Travel Through the Lens of AI with with Booking.com CEO Glenn Fogel

00:15:23 · Glenn FogelPlay from here

[00:15:23] S0: So again, we wanna reduce this to understanding what does the customer want. Many people with travel find it very frustrating. I know that. People that will travel find very frustrating. Trying to put together a complicated trip with family, let's say, multiple destinations, different things you wanna do. It's complex. It's pain. You start planning it, then you stop because it's just too much of a pain. And everybody would like something else. Many people would like something else to do it for them. In fact, that's why you'll find very wealthy people have travel concierge people who are actual human beings who really understand the needs of that customer, what they really like and not, and they will do a lot of the hard work for them. People aren't quite in that wealth zone. They'll have there's a partner or their spouse trying to it for them. I'll be perfectly honest. I'm exposing myself here, but I'll say it. Okay? My wife and I sometimes argue about, okay. Who's gonna have to do all the travel planning for this trip? Because it can be frustrating, etcetera. Now with AI, the beauty is it's gonna make it so much easier, and it's doing it right now. We are doing it right now. And let's use that generic term. Let's call it an agent. So I can't wait until we, Booking Holdings in our companies, are offering up these personalized agents that are they know everything about you, everything you want, and able to do so much more for you than any human travel agent could ever do because the machine never forgets anything. The machine has an infinite amount of permutation. It rapidly look through and choose what is the best thing, and it can go down and then back up. That doesn't work. Why? This doesn't fit that well. Can come back with it. Now, people always want some agency, so they make the decision themselves or at least confirm they want it. Most people aren't, for the most part, a complicated thing. They're going to want it to double check them, check them, or whatever, which is different than say a business person says, gotta go from New York to Chicago. And, you know, your assistant, your human assistant, right now, is doing it for you. That's like an agent doing it for you. He knows what flight you need and all that. That's great. Yeah. But when it's complicated, you want that agency.

00:17:34 · Glenn FogelPlay from here

So we at Booking Holdings, all our companies, we are doing that right now. In fact, if you go to Penny, which is Priceline's agentic AI system, and I just did it the other night. I put in a very complex need for a travel with the family where it was my wife and I, we wanna go up in front of the bus. I want the young adults who are adults, but don't think so. I want them in the back of the bus. They're starting. So I got two cabins now. There are one person has to go back to a different city. We're going to Europe. We're going to a city. We're not we're not actually doing the trip from that city where we're gonna land. How are gonna get from where we go? Should we have the hotel where we land and then travel the next day to the other city, or should we go that night? How are gonna do it? What restaurant? All the thing. And I didn't on Priceline, Penny, and it was incredible. I also added another things. I told it that, by the way, I got a lot of frequent flyer miles. So should I be using my miles or should I use it cash and for which ones? And it was just beautiful how it went back and forth and asked me questions like, how many miles do you have with each airline that I'm giving it? And then we're going through the flight part and how much of the cost. By the way, ended up, as I suspected, I'm using my miles for the upfront part for my wife and I. We're paying cash for the kids on our flights. We're going go to the hotel in the city that we landed. The next day, we're going to get a shelf. Was wonderful. It was wonderful. And that's what we want even more so. Here's the real important thing is when things go wrong and things go wrong in travel, nobody's fault. Many times, weather, mechanics, it happens. Okay? You wanna have that one point of contact that can everything because travel is like dominoes. One thing falls over, and it all starts falling over. And that's the beauty with AI being able to figure out being able to look ahead. What can we do? My goal is to have a system that actually we are able to predict well enough what the problem be before it happens and suggest changing. I have so many examples of this, but I see the future.

00:19:37 · Elad GilPlay from here

[00:19:37] S1: I guess at a sort of generic level, because your team on a call that we had prior said that Penny adoption, which again is this agentic tool that you've built for Priceline, has doubled every month for the past past few months. And it's generated a lift in conversion plus faster search, shorter path to booking, lower cancellation, higher customer success. So it seems like it's working in really interesting ways. Are there a common set of use cases that you think are most common for Penny? Are there you know, specific things that it doesn't do well that you just need the underlying models to get better for? I'm a little bit curious though.

