accounts, now they can do 100 accounts, right? So that’s like—just by saving all the time.

So a lot of the tasks are just becoming redundant. Even, like, you don’t need to talk to as many people anymore. There’s the fun part of talking to other people, but not like what happened, what I’m going to do, because now everything is visible. I get on a call with a customer, Gong already prepares me for the meeting, so I don’t need to call the account team. Usually the way it used to work, you know, I’d get, like, five people from the account. We schedule, like, a pre-meeting briefing. They prepare a document with all the questions. And it’s probably, like, five hours of some highly-paid people. Now it’s 30 seconds, right? I just need to read. If I have a question, I ask. So it’s a huge time saver and, you know, we’re not even yet at, like, level five driving, so the potential is, like, way bigger. Remember, like, 75 percent of a seller’s time is not customer facing. That’s the data. Everything else is the opportunity size.

The path to level five

Pat Grady: What level are we at today, and what’s the path to getting to level five?

Amit Bendov: It depends. So there are different components, like, for example at Gong, so some are at level two and some are level three and some are at level four. Level four is almost like driving. You know, let’s say I get on a call with a customer, Gong would create, like, the email for me, but I have to click ‘send.’ So this is like level four. It’s almost like I’m in control, which is smart. That’s level four. Level five is when it’ll send the email on my behalf. It’ll take a little bit of time. Some things are easier than others, and some things are not as mission critical, right? If you want to do people—everybody talks about, like, outbound SDRs, right? Cold calling. This is a pretty poor choice for current state of the art because first, it’s hard, it’s very hard for people to do that. Second, if it goes wrong, it’s very damaging to your brand, right? As we’ve seen. If you’ve seen some of the Cursor service agents, you know, changing privacy policy or airlines. So I wouldn’t let, like, AI talk to my customers, like, except for, like, very simple cases like support tickets that are pretty confined, but not anything that is complex. So for those, it’s still going to be level four until we get conviction that the technology can be a hundred percent trusted. But some areas are, you know—if it’s not—for example, now we have, like, role playing, right? AI, you could just practice, do practice call with AI and it’ll give you feedback, right? If this thing doesn’t work a hundred percent, it’s no big deal. Like, yeah, like, a little bit annoying, but you’re not embarrassed in front of customers.

Sonya Huang: Is that with, like, a virtual avatar?

Amit Bendov: Yes, yes, yes.

Sonya Huang: Oh, super cool.

Amit Bendov: Yes.

Do people hold AI to a higher standard?

Pat Grady: The comment on, “until it’s a hundred percent trusted,” do you think people—or I guess, in terms of what you’ve observed with your customers and the users of the product, do people hold AI to a higher standard than they hold themselves? I would guess most of those reps or BDRs or SDRs are not a hundred percent all the time.

Amit Bendov: Yes and no. So the yes? Actually, fun fact, like, when we started Gong, we actually did not show the transcription, right? So you couldn’t see—the transcription was there, but someone advised us, like, a smart person that did it in, like, another application, don’t show the transcript because it’s 70 percent accurate. Which means, like, three out of ten words will be wrong. When someone reads that, it’ll just be an awful user experience. So we hid it. We allow them to search, we show some things, and people were super happy. But we couldn’t show the thing because it just wasn’t good. So people do expect perfection with AI. You know, someone self driving a Tesla, makes an accident, it’s major headlines, right? But, you know, people make so many more accidents, like, and nobody talks about it. That said, I do see that the reactions to—for example, when people ask questions at Gong, or they get the summaries or they get—everybody’s very excited. They know it’s not perfect. Like, it’s, you know, maybe 80, 85 percent correct. But the value, because it’s so fast and so easy, I don’t see a lot of people complaining. So I think people are able to tolerate somewhat lower quality for ease of use. So for example, when I was a teenager, we had, like, hi-fi systems, right? That’s how you’d listen to music, either on headphones or, like, on mono, just one speaker, right? How can you listen to that? Just poor audio quality, right? But it’s so easy that people are willing to put up with the simpler and easier technology. And this is, like, definitely a lot simpler. So we see a lot of—generally the sentiment is very positive.

Sonya Huang: I have no idea what a hi-fi system is.

Amit Bendov: Yes, I bought one. My wife wanted to kill me, but I bought, like, major speakers in our basement and. And she said, “You did what?” Yeah, I just missed that audio quality.

