Why AI Will Transform Customer Experience: Cresta CEO Ping Wu and Sequoia’s Doug Leone

0:00Today, if you think about the business, they feel like multiple personalities to the customer. So in the sales phase, they call you very, very aggressively. And once you sign up and become a customer, you're dealing with entirely different personalities, right? And you're dealing with service departments. I feel like these are really disconnected, right? And I do feel like AI agents can make this entire experience a continuous, long-going conversation throughout the entire customer journey. And LIM is a perfect tool to do that. And that will really bring the level of personalization, the level of customer experience that wasn't possible before.

0:55Hi, and welcome to Training Data. Today, we're joined by Cresta CEO Ping Wu and Sequoia's Doug Leone, who sits on the Cresta board. Today's episode dives into the gnarly world of the contact center, a giant legacy industry filled with slow-moving incumbents that is responsible for driving the vast majority of company-customer conversations. Ping understands this world deeply, having first built Google's contact center business, before becoming product leader and then CEO of Cresta. ping joins us to talk about the different waves of technology that have hit the call center how he sees the future of customer experience evolving with llms towards an abundance future and why his playbook is to meet customers where they are blending human agent assist with autonomous digital agents doug leone also shares his perspectives from several decades of investing in company building and his hot takes on whether we're in an ai bubble he also shares where he believes the value will accrue in AI.

1:48Hint, it's in the application layer in this gnarly last mile. Enjoy the show. Ping, welcome to the show. And thank you for bringing along our special guest, Doug Leone, as well on your board. My pleasure. Thank you. Thank you both for joining. Ping, I want to start by asking, a big part of the AI thesis is that AI is going to replace labor globally and that the TAM is in the tens of trillions of dollars. Obviously, the contact center, the call center, is a big pool of labor that, you know, is just begging to be automated. If you had to guess, how much of call center labor spend will actually be automated fully by AI?

2:25Yeah, so we internally, we have spent a lot of time debating about this. The reality is, I don't think anyone knows for sure. And if you ask, depends on really what they're selling. And you ask different people, and they give you different answers. And some people will say that 100 % human will be gone in contact center. And some gardeners' research actually shows that none of the Fortune 500 over the next five years will have contact center gone entirely humanless. So it's also probably falling into somewhere in the middle. And in fact, we got asked this question two years ago when GPT-4 first came out.

3:05And a lot of people will say that maybe in two or three years, there will no longer be humans in the context that are. So at that time, our belief is that probably the transformation, especially for existing Fortune 500 companies, will probably take way longer than a lot of people think. Doug, what do you think? What's your bet? At the limit, it's 100%. But I'm mindful that there are still IBM mainframes and cobalt being used in America in a banking system. So to me, it's not really what percent. To me, it's the speed of which this is going to happen. Is it going to happen within 10, 20, 25 years, 30 years?

3:47Because whether the answer is 30 % or 60%, if it happens in 50 years, that means one thing for companies like Crest. If it happens in three years, it means something else. So the end number is not the relevant metric for me. To me, it's the speed of adoption. Great distinction. Ping, you've been working in the contact center AI space for well over a decade. Prior to becoming CEO at Cresta, you ran the equivalent function over at Google. And so maybe for those of us in the audience that don't know the contact center market, can you tell us a little bit about what it is, how big it is, and how technology has served it so far?

4:26Yeah. When we first talk about contact center, a lot of people will naturally think about call centers. A lot of humans sitting there listening, answering calls. But contact center really is a broader category, including the OMI channel interactions from emails to digital chats and on websites and in apps, and also including calls, of course. And the overall market is quite big. And there are historically around 17 to 20 million agents, human agents, actually work in the contact center. For the software market, it's probably in the tens of billions. And for AI markets, according to some research, it will be in the high tens of billions of dollars.