00:20:14 · Glenn FogelPlay from here

[00:20:14] S0: Well, the actual we just have some areas where we're we're coming out with some new things on it, but here's something really important. So when you ask me the questions, when you say it's so great, but you tell me it's not really doing much to, you know, the numbers. It doesn't really show up much in the numbers yet because it's still really, really small in terms of the absolute number. We ain't gotta talk scale here. You know, last year, we did a 186,000,000,000 worth of travel. That that's a lot of travel. You don't get over a billion room nights. So the actual numbers, so why? Well, part of it is we're not pushing it really fully. There's one of the issues that I always wanna think about is what's the cost of this? And that's not so easy to understand. What is the cost? That's what's developing of running it. How many tokens are we consuming? Where? Where? Where? How many times are they coming back and forth or doing? Tell me how much was the cost of us getting that trip for that person, and what is our ROI going to be? Then the next thing is, well, what's the return long term? Did it mean lifetime value? Did they come back? Are the loyalties up or what? How much? And will it change? These are things that we don't know yet that we're gonna have to continue to work on, develop till we know. And by the way, the whole thing of token economics now, which model should we be using, for which purpose, and when, and stuff. You know, obviously, you can get tokens a lot cheaper and certain parts to different models, and they're a lot cheaper. And that's something that we have to look at very closely too. So it is fascinating that we can do things that I I'm so thrilled that we do. Like, for example, things like using customer service right now. Customer service where we're using AI, it's it's great. It happens much faster. You you know, instead of having to staff your humans and at peak time, somebody's got to wait for somebody to pick up. We've all been in that line. In that queue, waiting for someone to pick up, and we hate it. But now with AI, the computer can pick it up. It's not a problem. And solve the problem even better and faster, than you never will have in the future.

00:22:18 · Glenn Fogel, Elad GilPlay from here

When you finally talk to a human, the human says, I'm sorry, you'll have to be on hold again while I get somebody else who can solve that problem, which you by then you wanna throttle somebody, AI will solve that problem. But here's the question again about that is sometimes though, you want to figure out because people want to talk to humans sometimes. You got to balance that because what you don't want to do is end up, yeah, you can do it all AI, but actually that's not what the customer wants. And in the end, it's always what's best for the customer. [00:22:49] S1: Yeah. That makes sense. And I I think you said on your q one call that customer service costs are already down about 10%. Well, we For reservation and [00:22:56] S0: Let's booking security about 10 just go let's go this just this Our costs per customer service per contact are down. Mhmm. Mhmm. That's great. Customer satisfaction is up. That's even better. But we have to make sure that we are able to always recognize some customers want a human being and some customers are, you know, you're happy as could be just through AI. [00:23:24] S1: Yeah. That makes sense. I mean, I I think you also mentioned that you're investing something like $550,000,000 of cost savings into AI and platform on that on that same quarterly call. Where are you investing it, or where where are you putting the brunt of that, both capital and effort?

00:23:24 · Elad Gil, Glenn FogelPlay from here

[00:23:24] S1: Yeah. That makes sense. I mean, I I think you also mentioned that you're investing something like $550,000,000 of cost savings into AI and platform on that on that same quarterly call. Where are you investing it, or where where are you putting the brunt of that, both capital and effort? [00:23:39] S0: Yeah. So we and and the amount we're investing is actually higher. We talked about 700,000,000 approximately this year is being invested, but it's in many, many different areas, just, you know, developing more AI. Though AI, there's definitely money going to, call it tech enablement, but there are different projects, different areas. I would not put that all into and say, oh, you're investing in techno old and and AI. That's not correct. There are lots of areas of investment. We talked to them on the call. That's not what's important is the idea that but you've got savings. You've got money. You've got cash flow. How much should you be putting in reinvesting in the company? How much should you be looking perhaps acquisitions? And how much should we handing back to shareholders? And that's always a balance, trying to figure out what's the right ratio, what is it. It really is the first thing is, do we believe investing in the company is gonna give a positive ROI that's sufficient to justify doing that? Or after that, are there acquisitions? And if you can't do either of those, then get the money back to the shareholders because they can then invest it better than you can. And that's what I've always believed in.