Agents are real

Sonya Huang: Love it. Amit, what’s your take on agents, and how are you guys approaching agents, building, selling agents at Gong?

Amit Bendov: We think agents are real. Again, like a lot of other things, there is a bit of, like, inflated expectations right now. It’s like it’s going to do everything. So everybody, like, excuse me, agents aren’t taking your job anytime soon. But they can definitely take parts of your job, the parts that you don’t like doing and it’s a waste of your time. So the approach that we’re taking is, like, task-specific agents. They’re not developed, like, to do anything, there’s no writing code. So we have, for example, like, we spoke about, like, Briefer, right. So here’s, like, brief me for accounts. There is an agent that trained for this task. It has parameters, and it’s built in the workflow, right? And we have dozens of them. That’s the approach that we believe are great for enterprise applications. General purpose are very hard to nail because they could go in all sorts of directions. But it’s a real thing. Also interesting, the line between, like, simple automation and agents, like, isn’t clear if you look at it. Some of them, like, it’s the same thing but it’s also very different. So the question, can they make decisions? Again, for non-critical decisions that aren’t, like, a huge deal, they can definitely do a great job. But agents can definitely do quite a bit of our work.

Sonya Huang: Have the newer model capabilities, and in particular the reasoning models, have those unlocked new capabilities for Gong?

Amit Bendov: Not yet. I think that there’s a line that I’m not sure that even, like, transformer technology is capable of, which is like can you rely a hundred percent of something that will be true, right? Just truthfulness. Like, not 99 percent. A hundred percent, right? So there is a category of work that has to be—you know, you send a proposal to a customer, that can’t be, like, 99 percent, right? If it’s like one percent of the cases, then you send something that is like totally wrong pricing or over-discounting or something is like a hallucination. So even with the reasoning it’s getting better, so I think it increases the classes of tasks that make sense. But if you talk, like, AGI or things that absolutely, like, must happen, you know, calculate commissions to sellers, right? You get it wrong, it’s very bad, right? So I think it’s a quantitative improvement. Still not a qualitative. Qualitative is that’s one hundred percent trusty, and that’ll be—some would say even if it’s like, you know, Yann LeCun or David Deutsch, they would say, like, it’s not even within the realm of transformer technology because of the statistical nature of the approach.

Sonya Huang: Do you agree with Yann’s take?

Amit Bendov: Yes, but I also know there’s a possibility that maybe, like—and he’s much smarter than I am—that we’re not seeing that someone would prove us wrong. Which would be great. But yeah, right now there’s also an issue of accountability in both legal but also from a work perspective. For example, Gong now has the ability to update all opportunity records, for example. So that’s a no brainer, right? Nobody needs to log into CRM and update fields anymore. Some companies still want the seller to say “Yes, yes, yes, yes.” Because otherwise they can blame AI for, “Oh, I didn’t say that,” right? It’s like AI, and the AI could be wrong, right? It’s like the risk of error. So there’s a difference between an analog computer and a digital computer, right? Digital computer has error correction which means you know if a message was sent over a line, there’s errors, it’ll get there exactly as it is, right? And transformer, maybe it’ll be enhanced in a way that we’re not thinking about it. It’ll take, like, a different kind of technology to get there. My two cents.

The sales team of the future

Sonya Huang: Yeah. What do you think the sales team of the future is going to look like? And maybe you don’t have a high fidelity point of view on that, but how quickly do you think the composition, the team composition of a sales team is going to change? Like, if you take the software engineering world as analogy, I think that’s changing rapidly in terms of size of software engineering teams, skill sets. How quickly do you think the sales world is going to change, by contrast?

Amit Bendov: It’s already changing. I think that it’ll be gradual. So there are some, you know, very transactional sales, for example. You know, I want to buy an iPhone or something. That’ll go first because that could certainly be automated. Or I want to upgrade my cellular plan or whatever it is, right? That can be handled. Complex things like I want to buy a house or a mortgage or enterprise software, that’s more complicated. But I do not see people doing clerical work, just updating forms. I do not see the traditional forecasting. I do think that there are things that are some very far-reaching consequences, right? Right now people are doing manual forecasting, right? I don’t think that’s necessary because software and AI can do a way better job.