5:12And is the use case mostly, you know, customers calling in to complain, customer support? Is that what these contact centers are mostly used for? Oh, so, yeah. So, customer call in, there are all kind of reasons they call in, right? Complaints are fixing the issue. But also, I think a lot of people may not realize that there are probably a quarter of the contact center, 25%, is actually revenue generating. They're including selling stuff or collecting money or retaining customers and that kind of conversations. So it's not 100 % customer support. So I have a question for you that I never asked you.

5:47If you look at the contact center, and I'm old enough to date myself, you go back 30 years, you heard names of Aya and God knows whoever else that's barely living in and out of bankruptcy. You go back 15 years, you see genesis of the world. What caused a bright young engineer called Peng Wu 15 years ago to be attracted with this market? And one could have said, it's always been a stodgy market. It's always been of low interest. It always created these slow-growing companies. What is it that interested you now? Of course, now we understand it's a vibrant market with lots of opportunity. But turning the clock back 10 years ago, what attracted you to this market?

6:31First of all, 15 years ago, I didn't even realize that's a long history of slow growth on the market. Otherwise, maybe I would think differently. And second, at that time, I just do remember there's a period of time, there's a lot of excitement of conversation, AI technology, and especially around consumer-facing speakers. And at that time, people think that that would disrupt Google, that would become the entry point for all the consumer interactions. and I happen to really believe that the contact center will probably be the most exciting opportunity for conversation AI to transform. And it's because it has all the issues that traditionally people get excited about, VC get excited about.

7:13It's a massive market, a lot of humans working there and it's in the middle between businesses and customers, right? And it's all the interaction going through. And also no one's happy in contact center. So if you, you know, by no one, I mean there are three different parties. There are customers that call in that most of us may not be too happy because the wait time is very long. And agents, by the way, I think a lot of people may not realize the agent, the workforce attrition in contact centers is massive. It's on average of 35 to 40 percent. In some cases during COVID, some companies have more than 100 percent turnover.

7:47I mean, right. So it's very high stress and it's not a very fun job. And also the business also feel like there are always the opportunity to do more with less. It seems no one is happy and it's a massive market. But I think, you know, that's the great opportunity for AI and technology to bring abundance. And then abundance is the answer, in my opinion, to solve all these issues. So you were working on this at Google 10 years ago. I imagine this was the small language model wave, the BERT days. Was the technology ready at that point? and maybe walk us through the different waves of technology that have hit the contact center.

8:23Yeah, so that's a great question. Even long before that, there's technology called IVR that you press one, two, three for different routes and for different call reasons. And then since then, there are innovation around the input. Instead of pressing, you can directly speak natural language and that's with the advance of natural language processing and TTS and text-to-speech generation. that experience getting better and better. For when we first started in contact center AI at Google, it's even before BERT, actually. It's before Transformers. It's mainly using AI, or at that time, using AI to do classification, intent classification and entity extraction using pre-Transformer models.

9:09But the conversation experience is still manually crafted. So that's the last generation of technology. And then after that, of course, the Transformer came along. Initially, it's also for classification purposes. Still, the experience is manually crafted. But then the LIMs entirely changed the whole thing. Not only the conversation experience on automation side, but also just you can understand conversation in a way that never was able before. And what does that mean practically in terms of the rollout of this technology inside contact centers? Does it mean that customers were just extremely unhappy when it was IVR and then they were slightly less unhappy when you started to have kind of more transformers in the flow?

9:48And now customers are very happy to be talking to an LLM-based agent? Or how has the evolution of technology changed the customer experience? Yeah, I think the way we like to think about it is really from the first principle, right? And, you know, there are a lot of the conversations shouldn't even happen in our view. And, you know, the fact that it happens because the customer is not happy. I think the solution for that is to use the AI to really understand, to bring 100 % visibility into all interaction in the contact center today. And using AI to analyze it and then to do deep research and then find out the root cause.

10:25And then that usually reflects some process broken or website updates that freak out people or firmware update that bring down network and all that kind of stuff. So you need to fix that first, right? And first, avoid interaction if it's not necessary, right? And beyond that, I do feel like their AI can automate a lot of interactions that no one wants to have. Like neither the business nor the customer want to have those interactions. Those are what we call low emotion value interactions that should be self-served. And then on top of that, I do think that contact center AI will enable new interactions.

11:04That's the ones that you cannot afford to do that today. So all these are improving customer experience. Do you think end customers will ever prefer talking to an AI agent over a human agent? And have we reached that point yet? So look, I mean, that's a really interesting question. So I've been thinking about this on my way here. So I never met anyone to have this experience of talking to a custom support agent on the phone and go, I'm really frustrated. Send me your AI, please. And we never had that experience. And in fact, I would encourage people to look up some of the companies and search for their custom service.

11:44The first question that people ask on Google, and Google will surface, what is the most popular question? The first question is always, how do I talk to a live person for this type of, you know, custom service? So I think that that time probably hasn't arrived fully yet. It depends on what kind of interactions, again. I'm maybe too techno-optimistic or AGI-pilled here, but I feel like I've seen some recordings now where, you know, AI can be emotionally intelligent. It has infinite patience, right? It's not trying to hit some metric on time to resolution. and so for example if somebody calls in and they're having a really bad day for example your AI can be a lot more patient and empathetic than a human agent even could and so I'm sort of optimistic on the side of the bots here.

12:32Well I agree there's the human component of patience or the subtleties of humanity but there's also the training of the agent versus the training of the AI. Three years from now who's going to be much more much more equipped to answer a question. It's clear that AI is the answer. I kind of think of gold versus Bitcoin. Somehow the analogy came to my mind as you said that. It is clear that Bitcoin is going to win. It is clear that Bitcoin is going to be worth more than gold. Not investment advice. Not investment advice. But it is clear that the agents, by definition, and a lot of which don't even reside in America.

13:13There's a language component. I'm not saying anything bad about the agents, but there's a language component. There's a training component. There's the human component. And I think in all those dimensions, I think AI is going to win in the next two to three years. Bitcoin as digital gold is a really interesting analogy to the digital agent versus the human agent question. Yeah. From our perspective, we really want to meet customers where they are today. So unlike self-driving cars, you really have to automate the entire thing 100 % of time. Otherwise, you do not have the economic impact. For contact center, what we find is very unique is that the work is very divisible.

13:52So first, the conversation is, you know, those are every conversation is independent unit. And you can automate X percent of conversation that's ready to be automated. And for a lot of reason, we can get into details. And then for the remaining ones, you can still use AI to assist humans and to take away the initial maybe 10 % of the interactions like authentication or intake or lead qualification and then take away all the after-call work. And also we have AI agents to help humans in the middle of the conversation, to do knowledge retrieval, to do data entries, all that stuff. So that's not mutually exclusive.

14:29And as long as we feel like customer not ready to say that we just need to turn on our call center today and then go full AI, we feel like there is a long, you know, depending again, what kind of business and what kind of, you know, technical, you know, the IT infrastructure. So I think the journey will probably take a different timeframe, but our goal is really meet the customer where they are. So Crest is in an interesting position because you both have the agent assist product that helps make existing contact center agents more productive. And then you have the actual AI agent product that is directly customer facing, you know, autonomous agents.

15:04Where do you think most customers are today? Are they ready to go full force, just put the agent on my website, let it go crazy? Are they experimenting with that? Where is the customer today? It depends on the customer. If you and I start an e-bike store today on Shopify, and we can automate 100%, I'm sure, because it really depends on how complex is our product. It can be ordered or magnitude difference between a simple product like e-bike or versus a real world touching many different countries and then millions of tens of millions of people. So it's very different. And then that impacts the complexity of the conversation handled by the contact center.

15:43And then the other part is the IT infrastructure. A lot of people may actually realize that before you actually enter the contact center, you will feel like, oh, this should be easily, very easy to automate. The reality is a lot of those things that humans do in the contact center today is optimize for humans. So those system record or the system action ticketing system, these have been around for decades. A lot of them just simply do not have APIs, right? So the only thing that to make changes is through a graphic user interface that optimize for humans. And without a real-time API, just, you know, again, these are not AI problems.