You know, companies have sales stages in their process. Every company has, you know, their five or six stages. You don’t really need that. That’s a management tool that was created, like, you know, 50 years ago so we can get some visibility to where the process is. But actually everything can be done way smarter with AI. So I think that the process can change, the people can change. We see great adoption of the technology because again, it’s so easy that it’s cross generational right now, that people are very eager. And sometimes their imagination is even faster than our speed of development. “Oh, can you do this? Can you do that?” So people are very eager, and I think that they’ll be augmented by AI. The BDR role, I’m not sure that it’ll be around, not necessarily because the software is going to replace, but sellers could do their own thing if they have the right tools. So fewer people could do more work. Remember, BDR did not exist 30 years ago. It was created for fast, hypergrowth, fast companies. Most companies in the world don’t have that. So I think we’re going to augment the sellers, and they’ll be able to address a lot more customers.

Value-based pricing

Pat Grady: I mean, it’s easy to imagine that sales team of the future being smaller on balance than the sales teams of the present. Each individual is far more productive because of wonderful tools like Gong that give them superpowers. The thing I’m curious about is for you as a business, you create a lot of value with the product that you offer. You capture that value today, I believe primarily through a seat-based pricing model. If there’s this countervailing force on seats, which is ironically you’re making people more productive, therefore they need fewer seats, over time, how does your pricing and packaging evolve? How do you capture more of that value that you’re creating if seats aren’t going up as fast as they might have historically?

Amit Bendov: I love the question, Pat. So there are multiple forces. First, I’m not sure there’ll be fewer sellers. They’ll be different, but the economy grows, kind of GDP grows over time. There’ll be products and services we’re not imagining right now that will be there. So it’s not necessarily, like, fewer people, but people will be more efficient. But we will start to add the consumption level or usage pricing. Like, this year we’re coming with an orchestration product that will be a great fit. When we started Gong, actually, we asked people, like, do you want to do it, like, based on usage or based on seats? And most people that we surveyed, most buyers said, “Oh, per seat right now.” Because they use, like, CRM as an anchor point, right? And we didn’t want to innovate on too many fronts. So we said okay, we innovate on the product. Pricing? We’ll keep it simple.

But we always—and probably in the pitch deck, like, from Series B or whenever we did, we said AI will be bigger than cloud, right? Because cloud is an IT revolution and AI is a work revolution. So we never saw ourselves as software company, but more like a BPO. And the potential is 10 times bigger, because if you take—you know, most sales tech, like, you know, $1,000 a seat, and I think it could easily be, like, you know, $1,000 or more per month, because if you think of how many—you know, people are costing $200,000 a year, you save 70 percent. That’s $140,000, right? You take 10 percent of that, it’s still a bargain for the CFO, right? And the company. So the potential is absolutely there, whether it’s usage based or just higher per-seat pricing, it has to be aligned with the value. But I think the world is more ready now to look at value pricing.

Sonya Huang: I want to do a quick aside from AI for a second because I think that Gong is one of the only companies that’s really re-inflected revenue growth at pretty meaningful scale. Talk to us about what it was like going through sales tech winter over the last couple years, and how you made it through to the other side, and any lessons for other founders.

Amit Bendov: Do we really want to get into that, Sonya? So early 2023, really facing, like, a tough headwind, right? The market was tanking. We had a lot of technology companies as users. Our product suite wasn’t as complete as it is today. So we were at a disadvantage where companies are looking to cut budget and consolidate. We’re losing very happy customers. But they said, “Listen, we have to choose, like, one vendor.” And so we’re disadvantaged from that perspective. Our game wasn’t top notch. Like, when we started in 2016, we had to hustle our way and we had that muscle, and, you know, then Gong became very famous and the market was very good. So we’ve lost a lot of the muscle tissue, so we didn’t have to be very good in terms of how we support customers, and how we sell. And all the company became hard.

So it was like this perfect storm and everything, and we almost came to a halt. Very challenging and demoralizing to the team and, you know, when customers say, “We love you but we’re leaving,” or some companies were going out of business. So it was tough, but I never lost conviction that we can turn this around, right? And we started rolling our sleeves and got to work. So we launched two new products, Forecast and Engage, like, in great speed. Fortunately we had enough money, so we raised a lot of money. We never burnt a lot of money, so when we always need, people ask, “Why are you raising?” This is, like, for a rainy day that we didn’t know when it’s going to come, but we knew it will, right?