16:20And we believe that, you know, these are the opportunities that we work with our customer to develop those real-time APIs. And so that's why we feel like those transformation depends on the nature of business would take different time frame. It's interesting you made the self-driving car analogy earlier because I was thinking about your business earlier this morning and if you think about Tesla, part of the beauty of them getting to full autonomy is that they have so much data coming in from their cars even when they're on L2, right? For you guys, because you are the call center, you're the agent assist, you actually get full data of the conversation, whether it's voice, whether it's conversational-based digitally, and that can become a training base for customers to automate more and more of their conversations over to the agent over time.

17:06Yes, 100%. And in fact, when we first, my first, the journey when I first started seven, eight years ago, it's really automation only. I really believe it should be automation only. Fast forward, we run into all kinds of real deployments, and then we really actually broaden my own horizon. then I believe that in order to really do the best possible automation, it's counterintuitively. You need to know what actually happened in the contact center, what are humans actually doing. So not only just the conversations, but also what they're seeing on the screen. That's super important to actually build the best automation possible.

17:45One of them is the sex appeal. It's the sizzle. It's what everybody wants to talk about, which you have to have, otherwise you're a tired old company. The other is the realities of our business to run and what they need. And so if you are one of these new age companies, you're quickly going to hit a wall because you don't have the data and you don't have the systems that you really need to run a contact center. But if you're at the former, don't have the latter, then you're labeled as an online company. So here in our case, we understood this a while back and we make sure we invested. we not only we double down on the operational system for agent assist, but we also develop the sex appeal product because that's what all the customers want to talk about day one.

18:30And another aspect of it is really just tied to the point I made earlier, is that a lot of those calls shouldn't really happen. People call in, there's no way to make them happy. It's because they're not happy to begin with, right? And if your product works, if your process works, they shouldn't really happen. So if, look, if this room, we feel really, really cold, maybe the answer is not a heater. Maybe there's a broken window or there is a patio door wide open. The solution is turn on the light and see the root cause and then fix that first before you turn on the heater. Yeah. Love that. Customer support is one of those, you know, canonical examples of where people think large language models will be most transformative.

19:11And, you know, it's almost a consensus category for venture startups at this point. How do you compete? What is it like to compete when everyone has access to the same LLMs and is, you know, latching onto the same big picture vision? Yeah, so again, in order to really deliver value in the context of the transformation, it's not just the models. It's just not a model. The model is a bunch of weights and the data, and, you know, itself is not going to provide a value, right? And now the question is how much you need to build on top of it to deliver that value. If that layer is very, very thin, then I would argue probably you don't have much opportunity to accue value.

19:50And then also, if that layer will be gone, when the model gets better, there's no way you have a durable business. But that is not the case for contact centers. And where a majority of the agencies are still on-premise and where a lot of there are so many. Look, our average agents in the Fortune 500, we look at some surveys. they interact with eight to ten different systems. Remember, these companies also apply to other companies over years, over decades. Those backend systems may not even talk to each other. You know, it depends on where you book the flight or depends on where you book the hotel.

20:25They may need to log into different systems, right? So that's the reality we're talking about. So that's why, you know, we believe our strategy is meeting customers where they are and then drive value on day one. Vertical integration from the stake to the sizzle. That's how you win. What do you think is overhyped and what's underhyped in the kind of contact center AI space right now? Yeah, for overhyped, I think it's the mindset of scarcity. Is the job displacement, I think in the short term, is probably a little overhyped. And what's underhyped is the mindset of abundance. Think about new experience that AI can enable.

21:10For example, can you talk to a website? Can you directly talk to the app? And can you turn a synchronous interaction into an asynchronous interaction? Can you talk to an airline app and say that I want you to do this XYZ and then call me back when you get it done? And then can you have that super multi-language AI agent to have those conversations? Or there are so many interactions that today you just cannot happen just simply because you do not have the staff, right? And then the other thing actually I feel is really underhyped is people really seem obsessed with one side of the conversation, which is the workforce.

21:51And then people ask, you know, how many of the workforce were replaced by AI? But no one ever asked the question is how many inbound calls will be replaced by AI? So my belief is that there will be, over the next few years, you will probably see a race to getting the AI assistant on the consumer aggregators. And then a lot of things that consumer probably will dedicate to the AI assistant, including making the phone calls. So I think that's maybe an interesting thing to pay attention to. That's really cool. Okay, so you could talk to the United Airlines app and have it, you know, asynchronously go figure something out for you and call you back.

22:28Is that something that you're working on? We have no comment on that. Okay, very cool. Okay, I want to transition to talk a little bit about company building. Doug, you've been around the block for a while. You've seen the movie a few times. It means I'm old. That's what you just said. I was trying to say it nicely. How is building a company right now, you're seeing this live with Ping, how is building a company and AI different from your last few decades of building legendary companies? It's not very different. Uh, what I mean by that is you need a terrific founder and we'll talk about the Cresta situation a little later, hopefully.

23:11Um, you need to plug in world-class engineers at the very start, unless you start with A pluses, you'll never move up. You'll only be moving down. You have to plug in salespeople that are not administrators that are fresh. Fresh, maybe they were regional sales manager early on because one, you can't get the world-class people. And two, if you get them, they're too big for the company. You have to figure out what the ramp is that you're willing to fund. You have to figure out what the role of marketing is. You have to solve this thing that I call the merchandising cycle that's been getting some play online, which is from product marketing to BDRs to revenue.

23:54Wherever that's broken, it looks like a bad sales guy, a bad VP of sales, but you have to get that right. And so I think the business fundamentals are very similar. I do think one of the characteristics of the companies that are doing the best in AI right now is they just move with extreme speed. And maybe that's always been the case, but I think it's even more intense right now. How do you think about instilling the need for speed in the companies you work with and even at Sequoia? So I thought of answering that as part of my answer. And the reason I left it out, all the boards I'm on move with extreme speed.

24:26And that's because I paint a picture for the founders of a river, a river with rocks. And the founders and the CEO's job is to remove those rocks. So when you give me next year's plan, I don't care that's 150 % net new AR growth. I want to know why the plan is the plan. And I want to challenge you why it's not 3x that. And maybe the answer is funding, but we can get funding in this market. Maybe the answer is management experience. Well, that's often a good answer. Some people will say market. Well, no way that's market. We're a little company that is. And so in my mind, it's forcing the understanding that these companies are capable of doing things which they don't believe they are capable of doing yet and to remove those rocks.

25:18And I push and I push and I push and I said, why can't we go faster and do it in a linear fashion? Because God forbid something isn't going to happen. And if you hire 250 salespeople in Q1 and then you realize in Q3 something's wrong, in Q3 something's wrong with the product, then you're stuck with a burn. So I'm a believer and I hear, no, we got to train them all the time. Baloney. Give us, please, a revenue ramp that's linear so we can make mid-course corruptions up and down. And let's not be stuck by these numbers. We have 10 fingers, 100 % growth. That's all bullshit. How fast can we possibly grow?

25:54That's always been the mantra and all the boards that I've served on. AI is not different. What does Crestha need to do next? What does Crestha need to do over the next five plus years in order to become a great company, a legendary company? So, well, first of all, it has to continue to develop product. It has to continue to put one foot in front of the other. It has to always see whenever some people reach a Pita principle of their role, it has to be relatively aggressive in making sure it hires people that are capable of taking it from that point on and forward. Staying away from these, quote, very experienced people that start feeling a bit like suits and administrators.

26:36Point one, that's the most important thing. but the other thing that Cresta has to do it is to up its game in marketing there's a lot of companies, I use the word the sizzle there's a lot of company with a lot of sizzle and no stake we have a whole bunch of stake we're a modern company, we're best in class in one category we're going to be best in class in the other category we have beautiful growing run rate in both the agent assist and in the AI part of the product, in the automated part of the product, I just think we need to attach a marketing overlay so we become a household name out of the market.