So we decided that where everybody were laying off people, we said this is an opportunity for us. It’ll be harder for the competition. Now we’re going to keep the foot on the gas pedal. That’s one. Second, we improved our act when we sell. We had to create a bulletproof business case that a CFO would approve. It’s not just that, you know, buy Gong because it’s cool and it’ll change your life. So it has to show real value, how we support customers. And we tried a lot of things, and you don’t see immediate impact. Some of the things that you’re doing, it might take, like, two or three quarters. So you experiment with quite a few things and nothing seems to be working. So it’s a very, very challenging situation. But the team was able to turn it around. So all these things. Eventually the product, beefing up the product suite, improving our game. And fortunately, ChatGPT came out and it gave us a huge boost. There are a lot of people who spelled, like, the death of Gong. “Oh, now everybody can do—generative AI will make everything possible.” That was slightly exaggerated. But that actually gave us, like, a really nice tailwind because customers saw, like, a lot more value in the solution. So all these things together helped us turn it around, and now we’re accelerating. I don’t know when this will be aired, but even, like, this quarter is even, like, faster than the previous quarter, Sonya, I’ll give you, like …

Sonya Huang: Love it.

Amit Bendov: Yeah, so we had—it’s now seven consecutive quarters of accelerating and, you know, we hope we have not seen the end.

Sonya Huang: I mean, I think your grit and the way that you dug in and just led the company through that period, and never lost any confidence whatsoever in the full vision for what Gong could become, I think I have huge respect and admiration, we all do, for how you weathered that storm. And I think you’ve now earned the right to really go big and go pursue that big ambition. Should we close it out with some rapid fire questions?

Lightning round

Amit Bendov: Oh, I’m nervous. But yeah, bring it on.

Sonya Huang: [laughs] Okay. These are intended to be, like, one word or one sentence answers, whatever comes to mind quickly. Okay, favorite new AI application in your personal life or at work, other than Gong.

Amit Bendov: ChatGPT, easily. I use it, like, 15 times a day easily. Yeah. Yeah, for everything. I don’t want to tell you for what, but yeah.

Pat Grady: [laughs] All right, how about one piece of advice for founders who are building AI companies at the application layer.

Amit Bendov: Keep your eyes on the customer, talk to customers. Don’t believe your investors, the influencers, all of that. I love you all. Just talk to customers, see what they really need. Be the fastest thing that works now, not, like, in two years where the hype is just follow. Keep your eyes on the ball.

Pat Grady: Love it.

Sonya Huang: I don’t love that so much.

Pat Grady: [laughs]

Sonya Huang: I’m kidding, I’m kidding.

Amit Bendov: It was rapid. If you give me a little more time, maybe I’ll give you more politically correct.

Sonya Huang: I’m completely kidding. In two or three years time, will we have virtual avatars actually selling to customers directly, yes or no?

Amit Bendov: Yes, yes. Yes, I think for simple products, yeah, that’s definitely a possibility.

Pat Grady: How about one recommended piece of content for people who are interested in AI. Something they should read or listen to.

Amit Bendov: You know, just follow your interest. I’m not loyal to any one source. I listen to all kinds of things. I just put, like, my interests on YouTube and that’s how I find information and look at it. I do like The Beginning of Infinity by David Deutsch. It’s not the easiest read, but this book—it’s not just on AI, but it talks about what’s next. Like, AI is part of it, and this is like a mind-changing book in my mind.

Sonya Huang: Amit, do you think AI is capable of fully autonomously signing a million-dollar contract? And what year will that happen?

Amit Bendov: Not in the next, like, three to five years in my opinion. It’ll need something that’s beyond transformers, something that is not like an analog computer, is more digital, that can be relied 100 percent. And I don’t know what it is, and I don’t know that anyone knows today what it is, but it’ll take, like, a different level of technology. This is recorded, so let’s put something on a calendar for, like, three to five years and see if I was wrong or right.

Pat Grady: [laughs]

Sonya Huang: Let’s do it. I think you’ve tended to be right whenever we’ve disagreed in the past, Amit. Thank you so much for joining us today. We really enjoyed the discussion, and congratulations on persevering through sales tech winter and making it through to this very exciting time for AI and for the world.

Amit Bendov: Well, it was fun. Thank you so much.

Mentioned in this episode: 

Mentioned in this episode: 

• “New paradigm of AI architectures”: Yann LeCun’s talk at Davos where he talks about the world beyond transformers and LLMs in the next 3-5 years.
• The Beginning of Infinity: Book by David Deutsch that Amit says is “mind-changing.”